From 47ebb1fa20f17f8e04625b818c5f0980a589a250 Mon Sep 17 00:00:00 2001 From: bjpatrick <137509145+bjpatrick@users.noreply.github.com> Date: Tue, 7 May 2024 08:54:16 -0500 Subject: [PATCH 01/18] Update pyproject.toml Adding maite v0.4.0 and modelscan v0.1.1 --- pyproject.toml | 2 ++ 1 file changed, 2 insertions(+) diff --git a/pyproject.toml b/pyproject.toml index 5c8852d47..aa6dd2e27 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -128,7 +128,9 @@ worker = [ "async_timeout", "adversarial-robustness-toolbox>=1.9.0", "imgaug>=0.4.0", + "maite[all_interop]>=0.4.0", "matplotlib", + "modelscan>=0.1.1", "nrtk>=0.3.0", "opencv-python", "Pillow>=9.2.0", From 76ac38c5acb74334976ed8a5bac872db65426dbd Mon Sep 17 00:00:00 2001 From: bjpatrick <137509145+bjpatrick@users.noreply.github.com> Date: Tue, 7 May 2024 08:57:25 -0500 Subject: [PATCH 02/18] Update pip-compile.yml --- .github/workflows/pip-compile.yml | 3 +++ 1 file changed, 3 insertions(+) diff --git a/.github/workflows/pip-compile.yml b/.github/workflows/pip-compile.yml index 3c9084bd0..ca875275f 100644 --- a/.github/workflows/pip-compile.yml +++ b/.github/workflows/pip-compile.yml @@ -19,6 +19,9 @@ name: pip-compile runs on: schedule: - cron: "10 1 * * *" # at 1:10am every day + push: + branches: + - "**" jobs: pip-compile: From 6a4e8e3ee678294cba5f32d9e633bb7a22f17598 Mon Sep 17 00:00:00 2001 From: bjpatrick <137509145+bjpatrick@users.noreply.github.com> Date: Tue, 7 May 2024 09:19:28 -0500 Subject: [PATCH 03/18] Add files via upload updating requirements files to include maite and modelscan --- ...-amd64-py3.11-requirements-dev-pytorch.txt | 69 +++++++---- ...d64-py3.11-requirements-dev-tensorflow.txt | 117 +++++++++++++----- .../linux-amd64-py3.11-requirements-dev.txt | 116 ++++++++++++----- ...-arm64-py3.11-requirements-dev-pytorch.txt | 69 +++++++---- ...m64-py3.11-requirements-dev-tensorflow.txt | 83 ++++++++----- .../linux-arm64-py3.11-requirements-dev.txt | 82 +++++++----- ...-amd64-py3.11-requirements-dev-pytorch.txt | 69 +++++++---- ...d64-py3.11-requirements-dev-tensorflow.txt | 83 ++++++++----- .../macos-amd64-py3.11-requirements-dev.txt | 82 +++++++----- ...-arm64-py3.11-requirements-dev-pytorch.txt | 69 +++++++---- ...m64-py3.11-requirements-dev-tensorflow.txt | 83 ++++++++----- .../macos-arm64-py3.11-requirements-dev.txt | 82 +++++++----- ...-amd64-py3.11-requirements-dev-pytorch.txt | 69 +++++++---- ...d64-py3.11-requirements-dev-tensorflow.txt | 87 ++++++++----- .../win-amd64-py3.11-requirements-dev.txt | 88 ++++++++----- 15 files changed, 829 insertions(+), 419 deletions(-) diff --git a/requirements/linux-amd64-py3.11-requirements-dev-pytorch.txt b/requirements/linux-amd64-py3.11-requirements-dev-pytorch.txt index 47b93ffa4..135bbd14d 100644 --- a/requirements/linux-amd64-py3.11-requirements-dev-pytorch.txt +++ b/requirements/linux-amd64-py3.11-requirements-dev-pytorch.txt @@ -56,7 +56,7 @@ attrs==23.2.0 # referencing autopep8==2.1.0 # via dioptra (pyproject.toml) -babel==2.14.0 +babel==2.15.0 # via # jupyterlab-server # sphinx @@ -70,13 +70,13 @@ bleach==6.1.0 # via # kaggle # nbconvert -blinker==1.8.1 +blinker==1.8.2 # via flask -boto3==1.34.93 +boto3==1.34.99 # via # dioptra # dioptra (pyproject.toml) -botocore==1.34.93 +botocore==1.34.99 # via # boto3 # s3transfer @@ -113,6 +113,7 @@ click==8.1.7 # distributed # flask # mlflow + # modelscan # pip-tools # prefect # rq @@ -138,7 +139,7 @@ croniter==2.0.5 # via prefect cycler==0.12.1 # via matplotlib -dask==2024.4.2 +dask==2024.5.0 # via # distributed # prefect @@ -150,7 +151,7 @@ defusedxml==0.7.1 # via nbconvert distlib==0.3.8 # via virtualenv -distributed==2024.4.2 +distributed==2024.5.0 # via prefect docker==7.0.0 # via @@ -195,7 +196,7 @@ flask-accepts==0.18.4 # via # dioptra # dioptra (pyproject.toml) -flask-cors==4.0.0 +flask-cors==4.0.1 # via # dioptra # dioptra (pyproject.toml) @@ -246,7 +247,7 @@ graphql-relay==3.2.0 # via graphene greenlet==3.0.3 # via sqlalchemy -grpcio==1.62.2 +grpcio==1.63.0 # via tensorboard gunicorn==21.2.0 # via mlflow @@ -306,7 +307,7 @@ itsdangerous==2.2.0 # via flask jedi==0.19.1 # via ipython -jinja2==3.1.3 +jinja2==3.1.4 # via # cookiecutter # distributed @@ -325,13 +326,13 @@ jmespath==1.0.1 # via # boto3 # botocore -joblib==1.4.0 +joblib==1.4.2 # via scikit-learn json5==0.9.25 # via jupyterlab-server jsonpointer==2.4 # via jsonschema -jsonschema[format-nongpl]==4.21.1 +jsonschema[format-nongpl]==4.22.0 # via # dioptra # dioptra (pyproject.toml) @@ -400,6 +401,8 @@ locket==1.0.0 # partd lsprotocol==2023.0.1 # via pygls +maite[all-interop]==0.5.0 + # via dioptra (pyproject.toml) mako==1.3.3 # via alembic markdown==3.6 @@ -414,7 +417,7 @@ markupsafe==2.1.5 # mako # nbconvert # werkzeug -marshmallow==3.21.1 +marshmallow==3.21.2 # via # dioptra # dioptra (pyproject.toml) @@ -442,6 +445,8 @@ mistune==3.0.2 # via nbconvert mlflow==2.12.1 # via dioptra (pyproject.toml) +modelscan==0.7.3 + # via dioptra (pyproject.toml) mpmath==1.3.0 # via sympy msgpack==1.0.8 @@ -482,9 +487,9 @@ notebook-shim==0.2.4 # via # jupyterlab # notebook -nrtk==0.3.1 +nrtk==0.4.0 # via dioptra (pyproject.toml) -numpy==1.26.4 +numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy @@ -492,8 +497,10 @@ numpy==1.26.4 # dioptra (pyproject.toml) # imageio # imgaug + # maite # matplotlib # mlflow + # modelscan # nrtk # opencv-python # pandas @@ -583,7 +590,7 @@ pandocfilters==1.5.1 # via nbconvert parso==0.8.4 # via jedi -partd==1.4.1 +partd==1.4.2 # via dask passlib==1.7.4 # via @@ -643,7 +650,7 @@ pyarrow==15.0.2 # via # dioptra (pyproject.toml) # mlflow -pybsm==0.1.1 +pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via @@ -662,7 +669,7 @@ pyflakes==3.2.0 # via flake8 pygls==1.3.1 # via esbonio -pygments==2.17.2 +pygments==2.18.0 # via # ipython # jupyter-console @@ -731,14 +738,14 @@ pyyaml==6.0.1 # jupyter-events # mlflow # prefect -pyzmq==26.0.2 +pyzmq==26.0.3 # via # ipykernel # jupyter-client # jupyter-console # jupyter-server # qtconsole -qtconsole==5.5.1 +qtconsole==5.5.2 # via jupyter qtpy==2.4.1 # via qtconsole @@ -749,7 +756,7 @@ redis==5.0.4 # dioptra # dioptra (pyproject.toml) # rq -referencing==0.35.0 +referencing==0.35.1 # via # jsonschema # jsonschema-specifications @@ -775,12 +782,14 @@ rfc3986-validator==0.1.1 # jsonschema # jupyter-events rich==13.7.1 - # via dioptra (pyproject.toml) -rpds-py==0.18.0 + # via + # dioptra (pyproject.toml) + # modelscan +rpds-py==0.18.1 # via # jsonschema # referencing -rq==1.16.1 +rq==1.16.2 # via # dioptra # dioptra (pyproject.toml) @@ -879,7 +888,7 @@ sphinxcontrib-qthelp==1.0.7 # via sphinx sphinxcontrib-serializinghtml==1.1.10 # via sphinx -sqlalchemy==2.0.29 +sqlalchemy==2.0.30 # via # alembic # dioptra @@ -904,6 +913,8 @@ tensorboard==2.16.2 # via dioptra (pyproject.toml) tensorboard-data-server==0.7.2 # via tensorboard +tensorflow-io-gcs-filesystem==0.34.0 + # via modelscan terminado==0.18.1 # via # jupyter-server @@ -912,7 +923,7 @@ text-unidecode==1.3 # via python-slugify threadpoolctl==3.5.0 # via scikit-learn -tifffile==2024.4.24 +tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum @@ -922,6 +933,8 @@ toml==0.10.2 # via prefect tomli==2.0.1 # via dioptra (pyproject.toml) +tomlkit==0.12.4 + # via modelscan toolz==0.12.1 # via # dask @@ -930,6 +943,7 @@ toolz==0.12.1 torch==2.2.2 # via # -r requirements-dev-pytorch.in + # maite # torchaudio # torchvision torchaudio==2.2.2 @@ -947,7 +961,7 @@ tornado==6.4 # terminado tox==4.15.0 # via dioptra (pyproject.toml) -tqdm==4.66.2 +tqdm==4.66.4 # via # adversarial-robustness-toolbox # kaggle @@ -979,6 +993,7 @@ typing-extensions==4.11.0 # dioptra # dioptra (pyproject.toml) # ipython + # maite # sqlalchemy # torch tzdata==2024.1 @@ -1009,7 +1024,7 @@ webencodings==0.5.1 # tinycss2 websocket-client==1.8.0 # via jupyter-server -werkzeug==3.0.2 +werkzeug==3.0.3 # via # dioptra # dioptra (pyproject.toml) diff --git a/requirements/linux-amd64-py3.11-requirements-dev-tensorflow.txt b/requirements/linux-amd64-py3.11-requirements-dev-tensorflow.txt index 3f1912094..41b6c0869 100644 --- a/requirements/linux-amd64-py3.11-requirements-dev-tensorflow.txt +++ b/requirements/linux-amd64-py3.11-requirements-dev-tensorflow.txt @@ -59,7 +59,7 @@ attrs==23.2.0 # referencing autopep8==2.1.0 # via dioptra (pyproject.toml) -babel==2.14.0 +babel==2.15.0 # via # jupyterlab-server # sphinx @@ -73,13 +73,13 @@ bleach==6.1.0 # via # kaggle # nbconvert -blinker==1.8.1 +blinker==1.8.2 # via flask -boto3==1.34.93 +boto3==1.34.99 # via # dioptra # dioptra (pyproject.toml) -botocore==1.34.93 +botocore==1.34.99 # via # boto3 # s3transfer @@ -116,6 +116,7 @@ click==8.1.7 # distributed # flask # mlflow + # modelscan # pip-tools # prefect # rq @@ -141,7 +142,7 @@ croniter==2.0.5 # via prefect cycler==0.12.1 # via matplotlib -dask==2024.4.2 +dask==2024.5.0 # via # distributed # prefect @@ -153,7 +154,7 @@ defusedxml==0.7.1 # via nbconvert distlib==0.3.8 # via virtualenv -distributed==2024.4.2 +distributed==2024.5.0 # via prefect docker==7.0.0 # via @@ -174,7 +175,9 @@ fastjsonschema==2.19.1 # via nbformat filelock==3.14.0 # via + # torch # tox + # triton # virtualenv flake8==7.0.0 # via @@ -196,7 +199,7 @@ flask-accepts==0.18.4 # via # dioptra # dioptra (pyproject.toml) -flask-cors==4.0.0 +flask-cors==4.0.1 # via # dioptra # dioptra (pyproject.toml) @@ -233,6 +236,7 @@ frozenlist==1.4.1 fsspec==2024.3.1 # via # dask + # torch # universal-pathlib gast==0.5.4 # via tensorflow @@ -252,7 +256,7 @@ graphql-relay==3.2.0 # via graphene greenlet==3.0.3 # via sqlalchemy -grpcio==1.62.2 +grpcio==1.63.0 # via # tensorboard # tensorflow @@ -318,7 +322,7 @@ itsdangerous==2.2.0 # via flask jedi==0.19.1 # via ipython -jinja2==3.1.3 +jinja2==3.1.4 # via # cookiecutter # distributed @@ -330,19 +334,20 @@ jinja2==3.1.3 # mlflow # nbconvert # sphinx + # torch jinja2-time==0.2.0 # via cookiecutter jmespath==1.0.1 # via # boto3 # botocore -joblib==1.4.0 +joblib==1.4.2 # via scikit-learn json5==0.9.25 # via jupyterlab-server jsonpointer==2.4 # via jsonschema -jsonschema[format-nongpl]==4.21.1 +jsonschema[format-nongpl]==4.22.0 # via # dioptra # dioptra (pyproject.toml) @@ -415,6 +420,8 @@ locket==1.0.0 # partd lsprotocol==2023.0.1 # via pygls +maite[all-interop]==0.5.0 + # via dioptra (pyproject.toml) mako==1.3.3 # via alembic markdown==3.6 @@ -429,7 +436,7 @@ markupsafe==2.1.5 # mako # nbconvert # werkzeug -marshmallow==3.21.1 +marshmallow==3.21.2 # via # dioptra # dioptra (pyproject.toml) @@ -461,6 +468,10 @@ ml-dtypes==0.3.2 # tensorflow mlflow==2.12.1 # via dioptra (pyproject.toml) +modelscan==0.7.3 + # via dioptra (pyproject.toml) +mpmath==1.3.0 + # via sympy msgpack==1.0.8 # via # distributed @@ -492,16 +503,18 @@ nbformat==5.10.4 nest-asyncio==1.6.0 # via ipykernel networkx==3.3 - # via scikit-image + # via + # scikit-image + # torch notebook==7.1.3 # via jupyter notebook-shim==0.2.4 # via # jupyterlab # notebook -nrtk==0.3.1 +nrtk==0.4.0 # via dioptra (pyproject.toml) -numpy==1.26.4 +numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy @@ -511,9 +524,11 @@ numpy==1.26.4 # imageio # imgaug # keras + # maite # matplotlib # ml-dtypes # mlflow + # modelscan # nrtk # opencv-python # opt-einsum @@ -532,6 +547,37 @@ numpy==1.26.4 # tensorboard # tensorflow # tifffile +nvidia-cublas-cu12==12.1.3.1 + # via + # nvidia-cudnn-cu12 + # nvidia-cusolver-cu12 + # torch +nvidia-cuda-cupti-cu12==12.1.105 + # via torch +nvidia-cuda-nvrtc-cu12==12.1.105 + # via torch +nvidia-cuda-runtime-cu12==12.1.105 + # via torch +nvidia-cudnn-cu12==8.9.2.26 + # via torch +nvidia-cufft-cu12==11.0.2.54 + # via torch +nvidia-curand-cu12==10.3.2.106 + # via torch +nvidia-cusolver-cu12==11.4.5.107 + # via torch +nvidia-cusparse-cu12==12.1.0.106 + # via + # nvidia-cusolver-cu12 + # torch +nvidia-nccl-cu12==2.20.5 + # via torch +nvidia-nvjitlink-cu12==12.4.127 + # via + # nvidia-cusolver-cu12 + # nvidia-cusparse-cu12 +nvidia-nvtx-cu12==12.1.105 + # via torch opencv-python==4.9.0.80 # via # dioptra (pyproject.toml) @@ -578,7 +624,7 @@ pandocfilters==1.5.1 # via nbconvert parso==0.8.4 # via jedi -partd==1.4.1 +partd==1.4.2 # via dask passlib==1.7.4 # via @@ -638,7 +684,7 @@ pyarrow==15.0.2 # via # dioptra (pyproject.toml) # mlflow -pybsm==0.1.1 +pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via @@ -657,7 +703,7 @@ pyflakes==3.2.0 # via flake8 pygls==1.3.1 # via esbonio -pygments==2.17.2 +pygments==2.18.0 # via # ipython # jupyter-console @@ -726,14 +772,14 @@ pyyaml==6.0.1 # jupyter-events # mlflow # prefect -pyzmq==26.0.2 +pyzmq==26.0.3 # via # ipykernel # jupyter-client # jupyter-console # jupyter-server # qtconsole -qtconsole==5.5.1 +qtconsole==5.5.2 # via jupyter qtpy==2.4.1 # via qtconsole @@ -744,7 +790,7 @@ redis==5.0.4 # dioptra # dioptra (pyproject.toml) # rq -referencing==0.35.0 +referencing==0.35.1 # via # jsonschema # jsonschema-specifications @@ -774,11 +820,12 @@ rich==13.7.1 # via # dioptra (pyproject.toml) # keras -rpds-py==0.18.0 + # modelscan +rpds-py==0.18.1 # via # jsonschema # referencing -rq==1.16.1 +rq==1.16.2 # via # dioptra # dioptra (pyproject.toml) @@ -880,7 +927,7 @@ sphinxcontrib-qthelp==1.0.7 # via sphinx sphinxcontrib-serializinghtml==1.1.10 # via sphinx -sqlalchemy==2.0.29 +sqlalchemy==2.0.30 # via # alembic # dioptra @@ -895,6 +942,8 @@ structlog==24.1.0 # via # dioptra # dioptra (pyproject.toml) +sympy==1.12 + # via torch tabulate==0.9.0 # via prefect tblib==3.0.0 @@ -907,8 +956,10 @@ tensorboard-data-server==0.7.2 # via tensorboard tensorflow==2.16.1 # via -r requirements-dev-tensorflow.in -tensorflow-io-gcs-filesystem==0.36.0 - # via tensorflow +tensorflow-io-gcs-filesystem==0.34.0 + # via + # modelscan + # tensorflow termcolor==2.4.0 # via tensorflow terminado==0.18.1 @@ -919,7 +970,7 @@ text-unidecode==1.3 # via python-slugify threadpoolctl==3.5.0 # via scikit-learn -tifffile==2024.4.24 +tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum @@ -929,11 +980,15 @@ toml==0.10.2 # via prefect tomli==2.0.1 # via dioptra (pyproject.toml) +tomlkit==0.12.4 + # via modelscan toolz==0.12.1 # via # dask # distributed # partd +torch==2.3.0 + # via maite tornado==6.4 # via # distributed @@ -945,7 +1000,7 @@ tornado==6.4 # terminado tox==4.15.0 # via dioptra (pyproject.toml) -tqdm==4.66.2 +tqdm==4.66.4 # via # adversarial-robustness-toolbox # kaggle @@ -967,6 +1022,8 @@ traitlets==5.14.3 # nbconvert # nbformat # qtconsole +triton==2.3.0 + # via torch types-python-dateutil==2.9.0.20240316 # via arrow typing-extensions==4.11.0 @@ -975,9 +1032,11 @@ typing-extensions==4.11.0 # dioptra # dioptra (pyproject.toml) # ipython + # maite # optree # sqlalchemy # tensorflow + # torch tzdata==2024.1 # via # pandas @@ -1006,7 +1065,7 @@ webencodings==0.5.1 # tinycss2 websocket-client==1.8.0 # via jupyter-server -werkzeug==3.0.2 +werkzeug==3.0.3 # via # dioptra # dioptra (pyproject.toml) diff --git a/requirements/linux-amd64-py3.11-requirements-dev.txt b/requirements/linux-amd64-py3.11-requirements-dev.txt index 1f1fb3345..dc7a11b4c 100644 --- a/requirements/linux-amd64-py3.11-requirements-dev.txt +++ b/requirements/linux-amd64-py3.11-requirements-dev.txt @@ -54,7 +54,7 @@ attrs==23.2.0 # referencing autopep8==2.1.0 # via dioptra (pyproject.toml) -babel==2.14.0 +babel==2.15.0 # via # jupyterlab-server # sphinx @@ -68,13 +68,13 @@ bleach==6.1.0 # via # kaggle # nbconvert -blinker==1.8.1 +blinker==1.8.2 # via flask -boto3==1.34.93 +boto3==1.34.99 # via # dioptra # dioptra (pyproject.toml) -botocore==1.34.93 +botocore==1.34.99 # via # boto3 # s3transfer @@ -111,6 +111,7 @@ click==8.1.7 # distributed # flask # mlflow + # modelscan # pip-tools # prefect # rq @@ -136,7 +137,7 @@ croniter==2.0.5 # via prefect cycler==0.12.1 # via matplotlib -dask==2024.4.2 +dask==2024.5.0 # via # distributed # prefect @@ -148,7 +149,7 @@ defusedxml==0.7.1 # via nbconvert distlib==0.3.8 # via virtualenv -distributed==2024.4.2 +distributed==2024.5.0 # via prefect docker==7.0.0 # via @@ -169,7 +170,9 @@ fastjsonschema==2.19.1 # via nbformat filelock==3.14.0 # via + # torch # tox + # triton # virtualenv flake8==7.0.0 # via @@ -191,7 +194,7 @@ flask-accepts==0.18.4 # via # dioptra # dioptra (pyproject.toml) -flask-cors==4.0.0 +flask-cors==4.0.1 # via # dioptra # dioptra (pyproject.toml) @@ -226,6 +229,7 @@ frozenlist==1.4.1 fsspec==2024.3.1 # via # dask + # torch # universal-pathlib gitdb==4.0.11 # via gitpython @@ -241,7 +245,7 @@ graphql-relay==3.2.0 # via graphene greenlet==3.0.3 # via sqlalchemy -grpcio==1.62.2 +grpcio==1.63.0 # via tensorboard gunicorn==21.2.0 # via mlflow @@ -301,7 +305,7 @@ itsdangerous==2.2.0 # via flask jedi==0.19.1 # via ipython -jinja2==3.1.3 +jinja2==3.1.4 # via # cookiecutter # distributed @@ -313,19 +317,20 @@ jinja2==3.1.3 # mlflow # nbconvert # sphinx + # torch jinja2-time==0.2.0 # via cookiecutter jmespath==1.0.1 # via # boto3 # botocore -joblib==1.4.0 +joblib==1.4.2 # via scikit-learn json5==0.9.25 # via jupyterlab-server jsonpointer==2.4 # via jsonschema -jsonschema[format-nongpl]==4.21.1 +jsonschema[format-nongpl]==4.22.0 # via # dioptra # dioptra (pyproject.toml) @@ -394,6 +399,8 @@ locket==1.0.0 # partd lsprotocol==2023.0.1 # via pygls +maite[all-interop]==0.5.0 + # via dioptra (pyproject.toml) mako==1.3.3 # via alembic markdown==3.6 @@ -408,7 +415,7 @@ markupsafe==2.1.5 # mako # nbconvert # werkzeug -marshmallow==3.21.1 +marshmallow==3.21.2 # via # dioptra # dioptra (pyproject.toml) @@ -436,6 +443,10 @@ mistune==3.0.2 # via nbconvert mlflow==2.12.1 # via dioptra (pyproject.toml) +modelscan==0.7.3 + # via dioptra (pyproject.toml) +mpmath==1.3.0 + # via sympy msgpack==1.0.8 # via # distributed @@ -465,16 +476,18 @@ nbformat==5.10.4 nest-asyncio==1.6.0 # via ipykernel networkx==3.3 - # via scikit-image + # via + # scikit-image + # torch notebook==7.1.3 # via jupyter notebook-shim==0.2.4 # via # jupyterlab # notebook -nrtk==0.3.1 +nrtk==0.4.0 # via dioptra (pyproject.toml) -numpy==1.26.4 +numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy @@ -482,8 +495,10 @@ numpy==1.26.4 # dioptra (pyproject.toml) # imageio # imgaug + # maite # matplotlib # mlflow + # modelscan # nrtk # opencv-python # pandas @@ -500,6 +515,37 @@ numpy==1.26.4 # smqtk-image-io # tensorboard # tifffile +nvidia-cublas-cu12==12.1.3.1 + # via + # nvidia-cudnn-cu12 + # nvidia-cusolver-cu12 + # torch +nvidia-cuda-cupti-cu12==12.1.105 + # via torch +nvidia-cuda-nvrtc-cu12==12.1.105 + # via torch +nvidia-cuda-runtime-cu12==12.1.105 + # via torch +nvidia-cudnn-cu12==8.9.2.26 + # via torch +nvidia-cufft-cu12==11.0.2.54 + # via torch +nvidia-curand-cu12==10.3.2.106 + # via torch +nvidia-cusolver-cu12==11.4.5.107 + # via torch +nvidia-cusparse-cu12==12.1.0.106 + # via + # nvidia-cusolver-cu12 + # torch +nvidia-nccl-cu12==2.20.5 + # via torch +nvidia-nvjitlink-cu12==12.4.127 + # via + # nvidia-cusolver-cu12 + # nvidia-cusparse-cu12 +nvidia-nvtx-cu12==12.1.105 + # via torch opencv-python==4.9.0.80 # via # dioptra (pyproject.toml) @@ -541,7 +587,7 @@ pandocfilters==1.5.1 # via nbconvert parso==0.8.4 # via jedi -partd==1.4.1 +partd==1.4.2 # via dask passlib==1.7.4 # via @@ -600,7 +646,7 @@ pyarrow==15.0.2 # via # dioptra (pyproject.toml) # mlflow -pybsm==0.1.1 +pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via @@ -619,7 +665,7 @@ pyflakes==3.2.0 # via flake8 pygls==1.3.1 # via esbonio -pygments==2.17.2 +pygments==2.18.0 # via # ipython # jupyter-console @@ -688,14 +734,14 @@ pyyaml==6.0.1 # jupyter-events # mlflow # prefect -pyzmq==26.0.2 +pyzmq==26.0.3 # via # ipykernel # jupyter-client # jupyter-console # jupyter-server # qtconsole -qtconsole==5.5.1 +qtconsole==5.5.2 # via jupyter qtpy==2.4.1 # via qtconsole @@ -706,7 +752,7 @@ redis==5.0.4 # dioptra # dioptra (pyproject.toml) # rq -referencing==0.35.0 +referencing==0.35.1 # via # jsonschema # jsonschema-specifications @@ -732,12 +778,14 @@ rfc3986-validator==0.1.1 # jsonschema # jupyter-events rich==13.7.1 - # via dioptra (pyproject.toml) -rpds-py==0.18.0 + # via + # dioptra (pyproject.toml) + # modelscan +rpds-py==0.18.1 # via # jsonschema # referencing -rq==1.16.1 +rq==1.16.2 # via # dioptra # dioptra (pyproject.toml) @@ -836,7 +884,7 @@ sphinxcontrib-qthelp==1.0.7 # via sphinx sphinxcontrib-serializinghtml==1.1.10 # via sphinx -sqlalchemy==2.0.29 +sqlalchemy==2.0.30 # via # alembic # dioptra @@ -851,6 +899,8 @@ structlog==24.1.0 # via # dioptra # dioptra (pyproject.toml) +sympy==1.12 + # via torch tabulate==0.9.0 # via prefect tblib==3.0.0 @@ -859,6 +909,8 @@ tensorboard==2.16.2 # via dioptra (pyproject.toml) tensorboard-data-server==0.7.2 # via tensorboard +tensorflow-io-gcs-filesystem==0.34.0 + # via modelscan terminado==0.18.1 # via # jupyter-server @@ -867,7 +919,7 @@ text-unidecode==1.3 # via python-slugify threadpoolctl==3.5.0 # via scikit-learn -tifffile==2024.4.24 +tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum @@ -877,11 +929,15 @@ toml==0.10.2 # via prefect tomli==2.0.1 # via dioptra (pyproject.toml) +tomlkit==0.12.4 + # via modelscan toolz==0.12.1 # via # dask # distributed # partd +torch==2.3.0 + # via maite tornado==6.4 # via # distributed @@ -893,7 +949,7 @@ tornado==6.4 # terminado tox==4.15.0 # via dioptra (pyproject.toml) -tqdm==4.66.2 +tqdm==4.66.4 # via # adversarial-robustness-toolbox # kaggle @@ -915,6 +971,8 @@ traitlets==5.14.3 # nbconvert # nbformat # qtconsole +triton==2.3.0 + # via torch types-python-dateutil==2.9.0.20240316 # via arrow typing-extensions==4.11.0 @@ -923,7 +981,9 @@ typing-extensions==4.11.0 # dioptra # dioptra (pyproject.toml) # ipython + # maite # sqlalchemy + # torch tzdata==2024.1 # via # pandas @@ -952,7 +1012,7 @@ webencodings==0.5.1 # tinycss2 websocket-client==1.8.0 # via jupyter-server -werkzeug==3.0.2 +werkzeug==3.0.3 # via # dioptra # dioptra (pyproject.toml) diff --git a/requirements/linux-arm64-py3.11-requirements-dev-pytorch.txt b/requirements/linux-arm64-py3.11-requirements-dev-pytorch.txt index a7aa49681..05c3475ee 100644 --- a/requirements/linux-arm64-py3.11-requirements-dev-pytorch.txt +++ b/requirements/linux-arm64-py3.11-requirements-dev-pytorch.txt @@ -56,7 +56,7 @@ attrs==23.2.0 # referencing autopep8==2.1.0 # via dioptra (pyproject.toml) -babel==2.14.0 +babel==2.15.0 # via # jupyterlab-server # sphinx @@ -70,13 +70,13 @@ bleach==6.1.0 # via # kaggle # nbconvert -blinker==1.8.1 +blinker==1.8.2 # via flask -boto3==1.34.93 +boto3==1.34.99 # via # dioptra # dioptra (pyproject.toml) -botocore==1.34.93 +botocore==1.34.99 # via # boto3 # s3transfer @@ -113,6 +113,7 @@ click==8.1.7 # distributed # flask # mlflow + # modelscan # pip-tools # prefect # rq @@ -138,7 +139,7 @@ croniter==2.0.5 # via prefect cycler==0.12.1 # via matplotlib -dask==2024.4.2 +dask==2024.5.0 # via # distributed # prefect @@ -150,7 +151,7 @@ defusedxml==0.7.1 # via nbconvert distlib==0.3.8 # via virtualenv -distributed==2024.4.2 +distributed==2024.5.0 # via prefect docker==7.0.0 # via @@ -194,7 +195,7 @@ flask-accepts==0.18.4 # via # dioptra # dioptra (pyproject.toml) -flask-cors==4.0.0 +flask-cors==4.0.1 # via # dioptra # dioptra (pyproject.toml) @@ -245,7 +246,7 @@ graphql-relay==3.2.0 # via graphene greenlet==3.0.3 # via sqlalchemy -grpcio==1.62.2 +grpcio==1.63.0 # via tensorboard gunicorn==21.2.0 # via mlflow @@ -305,7 +306,7 @@ itsdangerous==2.2.0 # via flask jedi==0.19.1 # via ipython -jinja2==3.1.3 +jinja2==3.1.4 # via # cookiecutter # distributed @@ -324,13 +325,13 @@ jmespath==1.0.1 # via # boto3 # botocore -joblib==1.4.0 +joblib==1.4.2 # via scikit-learn json5==0.9.25 # via jupyterlab-server jsonpointer==2.4 # via jsonschema -jsonschema[format-nongpl]==4.21.1 +jsonschema[format-nongpl]==4.22.0 # via # dioptra # dioptra (pyproject.toml) @@ -399,6 +400,8 @@ locket==1.0.0 # partd lsprotocol==2023.0.1 # via pygls +maite[all-interop]==0.5.0 + # via dioptra (pyproject.toml) mako==1.3.3 # via alembic markdown==3.6 @@ -413,7 +416,7 @@ markupsafe==2.1.5 # mako # nbconvert # werkzeug -marshmallow==3.21.1 +marshmallow==3.21.2 # via # dioptra # dioptra (pyproject.toml) @@ -441,6 +444,8 @@ mistune==3.0.2 # via nbconvert mlflow==2.12.1 # via dioptra (pyproject.toml) +modelscan==0.7.3 + # via dioptra (pyproject.toml) mpmath==1.3.0 # via sympy msgpack==1.0.8 @@ -481,9 +486,9 @@ notebook-shim==0.2.4 # via # jupyterlab # notebook -nrtk==0.3.1 +nrtk==0.4.0 # via dioptra (pyproject.toml) -numpy==1.26.4 +numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy @@ -491,8 +496,10 @@ numpy==1.26.4 # dioptra (pyproject.toml) # imageio # imgaug + # maite # matplotlib # mlflow + # modelscan # nrtk # opencv-python # pandas @@ -551,7 +558,7 @@ pandocfilters==1.5.1 # via nbconvert parso==0.8.4 # via jedi -partd==1.4.1 +partd==1.4.2 # via dask passlib==1.7.4 # via @@ -611,7 +618,7 @@ pyarrow==15.0.2 # via # dioptra (pyproject.toml) # mlflow -pybsm==0.1.1 +pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via @@ -630,7 +637,7 @@ pyflakes==3.2.0 # via flake8 pygls==1.3.1 # via esbonio -pygments==2.17.2 +pygments==2.18.0 # via # ipython # jupyter-console @@ -699,14 +706,14 @@ pyyaml==6.0.1 # jupyter-events # mlflow # prefect -pyzmq==26.0.2 +pyzmq==26.0.3 # via # ipykernel # jupyter-client # jupyter-console # jupyter-server # qtconsole -qtconsole==5.5.1 +qtconsole==5.5.2 # via jupyter qtpy==2.4.1 # via qtconsole @@ -717,7 +724,7 @@ redis==5.0.4 # dioptra # dioptra (pyproject.toml) # rq -referencing==0.35.0 +referencing==0.35.1 # via # jsonschema # jsonschema-specifications @@ -743,12 +750,14 @@ rfc3986-validator==0.1.1 # jsonschema # jupyter-events rich==13.7.1 - # via dioptra (pyproject.toml) -rpds-py==0.18.0 + # via + # dioptra (pyproject.toml) + # modelscan +rpds-py==0.18.1 # via # jsonschema # referencing -rq==1.16.1 +rq==1.16.2 # via # dioptra # dioptra (pyproject.toml) @@ -847,7 +856,7 @@ sphinxcontrib-qthelp==1.0.7 # via sphinx sphinxcontrib-serializinghtml==1.1.10 # via sphinx -sqlalchemy==2.0.29 +sqlalchemy==2.0.30 # via # alembic # dioptra @@ -872,6 +881,8 @@ tensorboard==2.16.2 # via dioptra (pyproject.toml) tensorboard-data-server==0.7.2 # via tensorboard +tensorflow-io-gcs-filesystem==0.34.0 + # via modelscan terminado==0.18.1 # via # jupyter-server @@ -880,7 +891,7 @@ text-unidecode==1.3 # via python-slugify threadpoolctl==3.5.0 # via scikit-learn -tifffile==2024.4.24 +tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum @@ -890,6 +901,8 @@ toml==0.10.2 # via prefect tomli==2.0.1 # via dioptra (pyproject.toml) +tomlkit==0.12.4 + # via modelscan toolz==0.12.1 # via # dask @@ -898,6 +911,7 @@ toolz==0.12.1 torch==2.2.2 # via # -r requirements-dev-pytorch.in + # maite # torchaudio # torchvision torchaudio==2.2.2 @@ -915,7 +929,7 @@ tornado==6.4 # terminado tox==4.15.0 # via dioptra (pyproject.toml) -tqdm==4.66.2 +tqdm==4.66.4 # via # adversarial-robustness-toolbox # kaggle @@ -945,6 +959,7 @@ typing-extensions==4.11.0 # dioptra # dioptra (pyproject.toml) # ipython + # maite # sqlalchemy # torch tzdata==2024.1 @@ -975,7 +990,7 @@ webencodings==0.5.1 # tinycss2 websocket-client==1.8.0 # via jupyter-server -werkzeug==3.0.2 +werkzeug==3.0.3 # via # dioptra # dioptra (pyproject.toml) diff --git a/requirements/linux-arm64-py3.11-requirements-dev-tensorflow.txt b/requirements/linux-arm64-py3.11-requirements-dev-tensorflow.txt index 1d928e30a..6b1f24ecd 100644 --- a/requirements/linux-arm64-py3.11-requirements-dev-tensorflow.txt +++ b/requirements/linux-arm64-py3.11-requirements-dev-tensorflow.txt @@ -59,7 +59,7 @@ attrs==23.2.0 # referencing autopep8==2.1.0 # via dioptra (pyproject.toml) -babel==2.14.0 +babel==2.15.0 # via # jupyterlab-server # sphinx @@ -73,13 +73,13 @@ bleach==6.1.0 # via # kaggle # nbconvert -blinker==1.8.1 +blinker==1.8.2 # via flask -boto3==1.34.93 +boto3==1.34.99 # via # dioptra # dioptra (pyproject.toml) -botocore==1.34.93 +botocore==1.34.99 # via # boto3 # s3transfer @@ -116,6 +116,7 @@ click==8.1.7 # distributed # flask # mlflow + # modelscan # pip-tools # prefect # rq @@ -141,7 +142,7 @@ croniter==2.0.5 # via prefect cycler==0.12.1 # via matplotlib -dask==2024.4.2 +dask==2024.5.0 # via # distributed # prefect @@ -153,7 +154,7 @@ defusedxml==0.7.1 # via nbconvert distlib==0.3.8 # via virtualenv -distributed==2024.4.2 +distributed==2024.5.0 # via prefect docker==7.0.0 # via @@ -174,6 +175,7 @@ fastjsonschema==2.19.1 # via nbformat filelock==3.14.0 # via + # torch # tox # virtualenv flake8==7.0.0 @@ -196,7 +198,7 @@ flask-accepts==0.18.4 # via # dioptra # dioptra (pyproject.toml) -flask-cors==4.0.0 +flask-cors==4.0.1 # via # dioptra # dioptra (pyproject.toml) @@ -233,6 +235,7 @@ frozenlist==1.4.1 fsspec==2024.3.1 # via # dask + # torch # universal-pathlib gast==0.5.4 # via tensorflow @@ -252,7 +255,7 @@ graphql-relay==3.2.0 # via graphene greenlet==3.0.3 # via sqlalchemy -grpcio==1.62.2 +grpcio==1.63.0 # via # tensorboard # tensorflow @@ -318,7 +321,7 @@ itsdangerous==2.2.0 # via flask jedi==0.19.1 # via ipython -jinja2==3.1.3 +jinja2==3.1.4 # via # cookiecutter # distributed @@ -330,19 +333,20 @@ jinja2==3.1.3 # mlflow # nbconvert # sphinx + # torch jinja2-time==0.2.0 # via cookiecutter jmespath==1.0.1 # via # boto3 # botocore -joblib==1.4.0 +joblib==1.4.2 # via scikit-learn json5==0.9.25 # via jupyterlab-server jsonpointer==2.4 # via jsonschema -jsonschema[format-nongpl]==4.21.1 +jsonschema[format-nongpl]==4.22.0 # via # dioptra # dioptra (pyproject.toml) @@ -415,6 +419,8 @@ locket==1.0.0 # partd lsprotocol==2023.0.1 # via pygls +maite[all-interop]==0.5.0 + # via dioptra (pyproject.toml) mako==1.3.3 # via alembic markdown==3.6 @@ -429,7 +435,7 @@ markupsafe==2.1.5 # mako # nbconvert # werkzeug -marshmallow==3.21.1 +marshmallow==3.21.2 # via # dioptra # dioptra (pyproject.toml) @@ -461,6 +467,10 @@ ml-dtypes==0.3.2 # tensorflow mlflow==2.12.1 # via dioptra (pyproject.toml) +modelscan==0.7.3 + # via dioptra (pyproject.toml) +mpmath==1.3.0 + # via sympy msgpack==1.0.8 # via # distributed @@ -492,16 +502,18 @@ nbformat==5.10.4 nest-asyncio==1.6.0 # via ipykernel networkx==3.3 - # via scikit-image + # via + # scikit-image + # torch notebook==7.1.3 # via jupyter notebook-shim==0.2.4 # via # jupyterlab # notebook -nrtk==0.3.1 +nrtk==0.4.0 # via dioptra (pyproject.toml) -numpy==1.26.4 +numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy @@ -511,9 +523,11 @@ numpy==1.26.4 # imageio # imgaug # keras + # maite # matplotlib # ml-dtypes # mlflow + # modelscan # nrtk # opencv-python # opt-einsum @@ -578,7 +592,7 @@ pandocfilters==1.5.1 # via nbconvert parso==0.8.4 # via jedi -partd==1.4.1 +partd==1.4.2 # via dask passlib==1.7.4 # via @@ -638,7 +652,7 @@ pyarrow==15.0.2 # via # dioptra (pyproject.toml) # mlflow -pybsm==0.1.1 +pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via @@ -657,7 +671,7 @@ pyflakes==3.2.0 # via flake8 pygls==1.3.1 # via esbonio -pygments==2.17.2 +pygments==2.18.0 # via # ipython # jupyter-console @@ -726,14 +740,14 @@ pyyaml==6.0.1 # jupyter-events # mlflow # prefect -pyzmq==26.0.2 +pyzmq==26.0.3 # via # ipykernel # jupyter-client # jupyter-console # jupyter-server # qtconsole -qtconsole==5.5.1 +qtconsole==5.5.2 # via jupyter qtpy==2.4.1 # via qtconsole @@ -744,7 +758,7 @@ redis==5.0.4 # dioptra # dioptra (pyproject.toml) # rq -referencing==0.35.0 +referencing==0.35.1 # via # jsonschema # jsonschema-specifications @@ -774,11 +788,12 @@ rich==13.7.1 # via # dioptra (pyproject.toml) # keras -rpds-py==0.18.0 + # modelscan +rpds-py==0.18.1 # via # jsonschema # referencing -rq==1.16.1 +rq==1.16.2 # via # dioptra # dioptra (pyproject.toml) @@ -880,7 +895,7 @@ sphinxcontrib-qthelp==1.0.7 # via sphinx sphinxcontrib-serializinghtml==1.1.10 # via sphinx -sqlalchemy==2.0.29 +sqlalchemy==2.0.30 # via # alembic # dioptra @@ -895,6 +910,8 @@ structlog==24.1.0 # via # dioptra # dioptra (pyproject.toml) +sympy==1.12 + # via torch tabulate==0.9.0 # via prefect tblib==3.0.0 @@ -907,8 +924,10 @@ tensorboard-data-server==0.7.2 # via tensorboard tensorflow==2.16.1 # via -r requirements-dev-tensorflow.in -tensorflow-io-gcs-filesystem==0.36.0 - # via tensorflow +tensorflow-io-gcs-filesystem==0.34.0 + # via + # modelscan + # tensorflow termcolor==2.4.0 # via tensorflow terminado==0.18.1 @@ -919,7 +938,7 @@ text-unidecode==1.3 # via python-slugify threadpoolctl==3.5.0 # via scikit-learn -tifffile==2024.4.24 +tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum @@ -929,11 +948,15 @@ toml==0.10.2 # via prefect tomli==2.0.1 # via dioptra (pyproject.toml) +tomlkit==0.12.4 + # via modelscan toolz==0.12.1 # via # dask # distributed # partd +torch==2.3.0 + # via maite tornado==6.4 # via # distributed @@ -945,7 +968,7 @@ tornado==6.4 # terminado tox==4.15.0 # via dioptra (pyproject.toml) -tqdm==4.66.2 +tqdm==4.66.4 # via # adversarial-robustness-toolbox # kaggle @@ -975,9 +998,11 @@ typing-extensions==4.11.0 # dioptra # dioptra (pyproject.toml) # ipython + # maite # optree # sqlalchemy # tensorflow + # torch tzdata==2024.1 # via # pandas @@ -1006,7 +1031,7 @@ webencodings==0.5.1 # tinycss2 websocket-client==1.8.0 # via jupyter-server -werkzeug==3.0.2 +werkzeug==3.0.3 # via # dioptra # dioptra (pyproject.toml) diff --git a/requirements/linux-arm64-py3.11-requirements-dev.txt b/requirements/linux-arm64-py3.11-requirements-dev.txt index dd3b03150..db53c5b08 100644 --- a/requirements/linux-arm64-py3.11-requirements-dev.txt +++ b/requirements/linux-arm64-py3.11-requirements-dev.txt @@ -54,7 +54,7 @@ attrs==23.2.0 # referencing autopep8==2.1.0 # via dioptra (pyproject.toml) -babel==2.14.0 +babel==2.15.0 # via # jupyterlab-server # sphinx @@ -68,13 +68,13 @@ bleach==6.1.0 # via # kaggle # nbconvert -blinker==1.8.1 +blinker==1.8.2 # via flask -boto3==1.34.93 +boto3==1.34.99 # via # dioptra # dioptra (pyproject.toml) -botocore==1.34.93 +botocore==1.34.99 # via # boto3 # s3transfer @@ -111,6 +111,7 @@ click==8.1.7 # distributed # flask # mlflow + # modelscan # pip-tools # prefect # rq @@ -136,7 +137,7 @@ croniter==2.0.5 # via prefect cycler==0.12.1 # via matplotlib -dask==2024.4.2 +dask==2024.5.0 # via # distributed # prefect @@ -148,7 +149,7 @@ defusedxml==0.7.1 # via nbconvert distlib==0.3.8 # via virtualenv -distributed==2024.4.2 +distributed==2024.5.0 # via prefect docker==7.0.0 # via @@ -169,6 +170,7 @@ fastjsonschema==2.19.1 # via nbformat filelock==3.14.0 # via + # torch # tox # virtualenv flake8==7.0.0 @@ -191,7 +193,7 @@ flask-accepts==0.18.4 # via # dioptra # dioptra (pyproject.toml) -flask-cors==4.0.0 +flask-cors==4.0.1 # via # dioptra # dioptra (pyproject.toml) @@ -226,6 +228,7 @@ frozenlist==1.4.1 fsspec==2024.3.1 # via # dask + # torch # universal-pathlib gitdb==4.0.11 # via gitpython @@ -241,7 +244,7 @@ graphql-relay==3.2.0 # via graphene greenlet==3.0.3 # via sqlalchemy -grpcio==1.62.2 +grpcio==1.63.0 # via tensorboard gunicorn==21.2.0 # via mlflow @@ -301,7 +304,7 @@ itsdangerous==2.2.0 # via flask jedi==0.19.1 # via ipython -jinja2==3.1.3 +jinja2==3.1.4 # via # cookiecutter # distributed @@ -313,19 +316,20 @@ jinja2==3.1.3 # mlflow # nbconvert # sphinx + # torch jinja2-time==0.2.0 # via cookiecutter jmespath==1.0.1 # via # boto3 # botocore -joblib==1.4.0 +joblib==1.4.2 # via scikit-learn json5==0.9.25 # via jupyterlab-server jsonpointer==2.4 # via jsonschema -jsonschema[format-nongpl]==4.21.1 +jsonschema[format-nongpl]==4.22.0 # via # dioptra # dioptra (pyproject.toml) @@ -394,6 +398,8 @@ locket==1.0.0 # partd lsprotocol==2023.0.1 # via pygls +maite[all-interop]==0.5.0 + # via dioptra (pyproject.toml) mako==1.3.3 # via alembic markdown==3.6 @@ -408,7 +414,7 @@ markupsafe==2.1.5 # mako # nbconvert # werkzeug -marshmallow==3.21.1 +marshmallow==3.21.2 # via # dioptra # dioptra (pyproject.toml) @@ -436,6 +442,10 @@ mistune==3.0.2 # via nbconvert mlflow==2.12.1 # via dioptra (pyproject.toml) +modelscan==0.7.3 + # via dioptra (pyproject.toml) +mpmath==1.3.0 + # via sympy msgpack==1.0.8 # via # distributed @@ -465,16 +475,18 @@ nbformat==5.10.4 nest-asyncio==1.6.0 # via ipykernel networkx==3.3 - # via scikit-image + # via + # scikit-image + # torch notebook==7.1.3 # via jupyter notebook-shim==0.2.4 # via # jupyterlab # notebook -nrtk==0.3.1 +nrtk==0.4.0 # via dioptra (pyproject.toml) -numpy==1.26.4 +numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy @@ -482,8 +494,10 @@ numpy==1.26.4 # dioptra (pyproject.toml) # imageio # imgaug + # maite # matplotlib # mlflow + # modelscan # nrtk # opencv-python # pandas @@ -541,7 +555,7 @@ pandocfilters==1.5.1 # via nbconvert parso==0.8.4 # via jedi -partd==1.4.1 +partd==1.4.2 # via dask passlib==1.7.4 # via @@ -600,7 +614,7 @@ pyarrow==15.0.2 # via # dioptra (pyproject.toml) # mlflow -pybsm==0.1.1 +pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via @@ -619,7 +633,7 @@ pyflakes==3.2.0 # via flake8 pygls==1.3.1 # via esbonio -pygments==2.17.2 +pygments==2.18.0 # via # ipython # jupyter-console @@ -688,14 +702,14 @@ pyyaml==6.0.1 # jupyter-events # mlflow # prefect -pyzmq==26.0.2 +pyzmq==26.0.3 # via # ipykernel # jupyter-client # jupyter-console # jupyter-server # qtconsole -qtconsole==5.5.1 +qtconsole==5.5.2 # via jupyter qtpy==2.4.1 # via qtconsole @@ -706,7 +720,7 @@ redis==5.0.4 # dioptra # dioptra (pyproject.toml) # rq -referencing==0.35.0 +referencing==0.35.1 # via # jsonschema # jsonschema-specifications @@ -732,12 +746,14 @@ rfc3986-validator==0.1.1 # jsonschema # jupyter-events rich==13.7.1 - # via dioptra (pyproject.toml) -rpds-py==0.18.0 + # via + # dioptra (pyproject.toml) + # modelscan +rpds-py==0.18.1 # via # jsonschema # referencing -rq==1.16.1 +rq==1.16.2 # via # dioptra # dioptra (pyproject.toml) @@ -836,7 +852,7 @@ sphinxcontrib-qthelp==1.0.7 # via sphinx sphinxcontrib-serializinghtml==1.1.10 # via sphinx -sqlalchemy==2.0.29 +sqlalchemy==2.0.30 # via # alembic # dioptra @@ -851,6 +867,8 @@ structlog==24.1.0 # via # dioptra # dioptra (pyproject.toml) +sympy==1.12 + # via torch tabulate==0.9.0 # via prefect tblib==3.0.0 @@ -859,6 +877,8 @@ tensorboard==2.16.2 # via dioptra (pyproject.toml) tensorboard-data-server==0.7.2 # via tensorboard +tensorflow-io-gcs-filesystem==0.34.0 + # via modelscan terminado==0.18.1 # via # jupyter-server @@ -867,7 +887,7 @@ text-unidecode==1.3 # via python-slugify threadpoolctl==3.5.0 # via scikit-learn -tifffile==2024.4.24 +tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum @@ -877,11 +897,15 @@ toml==0.10.2 # via prefect tomli==2.0.1 # via dioptra (pyproject.toml) +tomlkit==0.12.4 + # via modelscan toolz==0.12.1 # via # dask # distributed # partd +torch==2.3.0 + # via maite tornado==6.4 # via # distributed @@ -893,7 +917,7 @@ tornado==6.4 # terminado tox==4.15.0 # via dioptra (pyproject.toml) -tqdm==4.66.2 +tqdm==4.66.4 # via # adversarial-robustness-toolbox # kaggle @@ -923,7 +947,9 @@ typing-extensions==4.11.0 # dioptra # dioptra (pyproject.toml) # ipython + # maite # sqlalchemy + # torch tzdata==2024.1 # via # pandas @@ -952,7 +978,7 @@ webencodings==0.5.1 # tinycss2 websocket-client==1.8.0 # via jupyter-server -werkzeug==3.0.2 +werkzeug==3.0.3 # via # dioptra # dioptra (pyproject.toml) diff --git a/requirements/macos-amd64-py3.11-requirements-dev-pytorch.txt b/requirements/macos-amd64-py3.11-requirements-dev-pytorch.txt index 6d4802007..0be73e208 100644 --- a/requirements/macos-amd64-py3.11-requirements-dev-pytorch.txt +++ b/requirements/macos-amd64-py3.11-requirements-dev-pytorch.txt @@ -58,7 +58,7 @@ attrs==23.2.0 # referencing autopep8==2.1.0 # via dioptra (pyproject.toml) -babel==2.14.0 +babel==2.15.0 # via # jupyterlab-server # sphinx @@ -72,13 +72,13 @@ bleach==6.1.0 # via # kaggle # nbconvert -blinker==1.8.1 +blinker==1.8.2 # via flask -boto3==1.34.93 +boto3==1.34.99 # via # dioptra # dioptra (pyproject.toml) -botocore==1.34.93 +botocore==1.34.99 # via # boto3 # s3transfer @@ -115,6 +115,7 @@ click==8.1.7 # distributed # flask # mlflow + # modelscan # pip-tools # prefect # rq @@ -140,7 +141,7 @@ croniter==2.0.5 # via prefect cycler==0.12.1 # via matplotlib -dask==2024.4.2 +dask==2024.5.0 # via # distributed # prefect @@ -152,7 +153,7 @@ defusedxml==0.7.1 # via nbconvert distlib==0.3.8 # via virtualenv -distributed==2024.4.2 +distributed==2024.5.0 # via prefect docker==7.0.0 # via @@ -196,7 +197,7 @@ flask-accepts==0.18.4 # via # dioptra # dioptra (pyproject.toml) -flask-cors==4.0.0 +flask-cors==4.0.1 # via # dioptra # dioptra (pyproject.toml) @@ -247,7 +248,7 @@ graphql-relay==3.2.0 # via graphene greenlet==3.0.3 # via sqlalchemy -grpcio==1.62.2 +grpcio==1.63.0 # via tensorboard gunicorn==21.2.0 # via mlflow @@ -307,7 +308,7 @@ itsdangerous==2.2.0 # via flask jedi==0.19.1 # via ipython -jinja2==3.1.3 +jinja2==3.1.4 # via # cookiecutter # distributed @@ -326,13 +327,13 @@ jmespath==1.0.1 # via # boto3 # botocore -joblib==1.4.0 +joblib==1.4.2 # via scikit-learn json5==0.9.25 # via jupyterlab-server jsonpointer==2.4 # via jsonschema -jsonschema[format-nongpl]==4.21.1 +jsonschema[format-nongpl]==4.22.0 # via # dioptra # dioptra (pyproject.toml) @@ -401,6 +402,8 @@ locket==1.0.0 # partd lsprotocol==2023.0.1 # via pygls +maite[all-interop]==0.5.0 + # via dioptra (pyproject.toml) mako==1.3.3 # via alembic markdown==3.6 @@ -415,7 +418,7 @@ markupsafe==2.1.5 # mako # nbconvert # werkzeug -marshmallow==3.21.1 +marshmallow==3.21.2 # via # dioptra # dioptra (pyproject.toml) @@ -443,6 +446,8 @@ mistune==3.0.2 # via nbconvert mlflow==2.12.1 # via dioptra (pyproject.toml) +modelscan==0.7.3 + # via dioptra (pyproject.toml) mpmath==1.3.0 # via sympy msgpack==1.0.8 @@ -483,9 +488,9 @@ notebook-shim==0.2.4 # via # jupyterlab # notebook -nrtk==0.3.1 +nrtk==0.4.0 # via dioptra (pyproject.toml) -numpy==1.26.4 +numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy @@ -493,8 +498,10 @@ numpy==1.26.4 # dioptra (pyproject.toml) # imageio # imgaug + # maite # matplotlib # mlflow + # modelscan # nrtk # opencv-python # pandas @@ -553,7 +560,7 @@ pandocfilters==1.5.1 # via nbconvert parso==0.8.4 # via jedi -partd==1.4.1 +partd==1.4.2 # via dask passlib==1.7.4 # via @@ -613,7 +620,7 @@ pyarrow==15.0.2 # via # dioptra (pyproject.toml) # mlflow -pybsm==0.1.1 +pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via @@ -632,7 +639,7 @@ pyflakes==3.2.0 # via flake8 pygls==1.3.1 # via esbonio -pygments==2.17.2 +pygments==2.18.0 # via # ipython # jupyter-console @@ -701,14 +708,14 @@ pyyaml==6.0.1 # jupyter-events # mlflow # prefect -pyzmq==26.0.2 +pyzmq==26.0.3 # via # ipykernel # jupyter-client # jupyter-console # jupyter-server # qtconsole -qtconsole==5.5.1 +qtconsole==5.5.2 # via jupyter qtpy==2.4.1 # via qtconsole @@ -719,7 +726,7 @@ redis==5.0.4 # dioptra # dioptra (pyproject.toml) # rq -referencing==0.35.0 +referencing==0.35.1 # via # jsonschema # jsonschema-specifications @@ -745,12 +752,14 @@ rfc3986-validator==0.1.1 # jsonschema # jupyter-events rich==13.7.1 - # via dioptra (pyproject.toml) -rpds-py==0.18.0 + # via + # dioptra (pyproject.toml) + # modelscan +rpds-py==0.18.1 # via # jsonschema # referencing -rq==1.16.1 +rq==1.16.2 # via # dioptra # dioptra (pyproject.toml) @@ -849,7 +858,7 @@ sphinxcontrib-qthelp==1.0.7 # via sphinx sphinxcontrib-serializinghtml==1.1.10 # via sphinx -sqlalchemy==2.0.29 +sqlalchemy==2.0.30 # via # alembic # dioptra @@ -874,6 +883,8 @@ tensorboard==2.16.2 # via dioptra (pyproject.toml) tensorboard-data-server==0.7.2 # via tensorboard +tensorflow-io-gcs-filesystem==0.34.0 + # via modelscan terminado==0.18.1 # via # jupyter-server @@ -882,7 +893,7 @@ text-unidecode==1.3 # via python-slugify threadpoolctl==3.5.0 # via scikit-learn -tifffile==2024.4.24 +tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum @@ -892,6 +903,8 @@ toml==0.10.2 # via prefect tomli==2.0.1 # via dioptra (pyproject.toml) +tomlkit==0.12.4 + # via modelscan toolz==0.12.1 # via # dask @@ -900,6 +913,7 @@ toolz==0.12.1 torch==2.2.2 # via # -r requirements-dev-pytorch.in + # maite # torchaudio # torchvision torchaudio==2.2.2 @@ -917,7 +931,7 @@ tornado==6.4 # terminado tox==4.15.0 # via dioptra (pyproject.toml) -tqdm==4.66.2 +tqdm==4.66.4 # via # adversarial-robustness-toolbox # kaggle @@ -947,6 +961,7 @@ typing-extensions==4.11.0 # dioptra # dioptra (pyproject.toml) # ipython + # maite # sqlalchemy # torch tzdata==2024.1 @@ -977,7 +992,7 @@ webencodings==0.5.1 # tinycss2 websocket-client==1.8.0 # via jupyter-server -werkzeug==3.0.2 +werkzeug==3.0.3 # via # dioptra # dioptra (pyproject.toml) diff --git a/requirements/macos-amd64-py3.11-requirements-dev-tensorflow.txt b/requirements/macos-amd64-py3.11-requirements-dev-tensorflow.txt index 11dc21f93..3a3ef6387 100644 --- a/requirements/macos-amd64-py3.11-requirements-dev-tensorflow.txt +++ b/requirements/macos-amd64-py3.11-requirements-dev-tensorflow.txt @@ -61,7 +61,7 @@ attrs==23.2.0 # referencing autopep8==2.1.0 # via dioptra (pyproject.toml) -babel==2.14.0 +babel==2.15.0 # via # jupyterlab-server # sphinx @@ -75,13 +75,13 @@ bleach==6.1.0 # via # kaggle # nbconvert -blinker==1.8.1 +blinker==1.8.2 # via flask -boto3==1.34.93 +boto3==1.34.99 # via # dioptra # dioptra (pyproject.toml) -botocore==1.34.93 +botocore==1.34.99 # via # boto3 # s3transfer @@ -118,6 +118,7 @@ click==8.1.7 # distributed # flask # mlflow + # modelscan # pip-tools # prefect # rq @@ -143,7 +144,7 @@ croniter==2.0.5 # via prefect cycler==0.12.1 # via matplotlib -dask==2024.4.2 +dask==2024.5.0 # via # distributed # prefect @@ -155,7 +156,7 @@ defusedxml==0.7.1 # via nbconvert distlib==0.3.8 # via virtualenv -distributed==2024.4.2 +distributed==2024.5.0 # via prefect docker==7.0.0 # via @@ -176,6 +177,7 @@ fastjsonschema==2.19.1 # via nbformat filelock==3.14.0 # via + # torch # tox # virtualenv flake8==7.0.0 @@ -198,7 +200,7 @@ flask-accepts==0.18.4 # via # dioptra # dioptra (pyproject.toml) -flask-cors==4.0.0 +flask-cors==4.0.1 # via # dioptra # dioptra (pyproject.toml) @@ -235,6 +237,7 @@ frozenlist==1.4.1 fsspec==2024.3.1 # via # dask + # torch # universal-pathlib gast==0.5.4 # via tensorflow @@ -254,7 +257,7 @@ graphql-relay==3.2.0 # via graphene greenlet==3.0.3 # via sqlalchemy -grpcio==1.62.2 +grpcio==1.63.0 # via # tensorboard # tensorflow @@ -320,7 +323,7 @@ itsdangerous==2.2.0 # via flask jedi==0.19.1 # via ipython -jinja2==3.1.3 +jinja2==3.1.4 # via # cookiecutter # distributed @@ -332,19 +335,20 @@ jinja2==3.1.3 # mlflow # nbconvert # sphinx + # torch jinja2-time==0.2.0 # via cookiecutter jmespath==1.0.1 # via # boto3 # botocore -joblib==1.4.0 +joblib==1.4.2 # via scikit-learn json5==0.9.25 # via jupyterlab-server jsonpointer==2.4 # via jsonschema -jsonschema[format-nongpl]==4.21.1 +jsonschema[format-nongpl]==4.22.0 # via # dioptra # dioptra (pyproject.toml) @@ -417,6 +421,8 @@ locket==1.0.0 # partd lsprotocol==2023.0.1 # via pygls +maite[all-interop]==0.5.0 + # via dioptra (pyproject.toml) mako==1.3.3 # via alembic markdown==3.6 @@ -431,7 +437,7 @@ markupsafe==2.1.5 # mako # nbconvert # werkzeug -marshmallow==3.21.1 +marshmallow==3.21.2 # via # dioptra # dioptra (pyproject.toml) @@ -463,6 +469,10 @@ ml-dtypes==0.3.2 # tensorflow mlflow==2.12.1 # via dioptra (pyproject.toml) +modelscan==0.7.3 + # via dioptra (pyproject.toml) +mpmath==1.3.0 + # via sympy msgpack==1.0.8 # via # distributed @@ -494,16 +504,18 @@ nbformat==5.10.4 nest-asyncio==1.6.0 # via ipykernel networkx==3.3 - # via scikit-image + # via + # scikit-image + # torch notebook==7.1.3 # via jupyter notebook-shim==0.2.4 # via # jupyterlab # notebook -nrtk==0.3.1 +nrtk==0.4.0 # via dioptra (pyproject.toml) -numpy==1.26.4 +numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy @@ -513,9 +525,11 @@ numpy==1.26.4 # imageio # imgaug # keras + # maite # matplotlib # ml-dtypes # mlflow + # modelscan # nrtk # opencv-python # opt-einsum @@ -580,7 +594,7 @@ pandocfilters==1.5.1 # via nbconvert parso==0.8.4 # via jedi -partd==1.4.1 +partd==1.4.2 # via dask passlib==1.7.4 # via @@ -640,7 +654,7 @@ pyarrow==15.0.2 # via # dioptra (pyproject.toml) # mlflow -pybsm==0.1.1 +pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via @@ -659,7 +673,7 @@ pyflakes==3.2.0 # via flake8 pygls==1.3.1 # via esbonio -pygments==2.17.2 +pygments==2.18.0 # via # ipython # jupyter-console @@ -728,14 +742,14 @@ pyyaml==6.0.1 # jupyter-events # mlflow # prefect -pyzmq==26.0.2 +pyzmq==26.0.3 # via # ipykernel # jupyter-client # jupyter-console # jupyter-server # qtconsole -qtconsole==5.5.1 +qtconsole==5.5.2 # via jupyter qtpy==2.4.1 # via qtconsole @@ -746,7 +760,7 @@ redis==5.0.4 # dioptra # dioptra (pyproject.toml) # rq -referencing==0.35.0 +referencing==0.35.1 # via # jsonschema # jsonschema-specifications @@ -776,11 +790,12 @@ rich==13.7.1 # via # dioptra (pyproject.toml) # keras -rpds-py==0.18.0 + # modelscan +rpds-py==0.18.1 # via # jsonschema # referencing -rq==1.16.1 +rq==1.16.2 # via # dioptra # dioptra (pyproject.toml) @@ -882,7 +897,7 @@ sphinxcontrib-qthelp==1.0.7 # via sphinx sphinxcontrib-serializinghtml==1.1.10 # via sphinx -sqlalchemy==2.0.29 +sqlalchemy==2.0.30 # via # alembic # dioptra @@ -897,6 +912,8 @@ structlog==24.1.0 # via # dioptra # dioptra (pyproject.toml) +sympy==1.12 + # via torch tabulate==0.9.0 # via prefect tblib==3.0.0 @@ -909,8 +926,10 @@ tensorboard-data-server==0.7.2 # via tensorboard tensorflow==2.16.1 # via -r requirements-dev-tensorflow.in -tensorflow-io-gcs-filesystem==0.36.0 - # via tensorflow +tensorflow-io-gcs-filesystem==0.34.0 + # via + # modelscan + # tensorflow termcolor==2.4.0 # via tensorflow terminado==0.18.1 @@ -921,7 +940,7 @@ text-unidecode==1.3 # via python-slugify threadpoolctl==3.5.0 # via scikit-learn -tifffile==2024.4.24 +tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum @@ -931,11 +950,15 @@ toml==0.10.2 # via prefect tomli==2.0.1 # via dioptra (pyproject.toml) +tomlkit==0.12.4 + # via modelscan toolz==0.12.1 # via # dask # distributed # partd +torch==2.2.2 + # via maite tornado==6.4 # via # distributed @@ -947,7 +970,7 @@ tornado==6.4 # terminado tox==4.15.0 # via dioptra (pyproject.toml) -tqdm==4.66.2 +tqdm==4.66.4 # via # adversarial-robustness-toolbox # kaggle @@ -977,9 +1000,11 @@ typing-extensions==4.11.0 # dioptra # dioptra (pyproject.toml) # ipython + # maite # optree # sqlalchemy # tensorflow + # torch tzdata==2024.1 # via # pandas @@ -1008,7 +1033,7 @@ webencodings==0.5.1 # tinycss2 websocket-client==1.8.0 # via jupyter-server -werkzeug==3.0.2 +werkzeug==3.0.3 # via # dioptra # dioptra (pyproject.toml) diff --git a/requirements/macos-amd64-py3.11-requirements-dev.txt b/requirements/macos-amd64-py3.11-requirements-dev.txt index d2c419178..69461d073 100644 --- a/requirements/macos-amd64-py3.11-requirements-dev.txt +++ b/requirements/macos-amd64-py3.11-requirements-dev.txt @@ -56,7 +56,7 @@ attrs==23.2.0 # referencing autopep8==2.1.0 # via dioptra (pyproject.toml) -babel==2.14.0 +babel==2.15.0 # via # jupyterlab-server # sphinx @@ -70,13 +70,13 @@ bleach==6.1.0 # via # kaggle # nbconvert -blinker==1.8.1 +blinker==1.8.2 # via flask -boto3==1.34.93 +boto3==1.34.99 # via # dioptra # dioptra (pyproject.toml) -botocore==1.34.93 +botocore==1.34.99 # via # boto3 # s3transfer @@ -113,6 +113,7 @@ click==8.1.7 # distributed # flask # mlflow + # modelscan # pip-tools # prefect # rq @@ -138,7 +139,7 @@ croniter==2.0.5 # via prefect cycler==0.12.1 # via matplotlib -dask==2024.4.2 +dask==2024.5.0 # via # distributed # prefect @@ -150,7 +151,7 @@ defusedxml==0.7.1 # via nbconvert distlib==0.3.8 # via virtualenv -distributed==2024.4.2 +distributed==2024.5.0 # via prefect docker==7.0.0 # via @@ -171,6 +172,7 @@ fastjsonschema==2.19.1 # via nbformat filelock==3.14.0 # via + # torch # tox # virtualenv flake8==7.0.0 @@ -193,7 +195,7 @@ flask-accepts==0.18.4 # via # dioptra # dioptra (pyproject.toml) -flask-cors==4.0.0 +flask-cors==4.0.1 # via # dioptra # dioptra (pyproject.toml) @@ -228,6 +230,7 @@ frozenlist==1.4.1 fsspec==2024.3.1 # via # dask + # torch # universal-pathlib gitdb==4.0.11 # via gitpython @@ -243,7 +246,7 @@ graphql-relay==3.2.0 # via graphene greenlet==3.0.3 # via sqlalchemy -grpcio==1.62.2 +grpcio==1.63.0 # via tensorboard gunicorn==21.2.0 # via mlflow @@ -303,7 +306,7 @@ itsdangerous==2.2.0 # via flask jedi==0.19.1 # via ipython -jinja2==3.1.3 +jinja2==3.1.4 # via # cookiecutter # distributed @@ -315,19 +318,20 @@ jinja2==3.1.3 # mlflow # nbconvert # sphinx + # torch jinja2-time==0.2.0 # via cookiecutter jmespath==1.0.1 # via # boto3 # botocore -joblib==1.4.0 +joblib==1.4.2 # via scikit-learn json5==0.9.25 # via jupyterlab-server jsonpointer==2.4 # via jsonschema -jsonschema[format-nongpl]==4.21.1 +jsonschema[format-nongpl]==4.22.0 # via # dioptra # dioptra (pyproject.toml) @@ -396,6 +400,8 @@ locket==1.0.0 # partd lsprotocol==2023.0.1 # via pygls +maite[all-interop]==0.5.0 + # via dioptra (pyproject.toml) mako==1.3.3 # via alembic markdown==3.6 @@ -410,7 +416,7 @@ markupsafe==2.1.5 # mako # nbconvert # werkzeug -marshmallow==3.21.1 +marshmallow==3.21.2 # via # dioptra # dioptra (pyproject.toml) @@ -438,6 +444,10 @@ mistune==3.0.2 # via nbconvert mlflow==2.12.1 # via dioptra (pyproject.toml) +modelscan==0.7.3 + # via dioptra (pyproject.toml) +mpmath==1.3.0 + # via sympy msgpack==1.0.8 # via # distributed @@ -467,16 +477,18 @@ nbformat==5.10.4 nest-asyncio==1.6.0 # via ipykernel networkx==3.3 - # via scikit-image + # via + # scikit-image + # torch notebook==7.1.3 # via jupyter notebook-shim==0.2.4 # via # jupyterlab # notebook -nrtk==0.3.1 +nrtk==0.4.0 # via dioptra (pyproject.toml) -numpy==1.26.4 +numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy @@ -484,8 +496,10 @@ numpy==1.26.4 # dioptra (pyproject.toml) # imageio # imgaug + # maite # matplotlib # mlflow + # modelscan # nrtk # opencv-python # pandas @@ -543,7 +557,7 @@ pandocfilters==1.5.1 # via nbconvert parso==0.8.4 # via jedi -partd==1.4.1 +partd==1.4.2 # via dask passlib==1.7.4 # via @@ -602,7 +616,7 @@ pyarrow==15.0.2 # via # dioptra (pyproject.toml) # mlflow -pybsm==0.1.1 +pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via @@ -621,7 +635,7 @@ pyflakes==3.2.0 # via flake8 pygls==1.3.1 # via esbonio -pygments==2.17.2 +pygments==2.18.0 # via # ipython # jupyter-console @@ -690,14 +704,14 @@ pyyaml==6.0.1 # jupyter-events # mlflow # prefect -pyzmq==26.0.2 +pyzmq==26.0.3 # via # ipykernel # jupyter-client # jupyter-console # jupyter-server # qtconsole -qtconsole==5.5.1 +qtconsole==5.5.2 # via jupyter qtpy==2.4.1 # via qtconsole @@ -708,7 +722,7 @@ redis==5.0.4 # dioptra # dioptra (pyproject.toml) # rq -referencing==0.35.0 +referencing==0.35.1 # via # jsonschema # jsonschema-specifications @@ -734,12 +748,14 @@ rfc3986-validator==0.1.1 # jsonschema # jupyter-events rich==13.7.1 - # via dioptra (pyproject.toml) -rpds-py==0.18.0 + # via + # dioptra (pyproject.toml) + # modelscan +rpds-py==0.18.1 # via # jsonschema # referencing -rq==1.16.1 +rq==1.16.2 # via # dioptra # dioptra (pyproject.toml) @@ -838,7 +854,7 @@ sphinxcontrib-qthelp==1.0.7 # via sphinx sphinxcontrib-serializinghtml==1.1.10 # via sphinx -sqlalchemy==2.0.29 +sqlalchemy==2.0.30 # via # alembic # dioptra @@ -853,6 +869,8 @@ structlog==24.1.0 # via # dioptra # dioptra (pyproject.toml) +sympy==1.12 + # via torch tabulate==0.9.0 # via prefect tblib==3.0.0 @@ -861,6 +879,8 @@ tensorboard==2.16.2 # via dioptra (pyproject.toml) tensorboard-data-server==0.7.2 # via tensorboard +tensorflow-io-gcs-filesystem==0.34.0 + # via modelscan terminado==0.18.1 # via # jupyter-server @@ -869,7 +889,7 @@ text-unidecode==1.3 # via python-slugify threadpoolctl==3.5.0 # via scikit-learn -tifffile==2024.4.24 +tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum @@ -879,11 +899,15 @@ toml==0.10.2 # via prefect tomli==2.0.1 # via dioptra (pyproject.toml) +tomlkit==0.12.4 + # via modelscan toolz==0.12.1 # via # dask # distributed # partd +torch==2.2.2 + # via maite tornado==6.4 # via # distributed @@ -895,7 +919,7 @@ tornado==6.4 # terminado tox==4.15.0 # via dioptra (pyproject.toml) -tqdm==4.66.2 +tqdm==4.66.4 # via # adversarial-robustness-toolbox # kaggle @@ -925,7 +949,9 @@ typing-extensions==4.11.0 # dioptra # dioptra (pyproject.toml) # ipython + # maite # sqlalchemy + # torch tzdata==2024.1 # via # pandas @@ -954,7 +980,7 @@ webencodings==0.5.1 # tinycss2 websocket-client==1.8.0 # via jupyter-server -werkzeug==3.0.2 +werkzeug==3.0.3 # via # dioptra # dioptra (pyproject.toml) diff --git a/requirements/macos-arm64-py3.11-requirements-dev-pytorch.txt b/requirements/macos-arm64-py3.11-requirements-dev-pytorch.txt index 3b5df101c..2e16f4346 100644 --- a/requirements/macos-arm64-py3.11-requirements-dev-pytorch.txt +++ b/requirements/macos-arm64-py3.11-requirements-dev-pytorch.txt @@ -58,7 +58,7 @@ attrs==23.2.0 # referencing autopep8==2.1.0 # via dioptra (pyproject.toml) -babel==2.14.0 +babel==2.15.0 # via # jupyterlab-server # sphinx @@ -72,13 +72,13 @@ bleach==6.1.0 # via # kaggle # nbconvert -blinker==1.8.1 +blinker==1.8.2 # via flask -boto3==1.34.93 +boto3==1.34.99 # via # dioptra # dioptra (pyproject.toml) -botocore==1.34.93 +botocore==1.34.99 # via # boto3 # s3transfer @@ -115,6 +115,7 @@ click==8.1.7 # distributed # flask # mlflow + # modelscan # pip-tools # prefect # rq @@ -140,7 +141,7 @@ croniter==2.0.5 # via prefect cycler==0.12.1 # via matplotlib -dask==2024.4.2 +dask==2024.5.0 # via # distributed # prefect @@ -152,7 +153,7 @@ defusedxml==0.7.1 # via nbconvert distlib==0.3.8 # via virtualenv -distributed==2024.4.2 +distributed==2024.5.0 # via prefect docker==7.0.0 # via @@ -196,7 +197,7 @@ flask-accepts==0.18.4 # via # dioptra # dioptra (pyproject.toml) -flask-cors==4.0.0 +flask-cors==4.0.1 # via # dioptra # dioptra (pyproject.toml) @@ -245,7 +246,7 @@ graphql-core==3.2.3 # graphql-relay graphql-relay==3.2.0 # via graphene -grpcio==1.62.2 +grpcio==1.63.0 # via tensorboard gunicorn==21.2.0 # via mlflow @@ -305,7 +306,7 @@ itsdangerous==2.2.0 # via flask jedi==0.19.1 # via ipython -jinja2==3.1.3 +jinja2==3.1.4 # via # cookiecutter # distributed @@ -324,13 +325,13 @@ jmespath==1.0.1 # via # boto3 # botocore -joblib==1.4.0 +joblib==1.4.2 # via scikit-learn json5==0.9.25 # via jupyterlab-server jsonpointer==2.4 # via jsonschema -jsonschema[format-nongpl]==4.21.1 +jsonschema[format-nongpl]==4.22.0 # via # dioptra # dioptra (pyproject.toml) @@ -399,6 +400,8 @@ locket==1.0.0 # partd lsprotocol==2023.0.1 # via pygls +maite[all-interop]==0.5.0 + # via dioptra (pyproject.toml) mako==1.3.3 # via alembic markdown==3.6 @@ -413,7 +416,7 @@ markupsafe==2.1.5 # mako # nbconvert # werkzeug -marshmallow==3.21.1 +marshmallow==3.21.2 # via # dioptra # dioptra (pyproject.toml) @@ -441,6 +444,8 @@ mistune==3.0.2 # via nbconvert mlflow==2.12.1 # via dioptra (pyproject.toml) +modelscan==0.7.3 + # via dioptra (pyproject.toml) mpmath==1.3.0 # via sympy msgpack==1.0.8 @@ -481,9 +486,9 @@ notebook-shim==0.2.4 # via # jupyterlab # notebook -nrtk==0.3.1 +nrtk==0.4.0 # via dioptra (pyproject.toml) -numpy==1.26.4 +numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy @@ -491,8 +496,10 @@ numpy==1.26.4 # dioptra (pyproject.toml) # imageio # imgaug + # maite # matplotlib # mlflow + # modelscan # nrtk # opencv-python # pandas @@ -551,7 +558,7 @@ pandocfilters==1.5.1 # via nbconvert parso==0.8.4 # via jedi -partd==1.4.1 +partd==1.4.2 # via dask passlib==1.7.4 # via @@ -611,7 +618,7 @@ pyarrow==15.0.2 # via # dioptra (pyproject.toml) # mlflow -pybsm==0.1.1 +pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via @@ -630,7 +637,7 @@ pyflakes==3.2.0 # via flake8 pygls==1.3.1 # via esbonio -pygments==2.17.2 +pygments==2.18.0 # via # ipython # jupyter-console @@ -699,14 +706,14 @@ pyyaml==6.0.1 # jupyter-events # mlflow # prefect -pyzmq==26.0.2 +pyzmq==26.0.3 # via # ipykernel # jupyter-client # jupyter-console # jupyter-server # qtconsole -qtconsole==5.5.1 +qtconsole==5.5.2 # via jupyter qtpy==2.4.1 # via qtconsole @@ -717,7 +724,7 @@ redis==5.0.4 # dioptra # dioptra (pyproject.toml) # rq -referencing==0.35.0 +referencing==0.35.1 # via # jsonschema # jsonschema-specifications @@ -743,12 +750,14 @@ rfc3986-validator==0.1.1 # jsonschema # jupyter-events rich==13.7.1 - # via dioptra (pyproject.toml) -rpds-py==0.18.0 + # via + # dioptra (pyproject.toml) + # modelscan +rpds-py==0.18.1 # via # jsonschema # referencing -rq==1.16.1 +rq==1.16.2 # via # dioptra # dioptra (pyproject.toml) @@ -847,7 +856,7 @@ sphinxcontrib-qthelp==1.0.7 # via sphinx sphinxcontrib-serializinghtml==1.1.10 # via sphinx -sqlalchemy==2.0.29 +sqlalchemy==2.0.30 # via # alembic # dioptra @@ -872,6 +881,8 @@ tensorboard==2.16.2 # via dioptra (pyproject.toml) tensorboard-data-server==0.7.2 # via tensorboard +tensorflow-io-gcs-filesystem==0.34.0 + # via modelscan terminado==0.18.1 # via # jupyter-server @@ -880,7 +891,7 @@ text-unidecode==1.3 # via python-slugify threadpoolctl==3.5.0 # via scikit-learn -tifffile==2024.4.24 +tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum @@ -890,6 +901,8 @@ toml==0.10.2 # via prefect tomli==2.0.1 # via dioptra (pyproject.toml) +tomlkit==0.12.4 + # via modelscan toolz==0.12.1 # via # dask @@ -898,6 +911,7 @@ toolz==0.12.1 torch==2.2.2 # via # -r requirements-dev-pytorch.in + # maite # torchaudio # torchvision torchaudio==2.2.2 @@ -915,7 +929,7 @@ tornado==6.4 # terminado tox==4.15.0 # via dioptra (pyproject.toml) -tqdm==4.66.2 +tqdm==4.66.4 # via # adversarial-robustness-toolbox # kaggle @@ -945,6 +959,7 @@ typing-extensions==4.11.0 # dioptra # dioptra (pyproject.toml) # ipython + # maite # sqlalchemy # torch tzdata==2024.1 @@ -975,7 +990,7 @@ webencodings==0.5.1 # tinycss2 websocket-client==1.8.0 # via jupyter-server -werkzeug==3.0.2 +werkzeug==3.0.3 # via # dioptra # dioptra (pyproject.toml) diff --git a/requirements/macos-arm64-py3.11-requirements-dev-tensorflow.txt b/requirements/macos-arm64-py3.11-requirements-dev-tensorflow.txt index 0270bc2da..67b3aa332 100644 --- a/requirements/macos-arm64-py3.11-requirements-dev-tensorflow.txt +++ b/requirements/macos-arm64-py3.11-requirements-dev-tensorflow.txt @@ -61,7 +61,7 @@ attrs==23.2.0 # referencing autopep8==2.1.0 # via dioptra (pyproject.toml) -babel==2.14.0 +babel==2.15.0 # via # jupyterlab-server # sphinx @@ -75,13 +75,13 @@ bleach==6.1.0 # via # kaggle # nbconvert -blinker==1.8.1 +blinker==1.8.2 # via flask -boto3==1.34.93 +boto3==1.34.99 # via # dioptra # dioptra (pyproject.toml) -botocore==1.34.93 +botocore==1.34.99 # via # boto3 # s3transfer @@ -118,6 +118,7 @@ click==8.1.7 # distributed # flask # mlflow + # modelscan # pip-tools # prefect # rq @@ -143,7 +144,7 @@ croniter==2.0.5 # via prefect cycler==0.12.1 # via matplotlib -dask==2024.4.2 +dask==2024.5.0 # via # distributed # prefect @@ -155,7 +156,7 @@ defusedxml==0.7.1 # via nbconvert distlib==0.3.8 # via virtualenv -distributed==2024.4.2 +distributed==2024.5.0 # via prefect docker==7.0.0 # via @@ -176,6 +177,7 @@ fastjsonschema==2.19.1 # via nbformat filelock==3.14.0 # via + # torch # tox # virtualenv flake8==7.0.0 @@ -198,7 +200,7 @@ flask-accepts==0.18.4 # via # dioptra # dioptra (pyproject.toml) -flask-cors==4.0.0 +flask-cors==4.0.1 # via # dioptra # dioptra (pyproject.toml) @@ -235,6 +237,7 @@ frozenlist==1.4.1 fsspec==2024.3.1 # via # dask + # torch # universal-pathlib gast==0.5.4 # via tensorflow @@ -252,7 +255,7 @@ graphql-core==3.2.3 # graphql-relay graphql-relay==3.2.0 # via graphene -grpcio==1.62.2 +grpcio==1.63.0 # via # tensorboard # tensorflow @@ -318,7 +321,7 @@ itsdangerous==2.2.0 # via flask jedi==0.19.1 # via ipython -jinja2==3.1.3 +jinja2==3.1.4 # via # cookiecutter # distributed @@ -330,19 +333,20 @@ jinja2==3.1.3 # mlflow # nbconvert # sphinx + # torch jinja2-time==0.2.0 # via cookiecutter jmespath==1.0.1 # via # boto3 # botocore -joblib==1.4.0 +joblib==1.4.2 # via scikit-learn json5==0.9.25 # via jupyterlab-server jsonpointer==2.4 # via jsonschema -jsonschema[format-nongpl]==4.21.1 +jsonschema[format-nongpl]==4.22.0 # via # dioptra # dioptra (pyproject.toml) @@ -415,6 +419,8 @@ locket==1.0.0 # partd lsprotocol==2023.0.1 # via pygls +maite[all-interop]==0.5.0 + # via dioptra (pyproject.toml) mako==1.3.3 # via alembic markdown==3.6 @@ -429,7 +435,7 @@ markupsafe==2.1.5 # mako # nbconvert # werkzeug -marshmallow==3.21.1 +marshmallow==3.21.2 # via # dioptra # dioptra (pyproject.toml) @@ -461,6 +467,10 @@ ml-dtypes==0.3.2 # tensorflow mlflow==2.12.1 # via dioptra (pyproject.toml) +modelscan==0.7.3 + # via dioptra (pyproject.toml) +mpmath==1.3.0 + # via sympy msgpack==1.0.8 # via # distributed @@ -492,16 +502,18 @@ nbformat==5.10.4 nest-asyncio==1.6.0 # via ipykernel networkx==3.3 - # via scikit-image + # via + # scikit-image + # torch notebook==7.1.3 # via jupyter notebook-shim==0.2.4 # via # jupyterlab # notebook -nrtk==0.3.1 +nrtk==0.4.0 # via dioptra (pyproject.toml) -numpy==1.26.4 +numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy @@ -511,9 +523,11 @@ numpy==1.26.4 # imageio # imgaug # keras + # maite # matplotlib # ml-dtypes # mlflow + # modelscan # nrtk # opencv-python # opt-einsum @@ -578,7 +592,7 @@ pandocfilters==1.5.1 # via nbconvert parso==0.8.4 # via jedi -partd==1.4.1 +partd==1.4.2 # via dask passlib==1.7.4 # via @@ -638,7 +652,7 @@ pyarrow==15.0.2 # via # dioptra (pyproject.toml) # mlflow -pybsm==0.1.1 +pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via @@ -657,7 +671,7 @@ pyflakes==3.2.0 # via flake8 pygls==1.3.1 # via esbonio -pygments==2.17.2 +pygments==2.18.0 # via # ipython # jupyter-console @@ -726,14 +740,14 @@ pyyaml==6.0.1 # jupyter-events # mlflow # prefect -pyzmq==26.0.2 +pyzmq==26.0.3 # via # ipykernel # jupyter-client # jupyter-console # jupyter-server # qtconsole -qtconsole==5.5.1 +qtconsole==5.5.2 # via jupyter qtpy==2.4.1 # via qtconsole @@ -744,7 +758,7 @@ redis==5.0.4 # dioptra # dioptra (pyproject.toml) # rq -referencing==0.35.0 +referencing==0.35.1 # via # jsonschema # jsonschema-specifications @@ -774,11 +788,12 @@ rich==13.7.1 # via # dioptra (pyproject.toml) # keras -rpds-py==0.18.0 + # modelscan +rpds-py==0.18.1 # via # jsonschema # referencing -rq==1.16.1 +rq==1.16.2 # via # dioptra # dioptra (pyproject.toml) @@ -881,7 +896,7 @@ sphinxcontrib-qthelp==1.0.7 # via sphinx sphinxcontrib-serializinghtml==1.1.10 # via sphinx -sqlalchemy==2.0.29 +sqlalchemy==2.0.30 # via # alembic # dioptra @@ -896,6 +911,8 @@ structlog==24.1.0 # via # dioptra # dioptra (pyproject.toml) +sympy==1.12 + # via torch tabulate==0.9.0 # via prefect tblib==3.0.0 @@ -908,8 +925,10 @@ tensorboard-data-server==0.7.2 # via tensorboard tensorflow==2.16.1 # via -r requirements-dev-tensorflow.in -tensorflow-io-gcs-filesystem==0.36.0 - # via tensorflow +tensorflow-io-gcs-filesystem==0.34.0 + # via + # modelscan + # tensorflow tensorflow-metal==1.1.0 ; sys_platform == "darwin" and (platform_machine == "aarch64" or platform_machine == "arm64") # via -r requirements-dev-tensorflow.in termcolor==2.4.0 @@ -922,7 +941,7 @@ text-unidecode==1.3 # via python-slugify threadpoolctl==3.5.0 # via scikit-learn -tifffile==2024.4.24 +tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum @@ -932,11 +951,15 @@ toml==0.10.2 # via prefect tomli==2.0.1 # via dioptra (pyproject.toml) +tomlkit==0.12.4 + # via modelscan toolz==0.12.1 # via # dask # distributed # partd +torch==2.3.0 + # via maite tornado==6.4 # via # distributed @@ -948,7 +971,7 @@ tornado==6.4 # terminado tox==4.15.0 # via dioptra (pyproject.toml) -tqdm==4.66.2 +tqdm==4.66.4 # via # adversarial-robustness-toolbox # kaggle @@ -978,9 +1001,11 @@ typing-extensions==4.11.0 # dioptra # dioptra (pyproject.toml) # ipython + # maite # optree # sqlalchemy # tensorflow + # torch tzdata==2024.1 # via # pandas @@ -1009,7 +1034,7 @@ webencodings==0.5.1 # tinycss2 websocket-client==1.8.0 # via jupyter-server -werkzeug==3.0.2 +werkzeug==3.0.3 # via # dioptra # dioptra (pyproject.toml) diff --git a/requirements/macos-arm64-py3.11-requirements-dev.txt b/requirements/macos-arm64-py3.11-requirements-dev.txt index 7984bbc64..9566ac0d8 100644 --- a/requirements/macos-arm64-py3.11-requirements-dev.txt +++ b/requirements/macos-arm64-py3.11-requirements-dev.txt @@ -56,7 +56,7 @@ attrs==23.2.0 # referencing autopep8==2.1.0 # via dioptra (pyproject.toml) -babel==2.14.0 +babel==2.15.0 # via # jupyterlab-server # sphinx @@ -70,13 +70,13 @@ bleach==6.1.0 # via # kaggle # nbconvert -blinker==1.8.1 +blinker==1.8.2 # via flask -boto3==1.34.93 +boto3==1.34.99 # via # dioptra # dioptra (pyproject.toml) -botocore==1.34.93 +botocore==1.34.99 # via # boto3 # s3transfer @@ -113,6 +113,7 @@ click==8.1.7 # distributed # flask # mlflow + # modelscan # pip-tools # prefect # rq @@ -138,7 +139,7 @@ croniter==2.0.5 # via prefect cycler==0.12.1 # via matplotlib -dask==2024.4.2 +dask==2024.5.0 # via # distributed # prefect @@ -150,7 +151,7 @@ defusedxml==0.7.1 # via nbconvert distlib==0.3.8 # via virtualenv -distributed==2024.4.2 +distributed==2024.5.0 # via prefect docker==7.0.0 # via @@ -171,6 +172,7 @@ fastjsonschema==2.19.1 # via nbformat filelock==3.14.0 # via + # torch # tox # virtualenv flake8==7.0.0 @@ -193,7 +195,7 @@ flask-accepts==0.18.4 # via # dioptra # dioptra (pyproject.toml) -flask-cors==4.0.0 +flask-cors==4.0.1 # via # dioptra # dioptra (pyproject.toml) @@ -228,6 +230,7 @@ frozenlist==1.4.1 fsspec==2024.3.1 # via # dask + # torch # universal-pathlib gitdb==4.0.11 # via gitpython @@ -241,7 +244,7 @@ graphql-core==3.2.3 # graphql-relay graphql-relay==3.2.0 # via graphene -grpcio==1.62.2 +grpcio==1.63.0 # via tensorboard gunicorn==21.2.0 # via mlflow @@ -301,7 +304,7 @@ itsdangerous==2.2.0 # via flask jedi==0.19.1 # via ipython -jinja2==3.1.3 +jinja2==3.1.4 # via # cookiecutter # distributed @@ -313,19 +316,20 @@ jinja2==3.1.3 # mlflow # nbconvert # sphinx + # torch jinja2-time==0.2.0 # via cookiecutter jmespath==1.0.1 # via # boto3 # botocore -joblib==1.4.0 +joblib==1.4.2 # via scikit-learn json5==0.9.25 # via jupyterlab-server jsonpointer==2.4 # via jsonschema -jsonschema[format-nongpl]==4.21.1 +jsonschema[format-nongpl]==4.22.0 # via # dioptra # dioptra (pyproject.toml) @@ -394,6 +398,8 @@ locket==1.0.0 # partd lsprotocol==2023.0.1 # via pygls +maite[all-interop]==0.5.0 + # via dioptra (pyproject.toml) mako==1.3.3 # via alembic markdown==3.6 @@ -408,7 +414,7 @@ markupsafe==2.1.5 # mako # nbconvert # werkzeug -marshmallow==3.21.1 +marshmallow==3.21.2 # via # dioptra # dioptra (pyproject.toml) @@ -436,6 +442,10 @@ mistune==3.0.2 # via nbconvert mlflow==2.12.1 # via dioptra (pyproject.toml) +modelscan==0.7.3 + # via dioptra (pyproject.toml) +mpmath==1.3.0 + # via sympy msgpack==1.0.8 # via # distributed @@ -465,16 +475,18 @@ nbformat==5.10.4 nest-asyncio==1.6.0 # via ipykernel networkx==3.3 - # via scikit-image + # via + # scikit-image + # torch notebook==7.1.3 # via jupyter notebook-shim==0.2.4 # via # jupyterlab # notebook -nrtk==0.3.1 +nrtk==0.4.0 # via dioptra (pyproject.toml) -numpy==1.26.4 +numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy @@ -482,8 +494,10 @@ numpy==1.26.4 # dioptra (pyproject.toml) # imageio # imgaug + # maite # matplotlib # mlflow + # modelscan # nrtk # opencv-python # pandas @@ -541,7 +555,7 @@ pandocfilters==1.5.1 # via nbconvert parso==0.8.4 # via jedi -partd==1.4.1 +partd==1.4.2 # via dask passlib==1.7.4 # via @@ -600,7 +614,7 @@ pyarrow==15.0.2 # via # dioptra (pyproject.toml) # mlflow -pybsm==0.1.1 +pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via @@ -619,7 +633,7 @@ pyflakes==3.2.0 # via flake8 pygls==1.3.1 # via esbonio -pygments==2.17.2 +pygments==2.18.0 # via # ipython # jupyter-console @@ -688,14 +702,14 @@ pyyaml==6.0.1 # jupyter-events # mlflow # prefect -pyzmq==26.0.2 +pyzmq==26.0.3 # via # ipykernel # jupyter-client # jupyter-console # jupyter-server # qtconsole -qtconsole==5.5.1 +qtconsole==5.5.2 # via jupyter qtpy==2.4.1 # via qtconsole @@ -706,7 +720,7 @@ redis==5.0.4 # dioptra # dioptra (pyproject.toml) # rq -referencing==0.35.0 +referencing==0.35.1 # via # jsonschema # jsonschema-specifications @@ -732,12 +746,14 @@ rfc3986-validator==0.1.1 # jsonschema # jupyter-events rich==13.7.1 - # via dioptra (pyproject.toml) -rpds-py==0.18.0 + # via + # dioptra (pyproject.toml) + # modelscan +rpds-py==0.18.1 # via # jsonschema # referencing -rq==1.16.1 +rq==1.16.2 # via # dioptra # dioptra (pyproject.toml) @@ -836,7 +852,7 @@ sphinxcontrib-qthelp==1.0.7 # via sphinx sphinxcontrib-serializinghtml==1.1.10 # via sphinx -sqlalchemy==2.0.29 +sqlalchemy==2.0.30 # via # alembic # dioptra @@ -851,6 +867,8 @@ structlog==24.1.0 # via # dioptra # dioptra (pyproject.toml) +sympy==1.12 + # via torch tabulate==0.9.0 # via prefect tblib==3.0.0 @@ -859,6 +877,8 @@ tensorboard==2.16.2 # via dioptra (pyproject.toml) tensorboard-data-server==0.7.2 # via tensorboard +tensorflow-io-gcs-filesystem==0.34.0 + # via modelscan terminado==0.18.1 # via # jupyter-server @@ -867,7 +887,7 @@ text-unidecode==1.3 # via python-slugify threadpoolctl==3.5.0 # via scikit-learn -tifffile==2024.4.24 +tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum @@ -877,11 +897,15 @@ toml==0.10.2 # via prefect tomli==2.0.1 # via dioptra (pyproject.toml) +tomlkit==0.12.4 + # via modelscan toolz==0.12.1 # via # dask # distributed # partd +torch==2.3.0 + # via maite tornado==6.4 # via # distributed @@ -893,7 +917,7 @@ tornado==6.4 # terminado tox==4.15.0 # via dioptra (pyproject.toml) -tqdm==4.66.2 +tqdm==4.66.4 # via # adversarial-robustness-toolbox # kaggle @@ -923,7 +947,9 @@ typing-extensions==4.11.0 # dioptra # dioptra (pyproject.toml) # ipython + # maite # sqlalchemy + # torch tzdata==2024.1 # via # pandas @@ -952,7 +978,7 @@ webencodings==0.5.1 # tinycss2 websocket-client==1.8.0 # via jupyter-server -werkzeug==3.0.2 +werkzeug==3.0.3 # via # dioptra # dioptra (pyproject.toml) diff --git a/requirements/win-amd64-py3.11-requirements-dev-pytorch.txt b/requirements/win-amd64-py3.11-requirements-dev-pytorch.txt index 79599995c..2b8cc3cae 100644 --- a/requirements/win-amd64-py3.11-requirements-dev-pytorch.txt +++ b/requirements/win-amd64-py3.11-requirements-dev-pytorch.txt @@ -56,7 +56,7 @@ attrs==23.2.0 # referencing autopep8==2.1.0 # via dioptra (pyproject.toml) -babel==2.14.0 +babel==2.15.0 # via # jupyterlab-server # sphinx @@ -70,13 +70,13 @@ bleach==6.1.0 # via # kaggle # nbconvert -blinker==1.8.1 +blinker==1.8.2 # via flask -boto3==1.34.93 +boto3==1.34.99 # via # dioptra # dioptra (pyproject.toml) -botocore==1.34.93 +botocore==1.34.99 # via # boto3 # s3transfer @@ -113,6 +113,7 @@ click==8.1.7 # distributed # flask # mlflow + # modelscan # pip-tools # prefect # rq @@ -145,7 +146,7 @@ croniter==2.0.5 # via prefect cycler==0.12.1 # via matplotlib -dask==2024.4.2 +dask==2024.5.0 # via # distributed # prefect @@ -157,7 +158,7 @@ defusedxml==0.7.1 # via nbconvert distlib==0.3.8 # via virtualenv -distributed==2024.4.2 +distributed==2024.5.0 # via prefect docker==7.0.0 # via @@ -201,7 +202,7 @@ flask-accepts==0.18.4 # via # dioptra # dioptra (pyproject.toml) -flask-cors==4.0.0 +flask-cors==4.0.1 # via # dioptra # dioptra (pyproject.toml) @@ -252,7 +253,7 @@ graphql-relay==3.2.0 # via graphene greenlet==3.0.3 # via sqlalchemy -grpcio==1.62.2 +grpcio==1.63.0 # via tensorboard h11==0.14.0 # via httpcore @@ -310,7 +311,7 @@ itsdangerous==2.2.0 # via flask jedi==0.19.1 # via ipython -jinja2==3.1.3 +jinja2==3.1.4 # via # cookiecutter # distributed @@ -329,13 +330,13 @@ jmespath==1.0.1 # via # boto3 # botocore -joblib==1.4.0 +joblib==1.4.2 # via scikit-learn json5==0.9.25 # via jupyterlab-server jsonpointer==2.4 # via jsonschema -jsonschema[format-nongpl]==4.21.1 +jsonschema[format-nongpl]==4.22.0 # via # dioptra # dioptra (pyproject.toml) @@ -404,6 +405,8 @@ locket==1.0.0 # partd lsprotocol==2023.0.1 # via pygls +maite[all-interop]==0.5.0 + # via dioptra (pyproject.toml) mako==1.3.3 # via alembic markdown==3.6 @@ -418,7 +421,7 @@ markupsafe==2.1.5 # mako # nbconvert # werkzeug -marshmallow==3.21.1 +marshmallow==3.21.2 # via # dioptra # dioptra (pyproject.toml) @@ -446,6 +449,8 @@ mistune==3.0.2 # via nbconvert mlflow==2.12.1 # via dioptra (pyproject.toml) +modelscan==0.7.3 + # via dioptra (pyproject.toml) mpmath==1.3.0 # via sympy msgpack==1.0.8 @@ -486,9 +491,9 @@ notebook-shim==0.2.4 # via # jupyterlab # notebook -nrtk==0.3.1 +nrtk==0.4.0 # via dioptra (pyproject.toml) -numpy==1.26.4 +numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy @@ -496,8 +501,10 @@ numpy==1.26.4 # dioptra (pyproject.toml) # imageio # imgaug + # maite # matplotlib # mlflow + # modelscan # nrtk # opencv-python # pandas @@ -555,7 +562,7 @@ pandocfilters==1.5.1 # via nbconvert parso==0.8.4 # via jedi -partd==1.4.1 +partd==1.4.2 # via dask passlib==1.7.4 # via @@ -609,7 +616,7 @@ pyarrow==15.0.2 # via # dioptra (pyproject.toml) # mlflow -pybsm==0.1.1 +pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via @@ -628,7 +635,7 @@ pyflakes==3.2.0 # via flake8 pygls==1.3.1 # via esbonio -pygments==2.17.2 +pygments==2.18.0 # via # ipython # jupyter-console @@ -706,14 +713,14 @@ pyyaml==6.0.1 # jupyter-events # mlflow # prefect -pyzmq==26.0.2 +pyzmq==26.0.3 # via # ipykernel # jupyter-client # jupyter-console # jupyter-server # qtconsole -qtconsole==5.5.1 +qtconsole==5.5.2 # via jupyter qtpy==2.4.1 # via qtconsole @@ -724,7 +731,7 @@ redis==5.0.4 # dioptra # dioptra (pyproject.toml) # rq -referencing==0.35.0 +referencing==0.35.1 # via # jsonschema # jsonschema-specifications @@ -750,12 +757,14 @@ rfc3986-validator==0.1.1 # jsonschema # jupyter-events rich==13.7.1 - # via dioptra (pyproject.toml) -rpds-py==0.18.0 + # via + # dioptra (pyproject.toml) + # modelscan +rpds-py==0.18.1 # via # jsonschema # referencing -rq==1.16.1 +rq==1.16.2 # via # dioptra # dioptra (pyproject.toml) @@ -854,7 +863,7 @@ sphinxcontrib-qthelp==1.0.7 # via sphinx sphinxcontrib-serializinghtml==1.1.10 # via sphinx -sqlalchemy==2.0.29 +sqlalchemy==2.0.30 # via # alembic # dioptra @@ -879,6 +888,8 @@ tensorboard==2.16.2 # via dioptra (pyproject.toml) tensorboard-data-server==0.7.2 # via tensorboard +tensorflow-io-gcs-filesystem==0.31.0 + # via modelscan terminado==0.18.1 # via # jupyter-server @@ -887,7 +898,7 @@ text-unidecode==1.3 # via python-slugify threadpoolctl==3.5.0 # via scikit-learn -tifffile==2024.4.24 +tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum @@ -897,6 +908,8 @@ toml==0.10.2 # via prefect tomli==2.0.1 # via dioptra (pyproject.toml) +tomlkit==0.12.4 + # via modelscan toolz==0.12.1 # via # dask @@ -905,6 +918,7 @@ toolz==0.12.1 torch==2.2.2 # via # -r requirements-dev-pytorch.in + # maite # torchaudio # torchvision torchaudio==2.2.2 @@ -922,7 +936,7 @@ tornado==6.4 # terminado tox==4.15.0 # via dioptra (pyproject.toml) -tqdm==4.66.2 +tqdm==4.66.4 # via # adversarial-robustness-toolbox # kaggle @@ -952,6 +966,7 @@ typing-extensions==4.11.0 # dioptra # dioptra (pyproject.toml) # ipython + # maite # sqlalchemy # torch tzdata==2024.1 @@ -984,7 +999,7 @@ webencodings==0.5.1 # tinycss2 websocket-client==1.8.0 # via jupyter-server -werkzeug==3.0.2 +werkzeug==3.0.3 # via # dioptra # dioptra (pyproject.toml) diff --git a/requirements/win-amd64-py3.11-requirements-dev-tensorflow.txt b/requirements/win-amd64-py3.11-requirements-dev-tensorflow.txt index a573d0ea1..addb0df75 100644 --- a/requirements/win-amd64-py3.11-requirements-dev-tensorflow.txt +++ b/requirements/win-amd64-py3.11-requirements-dev-tensorflow.txt @@ -59,7 +59,7 @@ attrs==23.2.0 # referencing autopep8==2.1.0 # via dioptra (pyproject.toml) -babel==2.14.0 +babel==2.15.0 # via # jupyterlab-server # sphinx @@ -73,13 +73,13 @@ bleach==6.1.0 # via # kaggle # nbconvert -blinker==1.8.1 +blinker==1.8.2 # via flask -boto3==1.34.93 +boto3==1.34.99 # via # dioptra # dioptra (pyproject.toml) -botocore==1.34.93 +botocore==1.34.99 # via # boto3 # s3transfer @@ -116,6 +116,7 @@ click==8.1.7 # distributed # flask # mlflow + # modelscan # pip-tools # prefect # rq @@ -148,7 +149,7 @@ croniter==2.0.5 # via prefect cycler==0.12.1 # via matplotlib -dask==2024.4.2 +dask==2024.5.0 # via # distributed # prefect @@ -160,7 +161,7 @@ defusedxml==0.7.1 # via nbconvert distlib==0.3.8 # via virtualenv -distributed==2024.4.2 +distributed==2024.5.0 # via prefect docker==7.0.0 # via @@ -181,6 +182,7 @@ fastjsonschema==2.19.1 # via nbformat filelock==3.14.0 # via + # torch # tox # virtualenv flake8==7.0.0 @@ -203,7 +205,7 @@ flask-accepts==0.18.4 # via # dioptra # dioptra (pyproject.toml) -flask-cors==4.0.0 +flask-cors==4.0.1 # via # dioptra # dioptra (pyproject.toml) @@ -240,6 +242,7 @@ frozenlist==1.4.1 fsspec==2024.3.1 # via # dask + # torch # universal-pathlib gast==0.5.4 # via tensorflow-intel @@ -259,7 +262,7 @@ graphql-relay==3.2.0 # via graphene greenlet==3.0.3 # via sqlalchemy -grpcio==1.62.2 +grpcio==1.63.0 # via # tensorboard # tensorflow-intel @@ -302,6 +305,8 @@ injector==0.21.0 # via # dioptra # dioptra (pyproject.toml) +intel-openmp==2021.4.0 + # via mkl ipykernel==6.29.4 # via # dioptra (pyproject.toml) @@ -323,7 +328,7 @@ itsdangerous==2.2.0 # via flask jedi==0.19.1 # via ipython -jinja2==3.1.3 +jinja2==3.1.4 # via # cookiecutter # distributed @@ -335,19 +340,20 @@ jinja2==3.1.3 # mlflow # nbconvert # sphinx + # torch jinja2-time==0.2.0 # via cookiecutter jmespath==1.0.1 # via # boto3 # botocore -joblib==1.4.0 +joblib==1.4.2 # via scikit-learn json5==0.9.25 # via jupyterlab-server jsonpointer==2.4 # via jsonschema -jsonschema[format-nongpl]==4.21.1 +jsonschema[format-nongpl]==4.22.0 # via # dioptra # dioptra (pyproject.toml) @@ -420,6 +426,8 @@ locket==1.0.0 # partd lsprotocol==2023.0.1 # via pygls +maite[all-interop]==0.5.0 + # via dioptra (pyproject.toml) mako==1.3.3 # via alembic markdown==3.6 @@ -434,7 +442,7 @@ markupsafe==2.1.5 # mako # nbconvert # werkzeug -marshmallow==3.21.1 +marshmallow==3.21.2 # via # dioptra # dioptra (pyproject.toml) @@ -460,12 +468,18 @@ mdurl==0.1.2 # via markdown-it-py mistune==3.0.2 # via nbconvert +mkl==2021.4.0 + # via torch ml-dtypes==0.3.2 # via # keras # tensorflow-intel mlflow==2.12.1 # via dioptra (pyproject.toml) +modelscan==0.7.3 + # via dioptra (pyproject.toml) +mpmath==1.3.0 + # via sympy msgpack==1.0.8 # via # distributed @@ -497,16 +511,18 @@ nbformat==5.10.4 nest-asyncio==1.6.0 # via ipykernel networkx==3.3 - # via scikit-image + # via + # scikit-image + # torch notebook==7.1.3 # via jupyter notebook-shim==0.2.4 # via # jupyterlab # notebook -nrtk==0.3.1 +nrtk==0.4.0 # via dioptra (pyproject.toml) -numpy==1.26.4 +numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy @@ -516,9 +532,11 @@ numpy==1.26.4 # imageio # imgaug # keras + # maite # matplotlib # ml-dtypes # mlflow + # modelscan # nrtk # opencv-python # opt-einsum @@ -582,7 +600,7 @@ pandocfilters==1.5.1 # via nbconvert parso==0.8.4 # via jedi -partd==1.4.1 +partd==1.4.2 # via dask passlib==1.7.4 # via @@ -636,7 +654,7 @@ pyarrow==15.0.2 # via # dioptra (pyproject.toml) # mlflow -pybsm==0.1.1 +pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via @@ -655,7 +673,7 @@ pyflakes==3.2.0 # via flake8 pygls==1.3.1 # via esbonio -pygments==2.17.2 +pygments==2.18.0 # via # ipython # jupyter-console @@ -733,14 +751,14 @@ pyyaml==6.0.1 # jupyter-events # mlflow # prefect -pyzmq==26.0.2 +pyzmq==26.0.3 # via # ipykernel # jupyter-client # jupyter-console # jupyter-server # qtconsole -qtconsole==5.5.1 +qtconsole==5.5.2 # via jupyter qtpy==2.4.1 # via qtconsole @@ -751,7 +769,7 @@ redis==5.0.4 # dioptra # dioptra (pyproject.toml) # rq -referencing==0.35.0 +referencing==0.35.1 # via # jsonschema # jsonschema-specifications @@ -781,11 +799,12 @@ rich==13.7.1 # via # dioptra (pyproject.toml) # keras -rpds-py==0.18.0 + # modelscan +rpds-py==0.18.1 # via # jsonschema # referencing -rq==1.16.1 +rq==1.16.2 # via # dioptra # dioptra (pyproject.toml) @@ -887,7 +906,7 @@ sphinxcontrib-qthelp==1.0.7 # via sphinx sphinxcontrib-serializinghtml==1.1.10 # via sphinx -sqlalchemy==2.0.29 +sqlalchemy==2.0.30 # via # alembic # dioptra @@ -902,8 +921,12 @@ structlog==24.1.0 # via # dioptra # dioptra (pyproject.toml) +sympy==1.12 + # via torch tabulate==0.9.0 # via prefect +tbb==2021.12.0 + # via mkl tblib==3.0.0 # via distributed tensorboard==2.16.2 @@ -917,7 +940,9 @@ tensorflow==2.16.1 tensorflow-intel==2.16.1 # via tensorflow tensorflow-io-gcs-filesystem==0.31.0 - # via tensorflow-intel + # via + # modelscan + # tensorflow-intel termcolor==2.4.0 # via tensorflow-intel terminado==0.18.1 @@ -928,7 +953,7 @@ text-unidecode==1.3 # via python-slugify threadpoolctl==3.5.0 # via scikit-learn -tifffile==2024.4.24 +tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum @@ -938,11 +963,15 @@ toml==0.10.2 # via prefect tomli==2.0.1 # via dioptra (pyproject.toml) +tomlkit==0.12.4 + # via modelscan toolz==0.12.1 # via # dask # distributed # partd +torch==2.3.0 + # via maite tornado==6.4 # via # distributed @@ -954,7 +983,7 @@ tornado==6.4 # terminado tox==4.15.0 # via dioptra (pyproject.toml) -tqdm==4.66.2 +tqdm==4.66.4 # via # adversarial-robustness-toolbox # kaggle @@ -984,9 +1013,11 @@ typing-extensions==4.11.0 # dioptra # dioptra (pyproject.toml) # ipython + # maite # optree # sqlalchemy # tensorflow-intel + # torch tzdata==2024.1 # via # pandas @@ -1017,7 +1048,7 @@ webencodings==0.5.1 # tinycss2 websocket-client==1.8.0 # via jupyter-server -werkzeug==3.0.2 +werkzeug==3.0.3 # via # dioptra # dioptra (pyproject.toml) diff --git a/requirements/win-amd64-py3.11-requirements-dev.txt b/requirements/win-amd64-py3.11-requirements-dev.txt index 69db1e0e2..eeab86edc 100644 --- a/requirements/win-amd64-py3.11-requirements-dev.txt +++ b/requirements/win-amd64-py3.11-requirements-dev.txt @@ -54,7 +54,7 @@ attrs==23.2.0 # referencing autopep8==2.1.0 # via dioptra (pyproject.toml) -babel==2.14.0 +babel==2.15.0 # via # jupyterlab-server # sphinx @@ -68,13 +68,13 @@ bleach==6.1.0 # via # kaggle # nbconvert -blinker==1.8.1 +blinker==1.8.2 # via flask -boto3==1.34.93 +boto3==1.34.99 # via # dioptra # dioptra (pyproject.toml) -botocore==1.34.93 +botocore==1.34.99 # via # boto3 # s3transfer @@ -111,6 +111,7 @@ click==8.1.7 # distributed # flask # mlflow + # modelscan # pip-tools # prefect # rq @@ -143,7 +144,7 @@ croniter==2.0.5 # via prefect cycler==0.12.1 # via matplotlib -dask==2024.4.2 +dask==2024.5.0 # via # distributed # prefect @@ -155,7 +156,7 @@ defusedxml==0.7.1 # via nbconvert distlib==0.3.8 # via virtualenv -distributed==2024.4.2 +distributed==2024.5.0 # via prefect docker==7.0.0 # via @@ -176,6 +177,7 @@ fastjsonschema==2.19.1 # via nbformat filelock==3.14.0 # via + # torch # tox # virtualenv flake8==7.0.0 @@ -198,7 +200,7 @@ flask-accepts==0.18.4 # via # dioptra # dioptra (pyproject.toml) -flask-cors==4.0.0 +flask-cors==4.0.1 # via # dioptra # dioptra (pyproject.toml) @@ -233,6 +235,7 @@ frozenlist==1.4.1 fsspec==2024.3.1 # via # dask + # torch # universal-pathlib gitdb==4.0.11 # via gitpython @@ -248,7 +251,7 @@ graphql-relay==3.2.0 # via graphene greenlet==3.0.3 # via sqlalchemy -grpcio==1.62.2 +grpcio==1.63.0 # via tensorboard h11==0.14.0 # via httpcore @@ -285,6 +288,8 @@ injector==0.21.0 # via # dioptra # dioptra (pyproject.toml) +intel-openmp==2021.4.0 + # via mkl ipykernel==6.29.4 # via # dioptra (pyproject.toml) @@ -306,7 +311,7 @@ itsdangerous==2.2.0 # via flask jedi==0.19.1 # via ipython -jinja2==3.1.3 +jinja2==3.1.4 # via # cookiecutter # distributed @@ -318,19 +323,20 @@ jinja2==3.1.3 # mlflow # nbconvert # sphinx + # torch jinja2-time==0.2.0 # via cookiecutter jmespath==1.0.1 # via # boto3 # botocore -joblib==1.4.0 +joblib==1.4.2 # via scikit-learn json5==0.9.25 # via jupyterlab-server jsonpointer==2.4 # via jsonschema -jsonschema[format-nongpl]==4.21.1 +jsonschema[format-nongpl]==4.22.0 # via # dioptra # dioptra (pyproject.toml) @@ -399,6 +405,8 @@ locket==1.0.0 # partd lsprotocol==2023.0.1 # via pygls +maite[all-interop]==0.5.0 + # via dioptra (pyproject.toml) mako==1.3.3 # via alembic markdown==3.6 @@ -413,7 +421,7 @@ markupsafe==2.1.5 # mako # nbconvert # werkzeug -marshmallow==3.21.1 +marshmallow==3.21.2 # via # dioptra # dioptra (pyproject.toml) @@ -439,8 +447,14 @@ mdurl==0.1.2 # via markdown-it-py mistune==3.0.2 # via nbconvert +mkl==2021.4.0 + # via torch mlflow==2.12.1 # via dioptra (pyproject.toml) +modelscan==0.7.3 + # via dioptra (pyproject.toml) +mpmath==1.3.0 + # via sympy msgpack==1.0.8 # via # distributed @@ -470,16 +484,18 @@ nbformat==5.10.4 nest-asyncio==1.6.0 # via ipykernel networkx==3.3 - # via scikit-image + # via + # scikit-image + # torch notebook==7.1.3 # via jupyter notebook-shim==0.2.4 # via # jupyterlab # notebook -nrtk==0.3.1 +nrtk==0.4.0 # via dioptra (pyproject.toml) -numpy==1.26.4 +numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy @@ -487,8 +503,10 @@ numpy==1.26.4 # dioptra (pyproject.toml) # imageio # imgaug + # maite # matplotlib # mlflow + # modelscan # nrtk # opencv-python # pandas @@ -545,7 +563,7 @@ pandocfilters==1.5.1 # via nbconvert parso==0.8.4 # via jedi -partd==1.4.1 +partd==1.4.2 # via dask passlib==1.7.4 # via @@ -598,7 +616,7 @@ pyarrow==15.0.2 # via # dioptra (pyproject.toml) # mlflow -pybsm==0.1.1 +pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via @@ -617,7 +635,7 @@ pyflakes==3.2.0 # via flake8 pygls==1.3.1 # via esbonio -pygments==2.17.2 +pygments==2.18.0 # via # ipython # jupyter-console @@ -695,14 +713,14 @@ pyyaml==6.0.1 # jupyter-events # mlflow # prefect -pyzmq==26.0.2 +pyzmq==26.0.3 # via # ipykernel # jupyter-client # jupyter-console # jupyter-server # qtconsole -qtconsole==5.5.1 +qtconsole==5.5.2 # via jupyter qtpy==2.4.1 # via qtconsole @@ -713,7 +731,7 @@ redis==5.0.4 # dioptra # dioptra (pyproject.toml) # rq -referencing==0.35.0 +referencing==0.35.1 # via # jsonschema # jsonschema-specifications @@ -739,12 +757,14 @@ rfc3986-validator==0.1.1 # jsonschema # jupyter-events rich==13.7.1 - # via dioptra (pyproject.toml) -rpds-py==0.18.0 + # via + # dioptra (pyproject.toml) + # modelscan +rpds-py==0.18.1 # via # jsonschema # referencing -rq==1.16.1 +rq==1.16.2 # via # dioptra # dioptra (pyproject.toml) @@ -843,7 +863,7 @@ sphinxcontrib-qthelp==1.0.7 # via sphinx sphinxcontrib-serializinghtml==1.1.10 # via sphinx -sqlalchemy==2.0.29 +sqlalchemy==2.0.30 # via # alembic # dioptra @@ -858,14 +878,20 @@ structlog==24.1.0 # via # dioptra # dioptra (pyproject.toml) +sympy==1.12 + # via torch tabulate==0.9.0 # via prefect +tbb==2021.12.0 + # via mkl tblib==3.0.0 # via distributed tensorboard==2.16.2 # via dioptra (pyproject.toml) tensorboard-data-server==0.7.2 # via tensorboard +tensorflow-io-gcs-filesystem==0.31.0 + # via modelscan terminado==0.18.1 # via # jupyter-server @@ -874,7 +900,7 @@ text-unidecode==1.3 # via python-slugify threadpoolctl==3.5.0 # via scikit-learn -tifffile==2024.4.24 +tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum @@ -884,11 +910,15 @@ toml==0.10.2 # via prefect tomli==2.0.1 # via dioptra (pyproject.toml) +tomlkit==0.12.4 + # via modelscan toolz==0.12.1 # via # dask # distributed # partd +torch==2.3.0 + # via maite tornado==6.4 # via # distributed @@ -900,7 +930,7 @@ tornado==6.4 # terminado tox==4.15.0 # via dioptra (pyproject.toml) -tqdm==4.66.2 +tqdm==4.66.4 # via # adversarial-robustness-toolbox # kaggle @@ -930,7 +960,9 @@ typing-extensions==4.11.0 # dioptra # dioptra (pyproject.toml) # ipython + # maite # sqlalchemy + # torch tzdata==2024.1 # via # pandas @@ -961,7 +993,7 @@ webencodings==0.5.1 # tinycss2 websocket-client==1.8.0 # via jupyter-server -werkzeug==3.0.2 +werkzeug==3.0.3 # via # dioptra # dioptra (pyproject.toml) From 71dd19d6783f5d6197f0192d293e1de2fd589e45 Mon Sep 17 00:00:00 2001 From: bjpatrick <137509145+bjpatrick@users.noreply.github.com> Date: Tue, 7 May 2024 09:22:11 -0500 Subject: [PATCH 04/18] Add files via upload Updating requirements files to include maite and modelscan --- ...64-py3.11-mlflow-tracking-requirements.txt | 14 +- ...-amd64-py3.11-pytorch-cpu-requirements.txt | 63 +++++---- ...-amd64-py3.11-pytorch-gpu-requirements.txt | 63 +++++---- ...inux-amd64-py3.11-restapi-requirements.txt | 24 ++-- ...64-py3.11-tensorflow2-cpu-requirements.txt | 116 +++++++++++++---- ...64-py3.11-tensorflow2-gpu-requirements.txt | 121 ++++++++++++++---- ...64-py3.11-mlflow-tracking-requirements.txt | 14 +- ...-arm64-py3.11-pytorch-cpu-requirements.txt | 63 +++++---- ...inux-arm64-py3.11-restapi-requirements.txt | 24 ++-- ...64-py3.11-tensorflow2-cpu-requirements.txt | 81 ++++++++---- 10 files changed, 392 insertions(+), 191 deletions(-) diff --git a/docker/requirements/linux-amd64-py3.11-mlflow-tracking-requirements.txt b/docker/requirements/linux-amd64-py3.11-mlflow-tracking-requirements.txt index 9ed827eef..06a660b60 100644 --- a/docker/requirements/linux-amd64-py3.11-mlflow-tracking-requirements.txt +++ b/docker/requirements/linux-amd64-py3.11-mlflow-tracking-requirements.txt @@ -8,11 +8,11 @@ alembic==1.13.1 # via mlflow aniso8601==9.0.1 # via graphene -blinker==1.8.1 +blinker==1.8.2 # via flask -boto3==1.34.93 +boto3==1.34.99 # via -r docker/pip-tools/mlflow-tracking-requirements.in -botocore==1.34.93 +botocore==1.34.99 # via # boto3 # s3transfer @@ -60,7 +60,7 @@ importlib-metadata==7.1.0 # via mlflow itsdangerous==2.2.0 # via flask -jinja2==3.1.3 +jinja2==3.1.4 # via # flask # mlflow @@ -68,7 +68,7 @@ jmespath==1.0.1 # via # boto3 # botocore -joblib==1.4.0 +joblib==1.4.2 # via scikit-learn kiwisolver==1.4.5 # via matplotlib @@ -145,7 +145,7 @@ six==1.16.0 # querystring-parser smmap==5.0.1 # via gitdb -sqlalchemy==2.0.29 +sqlalchemy==2.0.30 # via # alembic # mlflow @@ -164,7 +164,7 @@ urllib3==2.2.1 # botocore # docker # requests -werkzeug==3.0.2 +werkzeug==3.0.3 # via flask zipp==3.18.1 # via importlib-metadata diff --git a/docker/requirements/linux-amd64-py3.11-pytorch-cpu-requirements.txt b/docker/requirements/linux-amd64-py3.11-pytorch-cpu-requirements.txt index a7103f741..b2b8ef14c 100644 --- a/docker/requirements/linux-amd64-py3.11-pytorch-cpu-requirements.txt +++ b/docker/requirements/linux-amd64-py3.11-pytorch-cpu-requirements.txt @@ -25,11 +25,11 @@ attrs==23.2.0 # via # jsonschema # referencing -blinker==1.8.1 +blinker==1.8.2 # via flask -boto3==1.34.93 +boto3==1.34.99 # via dioptra (pyproject.toml) -botocore==1.34.93 +botocore==1.34.99 # via # boto3 # s3transfer @@ -44,6 +44,7 @@ click==8.1.7 # distributed # flask # mlflow + # modelscan # prefect # rq cloudpickle==3.0.0 @@ -58,11 +59,11 @@ croniter==2.0.5 # via prefect cycler==0.12.1 # via matplotlib -dask==2024.4.2 +dask==2024.5.0 # via # distributed # prefect -distributed==2024.4.2 +distributed==2024.5.0 # via prefect docker==7.0.0 # via @@ -87,7 +88,7 @@ flask==3.0.3 # mlflow flask-accepts==0.18.4 # via dioptra (pyproject.toml) -flask-cors==4.0.0 +flask-cors==4.0.1 # via dioptra (pyproject.toml) flask-login==0.6.3 # via dioptra (pyproject.toml) @@ -121,7 +122,7 @@ graphql-relay==3.2.0 # via graphene greenlet==3.0.3 # via sqlalchemy -grpcio==1.62.2 +grpcio==1.63.0 # via tensorboard gunicorn==21.2.0 # via mlflow @@ -145,7 +146,7 @@ injector==0.21.0 # via dioptra (pyproject.toml) itsdangerous==2.2.0 # via flask -jinja2==3.1.3 +jinja2==3.1.4 # via # distributed # flask @@ -155,9 +156,9 @@ jmespath==1.0.1 # via # boto3 # botocore -joblib==1.4.0 +joblib==1.4.2 # via scikit-learn -jsonschema==4.21.1 +jsonschema==4.22.0 # via # dioptra (pyproject.toml) # flask-restx @@ -171,6 +172,8 @@ locket==1.0.0 # via # distributed # partd +maite[all-interop]==0.5.0 + # via dioptra (pyproject.toml) mako==1.3.3 # via alembic markdown==3.6 @@ -184,7 +187,7 @@ markupsafe==2.1.5 # jinja2 # mako # werkzeug -marshmallow==3.21.1 +marshmallow==3.21.2 # via # dioptra (pyproject.toml) # flask-accepts @@ -203,6 +206,8 @@ mdurl==0.1.2 # via markdown-it-py mlflow==2.12.1 # via dioptra (pyproject.toml) +modelscan==0.7.3 + # via dioptra (pyproject.toml) mpmath==1.3.0 # via sympy msgpack==1.0.8 @@ -217,17 +222,19 @@ networkx==3.3 # via # scikit-image # torch -nrtk==0.3.1 +nrtk==0.4.0 # via dioptra (pyproject.toml) -numpy==1.26.4 +numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy # dioptra (pyproject.toml) # imageio # imgaug + # maite # matplotlib # mlflow + # modelscan # nrtk # opencv-python # pandas @@ -298,7 +305,7 @@ pandas==2.2.2 # via # dioptra (pyproject.toml) # mlflow -partd==1.4.1 +partd==1.4.2 # via dask passlib==1.7.4 # via dioptra (pyproject.toml) @@ -328,13 +335,13 @@ pyarrow==15.0.2 # via # dioptra (pyproject.toml) # mlflow -pybsm==0.1.1 +pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) # nrtk -pygments==2.17.2 +pygments==2.18.0 # via rich pyparsing==3.1.2 # via matplotlib @@ -374,7 +381,7 @@ redis==5.0.4 # via # dioptra (pyproject.toml) # rq -referencing==0.35.0 +referencing==0.35.1 # via # jsonschema # jsonschema-specifications @@ -386,12 +393,14 @@ requests==2.31.0 # prefect # smqtk-dataprovider rich==13.7.1 - # via dioptra (pyproject.toml) -rpds-py==0.18.0 + # via + # dioptra (pyproject.toml) + # modelscan +rpds-py==0.18.1 # via # jsonschema # referencing -rq==1.16.1 +rq==1.16.2 # via dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 @@ -455,7 +464,7 @@ smqtk-image-io==0.17.1 # smqtk-detection sortedcontainers==2.4.0 # via distributed -sqlalchemy==2.0.29 +sqlalchemy==2.0.30 # via # alembic # dioptra (pyproject.toml) @@ -475,16 +484,20 @@ tensorboard==2.16.2 # via dioptra (pyproject.toml) tensorboard-data-server==0.7.2 # via tensorboard +tensorflow-io-gcs-filesystem==0.34.0 + # via modelscan text-unidecode==1.3 # via python-slugify threadpoolctl==3.5.0 # via scikit-learn -tifffile==2024.4.24 +tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum toml==0.10.2 # via prefect +tomlkit==0.12.4 + # via modelscan toolz==0.12.1 # via # dask @@ -493,6 +506,7 @@ toolz==0.12.1 torch==2.2.2 # via # -r requirements-dev-pytorch.in + # maite # torchaudio # torchvision torchaudio==2.2.2 @@ -501,7 +515,7 @@ torchvision==0.17.2 # via -r requirements-dev-pytorch.in tornado==6.4 # via distributed -tqdm==4.66.2 +tqdm==4.66.4 # via # adversarial-robustness-toolbox # nrtk @@ -511,6 +525,7 @@ typing-extensions==4.11.0 # via # alembic # dioptra (pyproject.toml) + # maite # sqlalchemy # torch tzdata==2024.1 @@ -524,7 +539,7 @@ urllib3==2.2.1 # docker # prefect # requests -werkzeug==3.0.2 +werkzeug==3.0.3 # via # dioptra (pyproject.toml) # flask diff --git a/docker/requirements/linux-amd64-py3.11-pytorch-gpu-requirements.txt b/docker/requirements/linux-amd64-py3.11-pytorch-gpu-requirements.txt index 94a084a72..456fdf504 100644 --- a/docker/requirements/linux-amd64-py3.11-pytorch-gpu-requirements.txt +++ b/docker/requirements/linux-amd64-py3.11-pytorch-gpu-requirements.txt @@ -25,11 +25,11 @@ attrs==23.2.0 # via # jsonschema # referencing -blinker==1.8.1 +blinker==1.8.2 # via flask -boto3==1.34.93 +boto3==1.34.99 # via dioptra (pyproject.toml) -botocore==1.34.93 +botocore==1.34.99 # via # boto3 # s3transfer @@ -44,6 +44,7 @@ click==8.1.7 # distributed # flask # mlflow + # modelscan # prefect # rq cloudpickle==3.0.0 @@ -58,11 +59,11 @@ croniter==2.0.5 # via prefect cycler==0.12.1 # via matplotlib -dask==2024.4.2 +dask==2024.5.0 # via # distributed # prefect -distributed==2024.4.2 +distributed==2024.5.0 # via prefect docker==7.0.0 # via @@ -87,7 +88,7 @@ flask==3.0.3 # mlflow flask-accepts==0.18.4 # via dioptra (pyproject.toml) -flask-cors==4.0.0 +flask-cors==4.0.1 # via dioptra (pyproject.toml) flask-login==0.6.3 # via dioptra (pyproject.toml) @@ -121,7 +122,7 @@ graphql-relay==3.2.0 # via graphene greenlet==3.0.3 # via sqlalchemy -grpcio==1.62.2 +grpcio==1.63.0 # via tensorboard gunicorn==21.2.0 # via mlflow @@ -145,7 +146,7 @@ injector==0.21.0 # via dioptra (pyproject.toml) itsdangerous==2.2.0 # via flask -jinja2==3.1.3 +jinja2==3.1.4 # via # distributed # flask @@ -155,9 +156,9 @@ jmespath==1.0.1 # via # boto3 # botocore -joblib==1.4.0 +joblib==1.4.2 # via scikit-learn -jsonschema==4.21.1 +jsonschema==4.22.0 # via # dioptra (pyproject.toml) # flask-restx @@ -171,6 +172,8 @@ locket==1.0.0 # via # distributed # partd +maite[all-interop]==0.5.0 + # via dioptra (pyproject.toml) mako==1.3.3 # via alembic markdown==3.6 @@ -184,7 +187,7 @@ markupsafe==2.1.5 # jinja2 # mako # werkzeug -marshmallow==3.21.1 +marshmallow==3.21.2 # via # dioptra (pyproject.toml) # flask-accepts @@ -203,6 +206,8 @@ mdurl==0.1.2 # via markdown-it-py mlflow==2.12.1 # via dioptra (pyproject.toml) +modelscan==0.7.3 + # via dioptra (pyproject.toml) mpmath==1.3.0 # via sympy msgpack==1.0.8 @@ -217,17 +222,19 @@ networkx==3.3 # via # scikit-image # torch -nrtk==0.3.1 +nrtk==0.4.0 # via dioptra (pyproject.toml) -numpy==1.26.4 +numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy # dioptra (pyproject.toml) # imageio # imgaug + # maite # matplotlib # mlflow + # modelscan # nrtk # opencv-python # pandas @@ -298,7 +305,7 @@ pandas==2.2.2 # via # dioptra (pyproject.toml) # mlflow -partd==1.4.1 +partd==1.4.2 # via dask passlib==1.7.4 # via dioptra (pyproject.toml) @@ -328,13 +335,13 @@ pyarrow==15.0.2 # via # dioptra (pyproject.toml) # mlflow -pybsm==0.1.1 +pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) # nrtk -pygments==2.17.2 +pygments==2.18.0 # via rich pyparsing==3.1.2 # via matplotlib @@ -374,7 +381,7 @@ redis==5.0.4 # via # dioptra (pyproject.toml) # rq -referencing==0.35.0 +referencing==0.35.1 # via # jsonschema # jsonschema-specifications @@ -386,12 +393,14 @@ requests==2.31.0 # prefect # smqtk-dataprovider rich==13.7.1 - # via dioptra (pyproject.toml) -rpds-py==0.18.0 + # via + # dioptra (pyproject.toml) + # modelscan +rpds-py==0.18.1 # via # jsonschema # referencing -rq==1.16.1 +rq==1.16.2 # via dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 @@ -455,7 +464,7 @@ smqtk-image-io==0.17.1 # smqtk-detection sortedcontainers==2.4.0 # via distributed -sqlalchemy==2.0.29 +sqlalchemy==2.0.30 # via # alembic # dioptra (pyproject.toml) @@ -475,16 +484,20 @@ tensorboard==2.16.2 # via dioptra (pyproject.toml) tensorboard-data-server==0.7.2 # via tensorboard +tensorflow-io-gcs-filesystem==0.34.0 + # via modelscan text-unidecode==1.3 # via python-slugify threadpoolctl==3.5.0 # via scikit-learn -tifffile==2024.4.24 +tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum toml==0.10.2 # via prefect +tomlkit==0.12.4 + # via modelscan toolz==0.12.1 # via # dask @@ -493,6 +506,7 @@ toolz==0.12.1 torch==2.2.2 # via # -r requirements-dev-pytorch-gpu.in + # maite # torchaudio # torchvision torchaudio==2.2.2 @@ -501,7 +515,7 @@ torchvision==0.17.2 # via -r requirements-dev-pytorch-gpu.in tornado==6.4 # via distributed -tqdm==4.66.2 +tqdm==4.66.4 # via # adversarial-robustness-toolbox # nrtk @@ -511,6 +525,7 @@ typing-extensions==4.11.0 # via # alembic # dioptra (pyproject.toml) + # maite # sqlalchemy # torch tzdata==2024.1 @@ -524,7 +539,7 @@ urllib3==2.2.1 # docker # prefect # requests -werkzeug==3.0.2 +werkzeug==3.0.3 # via # dioptra (pyproject.toml) # flask diff --git a/docker/requirements/linux-amd64-py3.11-restapi-requirements.txt b/docker/requirements/linux-amd64-py3.11-restapi-requirements.txt index 4cccd2dc6..63f5c5f57 100644 --- a/docker/requirements/linux-amd64-py3.11-restapi-requirements.txt +++ b/docker/requirements/linux-amd64-py3.11-restapi-requirements.txt @@ -16,11 +16,11 @@ attrs==23.2.0 # via # jsonschema # referencing -blinker==1.8.1 +blinker==1.8.2 # via flask -boto3==1.34.93 +boto3==1.34.99 # via dioptra (pyproject.toml) -botocore==1.34.93 +botocore==1.34.99 # via # boto3 # s3transfer @@ -50,7 +50,7 @@ flask==3.0.3 # flask-sqlalchemy flask-accepts==0.18.4 # via dioptra (pyproject.toml) -flask-cors==4.0.0 +flask-cors==4.0.1 # via dioptra (pyproject.toml) flask-login==0.6.3 # via dioptra (pyproject.toml) @@ -82,13 +82,13 @@ injector==0.21.0 # via dioptra (pyproject.toml) itsdangerous==2.2.0 # via flask -jinja2==3.1.3 +jinja2==3.1.4 # via flask jmespath==1.0.1 # via # boto3 # botocore -jsonschema==4.21.1 +jsonschema==4.22.0 # via # dioptra (pyproject.toml) # flask-restx @@ -101,7 +101,7 @@ markupsafe==2.1.5 # jinja2 # mako # werkzeug -marshmallow==3.21.1 +marshmallow==3.21.2 # via # dioptra (pyproject.toml) # flask-accepts @@ -149,7 +149,7 @@ redis==5.0.4 # via # dioptra (pyproject.toml) # rq -referencing==0.35.0 +referencing==0.35.1 # via # jsonschema # jsonschema-specifications @@ -157,11 +157,11 @@ requests==2.31.0 # via # dioptra (pyproject.toml) # mlflow-skinny -rpds-py==0.18.0 +rpds-py==0.18.1 # via # jsonschema # referencing -rq==1.16.1 +rq==1.16.2 # via dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 @@ -173,7 +173,7 @@ six==1.16.0 # via python-dateutil smmap==5.0.1 # via gitdb -sqlalchemy==2.0.29 +sqlalchemy==2.0.30 # via # alembic # dioptra (pyproject.toml) @@ -193,7 +193,7 @@ urllib3==2.2.1 # via # botocore # requests -werkzeug==3.0.2 +werkzeug==3.0.3 # via # dioptra (pyproject.toml) # flask diff --git a/docker/requirements/linux-amd64-py3.11-tensorflow2-cpu-requirements.txt b/docker/requirements/linux-amd64-py3.11-tensorflow2-cpu-requirements.txt index d920ddff8..919361c6b 100644 --- a/docker/requirements/linux-amd64-py3.11-tensorflow2-cpu-requirements.txt +++ b/docker/requirements/linux-amd64-py3.11-tensorflow2-cpu-requirements.txt @@ -28,11 +28,11 @@ attrs==23.2.0 # via # jsonschema # referencing -blinker==1.8.1 +blinker==1.8.2 # via flask -boto3==1.34.93 +boto3==1.34.99 # via dioptra (pyproject.toml) -botocore==1.34.93 +botocore==1.34.99 # via # boto3 # s3transfer @@ -47,6 +47,7 @@ click==8.1.7 # distributed # flask # mlflow + # modelscan # prefect # rq cloudpickle==3.0.0 @@ -61,11 +62,11 @@ croniter==2.0.5 # via prefect cycler==0.12.1 # via matplotlib -dask==2024.4.2 +dask==2024.5.0 # via # distributed # prefect -distributed==2024.4.2 +distributed==2024.5.0 # via prefect docker==7.0.0 # via @@ -75,6 +76,10 @@ entrypoints==0.4 # via # dioptra (pyproject.toml) # mlflow +filelock==3.14.0 + # via + # torch + # triton flask==3.0.3 # via # dioptra (pyproject.toml) @@ -86,7 +91,7 @@ flask==3.0.3 # mlflow flask-accepts==0.18.4 # via dioptra (pyproject.toml) -flask-cors==4.0.0 +flask-cors==4.0.1 # via dioptra (pyproject.toml) flask-login==0.6.3 # via dioptra (pyproject.toml) @@ -105,7 +110,9 @@ flatbuffers==24.3.25 fonttools==4.51.0 # via matplotlib fsspec==2024.3.1 - # via dask + # via + # dask + # torch gast==0.5.4 # via tensorflow gitdb==4.0.11 @@ -124,7 +131,7 @@ graphql-relay==3.2.0 # via graphene greenlet==3.0.3 # via sqlalchemy -grpcio==1.62.2 +grpcio==1.63.0 # via # tensorboard # tensorflow @@ -154,18 +161,19 @@ injector==0.21.0 # via dioptra (pyproject.toml) itsdangerous==2.2.0 # via flask -jinja2==3.1.3 +jinja2==3.1.4 # via # distributed # flask # mlflow + # torch jmespath==1.0.1 # via # boto3 # botocore -joblib==1.4.0 +joblib==1.4.2 # via scikit-learn -jsonschema==4.21.1 +jsonschema==4.22.0 # via # dioptra (pyproject.toml) # flask-restx @@ -183,6 +191,8 @@ locket==1.0.0 # via # distributed # partd +maite[all-interop]==0.5.0 + # via dioptra (pyproject.toml) mako==1.3.3 # via alembic markdown==3.6 @@ -196,7 +206,7 @@ markupsafe==2.1.5 # jinja2 # mako # werkzeug -marshmallow==3.21.1 +marshmallow==3.21.2 # via # dioptra (pyproject.toml) # flask-accepts @@ -219,6 +229,10 @@ ml-dtypes==0.3.2 # tensorflow mlflow==2.12.1 # via dioptra (pyproject.toml) +modelscan==0.7.3 + # via dioptra (pyproject.toml) +mpmath==1.3.0 + # via sympy msgpack==1.0.8 # via # distributed @@ -230,10 +244,12 @@ mypy-extensions==1.0.0 namex==0.0.8 # via keras networkx==3.3 - # via scikit-image -nrtk==0.3.1 + # via + # scikit-image + # torch +nrtk==0.4.0 # via dioptra (pyproject.toml) -numpy==1.26.4 +numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy @@ -242,9 +258,11 @@ numpy==1.26.4 # imageio # imgaug # keras + # maite # matplotlib # ml-dtypes # mlflow + # modelscan # nrtk # opencv-python # opt-einsum @@ -263,6 +281,37 @@ numpy==1.26.4 # tensorboard # tensorflow # tifffile +nvidia-cublas-cu12==12.1.3.1 + # via + # nvidia-cudnn-cu12 + # nvidia-cusolver-cu12 + # torch +nvidia-cuda-cupti-cu12==12.1.105 + # via torch +nvidia-cuda-nvrtc-cu12==12.1.105 + # via torch +nvidia-cuda-runtime-cu12==12.1.105 + # via torch +nvidia-cudnn-cu12==8.9.2.26 + # via torch +nvidia-cufft-cu12==11.0.2.54 + # via torch +nvidia-curand-cu12==10.3.2.106 + # via torch +nvidia-cusolver-cu12==11.4.5.107 + # via torch +nvidia-cusparse-cu12==12.1.0.106 + # via + # nvidia-cusolver-cu12 + # torch +nvidia-nccl-cu12==2.20.5 + # via torch +nvidia-nvjitlink-cu12==12.4.127 + # via + # nvidia-cusolver-cu12 + # nvidia-cusparse-cu12 +nvidia-nvtx-cu12==12.1.105 + # via torch opencv-python==4.9.0.80 # via # dioptra (pyproject.toml) @@ -290,7 +339,7 @@ pandas==2.2.2 # via # dioptra (pyproject.toml) # mlflow -partd==1.4.1 +partd==1.4.2 # via dask passlib==1.7.4 # via dioptra (pyproject.toml) @@ -320,13 +369,13 @@ pyarrow==15.0.2 # via # dioptra (pyproject.toml) # mlflow -pybsm==0.1.1 +pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) # nrtk -pygments==2.17.2 +pygments==2.18.0 # via rich pyparsing==3.1.2 # via matplotlib @@ -366,7 +415,7 @@ redis==5.0.4 # via # dioptra (pyproject.toml) # rq -referencing==0.35.0 +referencing==0.35.1 # via # jsonschema # jsonschema-specifications @@ -382,11 +431,12 @@ rich==13.7.1 # via # dioptra (pyproject.toml) # keras -rpds-py==0.18.0 + # modelscan +rpds-py==0.18.1 # via # jsonschema # referencing -rq==1.16.1 +rq==1.16.2 # via dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 @@ -453,7 +503,7 @@ smqtk-image-io==0.17.1 # smqtk-detection sortedcontainers==2.4.0 # via distributed -sqlalchemy==2.0.29 +sqlalchemy==2.0.30 # via # alembic # dioptra (pyproject.toml) @@ -463,6 +513,8 @@ sqlparse==0.5.0 # via mlflow structlog==24.1.0 # via dioptra (pyproject.toml) +sympy==1.12 + # via torch tabulate==0.9.0 # via prefect tblib==3.0.0 @@ -475,38 +527,48 @@ tensorboard-data-server==0.7.2 # via tensorboard tensorflow==2.16.1 # via -r requirements-dev-tensorflow.in -tensorflow-io-gcs-filesystem==0.36.0 - # via tensorflow +tensorflow-io-gcs-filesystem==0.34.0 + # via + # modelscan + # tensorflow termcolor==2.4.0 # via tensorflow text-unidecode==1.3 # via python-slugify threadpoolctl==3.5.0 # via scikit-learn -tifffile==2024.4.24 +tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum toml==0.10.2 # via prefect +tomlkit==0.12.4 + # via modelscan toolz==0.12.1 # via # dask # distributed # partd +torch==2.3.0 + # via maite tornado==6.4 # via distributed -tqdm==4.66.2 +tqdm==4.66.4 # via # adversarial-robustness-toolbox # nrtk +triton==2.3.0 + # via torch typing-extensions==4.11.0 # via # alembic # dioptra (pyproject.toml) + # maite # optree # sqlalchemy # tensorflow + # torch tzdata==2024.1 # via # pandas @@ -518,7 +580,7 @@ urllib3==2.2.1 # docker # prefect # requests -werkzeug==3.0.2 +werkzeug==3.0.3 # via # dioptra (pyproject.toml) # flask diff --git a/docker/requirements/linux-amd64-py3.11-tensorflow2-gpu-requirements.txt b/docker/requirements/linux-amd64-py3.11-tensorflow2-gpu-requirements.txt index 16a0759fa..a2829c374 100644 --- a/docker/requirements/linux-amd64-py3.11-tensorflow2-gpu-requirements.txt +++ b/docker/requirements/linux-amd64-py3.11-tensorflow2-gpu-requirements.txt @@ -28,11 +28,11 @@ attrs==23.2.0 # via # jsonschema # referencing -blinker==1.8.1 +blinker==1.8.2 # via flask -boto3==1.34.93 +boto3==1.34.99 # via dioptra (pyproject.toml) -botocore==1.34.93 +botocore==1.34.99 # via # boto3 # s3transfer @@ -47,6 +47,7 @@ click==8.1.7 # distributed # flask # mlflow + # modelscan # prefect # rq cloudpickle==3.0.0 @@ -55,17 +56,19 @@ cloudpickle==3.0.0 # distributed # mlflow # prefect +cmake==3.29.2 + # via triton contourpy==1.2.1 # via matplotlib croniter==2.0.5 # via prefect cycler==0.12.1 # via matplotlib -dask==2024.4.2 +dask==2024.5.0 # via # distributed # prefect -distributed==2024.4.2 +distributed==2024.5.0 # via prefect docker==7.0.0 # via @@ -75,6 +78,10 @@ entrypoints==0.4 # via # dioptra (pyproject.toml) # mlflow +filelock==3.14.0 + # via + # torch + # triton flask==3.0.3 # via # dioptra (pyproject.toml) @@ -86,7 +93,7 @@ flask==3.0.3 # mlflow flask-accepts==0.18.4 # via dioptra (pyproject.toml) -flask-cors==4.0.0 +flask-cors==4.0.1 # via dioptra (pyproject.toml) flask-login==0.6.3 # via dioptra (pyproject.toml) @@ -124,7 +131,7 @@ graphql-relay==3.2.0 # via graphene greenlet==3.0.3 # via sqlalchemy -grpcio==1.62.2 +grpcio==1.63.0 # via # tensorboard # tensorflow @@ -154,18 +161,19 @@ injector==0.21.0 # via dioptra (pyproject.toml) itsdangerous==2.2.0 # via flask -jinja2==3.1.3 +jinja2==3.1.4 # via # distributed # flask # mlflow + # torch jmespath==1.0.1 # via # boto3 # botocore -joblib==1.4.0 +joblib==1.4.2 # via scikit-learn -jsonschema==4.21.1 +jsonschema==4.22.0 # via # dioptra (pyproject.toml) # flask-restx @@ -179,10 +187,14 @@ lazy-loader==0.4 # via scikit-image libclang==18.1.1 # via tensorflow +lit==18.1.4 + # via triton locket==1.0.0 # via # distributed # partd +maite[all-interop]==0.5.0 + # via dioptra (pyproject.toml) mako==1.3.3 # via alembic markdown==3.6 @@ -196,7 +208,7 @@ markupsafe==2.1.5 # jinja2 # mako # werkzeug -marshmallow==3.21.1 +marshmallow==3.21.2 # via # dioptra (pyproject.toml) # flask-accepts @@ -219,6 +231,10 @@ ml-dtypes==0.3.2 # tensorflow mlflow==2.12.1 # via dioptra (pyproject.toml) +modelscan==0.7.3 + # via dioptra (pyproject.toml) +mpmath==1.3.0 + # via sympy msgpack==1.0.8 # via # distributed @@ -230,10 +246,12 @@ mypy-extensions==1.0.0 namex==0.0.8 # via keras networkx==3.3 - # via scikit-image -nrtk==0.3.1 + # via + # scikit-image + # torch +nrtk==0.4.0 # via dioptra (pyproject.toml) -numpy==1.26.4 +numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy @@ -242,9 +260,11 @@ numpy==1.26.4 # imageio # imgaug # keras + # maite # matplotlib # ml-dtypes # mlflow + # modelscan # nrtk # opencv-python # opt-einsum @@ -263,33 +283,56 @@ numpy==1.26.4 # tensorboard # tensorflow # tifffile +nvidia-cublas-cu11==11.10.3.66 + # via + # nvidia-cudnn-cu11 + # nvidia-cusolver-cu11 + # torch nvidia-cublas-cu12==12.3.4.1 # via # nvidia-cudnn-cu12 # nvidia-cusolver-cu12 # tensorflow +nvidia-cuda-cupti-cu11==11.7.101 + # via torch nvidia-cuda-cupti-cu12==12.3.101 # via tensorflow nvidia-cuda-nvcc-cu12==12.3.107 # via tensorflow +nvidia-cuda-nvrtc-cu11==11.7.99 + # via torch nvidia-cuda-nvrtc-cu12==12.3.107 # via # nvidia-cudnn-cu12 # tensorflow +nvidia-cuda-runtime-cu11==11.7.99 + # via torch nvidia-cuda-runtime-cu12==12.3.101 # via tensorflow +nvidia-cudnn-cu11==8.5.0.96 + # via torch nvidia-cudnn-cu12==8.9.7.29 # via tensorflow +nvidia-cufft-cu11==10.9.0.58 + # via torch nvidia-cufft-cu12==11.0.12.1 # via tensorflow +nvidia-curand-cu11==10.2.10.91 + # via torch nvidia-curand-cu12==10.3.4.107 # via tensorflow +nvidia-cusolver-cu11==11.4.0.1 + # via torch nvidia-cusolver-cu12==11.5.4.101 # via tensorflow +nvidia-cusparse-cu11==11.7.4.91 + # via torch nvidia-cusparse-cu12==12.2.0.103 # via # nvidia-cusolver-cu12 # tensorflow +nvidia-nccl-cu11==2.14.3 + # via torch nvidia-nccl-cu12==2.19.3 # via tensorflow nvidia-nvjitlink-cu12==12.3.101 @@ -297,6 +340,8 @@ nvidia-nvjitlink-cu12==12.3.101 # nvidia-cusolver-cu12 # nvidia-cusparse-cu12 # tensorflow +nvidia-nvtx-cu11==11.7.91 + # via torch opencv-python==4.9.0.80 # via # dioptra (pyproject.toml) @@ -324,7 +369,7 @@ pandas==2.2.2 # via # dioptra (pyproject.toml) # mlflow -partd==1.4.1 +partd==1.4.2 # via dask passlib==1.7.4 # via dioptra (pyproject.toml) @@ -354,13 +399,13 @@ pyarrow==15.0.2 # via # dioptra (pyproject.toml) # mlflow -pybsm==0.1.1 +pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) # nrtk -pygments==2.17.2 +pygments==2.18.0 # via rich pyparsing==3.1.2 # via matplotlib @@ -400,7 +445,7 @@ redis==5.0.4 # via # dioptra (pyproject.toml) # rq -referencing==0.35.0 +referencing==0.35.1 # via # jsonschema # jsonschema-specifications @@ -416,11 +461,12 @@ rich==13.7.1 # via # dioptra (pyproject.toml) # keras -rpds-py==0.18.0 + # modelscan +rpds-py==0.18.1 # via # jsonschema # referencing -rq==1.16.1 +rq==1.16.2 # via dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 @@ -487,7 +533,7 @@ smqtk-image-io==0.17.1 # smqtk-detection sortedcontainers==2.4.0 # via distributed -sqlalchemy==2.0.29 +sqlalchemy==2.0.30 # via # alembic # dioptra (pyproject.toml) @@ -497,6 +543,8 @@ sqlparse==0.5.0 # via mlflow structlog==24.1.0 # via dioptra (pyproject.toml) +sympy==1.12 + # via torch tabulate==0.9.0 # via prefect tblib==3.0.0 @@ -509,38 +557,50 @@ tensorboard-data-server==0.7.2 # via tensorboard tensorflow[and-cuda]==2.16.1 ; sys_platform == "linux" and (platform_machine == "x86_64" or platform_machine == "amd64" or platform_machine == "AMD64") # via -r requirements-dev-tensorflow-gpu.in -tensorflow-io-gcs-filesystem==0.36.0 - # via tensorflow +tensorflow-io-gcs-filesystem==0.34.0 + # via + # modelscan + # tensorflow termcolor==2.4.0 # via tensorflow text-unidecode==1.3 # via python-slugify threadpoolctl==3.5.0 # via scikit-learn -tifffile==2024.4.24 +tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum toml==0.10.2 # via prefect +tomlkit==0.12.4 + # via modelscan toolz==0.12.1 # via # dask # distributed # partd +torch==2.0.1 + # via + # maite + # triton tornado==6.4 # via distributed -tqdm==4.66.2 +tqdm==4.66.4 # via # adversarial-robustness-toolbox # nrtk +triton==2.0.0 + # via torch typing-extensions==4.11.0 # via # alembic # dioptra (pyproject.toml) + # maite # optree # sqlalchemy # tensorflow + # torch tzdata==2024.1 # via # pandas @@ -552,7 +612,7 @@ urllib3==2.2.1 # docker # prefect # requests -werkzeug==3.0.2 +werkzeug==3.0.3 # via # dioptra (pyproject.toml) # flask @@ -561,7 +621,14 @@ werkzeug==3.0.2 # flask-restx # tensorboard wheel==0.43.0 - # via astunparse + # via + # astunparse + # nvidia-cublas-cu11 + # nvidia-cuda-cupti-cu11 + # nvidia-cuda-runtime-cu11 + # nvidia-curand-cu11 + # nvidia-cusparse-cu11 + # nvidia-nvtx-cu11 wrapt==1.16.0 # via tensorflow zict==3.0.0 diff --git a/docker/requirements/linux-arm64-py3.11-mlflow-tracking-requirements.txt b/docker/requirements/linux-arm64-py3.11-mlflow-tracking-requirements.txt index 1a7872050..a57a19e6c 100644 --- a/docker/requirements/linux-arm64-py3.11-mlflow-tracking-requirements.txt +++ b/docker/requirements/linux-arm64-py3.11-mlflow-tracking-requirements.txt @@ -8,11 +8,11 @@ alembic==1.13.1 # via mlflow aniso8601==9.0.1 # via graphene -blinker==1.8.1 +blinker==1.8.2 # via flask -boto3==1.34.93 +boto3==1.34.99 # via -r docker/pip-tools/mlflow-tracking-requirements.in -botocore==1.34.93 +botocore==1.34.99 # via # boto3 # s3transfer @@ -60,7 +60,7 @@ importlib-metadata==7.1.0 # via mlflow itsdangerous==2.2.0 # via flask -jinja2==3.1.3 +jinja2==3.1.4 # via # flask # mlflow @@ -68,7 +68,7 @@ jmespath==1.0.1 # via # boto3 # botocore -joblib==1.4.0 +joblib==1.4.2 # via scikit-learn kiwisolver==1.4.5 # via matplotlib @@ -145,7 +145,7 @@ six==1.16.0 # querystring-parser smmap==5.0.1 # via gitdb -sqlalchemy==2.0.29 +sqlalchemy==2.0.30 # via # alembic # mlflow @@ -164,7 +164,7 @@ urllib3==2.2.1 # botocore # docker # requests -werkzeug==3.0.2 +werkzeug==3.0.3 # via flask zipp==3.18.1 # via importlib-metadata diff --git a/docker/requirements/linux-arm64-py3.11-pytorch-cpu-requirements.txt b/docker/requirements/linux-arm64-py3.11-pytorch-cpu-requirements.txt index ef470ab31..b4a10559f 100644 --- a/docker/requirements/linux-arm64-py3.11-pytorch-cpu-requirements.txt +++ b/docker/requirements/linux-arm64-py3.11-pytorch-cpu-requirements.txt @@ -25,11 +25,11 @@ attrs==23.2.0 # via # jsonschema # referencing -blinker==1.8.1 +blinker==1.8.2 # via flask -boto3==1.34.93 +boto3==1.34.99 # via dioptra (pyproject.toml) -botocore==1.34.93 +botocore==1.34.99 # via # boto3 # s3transfer @@ -44,6 +44,7 @@ click==8.1.7 # distributed # flask # mlflow + # modelscan # prefect # rq cloudpickle==3.0.0 @@ -58,11 +59,11 @@ croniter==2.0.5 # via prefect cycler==0.12.1 # via matplotlib -dask==2024.4.2 +dask==2024.5.0 # via # distributed # prefect -distributed==2024.4.2 +distributed==2024.5.0 # via prefect docker==7.0.0 # via @@ -85,7 +86,7 @@ flask==3.0.3 # mlflow flask-accepts==0.18.4 # via dioptra (pyproject.toml) -flask-cors==4.0.0 +flask-cors==4.0.1 # via dioptra (pyproject.toml) flask-login==0.6.3 # via dioptra (pyproject.toml) @@ -119,7 +120,7 @@ graphql-relay==3.2.0 # via graphene greenlet==3.0.3 # via sqlalchemy -grpcio==1.62.2 +grpcio==1.63.0 # via tensorboard gunicorn==21.2.0 # via mlflow @@ -143,7 +144,7 @@ injector==0.21.0 # via dioptra (pyproject.toml) itsdangerous==2.2.0 # via flask -jinja2==3.1.3 +jinja2==3.1.4 # via # distributed # flask @@ -153,9 +154,9 @@ jmespath==1.0.1 # via # boto3 # botocore -joblib==1.4.0 +joblib==1.4.2 # via scikit-learn -jsonschema==4.21.1 +jsonschema==4.22.0 # via # dioptra (pyproject.toml) # flask-restx @@ -169,6 +170,8 @@ locket==1.0.0 # via # distributed # partd +maite[all-interop]==0.5.0 + # via dioptra (pyproject.toml) mako==1.3.3 # via alembic markdown==3.6 @@ -182,7 +185,7 @@ markupsafe==2.1.5 # jinja2 # mako # werkzeug -marshmallow==3.21.1 +marshmallow==3.21.2 # via # dioptra (pyproject.toml) # flask-accepts @@ -201,6 +204,8 @@ mdurl==0.1.2 # via markdown-it-py mlflow==2.12.1 # via dioptra (pyproject.toml) +modelscan==0.7.3 + # via dioptra (pyproject.toml) mpmath==1.3.0 # via sympy msgpack==1.0.8 @@ -215,17 +220,19 @@ networkx==3.3 # via # scikit-image # torch -nrtk==0.3.1 +nrtk==0.4.0 # via dioptra (pyproject.toml) -numpy==1.26.4 +numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy # dioptra (pyproject.toml) # imageio # imgaug + # maite # matplotlib # mlflow + # modelscan # nrtk # opencv-python # pandas @@ -265,7 +272,7 @@ pandas==2.2.2 # via # dioptra (pyproject.toml) # mlflow -partd==1.4.1 +partd==1.4.2 # via dask passlib==1.7.4 # via dioptra (pyproject.toml) @@ -295,13 +302,13 @@ pyarrow==15.0.2 # via # dioptra (pyproject.toml) # mlflow -pybsm==0.1.1 +pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) # nrtk -pygments==2.17.2 +pygments==2.18.0 # via rich pyparsing==3.1.2 # via matplotlib @@ -341,7 +348,7 @@ redis==5.0.4 # via # dioptra (pyproject.toml) # rq -referencing==0.35.0 +referencing==0.35.1 # via # jsonschema # jsonschema-specifications @@ -353,12 +360,14 @@ requests==2.31.0 # prefect # smqtk-dataprovider rich==13.7.1 - # via dioptra (pyproject.toml) -rpds-py==0.18.0 + # via + # dioptra (pyproject.toml) + # modelscan +rpds-py==0.18.1 # via # jsonschema # referencing -rq==1.16.1 +rq==1.16.2 # via dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 @@ -422,7 +431,7 @@ smqtk-image-io==0.17.1 # smqtk-detection sortedcontainers==2.4.0 # via distributed -sqlalchemy==2.0.29 +sqlalchemy==2.0.30 # via # alembic # dioptra (pyproject.toml) @@ -442,16 +451,20 @@ tensorboard==2.16.2 # via dioptra (pyproject.toml) tensorboard-data-server==0.7.2 # via tensorboard +tensorflow-io-gcs-filesystem==0.34.0 + # via modelscan text-unidecode==1.3 # via python-slugify threadpoolctl==3.5.0 # via scikit-learn -tifffile==2024.4.24 +tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum toml==0.10.2 # via prefect +tomlkit==0.12.4 + # via modelscan toolz==0.12.1 # via # dask @@ -460,6 +473,7 @@ toolz==0.12.1 torch==2.2.2 # via # -r requirements-dev-pytorch.in + # maite # torchaudio # torchvision torchaudio==2.2.2 @@ -468,7 +482,7 @@ torchvision==0.17.2 # via -r requirements-dev-pytorch.in tornado==6.4 # via distributed -tqdm==4.66.2 +tqdm==4.66.4 # via # adversarial-robustness-toolbox # nrtk @@ -476,6 +490,7 @@ typing-extensions==4.11.0 # via # alembic # dioptra (pyproject.toml) + # maite # sqlalchemy # torch tzdata==2024.1 @@ -489,7 +504,7 @@ urllib3==2.2.1 # docker # prefect # requests -werkzeug==3.0.2 +werkzeug==3.0.3 # via # dioptra (pyproject.toml) # flask diff --git a/docker/requirements/linux-arm64-py3.11-restapi-requirements.txt b/docker/requirements/linux-arm64-py3.11-restapi-requirements.txt index 40bcc822d..561aacc08 100644 --- a/docker/requirements/linux-arm64-py3.11-restapi-requirements.txt +++ b/docker/requirements/linux-arm64-py3.11-restapi-requirements.txt @@ -16,11 +16,11 @@ attrs==23.2.0 # via # jsonschema # referencing -blinker==1.8.1 +blinker==1.8.2 # via flask -boto3==1.34.93 +boto3==1.34.99 # via dioptra (pyproject.toml) -botocore==1.34.93 +botocore==1.34.99 # via # boto3 # s3transfer @@ -50,7 +50,7 @@ flask==3.0.3 # flask-sqlalchemy flask-accepts==0.18.4 # via dioptra (pyproject.toml) -flask-cors==4.0.0 +flask-cors==4.0.1 # via dioptra (pyproject.toml) flask-login==0.6.3 # via dioptra (pyproject.toml) @@ -82,13 +82,13 @@ injector==0.21.0 # via dioptra (pyproject.toml) itsdangerous==2.2.0 # via flask -jinja2==3.1.3 +jinja2==3.1.4 # via flask jmespath==1.0.1 # via # boto3 # botocore -jsonschema==4.21.1 +jsonschema==4.22.0 # via # dioptra (pyproject.toml) # flask-restx @@ -101,7 +101,7 @@ markupsafe==2.1.5 # jinja2 # mako # werkzeug -marshmallow==3.21.1 +marshmallow==3.21.2 # via # dioptra (pyproject.toml) # flask-accepts @@ -149,7 +149,7 @@ redis==5.0.4 # via # dioptra (pyproject.toml) # rq -referencing==0.35.0 +referencing==0.35.1 # via # jsonschema # jsonschema-specifications @@ -157,11 +157,11 @@ requests==2.31.0 # via # dioptra (pyproject.toml) # mlflow-skinny -rpds-py==0.18.0 +rpds-py==0.18.1 # via # jsonschema # referencing -rq==1.16.1 +rq==1.16.2 # via dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 @@ -173,7 +173,7 @@ six==1.16.0 # via python-dateutil smmap==5.0.1 # via gitdb -sqlalchemy==2.0.29 +sqlalchemy==2.0.30 # via # alembic # dioptra (pyproject.toml) @@ -193,7 +193,7 @@ urllib3==2.2.1 # via # botocore # requests -werkzeug==3.0.2 +werkzeug==3.0.3 # via # dioptra (pyproject.toml) # flask diff --git a/docker/requirements/linux-arm64-py3.11-tensorflow2-cpu-requirements.txt b/docker/requirements/linux-arm64-py3.11-tensorflow2-cpu-requirements.txt index cc28d6269..377d6b3d8 100644 --- a/docker/requirements/linux-arm64-py3.11-tensorflow2-cpu-requirements.txt +++ b/docker/requirements/linux-arm64-py3.11-tensorflow2-cpu-requirements.txt @@ -28,11 +28,11 @@ attrs==23.2.0 # via # jsonschema # referencing -blinker==1.8.1 +blinker==1.8.2 # via flask -boto3==1.34.93 +boto3==1.34.99 # via dioptra (pyproject.toml) -botocore==1.34.93 +botocore==1.34.99 # via # boto3 # s3transfer @@ -47,6 +47,7 @@ click==8.1.7 # distributed # flask # mlflow + # modelscan # prefect # rq cloudpickle==3.0.0 @@ -61,11 +62,11 @@ croniter==2.0.5 # via prefect cycler==0.12.1 # via matplotlib -dask==2024.4.2 +dask==2024.5.0 # via # distributed # prefect -distributed==2024.4.2 +distributed==2024.5.0 # via prefect docker==7.0.0 # via @@ -75,6 +76,8 @@ entrypoints==0.4 # via # dioptra (pyproject.toml) # mlflow +filelock==3.14.0 + # via torch flask==3.0.3 # via # dioptra (pyproject.toml) @@ -86,7 +89,7 @@ flask==3.0.3 # mlflow flask-accepts==0.18.4 # via dioptra (pyproject.toml) -flask-cors==4.0.0 +flask-cors==4.0.1 # via dioptra (pyproject.toml) flask-login==0.6.3 # via dioptra (pyproject.toml) @@ -105,7 +108,9 @@ flatbuffers==24.3.25 fonttools==4.51.0 # via matplotlib fsspec==2024.3.1 - # via dask + # via + # dask + # torch gast==0.5.4 # via tensorflow gitdb==4.0.11 @@ -124,7 +129,7 @@ graphql-relay==3.2.0 # via graphene greenlet==3.0.3 # via sqlalchemy -grpcio==1.62.2 +grpcio==1.63.0 # via # tensorboard # tensorflow @@ -154,18 +159,19 @@ injector==0.21.0 # via dioptra (pyproject.toml) itsdangerous==2.2.0 # via flask -jinja2==3.1.3 +jinja2==3.1.4 # via # distributed # flask # mlflow + # torch jmespath==1.0.1 # via # boto3 # botocore -joblib==1.4.0 +joblib==1.4.2 # via scikit-learn -jsonschema==4.21.1 +jsonschema==4.22.0 # via # dioptra (pyproject.toml) # flask-restx @@ -183,6 +189,8 @@ locket==1.0.0 # via # distributed # partd +maite[all-interop]==0.5.0 + # via dioptra (pyproject.toml) mako==1.3.3 # via alembic markdown==3.6 @@ -196,7 +204,7 @@ markupsafe==2.1.5 # jinja2 # mako # werkzeug -marshmallow==3.21.1 +marshmallow==3.21.2 # via # dioptra (pyproject.toml) # flask-accepts @@ -219,6 +227,10 @@ ml-dtypes==0.3.2 # tensorflow mlflow==2.12.1 # via dioptra (pyproject.toml) +modelscan==0.7.3 + # via dioptra (pyproject.toml) +mpmath==1.3.0 + # via sympy msgpack==1.0.8 # via # distributed @@ -230,10 +242,12 @@ mypy-extensions==1.0.0 namex==0.0.8 # via keras networkx==3.3 - # via scikit-image -nrtk==0.3.1 + # via + # scikit-image + # torch +nrtk==0.4.0 # via dioptra (pyproject.toml) -numpy==1.26.4 +numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy @@ -242,9 +256,11 @@ numpy==1.26.4 # imageio # imgaug # keras + # maite # matplotlib # ml-dtypes # mlflow + # modelscan # nrtk # opencv-python # opt-einsum @@ -290,7 +306,7 @@ pandas==2.2.2 # via # dioptra (pyproject.toml) # mlflow -partd==1.4.1 +partd==1.4.2 # via dask passlib==1.7.4 # via dioptra (pyproject.toml) @@ -320,13 +336,13 @@ pyarrow==15.0.2 # via # dioptra (pyproject.toml) # mlflow -pybsm==0.1.1 +pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) # nrtk -pygments==2.17.2 +pygments==2.18.0 # via rich pyparsing==3.1.2 # via matplotlib @@ -366,7 +382,7 @@ redis==5.0.4 # via # dioptra (pyproject.toml) # rq -referencing==0.35.0 +referencing==0.35.1 # via # jsonschema # jsonschema-specifications @@ -382,11 +398,12 @@ rich==13.7.1 # via # dioptra (pyproject.toml) # keras -rpds-py==0.18.0 + # modelscan +rpds-py==0.18.1 # via # jsonschema # referencing -rq==1.16.1 +rq==1.16.2 # via dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 @@ -453,7 +470,7 @@ smqtk-image-io==0.17.1 # smqtk-detection sortedcontainers==2.4.0 # via distributed -sqlalchemy==2.0.29 +sqlalchemy==2.0.30 # via # alembic # dioptra (pyproject.toml) @@ -463,6 +480,8 @@ sqlparse==0.5.0 # via mlflow structlog==24.1.0 # via dioptra (pyproject.toml) +sympy==1.12 + # via torch tabulate==0.9.0 # via prefect tblib==3.0.0 @@ -475,28 +494,34 @@ tensorboard-data-server==0.7.2 # via tensorboard tensorflow==2.16.1 # via -r requirements-dev-tensorflow.in -tensorflow-io-gcs-filesystem==0.36.0 - # via tensorflow +tensorflow-io-gcs-filesystem==0.34.0 + # via + # modelscan + # tensorflow termcolor==2.4.0 # via tensorflow text-unidecode==1.3 # via python-slugify threadpoolctl==3.5.0 # via scikit-learn -tifffile==2024.4.24 +tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum toml==0.10.2 # via prefect +tomlkit==0.12.4 + # via modelscan toolz==0.12.1 # via # dask # distributed # partd +torch==2.3.0 + # via maite tornado==6.4 # via distributed -tqdm==4.66.2 +tqdm==4.66.4 # via # adversarial-robustness-toolbox # nrtk @@ -504,9 +529,11 @@ typing-extensions==4.11.0 # via # alembic # dioptra (pyproject.toml) + # maite # optree # sqlalchemy # tensorflow + # torch tzdata==2024.1 # via # pandas @@ -518,7 +545,7 @@ urllib3==2.2.1 # docker # prefect # requests -werkzeug==3.0.2 +werkzeug==3.0.3 # via # dioptra (pyproject.toml) # flask From 39537aa1ec4913eac3b726b9e67c61ea1fe7d097 Mon Sep 17 00:00:00 2001 From: bjpatrick <137509145+bjpatrick@users.noreply.github.com> Date: Tue, 7 May 2024 10:45:26 -0500 Subject: [PATCH 05/18] Update pip-compile.yml --- .github/workflows/pip-compile.yml | 3 --- 1 file changed, 3 deletions(-) diff --git a/.github/workflows/pip-compile.yml b/.github/workflows/pip-compile.yml index ca875275f..3c9084bd0 100644 --- a/.github/workflows/pip-compile.yml +++ b/.github/workflows/pip-compile.yml @@ -19,9 +19,6 @@ name: pip-compile runs on: schedule: - cron: "10 1 * * *" # at 1:10am every day - push: - branches: - - "**" jobs: pip-compile: From 0f131047b408fd0e739dc5c1d2b1dd4a48604dc2 Mon Sep 17 00:00:00 2001 From: bjpatrick <137509145+bjpatrick@users.noreply.github.com> Date: Tue, 7 May 2024 13:30:05 -0500 Subject: [PATCH 06/18] Update pyproject.toml modifying maite to specifically use v0.4.0 --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index aa6dd2e27..79f319884 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -128,7 +128,7 @@ worker = [ "async_timeout", "adversarial-robustness-toolbox>=1.9.0", "imgaug>=0.4.0", - "maite[all_interop]>=0.4.0", + "maite[all_interop]=0.4.0", "matplotlib", "modelscan>=0.1.1", "nrtk>=0.3.0", From c0cee416743e3ecd43728d6a9414d84d898997b5 Mon Sep 17 00:00:00 2001 From: bjpatrick <137509145+bjpatrick@users.noreply.github.com> Date: Tue, 7 May 2024 13:31:37 -0500 Subject: [PATCH 07/18] Update pip-compile.yml --- .github/workflows/pip-compile.yml | 3 +++ 1 file changed, 3 insertions(+) diff --git a/.github/workflows/pip-compile.yml b/.github/workflows/pip-compile.yml index 3c9084bd0..ca875275f 100644 --- a/.github/workflows/pip-compile.yml +++ b/.github/workflows/pip-compile.yml @@ -19,6 +19,9 @@ name: pip-compile runs on: schedule: - cron: "10 1 * * *" # at 1:10am every day + push: + branches: + - "**" jobs: pip-compile: From c5ba53a2ad12e9245ecd8a4966c31a1e8976b994 Mon Sep 17 00:00:00 2001 From: bjpatrick <137509145+bjpatrick@users.noreply.github.com> Date: Tue, 7 May 2024 13:41:37 -0500 Subject: [PATCH 08/18] Update pyproject.toml --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 79f319884..daad096eb 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -128,7 +128,7 @@ worker = [ "async_timeout", "adversarial-robustness-toolbox>=1.9.0", "imgaug>=0.4.0", - "maite[all_interop]=0.4.0", + "maite[all_interop]==0.4.0", "matplotlib", "modelscan>=0.1.1", "nrtk>=0.3.0", From 8f84861d07cf081f42b7148dd613b2bac243d089 Mon Sep 17 00:00:00 2001 From: bjpatrick <137509145+bjpatrick@users.noreply.github.com> Date: Tue, 7 May 2024 13:42:22 -0500 Subject: [PATCH 09/18] Update pip-compile.yml From 4bb3e870b00b3659e38b353dfe30ad5dfe92cdaa Mon Sep 17 00:00:00 2001 From: bjpatrick <137509145+bjpatrick@users.noreply.github.com> Date: Tue, 7 May 2024 14:06:40 -0500 Subject: [PATCH 10/18] Add files via upload fixing maite version --- ...-amd64-py3.11-requirements-dev-pytorch.txt | 89 +++++++++++++++++- ...d64-py3.11-requirements-dev-tensorflow.txt | 92 ++++++++++++++++++- .../linux-amd64-py3.11-requirements-dev.txt | 92 ++++++++++++++++++- ...-arm64-py3.11-requirements-dev-pytorch.txt | 89 +++++++++++++++++- ...m64-py3.11-requirements-dev-tensorflow.txt | 92 ++++++++++++++++++- .../linux-arm64-py3.11-requirements-dev.txt | 92 ++++++++++++++++++- ...-amd64-py3.11-requirements-dev-pytorch.txt | 89 +++++++++++++++++- ...d64-py3.11-requirements-dev-tensorflow.txt | 92 ++++++++++++++++++- .../macos-amd64-py3.11-requirements-dev.txt | 92 ++++++++++++++++++- ...-arm64-py3.11-requirements-dev-pytorch.txt | 89 +++++++++++++++++- ...m64-py3.11-requirements-dev-tensorflow.txt | 92 ++++++++++++++++++- .../macos-arm64-py3.11-requirements-dev.txt | 92 ++++++++++++++++++- ...-amd64-py3.11-requirements-dev-pytorch.txt | 86 ++++++++++++++++- ...d64-py3.11-requirements-dev-tensorflow.txt | 89 +++++++++++++++++- .../win-amd64-py3.11-requirements-dev.txt | 89 +++++++++++++++++- 15 files changed, 1294 insertions(+), 62 deletions(-) diff --git a/requirements/linux-amd64-py3.11-requirements-dev-pytorch.txt b/requirements/linux-amd64-py3.11-requirements-dev-pytorch.txt index 135bbd14d..957261282 100644 --- a/requirements/linux-amd64-py3.11-requirements-dev-pytorch.txt +++ b/requirements/linux-amd64-py3.11-requirements-dev-pytorch.txt @@ -13,7 +13,10 @@ absl-py==2.1.0 adversarial-robustness-toolbox==1.17.1 # via dioptra (pyproject.toml) aiohttp==3.9.5 - # via dioptra (pyproject.toml) + # via + # datasets + # dioptra (pyproject.toml) + # fsspec aiosignal==1.3.1 # via aiohttp alabaster==0.7.16 @@ -124,7 +127,9 @@ cloudpickle==3.0.0 # mlflow # prefect colorama==0.4.6 - # via tox + # via + # pretty-errors + # tox comm==0.2.2 # via # ipykernel @@ -143,12 +148,18 @@ dask==2024.5.0 # via # distributed # prefect +datasets==2.19.1 + # via maite debugpy==1.8.1 # via ipykernel decorator==5.1.1 # via ipython defusedxml==0.7.1 # via nbconvert +dill==0.3.8 + # via + # datasets + # multiprocess distlib==0.3.8 # via virtualenv distributed==2024.5.0 @@ -172,8 +183,11 @@ fastjsonschema==2.19.1 # via nbformat filelock==3.14.0 # via + # datasets + # huggingface-hub # torch # tox + # transformers # triton # virtualenv flake8==7.0.0 @@ -228,9 +242,11 @@ frozenlist==1.4.1 # via # aiohttp # aiosignal -fsspec==2024.3.1 +fsspec[http]==2024.3.1 # via # dask + # datasets + # huggingface-hub # torch # universal-pathlib gitdb==4.0.11 @@ -257,6 +273,13 @@ httpcore==1.0.5 # via httpx httpx==0.27.0 # via jupyterlab +huggingface-hub==0.23.0 + # via + # datasets + # maite + # timm + # tokenizers + # transformers idna==3.7 # via # anyio @@ -395,13 +418,15 @@ kiwisolver==1.4.5 # via matplotlib lazy-loader==0.4 # via scikit-image +lightning-utilities==0.11.2 + # via torchmetrics locket==1.0.0 # via # distributed # partd lsprotocol==2023.0.1 # via pygls -maite[all-interop]==0.5.0 +maite[all-interop]==0.4.0 # via dioptra (pyproject.toml) mako==1.3.3 # via alembic @@ -461,6 +486,8 @@ multimethod==1.11.2 # via # dioptra # dioptra (pyproject.toml) +multiprocess==0.70.16 + # via datasets mypy-extensions==1.0.0 # via prefect nbclient==0.10.0 @@ -493,6 +520,7 @@ numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy + # datasets # dioptra # dioptra (pyproject.toml) # imageio @@ -517,7 +545,9 @@ numpy==1.24.0 # smqtk-image-io # tensorboard # tifffile + # torchmetrics # torchvision + # transformers nvidia-cublas-cu12==12.1.3.1 # via # nvidia-cudnn-cu12 @@ -561,14 +591,17 @@ packaging==24.0 # via # build # dask + # datasets # distributed # docker # gunicorn + # huggingface-hub # ipykernel # jupyter-server # jupyterlab # jupyterlab-server # lazy-loader + # lightning-utilities # marshmallow # matplotlib # mlflow @@ -580,9 +613,12 @@ packaging==24.0 # qtpy # scikit-image # sphinx + # torchmetrics # tox + # transformers pandas==2.2.2 # via + # datasets # dioptra # dioptra (pyproject.toml) # mlflow @@ -624,6 +660,8 @@ pluggy==1.5.0 # tox prefect==1.4.1 # via dioptra (pyproject.toml) +pretty-errors==1.2.25 + # via torchmetrics prometheus-client==0.20.0 # via jupyter-server prompt-toolkit==3.0.43 @@ -648,13 +686,17 @@ pure-eval==0.2.2 # via stack-data pyarrow==15.0.2 # via + # datasets # dioptra (pyproject.toml) # mlflow +pyarrow-hotfix==0.6 + # via datasets pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) + # maite # nrtk pycodestyle==2.11.1 # via @@ -732,12 +774,16 @@ pyyaml==6.0.1 # via # cookiecutter # dask + # datasets # dioptra # dioptra (pyproject.toml) # distributed + # huggingface-hub # jupyter-events # mlflow # prefect + # timm + # transformers pyzmq==26.0.3 # via # ipykernel @@ -761,18 +807,23 @@ referencing==0.35.1 # jsonschema # jsonschema-specifications # jupyter-events +regex==2024.4.28 + # via transformers requests==2.31.0 # via # cookiecutter + # datasets # dioptra # dioptra (pyproject.toml) # docker + # huggingface-hub # jupyterlab-server # kaggle # mlflow # prefect # smqtk-dataprovider # sphinx + # transformers rfc3339-validator==0.1.4 # via # jsonschema @@ -795,6 +846,10 @@ rq==1.16.2 # dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 +safetensors==0.4.3 + # via + # timm + # transformers scikit-image==0.23.2 # via # imgaug @@ -927,8 +982,12 @@ tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum +timm==0.9.16 + # via maite tinycss2==1.3.0 # via nbconvert +tokenizers==0.19.1 + # via transformers toml==0.10.2 # via prefect tomli==2.0.1 @@ -944,12 +1003,21 @@ torch==2.2.2 # via # -r requirements-dev-pytorch.in # maite + # timm # torchaudio + # torchmetrics # torchvision torchaudio==2.2.2 # via -r requirements-dev-pytorch.in +torcheval==0.0.7 + # via maite +torchmetrics==1.4.0 + # via maite torchvision==0.17.2 - # via -r requirements-dev-pytorch.in + # via + # -r requirements-dev-pytorch.in + # maite + # timm tornado==6.4 # via # distributed @@ -964,8 +1032,12 @@ tox==4.15.0 tqdm==4.66.4 # via # adversarial-robustness-toolbox + # datasets + # huggingface-hub # kaggle + # maite # nrtk + # transformers traitlets==5.14.3 # via # comm @@ -983,6 +1055,8 @@ traitlets==5.14.3 # nbconvert # nbformat # qtconsole +transformers==4.40.2 + # via maite triton==2.2.0 # via torch types-python-dateutil==2.9.0.20240316 @@ -992,10 +1066,13 @@ typing-extensions==4.11.0 # alembic # dioptra # dioptra (pyproject.toml) + # huggingface-hub # ipython + # lightning-utilities # maite # sqlalchemy # torch + # torcheval tzdata==2024.1 # via # pandas @@ -1039,6 +1116,8 @@ wheel==0.43.0 # pip-tools widgetsnbextension==4.0.10 # via ipywidgets +xxhash==3.4.1 + # via datasets yarl==1.9.4 # via aiohttp zict==3.0.0 diff --git a/requirements/linux-amd64-py3.11-requirements-dev-tensorflow.txt b/requirements/linux-amd64-py3.11-requirements-dev-tensorflow.txt index 41b6c0869..566942aef 100644 --- a/requirements/linux-amd64-py3.11-requirements-dev-tensorflow.txt +++ b/requirements/linux-amd64-py3.11-requirements-dev-tensorflow.txt @@ -14,7 +14,10 @@ absl-py==2.1.0 adversarial-robustness-toolbox==1.17.1 # via dioptra (pyproject.toml) aiohttp==3.9.5 - # via dioptra (pyproject.toml) + # via + # datasets + # dioptra (pyproject.toml) + # fsspec aiosignal==1.3.1 # via aiohttp alabaster==0.7.16 @@ -127,7 +130,9 @@ cloudpickle==3.0.0 # mlflow # prefect colorama==0.4.6 - # via tox + # via + # pretty-errors + # tox comm==0.2.2 # via # ipykernel @@ -146,12 +151,18 @@ dask==2024.5.0 # via # distributed # prefect +datasets==2.19.1 + # via maite debugpy==1.8.1 # via ipykernel decorator==5.1.1 # via ipython defusedxml==0.7.1 # via nbconvert +dill==0.3.8 + # via + # datasets + # multiprocess distlib==0.3.8 # via virtualenv distributed==2024.5.0 @@ -175,8 +186,11 @@ fastjsonschema==2.19.1 # via nbformat filelock==3.14.0 # via + # datasets + # huggingface-hub # torch # tox + # transformers # triton # virtualenv flake8==7.0.0 @@ -233,9 +247,11 @@ frozenlist==1.4.1 # via # aiohttp # aiosignal -fsspec==2024.3.1 +fsspec[http]==2024.3.1 # via # dask + # datasets + # huggingface-hub # torch # universal-pathlib gast==0.5.4 @@ -272,6 +288,13 @@ httpcore==1.0.5 # via httpx httpx==0.27.0 # via jupyterlab +huggingface-hub==0.23.0 + # via + # datasets + # maite + # timm + # tokenizers + # transformers idna==3.7 # via # anyio @@ -414,13 +437,15 @@ lazy-loader==0.4 # via scikit-image libclang==18.1.1 # via tensorflow +lightning-utilities==0.11.2 + # via torchmetrics locket==1.0.0 # via # distributed # partd lsprotocol==2023.0.1 # via pygls -maite[all-interop]==0.5.0 +maite[all-interop]==0.4.0 # via dioptra (pyproject.toml) mako==1.3.3 # via alembic @@ -484,6 +509,8 @@ multimethod==1.11.2 # via # dioptra # dioptra (pyproject.toml) +multiprocess==0.70.16 + # via datasets mypy-extensions==1.0.0 # via prefect namex==0.0.8 @@ -518,6 +545,7 @@ numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy + # datasets # dioptra # dioptra (pyproject.toml) # h5py @@ -547,6 +575,9 @@ numpy==1.24.0 # tensorboard # tensorflow # tifffile + # torchmetrics + # torchvision + # transformers nvidia-cublas-cu12==12.1.3.1 # via # nvidia-cudnn-cu12 @@ -594,14 +625,17 @@ packaging==24.0 # via # build # dask + # datasets # distributed # docker # gunicorn + # huggingface-hub # ipykernel # jupyter-server # jupyterlab # jupyterlab-server # lazy-loader + # lightning-utilities # marshmallow # matplotlib # mlflow @@ -614,9 +648,12 @@ packaging==24.0 # scikit-image # sphinx # tensorflow + # torchmetrics # tox + # transformers pandas==2.2.2 # via + # datasets # dioptra # dioptra (pyproject.toml) # mlflow @@ -643,6 +680,7 @@ pillow==10.3.0 # nrtk # scikit-image # smqtk-image-io + # torchvision pip-tools==7.4.1 # via dioptra (pyproject.toml) platformdirs==4.2.1 @@ -657,6 +695,8 @@ pluggy==1.5.0 # tox prefect==1.4.1 # via dioptra (pyproject.toml) +pretty-errors==1.2.25 + # via torchmetrics prometheus-client==0.20.0 # via jupyter-server prompt-toolkit==3.0.43 @@ -682,13 +722,17 @@ pure-eval==0.2.2 # via stack-data pyarrow==15.0.2 # via + # datasets # dioptra (pyproject.toml) # mlflow +pyarrow-hotfix==0.6 + # via datasets pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) + # maite # nrtk pycodestyle==2.11.1 # via @@ -766,12 +810,16 @@ pyyaml==6.0.1 # via # cookiecutter # dask + # datasets # dioptra # dioptra (pyproject.toml) # distributed + # huggingface-hub # jupyter-events # mlflow # prefect + # timm + # transformers pyzmq==26.0.3 # via # ipykernel @@ -795,12 +843,16 @@ referencing==0.35.1 # jsonschema # jsonschema-specifications # jupyter-events +regex==2024.4.28 + # via transformers requests==2.31.0 # via # cookiecutter + # datasets # dioptra # dioptra (pyproject.toml) # docker + # huggingface-hub # jupyterlab-server # kaggle # mlflow @@ -808,6 +860,7 @@ requests==2.31.0 # smqtk-dataprovider # sphinx # tensorflow + # transformers rfc3339-validator==0.1.4 # via # jsonschema @@ -831,6 +884,10 @@ rq==1.16.2 # dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 +safetensors==0.4.3 + # via + # timm + # transformers scikit-image==0.23.2 # via # imgaug @@ -974,8 +1031,12 @@ tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum +timm==0.9.16 + # via maite tinycss2==1.3.0 # via nbconvert +tokenizers==0.19.1 + # via transformers toml==0.10.2 # via prefect tomli==2.0.1 @@ -988,7 +1049,19 @@ toolz==0.12.1 # distributed # partd torch==2.3.0 + # via + # maite + # timm + # torchmetrics + # torchvision +torcheval==0.0.7 # via maite +torchmetrics==1.4.0 + # via maite +torchvision==0.18.0 + # via + # maite + # timm tornado==6.4 # via # distributed @@ -1003,8 +1076,12 @@ tox==4.15.0 tqdm==4.66.4 # via # adversarial-robustness-toolbox + # datasets + # huggingface-hub # kaggle + # maite # nrtk + # transformers traitlets==5.14.3 # via # comm @@ -1022,6 +1099,8 @@ traitlets==5.14.3 # nbconvert # nbformat # qtconsole +transformers==4.40.2 + # via maite triton==2.3.0 # via torch types-python-dateutil==2.9.0.20240316 @@ -1031,12 +1110,15 @@ typing-extensions==4.11.0 # alembic # dioptra # dioptra (pyproject.toml) + # huggingface-hub # ipython + # lightning-utilities # maite # optree # sqlalchemy # tensorflow # torch + # torcheval tzdata==2024.1 # via # pandas @@ -1083,6 +1165,8 @@ widgetsnbextension==4.0.10 # via ipywidgets wrapt==1.16.0 # via tensorflow +xxhash==3.4.1 + # via datasets yarl==1.9.4 # via aiohttp zict==3.0.0 diff --git a/requirements/linux-amd64-py3.11-requirements-dev.txt b/requirements/linux-amd64-py3.11-requirements-dev.txt index dc7a11b4c..e79a13dc5 100644 --- a/requirements/linux-amd64-py3.11-requirements-dev.txt +++ b/requirements/linux-amd64-py3.11-requirements-dev.txt @@ -11,7 +11,10 @@ absl-py==2.1.0 adversarial-robustness-toolbox==1.17.1 # via dioptra (pyproject.toml) aiohttp==3.9.5 - # via dioptra (pyproject.toml) + # via + # datasets + # dioptra (pyproject.toml) + # fsspec aiosignal==1.3.1 # via aiohttp alabaster==0.7.16 @@ -122,7 +125,9 @@ cloudpickle==3.0.0 # mlflow # prefect colorama==0.4.6 - # via tox + # via + # pretty-errors + # tox comm==0.2.2 # via # ipykernel @@ -141,12 +146,18 @@ dask==2024.5.0 # via # distributed # prefect +datasets==2.19.1 + # via maite debugpy==1.8.1 # via ipykernel decorator==5.1.1 # via ipython defusedxml==0.7.1 # via nbconvert +dill==0.3.8 + # via + # datasets + # multiprocess distlib==0.3.8 # via virtualenv distributed==2024.5.0 @@ -170,8 +181,11 @@ fastjsonschema==2.19.1 # via nbformat filelock==3.14.0 # via + # datasets + # huggingface-hub # torch # tox + # transformers # triton # virtualenv flake8==7.0.0 @@ -226,9 +240,11 @@ frozenlist==1.4.1 # via # aiohttp # aiosignal -fsspec==2024.3.1 +fsspec[http]==2024.3.1 # via # dask + # datasets + # huggingface-hub # torch # universal-pathlib gitdb==4.0.11 @@ -255,6 +271,13 @@ httpcore==1.0.5 # via httpx httpx==0.27.0 # via jupyterlab +huggingface-hub==0.23.0 + # via + # datasets + # maite + # timm + # tokenizers + # transformers idna==3.7 # via # anyio @@ -393,13 +416,15 @@ kiwisolver==1.4.5 # via matplotlib lazy-loader==0.4 # via scikit-image +lightning-utilities==0.11.2 + # via torchmetrics locket==1.0.0 # via # distributed # partd lsprotocol==2023.0.1 # via pygls -maite[all-interop]==0.5.0 +maite[all-interop]==0.4.0 # via dioptra (pyproject.toml) mako==1.3.3 # via alembic @@ -459,6 +484,8 @@ multimethod==1.11.2 # via # dioptra # dioptra (pyproject.toml) +multiprocess==0.70.16 + # via datasets mypy-extensions==1.0.0 # via prefect nbclient==0.10.0 @@ -491,6 +518,7 @@ numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy + # datasets # dioptra # dioptra (pyproject.toml) # imageio @@ -515,6 +543,9 @@ numpy==1.24.0 # smqtk-image-io # tensorboard # tifffile + # torchmetrics + # torchvision + # transformers nvidia-cublas-cu12==12.1.3.1 # via # nvidia-cudnn-cu12 @@ -558,14 +589,17 @@ packaging==24.0 # via # build # dask + # datasets # distributed # docker # gunicorn + # huggingface-hub # ipykernel # jupyter-server # jupyterlab # jupyterlab-server # lazy-loader + # lightning-utilities # marshmallow # matplotlib # mlflow @@ -577,9 +611,12 @@ packaging==24.0 # qtpy # scikit-image # sphinx + # torchmetrics # tox + # transformers pandas==2.2.2 # via + # datasets # dioptra # dioptra (pyproject.toml) # mlflow @@ -606,6 +643,7 @@ pillow==10.3.0 # nrtk # scikit-image # smqtk-image-io + # torchvision pip-tools==7.4.1 # via dioptra (pyproject.toml) platformdirs==4.2.1 @@ -620,6 +658,8 @@ pluggy==1.5.0 # tox prefect==1.4.1 # via dioptra (pyproject.toml) +pretty-errors==1.2.25 + # via torchmetrics prometheus-client==0.20.0 # via jupyter-server prompt-toolkit==3.0.43 @@ -644,13 +684,17 @@ pure-eval==0.2.2 # via stack-data pyarrow==15.0.2 # via + # datasets # dioptra (pyproject.toml) # mlflow +pyarrow-hotfix==0.6 + # via datasets pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) + # maite # nrtk pycodestyle==2.11.1 # via @@ -728,12 +772,16 @@ pyyaml==6.0.1 # via # cookiecutter # dask + # datasets # dioptra # dioptra (pyproject.toml) # distributed + # huggingface-hub # jupyter-events # mlflow # prefect + # timm + # transformers pyzmq==26.0.3 # via # ipykernel @@ -757,18 +805,23 @@ referencing==0.35.1 # jsonschema # jsonschema-specifications # jupyter-events +regex==2024.4.28 + # via transformers requests==2.31.0 # via # cookiecutter + # datasets # dioptra # dioptra (pyproject.toml) # docker + # huggingface-hub # jupyterlab-server # kaggle # mlflow # prefect # smqtk-dataprovider # sphinx + # transformers rfc3339-validator==0.1.4 # via # jsonschema @@ -791,6 +844,10 @@ rq==1.16.2 # dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 +safetensors==0.4.3 + # via + # timm + # transformers scikit-image==0.23.2 # via # imgaug @@ -923,8 +980,12 @@ tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum +timm==0.9.16 + # via maite tinycss2==1.3.0 # via nbconvert +tokenizers==0.19.1 + # via transformers toml==0.10.2 # via prefect tomli==2.0.1 @@ -937,7 +998,19 @@ toolz==0.12.1 # distributed # partd torch==2.3.0 + # via + # maite + # timm + # torchmetrics + # torchvision +torcheval==0.0.7 # via maite +torchmetrics==1.4.0 + # via maite +torchvision==0.18.0 + # via + # maite + # timm tornado==6.4 # via # distributed @@ -952,8 +1025,12 @@ tox==4.15.0 tqdm==4.66.4 # via # adversarial-robustness-toolbox + # datasets + # huggingface-hub # kaggle + # maite # nrtk + # transformers traitlets==5.14.3 # via # comm @@ -971,6 +1048,8 @@ traitlets==5.14.3 # nbconvert # nbformat # qtconsole +transformers==4.40.2 + # via maite triton==2.3.0 # via torch types-python-dateutil==2.9.0.20240316 @@ -980,10 +1059,13 @@ typing-extensions==4.11.0 # alembic # dioptra # dioptra (pyproject.toml) + # huggingface-hub # ipython + # lightning-utilities # maite # sqlalchemy # torch + # torcheval tzdata==2024.1 # via # pandas @@ -1027,6 +1109,8 @@ wheel==0.43.0 # pip-tools widgetsnbextension==4.0.10 # via ipywidgets +xxhash==3.4.1 + # via datasets yarl==1.9.4 # via aiohttp zict==3.0.0 diff --git a/requirements/linux-arm64-py3.11-requirements-dev-pytorch.txt b/requirements/linux-arm64-py3.11-requirements-dev-pytorch.txt index 05c3475ee..95a020b9b 100644 --- a/requirements/linux-arm64-py3.11-requirements-dev-pytorch.txt +++ b/requirements/linux-arm64-py3.11-requirements-dev-pytorch.txt @@ -13,7 +13,10 @@ absl-py==2.1.0 adversarial-robustness-toolbox==1.17.1 # via dioptra (pyproject.toml) aiohttp==3.9.5 - # via dioptra (pyproject.toml) + # via + # datasets + # dioptra (pyproject.toml) + # fsspec aiosignal==1.3.1 # via aiohttp alabaster==0.7.16 @@ -124,7 +127,9 @@ cloudpickle==3.0.0 # mlflow # prefect colorama==0.4.6 - # via tox + # via + # pretty-errors + # tox comm==0.2.2 # via # ipykernel @@ -143,12 +148,18 @@ dask==2024.5.0 # via # distributed # prefect +datasets==2.19.1 + # via maite debugpy==1.8.1 # via ipykernel decorator==5.1.1 # via ipython defusedxml==0.7.1 # via nbconvert +dill==0.3.8 + # via + # datasets + # multiprocess distlib==0.3.8 # via virtualenv distributed==2024.5.0 @@ -172,8 +183,11 @@ fastjsonschema==2.19.1 # via nbformat filelock==3.14.0 # via + # datasets + # huggingface-hub # torch # tox + # transformers # virtualenv flake8==7.0.0 # via @@ -227,9 +241,11 @@ frozenlist==1.4.1 # via # aiohttp # aiosignal -fsspec==2024.3.1 +fsspec[http]==2024.3.1 # via # dask + # datasets + # huggingface-hub # torch # universal-pathlib gitdb==4.0.11 @@ -256,6 +272,13 @@ httpcore==1.0.5 # via httpx httpx==0.27.0 # via jupyterlab +huggingface-hub==0.23.0 + # via + # datasets + # maite + # timm + # tokenizers + # transformers idna==3.7 # via # anyio @@ -394,13 +417,15 @@ kiwisolver==1.4.5 # via matplotlib lazy-loader==0.4 # via scikit-image +lightning-utilities==0.11.2 + # via torchmetrics locket==1.0.0 # via # distributed # partd lsprotocol==2023.0.1 # via pygls -maite[all-interop]==0.5.0 +maite[all-interop]==0.4.0 # via dioptra (pyproject.toml) mako==1.3.3 # via alembic @@ -460,6 +485,8 @@ multimethod==1.11.2 # via # dioptra # dioptra (pyproject.toml) +multiprocess==0.70.16 + # via datasets mypy-extensions==1.0.0 # via prefect nbclient==0.10.0 @@ -492,6 +519,7 @@ numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy + # datasets # dioptra # dioptra (pyproject.toml) # imageio @@ -516,7 +544,9 @@ numpy==1.24.0 # smqtk-image-io # tensorboard # tifffile + # torchmetrics # torchvision + # transformers opencv-python==4.9.0.80 # via # dioptra (pyproject.toml) @@ -529,14 +559,17 @@ packaging==24.0 # via # build # dask + # datasets # distributed # docker # gunicorn + # huggingface-hub # ipykernel # jupyter-server # jupyterlab # jupyterlab-server # lazy-loader + # lightning-utilities # marshmallow # matplotlib # mlflow @@ -548,9 +581,12 @@ packaging==24.0 # qtpy # scikit-image # sphinx + # torchmetrics # tox + # transformers pandas==2.2.2 # via + # datasets # dioptra # dioptra (pyproject.toml) # mlflow @@ -592,6 +628,8 @@ pluggy==1.5.0 # tox prefect==1.4.1 # via dioptra (pyproject.toml) +pretty-errors==1.2.25 + # via torchmetrics prometheus-client==0.20.0 # via jupyter-server prompt-toolkit==3.0.43 @@ -616,13 +654,17 @@ pure-eval==0.2.2 # via stack-data pyarrow==15.0.2 # via + # datasets # dioptra (pyproject.toml) # mlflow +pyarrow-hotfix==0.6 + # via datasets pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) + # maite # nrtk pycodestyle==2.11.1 # via @@ -700,12 +742,16 @@ pyyaml==6.0.1 # via # cookiecutter # dask + # datasets # dioptra # dioptra (pyproject.toml) # distributed + # huggingface-hub # jupyter-events # mlflow # prefect + # timm + # transformers pyzmq==26.0.3 # via # ipykernel @@ -729,18 +775,23 @@ referencing==0.35.1 # jsonschema # jsonschema-specifications # jupyter-events +regex==2024.4.28 + # via transformers requests==2.31.0 # via # cookiecutter + # datasets # dioptra # dioptra (pyproject.toml) # docker + # huggingface-hub # jupyterlab-server # kaggle # mlflow # prefect # smqtk-dataprovider # sphinx + # transformers rfc3339-validator==0.1.4 # via # jsonschema @@ -763,6 +814,10 @@ rq==1.16.2 # dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 +safetensors==0.4.3 + # via + # timm + # transformers scikit-image==0.23.2 # via # imgaug @@ -895,8 +950,12 @@ tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum +timm==0.9.16 + # via maite tinycss2==1.3.0 # via nbconvert +tokenizers==0.19.1 + # via transformers toml==0.10.2 # via prefect tomli==2.0.1 @@ -912,12 +971,21 @@ torch==2.2.2 # via # -r requirements-dev-pytorch.in # maite + # timm # torchaudio + # torchmetrics # torchvision torchaudio==2.2.2 # via -r requirements-dev-pytorch.in +torcheval==0.0.7 + # via maite +torchmetrics==1.4.0 + # via maite torchvision==0.17.2 - # via -r requirements-dev-pytorch.in + # via + # -r requirements-dev-pytorch.in + # maite + # timm tornado==6.4 # via # distributed @@ -932,8 +1000,12 @@ tox==4.15.0 tqdm==4.66.4 # via # adversarial-robustness-toolbox + # datasets + # huggingface-hub # kaggle + # maite # nrtk + # transformers traitlets==5.14.3 # via # comm @@ -951,6 +1023,8 @@ traitlets==5.14.3 # nbconvert # nbformat # qtconsole +transformers==4.40.2 + # via maite types-python-dateutil==2.9.0.20240316 # via arrow typing-extensions==4.11.0 @@ -958,10 +1032,13 @@ typing-extensions==4.11.0 # alembic # dioptra # dioptra (pyproject.toml) + # huggingface-hub # ipython + # lightning-utilities # maite # sqlalchemy # torch + # torcheval tzdata==2024.1 # via # pandas @@ -1005,6 +1082,8 @@ wheel==0.43.0 # pip-tools widgetsnbextension==4.0.10 # via ipywidgets +xxhash==3.4.1 + # via datasets yarl==1.9.4 # via aiohttp zict==3.0.0 diff --git a/requirements/linux-arm64-py3.11-requirements-dev-tensorflow.txt b/requirements/linux-arm64-py3.11-requirements-dev-tensorflow.txt index 6b1f24ecd..50ac80469 100644 --- a/requirements/linux-arm64-py3.11-requirements-dev-tensorflow.txt +++ b/requirements/linux-arm64-py3.11-requirements-dev-tensorflow.txt @@ -14,7 +14,10 @@ absl-py==2.1.0 adversarial-robustness-toolbox==1.17.1 # via dioptra (pyproject.toml) aiohttp==3.9.5 - # via dioptra (pyproject.toml) + # via + # datasets + # dioptra (pyproject.toml) + # fsspec aiosignal==1.3.1 # via aiohttp alabaster==0.7.16 @@ -127,7 +130,9 @@ cloudpickle==3.0.0 # mlflow # prefect colorama==0.4.6 - # via tox + # via + # pretty-errors + # tox comm==0.2.2 # via # ipykernel @@ -146,12 +151,18 @@ dask==2024.5.0 # via # distributed # prefect +datasets==2.19.1 + # via maite debugpy==1.8.1 # via ipykernel decorator==5.1.1 # via ipython defusedxml==0.7.1 # via nbconvert +dill==0.3.8 + # via + # datasets + # multiprocess distlib==0.3.8 # via virtualenv distributed==2024.5.0 @@ -175,8 +186,11 @@ fastjsonschema==2.19.1 # via nbformat filelock==3.14.0 # via + # datasets + # huggingface-hub # torch # tox + # transformers # virtualenv flake8==7.0.0 # via @@ -232,9 +246,11 @@ frozenlist==1.4.1 # via # aiohttp # aiosignal -fsspec==2024.3.1 +fsspec[http]==2024.3.1 # via # dask + # datasets + # huggingface-hub # torch # universal-pathlib gast==0.5.4 @@ -271,6 +287,13 @@ httpcore==1.0.5 # via httpx httpx==0.27.0 # via jupyterlab +huggingface-hub==0.23.0 + # via + # datasets + # maite + # timm + # tokenizers + # transformers idna==3.7 # via # anyio @@ -413,13 +436,15 @@ lazy-loader==0.4 # via scikit-image libclang==18.1.1 # via tensorflow +lightning-utilities==0.11.2 + # via torchmetrics locket==1.0.0 # via # distributed # partd lsprotocol==2023.0.1 # via pygls -maite[all-interop]==0.5.0 +maite[all-interop]==0.4.0 # via dioptra (pyproject.toml) mako==1.3.3 # via alembic @@ -483,6 +508,8 @@ multimethod==1.11.2 # via # dioptra # dioptra (pyproject.toml) +multiprocess==0.70.16 + # via datasets mypy-extensions==1.0.0 # via prefect namex==0.0.8 @@ -517,6 +544,7 @@ numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy + # datasets # dioptra # dioptra (pyproject.toml) # h5py @@ -546,6 +574,9 @@ numpy==1.24.0 # tensorboard # tensorflow # tifffile + # torchmetrics + # torchvision + # transformers opencv-python==4.9.0.80 # via # dioptra (pyproject.toml) @@ -562,14 +593,17 @@ packaging==24.0 # via # build # dask + # datasets # distributed # docker # gunicorn + # huggingface-hub # ipykernel # jupyter-server # jupyterlab # jupyterlab-server # lazy-loader + # lightning-utilities # marshmallow # matplotlib # mlflow @@ -582,9 +616,12 @@ packaging==24.0 # scikit-image # sphinx # tensorflow + # torchmetrics # tox + # transformers pandas==2.2.2 # via + # datasets # dioptra # dioptra (pyproject.toml) # mlflow @@ -611,6 +648,7 @@ pillow==10.3.0 # nrtk # scikit-image # smqtk-image-io + # torchvision pip-tools==7.4.1 # via dioptra (pyproject.toml) platformdirs==4.2.1 @@ -625,6 +663,8 @@ pluggy==1.5.0 # tox prefect==1.4.1 # via dioptra (pyproject.toml) +pretty-errors==1.2.25 + # via torchmetrics prometheus-client==0.20.0 # via jupyter-server prompt-toolkit==3.0.43 @@ -650,13 +690,17 @@ pure-eval==0.2.2 # via stack-data pyarrow==15.0.2 # via + # datasets # dioptra (pyproject.toml) # mlflow +pyarrow-hotfix==0.6 + # via datasets pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) + # maite # nrtk pycodestyle==2.11.1 # via @@ -734,12 +778,16 @@ pyyaml==6.0.1 # via # cookiecutter # dask + # datasets # dioptra # dioptra (pyproject.toml) # distributed + # huggingface-hub # jupyter-events # mlflow # prefect + # timm + # transformers pyzmq==26.0.3 # via # ipykernel @@ -763,12 +811,16 @@ referencing==0.35.1 # jsonschema # jsonschema-specifications # jupyter-events +regex==2024.4.28 + # via transformers requests==2.31.0 # via # cookiecutter + # datasets # dioptra # dioptra (pyproject.toml) # docker + # huggingface-hub # jupyterlab-server # kaggle # mlflow @@ -776,6 +828,7 @@ requests==2.31.0 # smqtk-dataprovider # sphinx # tensorflow + # transformers rfc3339-validator==0.1.4 # via # jsonschema @@ -799,6 +852,10 @@ rq==1.16.2 # dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 +safetensors==0.4.3 + # via + # timm + # transformers scikit-image==0.23.2 # via # imgaug @@ -942,8 +999,12 @@ tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum +timm==0.9.16 + # via maite tinycss2==1.3.0 # via nbconvert +tokenizers==0.19.1 + # via transformers toml==0.10.2 # via prefect tomli==2.0.1 @@ -956,7 +1017,19 @@ toolz==0.12.1 # distributed # partd torch==2.3.0 + # via + # maite + # timm + # torchmetrics + # torchvision +torcheval==0.0.7 # via maite +torchmetrics==1.4.0 + # via maite +torchvision==0.18.0 + # via + # maite + # timm tornado==6.4 # via # distributed @@ -971,8 +1044,12 @@ tox==4.15.0 tqdm==4.66.4 # via # adversarial-robustness-toolbox + # datasets + # huggingface-hub # kaggle + # maite # nrtk + # transformers traitlets==5.14.3 # via # comm @@ -990,6 +1067,8 @@ traitlets==5.14.3 # nbconvert # nbformat # qtconsole +transformers==4.40.2 + # via maite types-python-dateutil==2.9.0.20240316 # via arrow typing-extensions==4.11.0 @@ -997,12 +1076,15 @@ typing-extensions==4.11.0 # alembic # dioptra # dioptra (pyproject.toml) + # huggingface-hub # ipython + # lightning-utilities # maite # optree # sqlalchemy # tensorflow # torch + # torcheval tzdata==2024.1 # via # pandas @@ -1049,6 +1131,8 @@ widgetsnbextension==4.0.10 # via ipywidgets wrapt==1.16.0 # via tensorflow +xxhash==3.4.1 + # via datasets yarl==1.9.4 # via aiohttp zict==3.0.0 diff --git a/requirements/linux-arm64-py3.11-requirements-dev.txt b/requirements/linux-arm64-py3.11-requirements-dev.txt index db53c5b08..4a3754553 100644 --- a/requirements/linux-arm64-py3.11-requirements-dev.txt +++ b/requirements/linux-arm64-py3.11-requirements-dev.txt @@ -11,7 +11,10 @@ absl-py==2.1.0 adversarial-robustness-toolbox==1.17.1 # via dioptra (pyproject.toml) aiohttp==3.9.5 - # via dioptra (pyproject.toml) + # via + # datasets + # dioptra (pyproject.toml) + # fsspec aiosignal==1.3.1 # via aiohttp alabaster==0.7.16 @@ -122,7 +125,9 @@ cloudpickle==3.0.0 # mlflow # prefect colorama==0.4.6 - # via tox + # via + # pretty-errors + # tox comm==0.2.2 # via # ipykernel @@ -141,12 +146,18 @@ dask==2024.5.0 # via # distributed # prefect +datasets==2.19.1 + # via maite debugpy==1.8.1 # via ipykernel decorator==5.1.1 # via ipython defusedxml==0.7.1 # via nbconvert +dill==0.3.8 + # via + # datasets + # multiprocess distlib==0.3.8 # via virtualenv distributed==2024.5.0 @@ -170,8 +181,11 @@ fastjsonschema==2.19.1 # via nbformat filelock==3.14.0 # via + # datasets + # huggingface-hub # torch # tox + # transformers # virtualenv flake8==7.0.0 # via @@ -225,9 +239,11 @@ frozenlist==1.4.1 # via # aiohttp # aiosignal -fsspec==2024.3.1 +fsspec[http]==2024.3.1 # via # dask + # datasets + # huggingface-hub # torch # universal-pathlib gitdb==4.0.11 @@ -254,6 +270,13 @@ httpcore==1.0.5 # via httpx httpx==0.27.0 # via jupyterlab +huggingface-hub==0.23.0 + # via + # datasets + # maite + # timm + # tokenizers + # transformers idna==3.7 # via # anyio @@ -392,13 +415,15 @@ kiwisolver==1.4.5 # via matplotlib lazy-loader==0.4 # via scikit-image +lightning-utilities==0.11.2 + # via torchmetrics locket==1.0.0 # via # distributed # partd lsprotocol==2023.0.1 # via pygls -maite[all-interop]==0.5.0 +maite[all-interop]==0.4.0 # via dioptra (pyproject.toml) mako==1.3.3 # via alembic @@ -458,6 +483,8 @@ multimethod==1.11.2 # via # dioptra # dioptra (pyproject.toml) +multiprocess==0.70.16 + # via datasets mypy-extensions==1.0.0 # via prefect nbclient==0.10.0 @@ -490,6 +517,7 @@ numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy + # datasets # dioptra # dioptra (pyproject.toml) # imageio @@ -514,6 +542,9 @@ numpy==1.24.0 # smqtk-image-io # tensorboard # tifffile + # torchmetrics + # torchvision + # transformers opencv-python==4.9.0.80 # via # dioptra (pyproject.toml) @@ -526,14 +557,17 @@ packaging==24.0 # via # build # dask + # datasets # distributed # docker # gunicorn + # huggingface-hub # ipykernel # jupyter-server # jupyterlab # jupyterlab-server # lazy-loader + # lightning-utilities # marshmallow # matplotlib # mlflow @@ -545,9 +579,12 @@ packaging==24.0 # qtpy # scikit-image # sphinx + # torchmetrics # tox + # transformers pandas==2.2.2 # via + # datasets # dioptra # dioptra (pyproject.toml) # mlflow @@ -574,6 +611,7 @@ pillow==10.3.0 # nrtk # scikit-image # smqtk-image-io + # torchvision pip-tools==7.4.1 # via dioptra (pyproject.toml) platformdirs==4.2.1 @@ -588,6 +626,8 @@ pluggy==1.5.0 # tox prefect==1.4.1 # via dioptra (pyproject.toml) +pretty-errors==1.2.25 + # via torchmetrics prometheus-client==0.20.0 # via jupyter-server prompt-toolkit==3.0.43 @@ -612,13 +652,17 @@ pure-eval==0.2.2 # via stack-data pyarrow==15.0.2 # via + # datasets # dioptra (pyproject.toml) # mlflow +pyarrow-hotfix==0.6 + # via datasets pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) + # maite # nrtk pycodestyle==2.11.1 # via @@ -696,12 +740,16 @@ pyyaml==6.0.1 # via # cookiecutter # dask + # datasets # dioptra # dioptra (pyproject.toml) # distributed + # huggingface-hub # jupyter-events # mlflow # prefect + # timm + # transformers pyzmq==26.0.3 # via # ipykernel @@ -725,18 +773,23 @@ referencing==0.35.1 # jsonschema # jsonschema-specifications # jupyter-events +regex==2024.4.28 + # via transformers requests==2.31.0 # via # cookiecutter + # datasets # dioptra # dioptra (pyproject.toml) # docker + # huggingface-hub # jupyterlab-server # kaggle # mlflow # prefect # smqtk-dataprovider # sphinx + # transformers rfc3339-validator==0.1.4 # via # jsonschema @@ -759,6 +812,10 @@ rq==1.16.2 # dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 +safetensors==0.4.3 + # via + # timm + # transformers scikit-image==0.23.2 # via # imgaug @@ -891,8 +948,12 @@ tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum +timm==0.9.16 + # via maite tinycss2==1.3.0 # via nbconvert +tokenizers==0.19.1 + # via transformers toml==0.10.2 # via prefect tomli==2.0.1 @@ -905,7 +966,19 @@ toolz==0.12.1 # distributed # partd torch==2.3.0 + # via + # maite + # timm + # torchmetrics + # torchvision +torcheval==0.0.7 # via maite +torchmetrics==1.4.0 + # via maite +torchvision==0.18.0 + # via + # maite + # timm tornado==6.4 # via # distributed @@ -920,8 +993,12 @@ tox==4.15.0 tqdm==4.66.4 # via # adversarial-robustness-toolbox + # datasets + # huggingface-hub # kaggle + # maite # nrtk + # transformers traitlets==5.14.3 # via # comm @@ -939,6 +1016,8 @@ traitlets==5.14.3 # nbconvert # nbformat # qtconsole +transformers==4.40.2 + # via maite types-python-dateutil==2.9.0.20240316 # via arrow typing-extensions==4.11.0 @@ -946,10 +1025,13 @@ typing-extensions==4.11.0 # alembic # dioptra # dioptra (pyproject.toml) + # huggingface-hub # ipython + # lightning-utilities # maite # sqlalchemy # torch + # torcheval tzdata==2024.1 # via # pandas @@ -993,6 +1075,8 @@ wheel==0.43.0 # pip-tools widgetsnbextension==4.0.10 # via ipywidgets +xxhash==3.4.1 + # via datasets yarl==1.9.4 # via aiohttp zict==3.0.0 diff --git a/requirements/macos-amd64-py3.11-requirements-dev-pytorch.txt b/requirements/macos-amd64-py3.11-requirements-dev-pytorch.txt index 0be73e208..dc83474cb 100644 --- a/requirements/macos-amd64-py3.11-requirements-dev-pytorch.txt +++ b/requirements/macos-amd64-py3.11-requirements-dev-pytorch.txt @@ -13,7 +13,10 @@ absl-py==2.1.0 adversarial-robustness-toolbox==1.17.1 # via dioptra (pyproject.toml) aiohttp==3.9.5 - # via dioptra (pyproject.toml) + # via + # datasets + # dioptra (pyproject.toml) + # fsspec aiosignal==1.3.1 # via aiohttp alabaster==0.7.16 @@ -126,7 +129,9 @@ cloudpickle==3.0.0 # mlflow # prefect colorama==0.4.6 - # via tox + # via + # pretty-errors + # tox comm==0.2.2 # via # ipykernel @@ -145,12 +150,18 @@ dask==2024.5.0 # via # distributed # prefect +datasets==2.19.1 + # via maite debugpy==1.8.1 # via ipykernel decorator==5.1.1 # via ipython defusedxml==0.7.1 # via nbconvert +dill==0.3.8 + # via + # datasets + # multiprocess distlib==0.3.8 # via virtualenv distributed==2024.5.0 @@ -174,8 +185,11 @@ fastjsonschema==2.19.1 # via nbformat filelock==3.14.0 # via + # datasets + # huggingface-hub # torch # tox + # transformers # virtualenv flake8==7.0.0 # via @@ -229,9 +243,11 @@ frozenlist==1.4.1 # via # aiohttp # aiosignal -fsspec==2024.3.1 +fsspec[http]==2024.3.1 # via # dask + # datasets + # huggingface-hub # torch # universal-pathlib gitdb==4.0.11 @@ -258,6 +274,13 @@ httpcore==1.0.5 # via httpx httpx==0.27.0 # via jupyterlab +huggingface-hub==0.23.0 + # via + # datasets + # maite + # timm + # tokenizers + # transformers idna==3.7 # via # anyio @@ -396,13 +419,15 @@ kiwisolver==1.4.5 # via matplotlib lazy-loader==0.4 # via scikit-image +lightning-utilities==0.11.2 + # via torchmetrics locket==1.0.0 # via # distributed # partd lsprotocol==2023.0.1 # via pygls -maite[all-interop]==0.5.0 +maite[all-interop]==0.4.0 # via dioptra (pyproject.toml) mako==1.3.3 # via alembic @@ -462,6 +487,8 @@ multimethod==1.11.2 # via # dioptra # dioptra (pyproject.toml) +multiprocess==0.70.16 + # via datasets mypy-extensions==1.0.0 # via prefect nbclient==0.10.0 @@ -494,6 +521,7 @@ numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy + # datasets # dioptra # dioptra (pyproject.toml) # imageio @@ -518,7 +546,9 @@ numpy==1.24.0 # smqtk-image-io # tensorboard # tifffile + # torchmetrics # torchvision + # transformers opencv-python==4.9.0.80 # via # dioptra (pyproject.toml) @@ -531,14 +561,17 @@ packaging==24.0 # via # build # dask + # datasets # distributed # docker # gunicorn + # huggingface-hub # ipykernel # jupyter-server # jupyterlab # jupyterlab-server # lazy-loader + # lightning-utilities # marshmallow # matplotlib # mlflow @@ -550,9 +583,12 @@ packaging==24.0 # qtpy # scikit-image # sphinx + # torchmetrics # tox + # transformers pandas==2.2.2 # via + # datasets # dioptra # dioptra (pyproject.toml) # mlflow @@ -594,6 +630,8 @@ pluggy==1.5.0 # tox prefect==1.4.1 # via dioptra (pyproject.toml) +pretty-errors==1.2.25 + # via torchmetrics prometheus-client==0.20.0 # via jupyter-server prompt-toolkit==3.0.43 @@ -618,13 +656,17 @@ pure-eval==0.2.2 # via stack-data pyarrow==15.0.2 # via + # datasets # dioptra (pyproject.toml) # mlflow +pyarrow-hotfix==0.6 + # via datasets pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) + # maite # nrtk pycodestyle==2.11.1 # via @@ -702,12 +744,16 @@ pyyaml==6.0.1 # via # cookiecutter # dask + # datasets # dioptra # dioptra (pyproject.toml) # distributed + # huggingface-hub # jupyter-events # mlflow # prefect + # timm + # transformers pyzmq==26.0.3 # via # ipykernel @@ -731,18 +777,23 @@ referencing==0.35.1 # jsonschema # jsonschema-specifications # jupyter-events +regex==2024.4.28 + # via transformers requests==2.31.0 # via # cookiecutter + # datasets # dioptra # dioptra (pyproject.toml) # docker + # huggingface-hub # jupyterlab-server # kaggle # mlflow # prefect # smqtk-dataprovider # sphinx + # transformers rfc3339-validator==0.1.4 # via # jsonschema @@ -765,6 +816,10 @@ rq==1.16.2 # dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 +safetensors==0.4.3 + # via + # timm + # transformers scikit-image==0.23.2 # via # imgaug @@ -897,8 +952,12 @@ tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum +timm==0.9.16 + # via maite tinycss2==1.3.0 # via nbconvert +tokenizers==0.19.1 + # via transformers toml==0.10.2 # via prefect tomli==2.0.1 @@ -914,12 +973,21 @@ torch==2.2.2 # via # -r requirements-dev-pytorch.in # maite + # timm # torchaudio + # torchmetrics # torchvision torchaudio==2.2.2 # via -r requirements-dev-pytorch.in +torcheval==0.0.7 + # via maite +torchmetrics==1.4.0 + # via maite torchvision==0.17.2 - # via -r requirements-dev-pytorch.in + # via + # -r requirements-dev-pytorch.in + # maite + # timm tornado==6.4 # via # distributed @@ -934,8 +1002,12 @@ tox==4.15.0 tqdm==4.66.4 # via # adversarial-robustness-toolbox + # datasets + # huggingface-hub # kaggle + # maite # nrtk + # transformers traitlets==5.14.3 # via # comm @@ -953,6 +1025,8 @@ traitlets==5.14.3 # nbconvert # nbformat # qtconsole +transformers==4.40.2 + # via maite types-python-dateutil==2.9.0.20240316 # via arrow typing-extensions==4.11.0 @@ -960,10 +1034,13 @@ typing-extensions==4.11.0 # alembic # dioptra # dioptra (pyproject.toml) + # huggingface-hub # ipython + # lightning-utilities # maite # sqlalchemy # torch + # torcheval tzdata==2024.1 # via # pandas @@ -1007,6 +1084,8 @@ wheel==0.43.0 # pip-tools widgetsnbextension==4.0.10 # via ipywidgets +xxhash==3.4.1 + # via datasets yarl==1.9.4 # via aiohttp zict==3.0.0 diff --git a/requirements/macos-amd64-py3.11-requirements-dev-tensorflow.txt b/requirements/macos-amd64-py3.11-requirements-dev-tensorflow.txt index 3a3ef6387..1c00c0167 100644 --- a/requirements/macos-amd64-py3.11-requirements-dev-tensorflow.txt +++ b/requirements/macos-amd64-py3.11-requirements-dev-tensorflow.txt @@ -14,7 +14,10 @@ absl-py==2.1.0 adversarial-robustness-toolbox==1.17.1 # via dioptra (pyproject.toml) aiohttp==3.9.5 - # via dioptra (pyproject.toml) + # via + # datasets + # dioptra (pyproject.toml) + # fsspec aiosignal==1.3.1 # via aiohttp alabaster==0.7.16 @@ -129,7 +132,9 @@ cloudpickle==3.0.0 # mlflow # prefect colorama==0.4.6 - # via tox + # via + # pretty-errors + # tox comm==0.2.2 # via # ipykernel @@ -148,12 +153,18 @@ dask==2024.5.0 # via # distributed # prefect +datasets==2.19.1 + # via maite debugpy==1.8.1 # via ipykernel decorator==5.1.1 # via ipython defusedxml==0.7.1 # via nbconvert +dill==0.3.8 + # via + # datasets + # multiprocess distlib==0.3.8 # via virtualenv distributed==2024.5.0 @@ -177,8 +188,11 @@ fastjsonschema==2.19.1 # via nbformat filelock==3.14.0 # via + # datasets + # huggingface-hub # torch # tox + # transformers # virtualenv flake8==7.0.0 # via @@ -234,9 +248,11 @@ frozenlist==1.4.1 # via # aiohttp # aiosignal -fsspec==2024.3.1 +fsspec[http]==2024.3.1 # via # dask + # datasets + # huggingface-hub # torch # universal-pathlib gast==0.5.4 @@ -273,6 +289,13 @@ httpcore==1.0.5 # via httpx httpx==0.27.0 # via jupyterlab +huggingface-hub==0.23.0 + # via + # datasets + # maite + # timm + # tokenizers + # transformers idna==3.7 # via # anyio @@ -415,13 +438,15 @@ lazy-loader==0.4 # via scikit-image libclang==18.1.1 # via tensorflow +lightning-utilities==0.11.2 + # via torchmetrics locket==1.0.0 # via # distributed # partd lsprotocol==2023.0.1 # via pygls -maite[all-interop]==0.5.0 +maite[all-interop]==0.4.0 # via dioptra (pyproject.toml) mako==1.3.3 # via alembic @@ -485,6 +510,8 @@ multimethod==1.11.2 # via # dioptra # dioptra (pyproject.toml) +multiprocess==0.70.16 + # via datasets mypy-extensions==1.0.0 # via prefect namex==0.0.8 @@ -519,6 +546,7 @@ numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy + # datasets # dioptra # dioptra (pyproject.toml) # h5py @@ -548,6 +576,9 @@ numpy==1.24.0 # tensorboard # tensorflow # tifffile + # torchmetrics + # torchvision + # transformers opencv-python==4.9.0.80 # via # dioptra (pyproject.toml) @@ -564,14 +595,17 @@ packaging==24.0 # via # build # dask + # datasets # distributed # docker # gunicorn + # huggingface-hub # ipykernel # jupyter-server # jupyterlab # jupyterlab-server # lazy-loader + # lightning-utilities # marshmallow # matplotlib # mlflow @@ -584,9 +618,12 @@ packaging==24.0 # scikit-image # sphinx # tensorflow + # torchmetrics # tox + # transformers pandas==2.2.2 # via + # datasets # dioptra # dioptra (pyproject.toml) # mlflow @@ -613,6 +650,7 @@ pillow==10.3.0 # nrtk # scikit-image # smqtk-image-io + # torchvision pip-tools==7.4.1 # via dioptra (pyproject.toml) platformdirs==4.2.1 @@ -627,6 +665,8 @@ pluggy==1.5.0 # tox prefect==1.4.1 # via dioptra (pyproject.toml) +pretty-errors==1.2.25 + # via torchmetrics prometheus-client==0.20.0 # via jupyter-server prompt-toolkit==3.0.43 @@ -652,13 +692,17 @@ pure-eval==0.2.2 # via stack-data pyarrow==15.0.2 # via + # datasets # dioptra (pyproject.toml) # mlflow +pyarrow-hotfix==0.6 + # via datasets pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) + # maite # nrtk pycodestyle==2.11.1 # via @@ -736,12 +780,16 @@ pyyaml==6.0.1 # via # cookiecutter # dask + # datasets # dioptra # dioptra (pyproject.toml) # distributed + # huggingface-hub # jupyter-events # mlflow # prefect + # timm + # transformers pyzmq==26.0.3 # via # ipykernel @@ -765,12 +813,16 @@ referencing==0.35.1 # jsonschema # jsonschema-specifications # jupyter-events +regex==2024.4.28 + # via transformers requests==2.31.0 # via # cookiecutter + # datasets # dioptra # dioptra (pyproject.toml) # docker + # huggingface-hub # jupyterlab-server # kaggle # mlflow @@ -778,6 +830,7 @@ requests==2.31.0 # smqtk-dataprovider # sphinx # tensorflow + # transformers rfc3339-validator==0.1.4 # via # jsonschema @@ -801,6 +854,10 @@ rq==1.16.2 # dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 +safetensors==0.4.3 + # via + # timm + # transformers scikit-image==0.23.2 # via # imgaug @@ -944,8 +1001,12 @@ tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum +timm==0.9.16 + # via maite tinycss2==1.3.0 # via nbconvert +tokenizers==0.19.1 + # via transformers toml==0.10.2 # via prefect tomli==2.0.1 @@ -958,7 +1019,19 @@ toolz==0.12.1 # distributed # partd torch==2.2.2 + # via + # maite + # timm + # torchmetrics + # torchvision +torcheval==0.0.7 # via maite +torchmetrics==1.4.0 + # via maite +torchvision==0.17.2 + # via + # maite + # timm tornado==6.4 # via # distributed @@ -973,8 +1046,12 @@ tox==4.15.0 tqdm==4.66.4 # via # adversarial-robustness-toolbox + # datasets + # huggingface-hub # kaggle + # maite # nrtk + # transformers traitlets==5.14.3 # via # comm @@ -992,6 +1069,8 @@ traitlets==5.14.3 # nbconvert # nbformat # qtconsole +transformers==4.40.2 + # via maite types-python-dateutil==2.9.0.20240316 # via arrow typing-extensions==4.11.0 @@ -999,12 +1078,15 @@ typing-extensions==4.11.0 # alembic # dioptra # dioptra (pyproject.toml) + # huggingface-hub # ipython + # lightning-utilities # maite # optree # sqlalchemy # tensorflow # torch + # torcheval tzdata==2024.1 # via # pandas @@ -1051,6 +1133,8 @@ widgetsnbextension==4.0.10 # via ipywidgets wrapt==1.16.0 # via tensorflow +xxhash==3.4.1 + # via datasets yarl==1.9.4 # via aiohttp zict==3.0.0 diff --git a/requirements/macos-amd64-py3.11-requirements-dev.txt b/requirements/macos-amd64-py3.11-requirements-dev.txt index 69461d073..b4ebd0efe 100644 --- a/requirements/macos-amd64-py3.11-requirements-dev.txt +++ b/requirements/macos-amd64-py3.11-requirements-dev.txt @@ -11,7 +11,10 @@ absl-py==2.1.0 adversarial-robustness-toolbox==1.17.1 # via dioptra (pyproject.toml) aiohttp==3.9.5 - # via dioptra (pyproject.toml) + # via + # datasets + # dioptra (pyproject.toml) + # fsspec aiosignal==1.3.1 # via aiohttp alabaster==0.7.16 @@ -124,7 +127,9 @@ cloudpickle==3.0.0 # mlflow # prefect colorama==0.4.6 - # via tox + # via + # pretty-errors + # tox comm==0.2.2 # via # ipykernel @@ -143,12 +148,18 @@ dask==2024.5.0 # via # distributed # prefect +datasets==2.19.1 + # via maite debugpy==1.8.1 # via ipykernel decorator==5.1.1 # via ipython defusedxml==0.7.1 # via nbconvert +dill==0.3.8 + # via + # datasets + # multiprocess distlib==0.3.8 # via virtualenv distributed==2024.5.0 @@ -172,8 +183,11 @@ fastjsonschema==2.19.1 # via nbformat filelock==3.14.0 # via + # datasets + # huggingface-hub # torch # tox + # transformers # virtualenv flake8==7.0.0 # via @@ -227,9 +241,11 @@ frozenlist==1.4.1 # via # aiohttp # aiosignal -fsspec==2024.3.1 +fsspec[http]==2024.3.1 # via # dask + # datasets + # huggingface-hub # torch # universal-pathlib gitdb==4.0.11 @@ -256,6 +272,13 @@ httpcore==1.0.5 # via httpx httpx==0.27.0 # via jupyterlab +huggingface-hub==0.23.0 + # via + # datasets + # maite + # timm + # tokenizers + # transformers idna==3.7 # via # anyio @@ -394,13 +417,15 @@ kiwisolver==1.4.5 # via matplotlib lazy-loader==0.4 # via scikit-image +lightning-utilities==0.11.2 + # via torchmetrics locket==1.0.0 # via # distributed # partd lsprotocol==2023.0.1 # via pygls -maite[all-interop]==0.5.0 +maite[all-interop]==0.4.0 # via dioptra (pyproject.toml) mako==1.3.3 # via alembic @@ -460,6 +485,8 @@ multimethod==1.11.2 # via # dioptra # dioptra (pyproject.toml) +multiprocess==0.70.16 + # via datasets mypy-extensions==1.0.0 # via prefect nbclient==0.10.0 @@ -492,6 +519,7 @@ numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy + # datasets # dioptra # dioptra (pyproject.toml) # imageio @@ -516,6 +544,9 @@ numpy==1.24.0 # smqtk-image-io # tensorboard # tifffile + # torchmetrics + # torchvision + # transformers opencv-python==4.9.0.80 # via # dioptra (pyproject.toml) @@ -528,14 +559,17 @@ packaging==24.0 # via # build # dask + # datasets # distributed # docker # gunicorn + # huggingface-hub # ipykernel # jupyter-server # jupyterlab # jupyterlab-server # lazy-loader + # lightning-utilities # marshmallow # matplotlib # mlflow @@ -547,9 +581,12 @@ packaging==24.0 # qtpy # scikit-image # sphinx + # torchmetrics # tox + # transformers pandas==2.2.2 # via + # datasets # dioptra # dioptra (pyproject.toml) # mlflow @@ -576,6 +613,7 @@ pillow==10.3.0 # nrtk # scikit-image # smqtk-image-io + # torchvision pip-tools==7.4.1 # via dioptra (pyproject.toml) platformdirs==4.2.1 @@ -590,6 +628,8 @@ pluggy==1.5.0 # tox prefect==1.4.1 # via dioptra (pyproject.toml) +pretty-errors==1.2.25 + # via torchmetrics prometheus-client==0.20.0 # via jupyter-server prompt-toolkit==3.0.43 @@ -614,13 +654,17 @@ pure-eval==0.2.2 # via stack-data pyarrow==15.0.2 # via + # datasets # dioptra (pyproject.toml) # mlflow +pyarrow-hotfix==0.6 + # via datasets pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) + # maite # nrtk pycodestyle==2.11.1 # via @@ -698,12 +742,16 @@ pyyaml==6.0.1 # via # cookiecutter # dask + # datasets # dioptra # dioptra (pyproject.toml) # distributed + # huggingface-hub # jupyter-events # mlflow # prefect + # timm + # transformers pyzmq==26.0.3 # via # ipykernel @@ -727,18 +775,23 @@ referencing==0.35.1 # jsonschema # jsonschema-specifications # jupyter-events +regex==2024.4.28 + # via transformers requests==2.31.0 # via # cookiecutter + # datasets # dioptra # dioptra (pyproject.toml) # docker + # huggingface-hub # jupyterlab-server # kaggle # mlflow # prefect # smqtk-dataprovider # sphinx + # transformers rfc3339-validator==0.1.4 # via # jsonschema @@ -761,6 +814,10 @@ rq==1.16.2 # dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 +safetensors==0.4.3 + # via + # timm + # transformers scikit-image==0.23.2 # via # imgaug @@ -893,8 +950,12 @@ tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum +timm==0.9.16 + # via maite tinycss2==1.3.0 # via nbconvert +tokenizers==0.19.1 + # via transformers toml==0.10.2 # via prefect tomli==2.0.1 @@ -907,7 +968,19 @@ toolz==0.12.1 # distributed # partd torch==2.2.2 + # via + # maite + # timm + # torchmetrics + # torchvision +torcheval==0.0.7 # via maite +torchmetrics==1.4.0 + # via maite +torchvision==0.17.2 + # via + # maite + # timm tornado==6.4 # via # distributed @@ -922,8 +995,12 @@ tox==4.15.0 tqdm==4.66.4 # via # adversarial-robustness-toolbox + # datasets + # huggingface-hub # kaggle + # maite # nrtk + # transformers traitlets==5.14.3 # via # comm @@ -941,6 +1018,8 @@ traitlets==5.14.3 # nbconvert # nbformat # qtconsole +transformers==4.40.2 + # via maite types-python-dateutil==2.9.0.20240316 # via arrow typing-extensions==4.11.0 @@ -948,10 +1027,13 @@ typing-extensions==4.11.0 # alembic # dioptra # dioptra (pyproject.toml) + # huggingface-hub # ipython + # lightning-utilities # maite # sqlalchemy # torch + # torcheval tzdata==2024.1 # via # pandas @@ -995,6 +1077,8 @@ wheel==0.43.0 # pip-tools widgetsnbextension==4.0.10 # via ipywidgets +xxhash==3.4.1 + # via datasets yarl==1.9.4 # via aiohttp zict==3.0.0 diff --git a/requirements/macos-arm64-py3.11-requirements-dev-pytorch.txt b/requirements/macos-arm64-py3.11-requirements-dev-pytorch.txt index 2e16f4346..d68b87813 100644 --- a/requirements/macos-arm64-py3.11-requirements-dev-pytorch.txt +++ b/requirements/macos-arm64-py3.11-requirements-dev-pytorch.txt @@ -13,7 +13,10 @@ absl-py==2.1.0 adversarial-robustness-toolbox==1.17.1 # via dioptra (pyproject.toml) aiohttp==3.9.5 - # via dioptra (pyproject.toml) + # via + # datasets + # dioptra (pyproject.toml) + # fsspec aiosignal==1.3.1 # via aiohttp alabaster==0.7.16 @@ -126,7 +129,9 @@ cloudpickle==3.0.0 # mlflow # prefect colorama==0.4.6 - # via tox + # via + # pretty-errors + # tox comm==0.2.2 # via # ipykernel @@ -145,12 +150,18 @@ dask==2024.5.0 # via # distributed # prefect +datasets==2.19.1 + # via maite debugpy==1.8.1 # via ipykernel decorator==5.1.1 # via ipython defusedxml==0.7.1 # via nbconvert +dill==0.3.8 + # via + # datasets + # multiprocess distlib==0.3.8 # via virtualenv distributed==2024.5.0 @@ -174,8 +185,11 @@ fastjsonschema==2.19.1 # via nbformat filelock==3.14.0 # via + # datasets + # huggingface-hub # torch # tox + # transformers # virtualenv flake8==7.0.0 # via @@ -229,9 +243,11 @@ frozenlist==1.4.1 # via # aiohttp # aiosignal -fsspec==2024.3.1 +fsspec[http]==2024.3.1 # via # dask + # datasets + # huggingface-hub # torch # universal-pathlib gitdb==4.0.11 @@ -256,6 +272,13 @@ httpcore==1.0.5 # via httpx httpx==0.27.0 # via jupyterlab +huggingface-hub==0.23.0 + # via + # datasets + # maite + # timm + # tokenizers + # transformers idna==3.7 # via # anyio @@ -394,13 +417,15 @@ kiwisolver==1.4.5 # via matplotlib lazy-loader==0.4 # via scikit-image +lightning-utilities==0.11.2 + # via torchmetrics locket==1.0.0 # via # distributed # partd lsprotocol==2023.0.1 # via pygls -maite[all-interop]==0.5.0 +maite[all-interop]==0.4.0 # via dioptra (pyproject.toml) mako==1.3.3 # via alembic @@ -460,6 +485,8 @@ multimethod==1.11.2 # via # dioptra # dioptra (pyproject.toml) +multiprocess==0.70.16 + # via datasets mypy-extensions==1.0.0 # via prefect nbclient==0.10.0 @@ -492,6 +519,7 @@ numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy + # datasets # dioptra # dioptra (pyproject.toml) # imageio @@ -516,7 +544,9 @@ numpy==1.24.0 # smqtk-image-io # tensorboard # tifffile + # torchmetrics # torchvision + # transformers opencv-python==4.9.0.80 # via # dioptra (pyproject.toml) @@ -529,14 +559,17 @@ packaging==24.0 # via # build # dask + # datasets # distributed # docker # gunicorn + # huggingface-hub # ipykernel # jupyter-server # jupyterlab # jupyterlab-server # lazy-loader + # lightning-utilities # marshmallow # matplotlib # mlflow @@ -548,9 +581,12 @@ packaging==24.0 # qtpy # scikit-image # sphinx + # torchmetrics # tox + # transformers pandas==2.2.2 # via + # datasets # dioptra # dioptra (pyproject.toml) # mlflow @@ -592,6 +628,8 @@ pluggy==1.5.0 # tox prefect==1.4.1 # via dioptra (pyproject.toml) +pretty-errors==1.2.25 + # via torchmetrics prometheus-client==0.20.0 # via jupyter-server prompt-toolkit==3.0.43 @@ -616,13 +654,17 @@ pure-eval==0.2.2 # via stack-data pyarrow==15.0.2 # via + # datasets # dioptra (pyproject.toml) # mlflow +pyarrow-hotfix==0.6 + # via datasets pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) + # maite # nrtk pycodestyle==2.11.1 # via @@ -700,12 +742,16 @@ pyyaml==6.0.1 # via # cookiecutter # dask + # datasets # dioptra # dioptra (pyproject.toml) # distributed + # huggingface-hub # jupyter-events # mlflow # prefect + # timm + # transformers pyzmq==26.0.3 # via # ipykernel @@ -729,18 +775,23 @@ referencing==0.35.1 # jsonschema # jsonschema-specifications # jupyter-events +regex==2024.4.28 + # via transformers requests==2.31.0 # via # cookiecutter + # datasets # dioptra # dioptra (pyproject.toml) # docker + # huggingface-hub # jupyterlab-server # kaggle # mlflow # prefect # smqtk-dataprovider # sphinx + # transformers rfc3339-validator==0.1.4 # via # jsonschema @@ -763,6 +814,10 @@ rq==1.16.2 # dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 +safetensors==0.4.3 + # via + # timm + # transformers scikit-image==0.23.2 # via # imgaug @@ -895,8 +950,12 @@ tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum +timm==0.9.16 + # via maite tinycss2==1.3.0 # via nbconvert +tokenizers==0.19.1 + # via transformers toml==0.10.2 # via prefect tomli==2.0.1 @@ -912,12 +971,21 @@ torch==2.2.2 # via # -r requirements-dev-pytorch.in # maite + # timm # torchaudio + # torchmetrics # torchvision torchaudio==2.2.2 # via -r requirements-dev-pytorch.in +torcheval==0.0.7 + # via maite +torchmetrics==1.4.0 + # via maite torchvision==0.17.2 - # via -r requirements-dev-pytorch.in + # via + # -r requirements-dev-pytorch.in + # maite + # timm tornado==6.4 # via # distributed @@ -932,8 +1000,12 @@ tox==4.15.0 tqdm==4.66.4 # via # adversarial-robustness-toolbox + # datasets + # huggingface-hub # kaggle + # maite # nrtk + # transformers traitlets==5.14.3 # via # comm @@ -951,6 +1023,8 @@ traitlets==5.14.3 # nbconvert # nbformat # qtconsole +transformers==4.40.2 + # via maite types-python-dateutil==2.9.0.20240316 # via arrow typing-extensions==4.11.0 @@ -958,10 +1032,13 @@ typing-extensions==4.11.0 # alembic # dioptra # dioptra (pyproject.toml) + # huggingface-hub # ipython + # lightning-utilities # maite # sqlalchemy # torch + # torcheval tzdata==2024.1 # via # pandas @@ -1005,6 +1082,8 @@ wheel==0.43.0 # pip-tools widgetsnbextension==4.0.10 # via ipywidgets +xxhash==3.4.1 + # via datasets yarl==1.9.4 # via aiohttp zict==3.0.0 diff --git a/requirements/macos-arm64-py3.11-requirements-dev-tensorflow.txt b/requirements/macos-arm64-py3.11-requirements-dev-tensorflow.txt index 67b3aa332..d644e4cae 100644 --- a/requirements/macos-arm64-py3.11-requirements-dev-tensorflow.txt +++ b/requirements/macos-arm64-py3.11-requirements-dev-tensorflow.txt @@ -14,7 +14,10 @@ absl-py==2.1.0 adversarial-robustness-toolbox==1.17.1 # via dioptra (pyproject.toml) aiohttp==3.9.5 - # via dioptra (pyproject.toml) + # via + # datasets + # dioptra (pyproject.toml) + # fsspec aiosignal==1.3.1 # via aiohttp alabaster==0.7.16 @@ -129,7 +132,9 @@ cloudpickle==3.0.0 # mlflow # prefect colorama==0.4.6 - # via tox + # via + # pretty-errors + # tox comm==0.2.2 # via # ipykernel @@ -148,12 +153,18 @@ dask==2024.5.0 # via # distributed # prefect +datasets==2.19.1 + # via maite debugpy==1.8.1 # via ipykernel decorator==5.1.1 # via ipython defusedxml==0.7.1 # via nbconvert +dill==0.3.8 + # via + # datasets + # multiprocess distlib==0.3.8 # via virtualenv distributed==2024.5.0 @@ -177,8 +188,11 @@ fastjsonschema==2.19.1 # via nbformat filelock==3.14.0 # via + # datasets + # huggingface-hub # torch # tox + # transformers # virtualenv flake8==7.0.0 # via @@ -234,9 +248,11 @@ frozenlist==1.4.1 # via # aiohttp # aiosignal -fsspec==2024.3.1 +fsspec[http]==2024.3.1 # via # dask + # datasets + # huggingface-hub # torch # universal-pathlib gast==0.5.4 @@ -271,6 +287,13 @@ httpcore==1.0.5 # via httpx httpx==0.27.0 # via jupyterlab +huggingface-hub==0.23.0 + # via + # datasets + # maite + # timm + # tokenizers + # transformers idna==3.7 # via # anyio @@ -413,13 +436,15 @@ lazy-loader==0.4 # via scikit-image libclang==18.1.1 # via tensorflow +lightning-utilities==0.11.2 + # via torchmetrics locket==1.0.0 # via # distributed # partd lsprotocol==2023.0.1 # via pygls -maite[all-interop]==0.5.0 +maite[all-interop]==0.4.0 # via dioptra (pyproject.toml) mako==1.3.3 # via alembic @@ -483,6 +508,8 @@ multimethod==1.11.2 # via # dioptra # dioptra (pyproject.toml) +multiprocess==0.70.16 + # via datasets mypy-extensions==1.0.0 # via prefect namex==0.0.8 @@ -517,6 +544,7 @@ numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy + # datasets # dioptra # dioptra (pyproject.toml) # h5py @@ -546,6 +574,9 @@ numpy==1.24.0 # tensorboard # tensorflow # tifffile + # torchmetrics + # torchvision + # transformers opencv-python==4.9.0.80 # via # dioptra (pyproject.toml) @@ -562,14 +593,17 @@ packaging==24.0 # via # build # dask + # datasets # distributed # docker # gunicorn + # huggingface-hub # ipykernel # jupyter-server # jupyterlab # jupyterlab-server # lazy-loader + # lightning-utilities # marshmallow # matplotlib # mlflow @@ -582,9 +616,12 @@ packaging==24.0 # scikit-image # sphinx # tensorflow + # torchmetrics # tox + # transformers pandas==2.2.2 # via + # datasets # dioptra # dioptra (pyproject.toml) # mlflow @@ -611,6 +648,7 @@ pillow==10.3.0 # nrtk # scikit-image # smqtk-image-io + # torchvision pip-tools==7.4.1 # via dioptra (pyproject.toml) platformdirs==4.2.1 @@ -625,6 +663,8 @@ pluggy==1.5.0 # tox prefect==1.4.1 # via dioptra (pyproject.toml) +pretty-errors==1.2.25 + # via torchmetrics prometheus-client==0.20.0 # via jupyter-server prompt-toolkit==3.0.43 @@ -650,13 +690,17 @@ pure-eval==0.2.2 # via stack-data pyarrow==15.0.2 # via + # datasets # dioptra (pyproject.toml) # mlflow +pyarrow-hotfix==0.6 + # via datasets pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) + # maite # nrtk pycodestyle==2.11.1 # via @@ -734,12 +778,16 @@ pyyaml==6.0.1 # via # cookiecutter # dask + # datasets # dioptra # dioptra (pyproject.toml) # distributed + # huggingface-hub # jupyter-events # mlflow # prefect + # timm + # transformers pyzmq==26.0.3 # via # ipykernel @@ -763,12 +811,16 @@ referencing==0.35.1 # jsonschema # jsonschema-specifications # jupyter-events +regex==2024.4.28 + # via transformers requests==2.31.0 # via # cookiecutter + # datasets # dioptra # dioptra (pyproject.toml) # docker + # huggingface-hub # jupyterlab-server # kaggle # mlflow @@ -776,6 +828,7 @@ requests==2.31.0 # smqtk-dataprovider # sphinx # tensorflow + # transformers rfc3339-validator==0.1.4 # via # jsonschema @@ -799,6 +852,10 @@ rq==1.16.2 # dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 +safetensors==0.4.3 + # via + # timm + # transformers scikit-image==0.23.2 # via # imgaug @@ -945,8 +1002,12 @@ tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum +timm==0.9.16 + # via maite tinycss2==1.3.0 # via nbconvert +tokenizers==0.19.1 + # via transformers toml==0.10.2 # via prefect tomli==2.0.1 @@ -959,7 +1020,19 @@ toolz==0.12.1 # distributed # partd torch==2.3.0 + # via + # maite + # timm + # torchmetrics + # torchvision +torcheval==0.0.7 # via maite +torchmetrics==1.4.0 + # via maite +torchvision==0.18.0 + # via + # maite + # timm tornado==6.4 # via # distributed @@ -974,8 +1047,12 @@ tox==4.15.0 tqdm==4.66.4 # via # adversarial-robustness-toolbox + # datasets + # huggingface-hub # kaggle + # maite # nrtk + # transformers traitlets==5.14.3 # via # comm @@ -993,6 +1070,8 @@ traitlets==5.14.3 # nbconvert # nbformat # qtconsole +transformers==4.40.2 + # via maite types-python-dateutil==2.9.0.20240316 # via arrow typing-extensions==4.11.0 @@ -1000,12 +1079,15 @@ typing-extensions==4.11.0 # alembic # dioptra # dioptra (pyproject.toml) + # huggingface-hub # ipython + # lightning-utilities # maite # optree # sqlalchemy # tensorflow # torch + # torcheval tzdata==2024.1 # via # pandas @@ -1053,6 +1135,8 @@ widgetsnbextension==4.0.10 # via ipywidgets wrapt==1.16.0 # via tensorflow +xxhash==3.4.1 + # via datasets yarl==1.9.4 # via aiohttp zict==3.0.0 diff --git a/requirements/macos-arm64-py3.11-requirements-dev.txt b/requirements/macos-arm64-py3.11-requirements-dev.txt index 9566ac0d8..5b4954fb3 100644 --- a/requirements/macos-arm64-py3.11-requirements-dev.txt +++ b/requirements/macos-arm64-py3.11-requirements-dev.txt @@ -11,7 +11,10 @@ absl-py==2.1.0 adversarial-robustness-toolbox==1.17.1 # via dioptra (pyproject.toml) aiohttp==3.9.5 - # via dioptra (pyproject.toml) + # via + # datasets + # dioptra (pyproject.toml) + # fsspec aiosignal==1.3.1 # via aiohttp alabaster==0.7.16 @@ -124,7 +127,9 @@ cloudpickle==3.0.0 # mlflow # prefect colorama==0.4.6 - # via tox + # via + # pretty-errors + # tox comm==0.2.2 # via # ipykernel @@ -143,12 +148,18 @@ dask==2024.5.0 # via # distributed # prefect +datasets==2.19.1 + # via maite debugpy==1.8.1 # via ipykernel decorator==5.1.1 # via ipython defusedxml==0.7.1 # via nbconvert +dill==0.3.8 + # via + # datasets + # multiprocess distlib==0.3.8 # via virtualenv distributed==2024.5.0 @@ -172,8 +183,11 @@ fastjsonschema==2.19.1 # via nbformat filelock==3.14.0 # via + # datasets + # huggingface-hub # torch # tox + # transformers # virtualenv flake8==7.0.0 # via @@ -227,9 +241,11 @@ frozenlist==1.4.1 # via # aiohttp # aiosignal -fsspec==2024.3.1 +fsspec[http]==2024.3.1 # via # dask + # datasets + # huggingface-hub # torch # universal-pathlib gitdb==4.0.11 @@ -254,6 +270,13 @@ httpcore==1.0.5 # via httpx httpx==0.27.0 # via jupyterlab +huggingface-hub==0.23.0 + # via + # datasets + # maite + # timm + # tokenizers + # transformers idna==3.7 # via # anyio @@ -392,13 +415,15 @@ kiwisolver==1.4.5 # via matplotlib lazy-loader==0.4 # via scikit-image +lightning-utilities==0.11.2 + # via torchmetrics locket==1.0.0 # via # distributed # partd lsprotocol==2023.0.1 # via pygls -maite[all-interop]==0.5.0 +maite[all-interop]==0.4.0 # via dioptra (pyproject.toml) mako==1.3.3 # via alembic @@ -458,6 +483,8 @@ multimethod==1.11.2 # via # dioptra # dioptra (pyproject.toml) +multiprocess==0.70.16 + # via datasets mypy-extensions==1.0.0 # via prefect nbclient==0.10.0 @@ -490,6 +517,7 @@ numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy + # datasets # dioptra # dioptra (pyproject.toml) # imageio @@ -514,6 +542,9 @@ numpy==1.24.0 # smqtk-image-io # tensorboard # tifffile + # torchmetrics + # torchvision + # transformers opencv-python==4.9.0.80 # via # dioptra (pyproject.toml) @@ -526,14 +557,17 @@ packaging==24.0 # via # build # dask + # datasets # distributed # docker # gunicorn + # huggingface-hub # ipykernel # jupyter-server # jupyterlab # jupyterlab-server # lazy-loader + # lightning-utilities # marshmallow # matplotlib # mlflow @@ -545,9 +579,12 @@ packaging==24.0 # qtpy # scikit-image # sphinx + # torchmetrics # tox + # transformers pandas==2.2.2 # via + # datasets # dioptra # dioptra (pyproject.toml) # mlflow @@ -574,6 +611,7 @@ pillow==10.3.0 # nrtk # scikit-image # smqtk-image-io + # torchvision pip-tools==7.4.1 # via dioptra (pyproject.toml) platformdirs==4.2.1 @@ -588,6 +626,8 @@ pluggy==1.5.0 # tox prefect==1.4.1 # via dioptra (pyproject.toml) +pretty-errors==1.2.25 + # via torchmetrics prometheus-client==0.20.0 # via jupyter-server prompt-toolkit==3.0.43 @@ -612,13 +652,17 @@ pure-eval==0.2.2 # via stack-data pyarrow==15.0.2 # via + # datasets # dioptra (pyproject.toml) # mlflow +pyarrow-hotfix==0.6 + # via datasets pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) + # maite # nrtk pycodestyle==2.11.1 # via @@ -696,12 +740,16 @@ pyyaml==6.0.1 # via # cookiecutter # dask + # datasets # dioptra # dioptra (pyproject.toml) # distributed + # huggingface-hub # jupyter-events # mlflow # prefect + # timm + # transformers pyzmq==26.0.3 # via # ipykernel @@ -725,18 +773,23 @@ referencing==0.35.1 # jsonschema # jsonschema-specifications # jupyter-events +regex==2024.4.28 + # via transformers requests==2.31.0 # via # cookiecutter + # datasets # dioptra # dioptra (pyproject.toml) # docker + # huggingface-hub # jupyterlab-server # kaggle # mlflow # prefect # smqtk-dataprovider # sphinx + # transformers rfc3339-validator==0.1.4 # via # jsonschema @@ -759,6 +812,10 @@ rq==1.16.2 # dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 +safetensors==0.4.3 + # via + # timm + # transformers scikit-image==0.23.2 # via # imgaug @@ -891,8 +948,12 @@ tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum +timm==0.9.16 + # via maite tinycss2==1.3.0 # via nbconvert +tokenizers==0.19.1 + # via transformers toml==0.10.2 # via prefect tomli==2.0.1 @@ -905,7 +966,19 @@ toolz==0.12.1 # distributed # partd torch==2.3.0 + # via + # maite + # timm + # torchmetrics + # torchvision +torcheval==0.0.7 # via maite +torchmetrics==1.4.0 + # via maite +torchvision==0.18.0 + # via + # maite + # timm tornado==6.4 # via # distributed @@ -920,8 +993,12 @@ tox==4.15.0 tqdm==4.66.4 # via # adversarial-robustness-toolbox + # datasets + # huggingface-hub # kaggle + # maite # nrtk + # transformers traitlets==5.14.3 # via # comm @@ -939,6 +1016,8 @@ traitlets==5.14.3 # nbconvert # nbformat # qtconsole +transformers==4.40.2 + # via maite types-python-dateutil==2.9.0.20240316 # via arrow typing-extensions==4.11.0 @@ -946,10 +1025,13 @@ typing-extensions==4.11.0 # alembic # dioptra # dioptra (pyproject.toml) + # huggingface-hub # ipython + # lightning-utilities # maite # sqlalchemy # torch + # torcheval tzdata==2024.1 # via # pandas @@ -993,6 +1075,8 @@ wheel==0.43.0 # pip-tools widgetsnbextension==4.0.10 # via ipywidgets +xxhash==3.4.1 + # via datasets yarl==1.9.4 # via aiohttp zict==3.0.0 diff --git a/requirements/win-amd64-py3.11-requirements-dev-pytorch.txt b/requirements/win-amd64-py3.11-requirements-dev-pytorch.txt index 2b8cc3cae..aa4f93704 100644 --- a/requirements/win-amd64-py3.11-requirements-dev-pytorch.txt +++ b/requirements/win-amd64-py3.11-requirements-dev-pytorch.txt @@ -13,7 +13,10 @@ absl-py==2.1.0 adversarial-robustness-toolbox==1.17.1 # via dioptra (pyproject.toml) aiohttp==3.9.5 - # via dioptra (pyproject.toml) + # via + # datasets + # dioptra (pyproject.toml) + # fsspec aiosignal==1.3.1 # via aiohttp alabaster==0.7.16 @@ -128,6 +131,7 @@ colorama==0.4.6 # build # click # ipython + # pretty-errors # pytest # sphinx # tox @@ -150,12 +154,18 @@ dask==2024.5.0 # via # distributed # prefect +datasets==2.19.1 + # via maite debugpy==1.8.1 # via ipykernel decorator==5.1.1 # via ipython defusedxml==0.7.1 # via nbconvert +dill==0.3.8 + # via + # datasets + # multiprocess distlib==0.3.8 # via virtualenv distributed==2024.5.0 @@ -179,8 +189,11 @@ fastjsonschema==2.19.1 # via nbformat filelock==3.14.0 # via + # datasets + # huggingface-hub # torch # tox + # transformers # virtualenv flake8==7.0.0 # via @@ -234,9 +247,11 @@ frozenlist==1.4.1 # via # aiohttp # aiosignal -fsspec==2024.3.1 +fsspec[http]==2024.3.1 # via # dask + # datasets + # huggingface-hub # torch # universal-pathlib gitdb==4.0.11 @@ -261,6 +276,13 @@ httpcore==1.0.5 # via httpx httpx==0.27.0 # via jupyterlab +huggingface-hub==0.23.0 + # via + # datasets + # maite + # timm + # tokenizers + # transformers idna==3.7 # via # anyio @@ -399,13 +421,15 @@ kiwisolver==1.4.5 # via matplotlib lazy-loader==0.4 # via scikit-image +lightning-utilities==0.11.2 + # via torchmetrics locket==1.0.0 # via # distributed # partd lsprotocol==2023.0.1 # via pygls -maite[all-interop]==0.5.0 +maite[all-interop]==0.4.0 # via dioptra (pyproject.toml) mako==1.3.3 # via alembic @@ -465,6 +489,8 @@ multimethod==1.11.2 # via # dioptra # dioptra (pyproject.toml) +multiprocess==0.70.16 + # via datasets mypy-extensions==1.0.0 # via prefect nbclient==0.10.0 @@ -497,6 +523,7 @@ numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy + # datasets # dioptra # dioptra (pyproject.toml) # imageio @@ -521,7 +548,9 @@ numpy==1.24.0 # smqtk-image-io # tensorboard # tifffile + # torchmetrics # torchvision + # transformers opencv-python==4.9.0.80 # via # dioptra (pyproject.toml) @@ -534,13 +563,16 @@ packaging==24.0 # via # build # dask + # datasets # distributed # docker + # huggingface-hub # ipykernel # jupyter-server # jupyterlab # jupyterlab-server # lazy-loader + # lightning-utilities # marshmallow # matplotlib # mlflow @@ -552,9 +584,12 @@ packaging==24.0 # qtpy # scikit-image # sphinx + # torchmetrics # tox + # transformers pandas==2.2.2 # via + # datasets # dioptra # dioptra (pyproject.toml) # mlflow @@ -594,6 +629,8 @@ pluggy==1.5.0 # tox prefect==1.4.1 # via dioptra (pyproject.toml) +pretty-errors==1.2.25 + # via torchmetrics prometheus-client==0.20.0 # via jupyter-server prompt-toolkit==3.0.43 @@ -614,13 +651,17 @@ pure-eval==0.2.2 # via stack-data pyarrow==15.0.2 # via + # datasets # dioptra (pyproject.toml) # mlflow +pyarrow-hotfix==0.6 + # via datasets pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) + # maite # nrtk pycodestyle==2.11.1 # via @@ -707,12 +748,16 @@ pyyaml==6.0.1 # via # cookiecutter # dask + # datasets # dioptra # dioptra (pyproject.toml) # distributed + # huggingface-hub # jupyter-events # mlflow # prefect + # timm + # transformers pyzmq==26.0.3 # via # ipykernel @@ -736,18 +781,23 @@ referencing==0.35.1 # jsonschema # jsonschema-specifications # jupyter-events +regex==2024.4.28 + # via transformers requests==2.31.0 # via # cookiecutter + # datasets # dioptra # dioptra (pyproject.toml) # docker + # huggingface-hub # jupyterlab-server # kaggle # mlflow # prefect # smqtk-dataprovider # sphinx + # transformers rfc3339-validator==0.1.4 # via # jsonschema @@ -770,6 +820,10 @@ rq==1.16.2 # dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 +safetensors==0.4.3 + # via + # timm + # transformers scikit-image==0.23.2 # via # imgaug @@ -902,8 +956,12 @@ tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum +timm==0.9.16 + # via maite tinycss2==1.3.0 # via nbconvert +tokenizers==0.19.1 + # via transformers toml==0.10.2 # via prefect tomli==2.0.1 @@ -919,12 +977,21 @@ torch==2.2.2 # via # -r requirements-dev-pytorch.in # maite + # timm # torchaudio + # torchmetrics # torchvision torchaudio==2.2.2 # via -r requirements-dev-pytorch.in +torcheval==0.0.7 + # via maite +torchmetrics==1.4.0 + # via maite torchvision==0.17.2 - # via -r requirements-dev-pytorch.in + # via + # -r requirements-dev-pytorch.in + # maite + # timm tornado==6.4 # via # distributed @@ -939,8 +1006,12 @@ tox==4.15.0 tqdm==4.66.4 # via # adversarial-robustness-toolbox + # datasets + # huggingface-hub # kaggle + # maite # nrtk + # transformers traitlets==5.14.3 # via # comm @@ -958,6 +1029,8 @@ traitlets==5.14.3 # nbconvert # nbformat # qtconsole +transformers==4.40.2 + # via maite types-python-dateutil==2.9.0.20240316 # via arrow typing-extensions==4.11.0 @@ -965,10 +1038,13 @@ typing-extensions==4.11.0 # alembic # dioptra # dioptra (pyproject.toml) + # huggingface-hub # ipython + # lightning-utilities # maite # sqlalchemy # torch + # torcheval tzdata==2024.1 # via # pandas @@ -1014,6 +1090,8 @@ wheel==0.43.0 # pip-tools widgetsnbextension==4.0.10 # via ipywidgets +xxhash==3.4.1 + # via datasets yarl==1.9.4 # via aiohttp zict==3.0.0 diff --git a/requirements/win-amd64-py3.11-requirements-dev-tensorflow.txt b/requirements/win-amd64-py3.11-requirements-dev-tensorflow.txt index addb0df75..319e820d2 100644 --- a/requirements/win-amd64-py3.11-requirements-dev-tensorflow.txt +++ b/requirements/win-amd64-py3.11-requirements-dev-tensorflow.txt @@ -14,7 +14,10 @@ absl-py==2.1.0 adversarial-robustness-toolbox==1.17.1 # via dioptra (pyproject.toml) aiohttp==3.9.5 - # via dioptra (pyproject.toml) + # via + # datasets + # dioptra (pyproject.toml) + # fsspec aiosignal==1.3.1 # via aiohttp alabaster==0.7.16 @@ -131,6 +134,7 @@ colorama==0.4.6 # build # click # ipython + # pretty-errors # pytest # sphinx # tox @@ -153,12 +157,18 @@ dask==2024.5.0 # via # distributed # prefect +datasets==2.19.1 + # via maite debugpy==1.8.1 # via ipykernel decorator==5.1.1 # via ipython defusedxml==0.7.1 # via nbconvert +dill==0.3.8 + # via + # datasets + # multiprocess distlib==0.3.8 # via virtualenv distributed==2024.5.0 @@ -182,8 +192,11 @@ fastjsonschema==2.19.1 # via nbformat filelock==3.14.0 # via + # datasets + # huggingface-hub # torch # tox + # transformers # virtualenv flake8==7.0.0 # via @@ -239,9 +252,11 @@ frozenlist==1.4.1 # via # aiohttp # aiosignal -fsspec==2024.3.1 +fsspec[http]==2024.3.1 # via # dask + # datasets + # huggingface-hub # torch # universal-pathlib gast==0.5.4 @@ -276,6 +291,13 @@ httpcore==1.0.5 # via httpx httpx==0.27.0 # via jupyterlab +huggingface-hub==0.23.0 + # via + # datasets + # maite + # timm + # tokenizers + # transformers idna==3.7 # via # anyio @@ -420,13 +442,15 @@ lazy-loader==0.4 # via scikit-image libclang==18.1.1 # via tensorflow-intel +lightning-utilities==0.11.2 + # via torchmetrics locket==1.0.0 # via # distributed # partd lsprotocol==2023.0.1 # via pygls -maite[all-interop]==0.5.0 +maite[all-interop]==0.4.0 # via dioptra (pyproject.toml) mako==1.3.3 # via alembic @@ -492,6 +516,8 @@ multimethod==1.11.2 # via # dioptra # dioptra (pyproject.toml) +multiprocess==0.70.16 + # via datasets mypy-extensions==1.0.0 # via prefect namex==0.0.8 @@ -526,6 +552,7 @@ numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy + # datasets # dioptra # dioptra (pyproject.toml) # h5py @@ -555,6 +582,9 @@ numpy==1.24.0 # tensorboard # tensorflow-intel # tifffile + # torchmetrics + # torchvision + # transformers opencv-python==4.9.0.80 # via # dioptra (pyproject.toml) @@ -571,13 +601,16 @@ packaging==24.0 # via # build # dask + # datasets # distributed # docker + # huggingface-hub # ipykernel # jupyter-server # jupyterlab # jupyterlab-server # lazy-loader + # lightning-utilities # marshmallow # matplotlib # mlflow @@ -590,9 +623,12 @@ packaging==24.0 # scikit-image # sphinx # tensorflow-intel + # torchmetrics # tox + # transformers pandas==2.2.2 # via + # datasets # dioptra # dioptra (pyproject.toml) # mlflow @@ -617,6 +653,7 @@ pillow==10.3.0 # nrtk # scikit-image # smqtk-image-io + # torchvision pip-tools==7.4.1 # via dioptra (pyproject.toml) platformdirs==4.2.1 @@ -631,6 +668,8 @@ pluggy==1.5.0 # tox prefect==1.4.1 # via dioptra (pyproject.toml) +pretty-errors==1.2.25 + # via torchmetrics prometheus-client==0.20.0 # via jupyter-server prompt-toolkit==3.0.43 @@ -652,13 +691,17 @@ pure-eval==0.2.2 # via stack-data pyarrow==15.0.2 # via + # datasets # dioptra (pyproject.toml) # mlflow +pyarrow-hotfix==0.6 + # via datasets pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) + # maite # nrtk pycodestyle==2.11.1 # via @@ -745,12 +788,16 @@ pyyaml==6.0.1 # via # cookiecutter # dask + # datasets # dioptra # dioptra (pyproject.toml) # distributed + # huggingface-hub # jupyter-events # mlflow # prefect + # timm + # transformers pyzmq==26.0.3 # via # ipykernel @@ -774,12 +821,16 @@ referencing==0.35.1 # jsonschema # jsonschema-specifications # jupyter-events +regex==2024.4.28 + # via transformers requests==2.31.0 # via # cookiecutter + # datasets # dioptra # dioptra (pyproject.toml) # docker + # huggingface-hub # jupyterlab-server # kaggle # mlflow @@ -787,6 +838,7 @@ requests==2.31.0 # smqtk-dataprovider # sphinx # tensorflow-intel + # transformers rfc3339-validator==0.1.4 # via # jsonschema @@ -810,6 +862,10 @@ rq==1.16.2 # dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 +safetensors==0.4.3 + # via + # timm + # transformers scikit-image==0.23.2 # via # imgaug @@ -957,8 +1013,12 @@ tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum +timm==0.9.16 + # via maite tinycss2==1.3.0 # via nbconvert +tokenizers==0.19.1 + # via transformers toml==0.10.2 # via prefect tomli==2.0.1 @@ -971,7 +1031,19 @@ toolz==0.12.1 # distributed # partd torch==2.3.0 + # via + # maite + # timm + # torchmetrics + # torchvision +torcheval==0.0.7 + # via maite +torchmetrics==1.4.0 # via maite +torchvision==0.18.0 + # via + # maite + # timm tornado==6.4 # via # distributed @@ -986,8 +1058,12 @@ tox==4.15.0 tqdm==4.66.4 # via # adversarial-robustness-toolbox + # datasets + # huggingface-hub # kaggle + # maite # nrtk + # transformers traitlets==5.14.3 # via # comm @@ -1005,6 +1081,8 @@ traitlets==5.14.3 # nbconvert # nbformat # qtconsole +transformers==4.40.2 + # via maite types-python-dateutil==2.9.0.20240316 # via arrow typing-extensions==4.11.0 @@ -1012,12 +1090,15 @@ typing-extensions==4.11.0 # alembic # dioptra # dioptra (pyproject.toml) + # huggingface-hub # ipython + # lightning-utilities # maite # optree # sqlalchemy # tensorflow-intel # torch + # torcheval tzdata==2024.1 # via # pandas @@ -1066,6 +1147,8 @@ widgetsnbextension==4.0.10 # via ipywidgets wrapt==1.16.0 # via tensorflow-intel +xxhash==3.4.1 + # via datasets yarl==1.9.4 # via aiohttp zict==3.0.0 diff --git a/requirements/win-amd64-py3.11-requirements-dev.txt b/requirements/win-amd64-py3.11-requirements-dev.txt index eeab86edc..0ef7676ba 100644 --- a/requirements/win-amd64-py3.11-requirements-dev.txt +++ b/requirements/win-amd64-py3.11-requirements-dev.txt @@ -11,7 +11,10 @@ absl-py==2.1.0 adversarial-robustness-toolbox==1.17.1 # via dioptra (pyproject.toml) aiohttp==3.9.5 - # via dioptra (pyproject.toml) + # via + # datasets + # dioptra (pyproject.toml) + # fsspec aiosignal==1.3.1 # via aiohttp alabaster==0.7.16 @@ -126,6 +129,7 @@ colorama==0.4.6 # build # click # ipython + # pretty-errors # pytest # sphinx # tox @@ -148,12 +152,18 @@ dask==2024.5.0 # via # distributed # prefect +datasets==2.19.1 + # via maite debugpy==1.8.1 # via ipykernel decorator==5.1.1 # via ipython defusedxml==0.7.1 # via nbconvert +dill==0.3.8 + # via + # datasets + # multiprocess distlib==0.3.8 # via virtualenv distributed==2024.5.0 @@ -177,8 +187,11 @@ fastjsonschema==2.19.1 # via nbformat filelock==3.14.0 # via + # datasets + # huggingface-hub # torch # tox + # transformers # virtualenv flake8==7.0.0 # via @@ -232,9 +245,11 @@ frozenlist==1.4.1 # via # aiohttp # aiosignal -fsspec==2024.3.1 +fsspec[http]==2024.3.1 # via # dask + # datasets + # huggingface-hub # torch # universal-pathlib gitdb==4.0.11 @@ -259,6 +274,13 @@ httpcore==1.0.5 # via httpx httpx==0.27.0 # via jupyterlab +huggingface-hub==0.23.0 + # via + # datasets + # maite + # timm + # tokenizers + # transformers idna==3.7 # via # anyio @@ -399,13 +421,15 @@ kiwisolver==1.4.5 # via matplotlib lazy-loader==0.4 # via scikit-image +lightning-utilities==0.11.2 + # via torchmetrics locket==1.0.0 # via # distributed # partd lsprotocol==2023.0.1 # via pygls -maite[all-interop]==0.5.0 +maite[all-interop]==0.4.0 # via dioptra (pyproject.toml) mako==1.3.3 # via alembic @@ -467,6 +491,8 @@ multimethod==1.11.2 # via # dioptra # dioptra (pyproject.toml) +multiprocess==0.70.16 + # via datasets mypy-extensions==1.0.0 # via prefect nbclient==0.10.0 @@ -499,6 +525,7 @@ numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy + # datasets # dioptra # dioptra (pyproject.toml) # imageio @@ -523,6 +550,9 @@ numpy==1.24.0 # smqtk-image-io # tensorboard # tifffile + # torchmetrics + # torchvision + # transformers opencv-python==4.9.0.80 # via # dioptra (pyproject.toml) @@ -535,13 +565,16 @@ packaging==24.0 # via # build # dask + # datasets # distributed # docker + # huggingface-hub # ipykernel # jupyter-server # jupyterlab # jupyterlab-server # lazy-loader + # lightning-utilities # marshmallow # matplotlib # mlflow @@ -553,9 +586,12 @@ packaging==24.0 # qtpy # scikit-image # sphinx + # torchmetrics # tox + # transformers pandas==2.2.2 # via + # datasets # dioptra # dioptra (pyproject.toml) # mlflow @@ -580,6 +616,7 @@ pillow==10.3.0 # nrtk # scikit-image # smqtk-image-io + # torchvision pip-tools==7.4.1 # via dioptra (pyproject.toml) platformdirs==4.2.1 @@ -594,6 +631,8 @@ pluggy==1.5.0 # tox prefect==1.4.1 # via dioptra (pyproject.toml) +pretty-errors==1.2.25 + # via torchmetrics prometheus-client==0.20.0 # via jupyter-server prompt-toolkit==3.0.43 @@ -614,13 +653,17 @@ pure-eval==0.2.2 # via stack-data pyarrow==15.0.2 # via + # datasets # dioptra (pyproject.toml) # mlflow +pyarrow-hotfix==0.6 + # via datasets pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) + # maite # nrtk pycodestyle==2.11.1 # via @@ -707,12 +750,16 @@ pyyaml==6.0.1 # via # cookiecutter # dask + # datasets # dioptra # dioptra (pyproject.toml) # distributed + # huggingface-hub # jupyter-events # mlflow # prefect + # timm + # transformers pyzmq==26.0.3 # via # ipykernel @@ -736,18 +783,23 @@ referencing==0.35.1 # jsonschema # jsonschema-specifications # jupyter-events +regex==2024.4.28 + # via transformers requests==2.31.0 # via # cookiecutter + # datasets # dioptra # dioptra (pyproject.toml) # docker + # huggingface-hub # jupyterlab-server # kaggle # mlflow # prefect # smqtk-dataprovider # sphinx + # transformers rfc3339-validator==0.1.4 # via # jsonschema @@ -770,6 +822,10 @@ rq==1.16.2 # dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 +safetensors==0.4.3 + # via + # timm + # transformers scikit-image==0.23.2 # via # imgaug @@ -904,8 +960,12 @@ tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum +timm==0.9.16 + # via maite tinycss2==1.3.0 # via nbconvert +tokenizers==0.19.1 + # via transformers toml==0.10.2 # via prefect tomli==2.0.1 @@ -918,7 +978,19 @@ toolz==0.12.1 # distributed # partd torch==2.3.0 + # via + # maite + # timm + # torchmetrics + # torchvision +torcheval==0.0.7 + # via maite +torchmetrics==1.4.0 # via maite +torchvision==0.18.0 + # via + # maite + # timm tornado==6.4 # via # distributed @@ -933,8 +1005,12 @@ tox==4.15.0 tqdm==4.66.4 # via # adversarial-robustness-toolbox + # datasets + # huggingface-hub # kaggle + # maite # nrtk + # transformers traitlets==5.14.3 # via # comm @@ -952,6 +1028,8 @@ traitlets==5.14.3 # nbconvert # nbformat # qtconsole +transformers==4.40.2 + # via maite types-python-dateutil==2.9.0.20240316 # via arrow typing-extensions==4.11.0 @@ -959,10 +1037,13 @@ typing-extensions==4.11.0 # alembic # dioptra # dioptra (pyproject.toml) + # huggingface-hub # ipython + # lightning-utilities # maite # sqlalchemy # torch + # torcheval tzdata==2024.1 # via # pandas @@ -1008,6 +1089,8 @@ wheel==0.43.0 # pip-tools widgetsnbextension==4.0.10 # via ipywidgets +xxhash==3.4.1 + # via datasets yarl==1.9.4 # via aiohttp zict==3.0.0 From 3f751a51e99d633139abf967c0f20c53504e98be Mon Sep 17 00:00:00 2001 From: bjpatrick <137509145+bjpatrick@users.noreply.github.com> Date: Tue, 7 May 2024 14:07:14 -0500 Subject: [PATCH 11/18] Add files via upload fixing maite version --- ...-amd64-py3.11-pytorch-cpu-requirements.txt | 103 ++++++++++++++++- ...-amd64-py3.11-pytorch-gpu-requirements.txt | 103 ++++++++++++++++- ...64-py3.11-tensorflow2-cpu-requirements.txt | 106 ++++++++++++++++- ...64-py3.11-tensorflow2-gpu-requirements.txt | 109 +++++++++++++++++- ...-arm64-py3.11-pytorch-cpu-requirements.txt | 106 ++++++++++++++++- ...64-py3.11-tensorflow2-cpu-requirements.txt | 109 +++++++++++++++++- 6 files changed, 612 insertions(+), 24 deletions(-) diff --git a/docker/requirements/linux-amd64-py3.11-pytorch-cpu-requirements.txt b/docker/requirements/linux-amd64-py3.11-pytorch-cpu-requirements.txt index b2b8ef14c..e620278ee 100644 --- a/docker/requirements/linux-amd64-py3.11-pytorch-cpu-requirements.txt +++ b/docker/requirements/linux-amd64-py3.11-pytorch-cpu-requirements.txt @@ -10,6 +10,12 @@ absl-py==2.1.0 # via tensorboard adversarial-robustness-toolbox==1.17.1 # via dioptra (pyproject.toml) +aiohttp==3.9.5 + # via + # datasets + # fsspec +aiosignal==1.3.1 + # via aiohttp alembic==1.13.1 # via # dioptra (pyproject.toml) @@ -23,6 +29,7 @@ async-timeout==4.0.3 # via dioptra (pyproject.toml) attrs==23.2.0 # via + # aiohttp # jsonschema # referencing blinker==1.8.2 @@ -53,6 +60,8 @@ cloudpickle==3.0.0 # distributed # mlflow # prefect +colorama==0.4.6 + # via pretty-errors contourpy==1.2.1 # via matplotlib croniter==2.0.5 @@ -63,6 +72,12 @@ dask==2024.5.0 # via # distributed # prefect +datasets==2.19.1 + # via maite +dill==0.3.8 + # via + # datasets + # multiprocess distributed==2024.5.0 # via prefect docker==7.0.0 @@ -75,7 +90,10 @@ entrypoints==0.4 # mlflow filelock==3.14.0 # via + # datasets + # huggingface-hub # torch + # transformers # triton flask==3.0.3 # via @@ -104,9 +122,15 @@ flask-sqlalchemy==3.1.1 # flask-migrate fonttools==4.51.0 # via matplotlib -fsspec==2024.3.1 +frozenlist==1.4.1 + # via + # aiohttp + # aiosignal +fsspec[http]==2024.3.1 # via # dask + # datasets + # huggingface-hub # torch gitdb==4.0.11 # via gitpython @@ -126,8 +150,17 @@ grpcio==1.63.0 # via tensorboard gunicorn==21.2.0 # via mlflow +huggingface-hub==0.23.0 + # via + # datasets + # maite + # timm + # tokenizers + # transformers idna==3.7 - # via requests + # via + # requests + # yarl imageio==2.34.1 # via # imgaug @@ -168,11 +201,13 @@ kiwisolver==1.4.5 # via matplotlib lazy-loader==0.4 # via scikit-image +lightning-utilities==0.11.2 + # via torchmetrics locket==1.0.0 # via # distributed # partd -maite[all-interop]==0.5.0 +maite[all-interop]==0.4.0 # via dioptra (pyproject.toml) mako==1.3.3 # via alembic @@ -214,8 +249,14 @@ msgpack==1.0.8 # via # distributed # prefect +multidict==6.0.5 + # via + # aiohttp + # yarl multimethod==1.11.2 # via dioptra (pyproject.toml) +multiprocess==0.70.16 + # via datasets mypy-extensions==1.0.0 # via prefect networkx==3.3 @@ -228,6 +269,7 @@ numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy + # datasets # dioptra (pyproject.toml) # imageio # imgaug @@ -251,7 +293,9 @@ numpy==1.24.0 # smqtk-image-io # tensorboard # tifffile + # torchmetrics # torchvision + # transformers nvidia-cublas-cu12==12.1.3.1 # via # nvidia-cudnn-cu12 @@ -292,17 +336,23 @@ opencv-python==4.9.0.80 packaging==24.0 # via # dask + # datasets # distributed # docker # gunicorn + # huggingface-hub # lazy-loader + # lightning-utilities # marshmallow # matplotlib # mlflow # prefect # scikit-image + # torchmetrics + # transformers pandas==2.2.2 # via + # datasets # dioptra (pyproject.toml) # mlflow partd==1.4.2 @@ -323,6 +373,8 @@ pillow==10.3.0 # torchvision prefect==1.4.1 # via dioptra (pyproject.toml) +pretty-errors==1.2.25 + # via torchmetrics protobuf==5.26.1 # via # mlflow @@ -333,13 +385,17 @@ psycopg2-binary==2.9.9 # via dioptra (pyproject.toml) pyarrow==15.0.2 # via + # datasets # dioptra (pyproject.toml) # mlflow +pyarrow-hotfix==0.6 + # via datasets pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) + # maite # nrtk pygments==2.18.0 # via rich @@ -371,10 +427,14 @@ pytz==2024.1 pyyaml==6.0.1 # via # dask + # datasets # dioptra (pyproject.toml) # distributed + # huggingface-hub # mlflow # prefect + # timm + # transformers querystring-parser==1.2.4 # via mlflow redis==5.0.4 @@ -385,13 +445,18 @@ referencing==0.35.1 # via # jsonschema # jsonschema-specifications +regex==2024.4.28 + # via transformers requests==2.31.0 # via + # datasets # dioptra (pyproject.toml) # docker + # huggingface-hub # mlflow # prefect # smqtk-dataprovider + # transformers rich==13.7.1 # via # dioptra (pyproject.toml) @@ -404,6 +469,10 @@ rq==1.16.2 # via dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 +safetensors==0.4.3 + # via + # timm + # transformers scikit-image==0.23.2 # via # imgaug @@ -494,6 +563,10 @@ tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum +timm==0.9.16 + # via maite +tokenizers==0.19.1 + # via transformers toml==0.10.2 # via prefect tomlkit==0.12.4 @@ -507,27 +580,45 @@ torch==2.2.2 # via # -r requirements-dev-pytorch.in # maite + # timm # torchaudio + # torchmetrics # torchvision torchaudio==2.2.2 # via -r requirements-dev-pytorch.in +torcheval==0.0.7 + # via maite +torchmetrics==1.4.0 + # via maite torchvision==0.17.2 - # via -r requirements-dev-pytorch.in + # via + # -r requirements-dev-pytorch.in + # maite + # timm tornado==6.4 # via distributed tqdm==4.66.4 # via # adversarial-robustness-toolbox + # datasets + # huggingface-hub + # maite # nrtk + # transformers +transformers==4.40.2 + # via maite triton==2.2.0 # via torch typing-extensions==4.11.0 # via # alembic # dioptra (pyproject.toml) + # huggingface-hub + # lightning-utilities # maite # sqlalchemy # torch + # torcheval tzdata==2024.1 # via # pandas @@ -547,6 +638,10 @@ werkzeug==3.0.3 # flask-login # flask-restx # tensorboard +xxhash==3.4.1 + # via datasets +yarl==1.9.4 + # via aiohttp zict==3.0.0 # via distributed zipp==3.18.1 diff --git a/docker/requirements/linux-amd64-py3.11-pytorch-gpu-requirements.txt b/docker/requirements/linux-amd64-py3.11-pytorch-gpu-requirements.txt index 456fdf504..9e59ba701 100644 --- a/docker/requirements/linux-amd64-py3.11-pytorch-gpu-requirements.txt +++ b/docker/requirements/linux-amd64-py3.11-pytorch-gpu-requirements.txt @@ -10,6 +10,12 @@ absl-py==2.1.0 # via tensorboard adversarial-robustness-toolbox==1.17.1 # via dioptra (pyproject.toml) +aiohttp==3.9.5 + # via + # datasets + # fsspec +aiosignal==1.3.1 + # via aiohttp alembic==1.13.1 # via # dioptra (pyproject.toml) @@ -23,6 +29,7 @@ async-timeout==4.0.3 # via dioptra (pyproject.toml) attrs==23.2.0 # via + # aiohttp # jsonschema # referencing blinker==1.8.2 @@ -53,6 +60,8 @@ cloudpickle==3.0.0 # distributed # mlflow # prefect +colorama==0.4.6 + # via pretty-errors contourpy==1.2.1 # via matplotlib croniter==2.0.5 @@ -63,6 +72,12 @@ dask==2024.5.0 # via # distributed # prefect +datasets==2.19.1 + # via maite +dill==0.3.8 + # via + # datasets + # multiprocess distributed==2024.5.0 # via prefect docker==7.0.0 @@ -75,7 +90,10 @@ entrypoints==0.4 # mlflow filelock==3.14.0 # via + # datasets + # huggingface-hub # torch + # transformers # triton flask==3.0.3 # via @@ -104,9 +122,15 @@ flask-sqlalchemy==3.1.1 # flask-migrate fonttools==4.51.0 # via matplotlib -fsspec==2024.3.1 +frozenlist==1.4.1 + # via + # aiohttp + # aiosignal +fsspec[http]==2024.3.1 # via # dask + # datasets + # huggingface-hub # torch gitdb==4.0.11 # via gitpython @@ -126,8 +150,17 @@ grpcio==1.63.0 # via tensorboard gunicorn==21.2.0 # via mlflow +huggingface-hub==0.23.0 + # via + # datasets + # maite + # timm + # tokenizers + # transformers idna==3.7 - # via requests + # via + # requests + # yarl imageio==2.34.1 # via # imgaug @@ -168,11 +201,13 @@ kiwisolver==1.4.5 # via matplotlib lazy-loader==0.4 # via scikit-image +lightning-utilities==0.11.2 + # via torchmetrics locket==1.0.0 # via # distributed # partd -maite[all-interop]==0.5.0 +maite[all-interop]==0.4.0 # via dioptra (pyproject.toml) mako==1.3.3 # via alembic @@ -214,8 +249,14 @@ msgpack==1.0.8 # via # distributed # prefect +multidict==6.0.5 + # via + # aiohttp + # yarl multimethod==1.11.2 # via dioptra (pyproject.toml) +multiprocess==0.70.16 + # via datasets mypy-extensions==1.0.0 # via prefect networkx==3.3 @@ -228,6 +269,7 @@ numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy + # datasets # dioptra (pyproject.toml) # imageio # imgaug @@ -251,7 +293,9 @@ numpy==1.24.0 # smqtk-image-io # tensorboard # tifffile + # torchmetrics # torchvision + # transformers nvidia-cublas-cu12==12.1.3.1 # via # nvidia-cudnn-cu12 @@ -292,17 +336,23 @@ opencv-python==4.9.0.80 packaging==24.0 # via # dask + # datasets # distributed # docker # gunicorn + # huggingface-hub # lazy-loader + # lightning-utilities # marshmallow # matplotlib # mlflow # prefect # scikit-image + # torchmetrics + # transformers pandas==2.2.2 # via + # datasets # dioptra (pyproject.toml) # mlflow partd==1.4.2 @@ -323,6 +373,8 @@ pillow==10.3.0 # torchvision prefect==1.4.1 # via dioptra (pyproject.toml) +pretty-errors==1.2.25 + # via torchmetrics protobuf==5.26.1 # via # mlflow @@ -333,13 +385,17 @@ psycopg2-binary==2.9.9 # via dioptra (pyproject.toml) pyarrow==15.0.2 # via + # datasets # dioptra (pyproject.toml) # mlflow +pyarrow-hotfix==0.6 + # via datasets pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) + # maite # nrtk pygments==2.18.0 # via rich @@ -371,10 +427,14 @@ pytz==2024.1 pyyaml==6.0.1 # via # dask + # datasets # dioptra (pyproject.toml) # distributed + # huggingface-hub # mlflow # prefect + # timm + # transformers querystring-parser==1.2.4 # via mlflow redis==5.0.4 @@ -385,13 +445,18 @@ referencing==0.35.1 # via # jsonschema # jsonschema-specifications +regex==2024.4.28 + # via transformers requests==2.31.0 # via + # datasets # dioptra (pyproject.toml) # docker + # huggingface-hub # mlflow # prefect # smqtk-dataprovider + # transformers rich==13.7.1 # via # dioptra (pyproject.toml) @@ -404,6 +469,10 @@ rq==1.16.2 # via dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 +safetensors==0.4.3 + # via + # timm + # transformers scikit-image==0.23.2 # via # imgaug @@ -494,6 +563,10 @@ tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum +timm==0.9.16 + # via maite +tokenizers==0.19.1 + # via transformers toml==0.10.2 # via prefect tomlkit==0.12.4 @@ -507,27 +580,45 @@ torch==2.2.2 # via # -r requirements-dev-pytorch-gpu.in # maite + # timm # torchaudio + # torchmetrics # torchvision torchaudio==2.2.2 # via -r requirements-dev-pytorch-gpu.in +torcheval==0.0.7 + # via maite +torchmetrics==1.4.0 + # via maite torchvision==0.17.2 - # via -r requirements-dev-pytorch-gpu.in + # via + # -r requirements-dev-pytorch-gpu.in + # maite + # timm tornado==6.4 # via distributed tqdm==4.66.4 # via # adversarial-robustness-toolbox + # datasets + # huggingface-hub + # maite # nrtk + # transformers +transformers==4.40.2 + # via maite triton==2.2.0 # via torch typing-extensions==4.11.0 # via # alembic # dioptra (pyproject.toml) + # huggingface-hub + # lightning-utilities # maite # sqlalchemy # torch + # torcheval tzdata==2024.1 # via # pandas @@ -547,6 +638,10 @@ werkzeug==3.0.3 # flask-login # flask-restx # tensorboard +xxhash==3.4.1 + # via datasets +yarl==1.9.4 + # via aiohttp zict==3.0.0 # via distributed zipp==3.18.1 diff --git a/docker/requirements/linux-amd64-py3.11-tensorflow2-cpu-requirements.txt b/docker/requirements/linux-amd64-py3.11-tensorflow2-cpu-requirements.txt index 919361c6b..f110b79a7 100644 --- a/docker/requirements/linux-amd64-py3.11-tensorflow2-cpu-requirements.txt +++ b/docker/requirements/linux-amd64-py3.11-tensorflow2-cpu-requirements.txt @@ -11,6 +11,12 @@ absl-py==2.1.0 # tensorflow adversarial-robustness-toolbox==1.17.1 # via dioptra (pyproject.toml) +aiohttp==3.9.5 + # via + # datasets + # fsspec +aiosignal==1.3.1 + # via aiohttp alembic==1.13.1 # via # dioptra (pyproject.toml) @@ -26,6 +32,7 @@ async-timeout==4.0.3 # via dioptra (pyproject.toml) attrs==23.2.0 # via + # aiohttp # jsonschema # referencing blinker==1.8.2 @@ -56,6 +63,8 @@ cloudpickle==3.0.0 # distributed # mlflow # prefect +colorama==0.4.6 + # via pretty-errors contourpy==1.2.1 # via matplotlib croniter==2.0.5 @@ -66,6 +75,12 @@ dask==2024.5.0 # via # distributed # prefect +datasets==2.19.1 + # via maite +dill==0.3.8 + # via + # datasets + # multiprocess distributed==2024.5.0 # via prefect docker==7.0.0 @@ -78,7 +93,10 @@ entrypoints==0.4 # mlflow filelock==3.14.0 # via + # datasets + # huggingface-hub # torch + # transformers # triton flask==3.0.3 # via @@ -109,9 +127,15 @@ flatbuffers==24.3.25 # via tensorflow fonttools==4.51.0 # via matplotlib -fsspec==2024.3.1 +frozenlist==1.4.1 + # via + # aiohttp + # aiosignal +fsspec[http]==2024.3.1 # via # dask + # datasets + # huggingface-hub # torch gast==0.5.4 # via tensorflow @@ -141,8 +165,17 @@ h5py==3.11.0 # via # keras # tensorflow +huggingface-hub==0.23.0 + # via + # datasets + # maite + # timm + # tokenizers + # transformers idna==3.7 - # via requests + # via + # requests + # yarl imageio==2.34.1 # via # imgaug @@ -187,11 +220,13 @@ lazy-loader==0.4 # via scikit-image libclang==18.1.1 # via tensorflow +lightning-utilities==0.11.2 + # via torchmetrics locket==1.0.0 # via # distributed # partd -maite[all-interop]==0.5.0 +maite[all-interop]==0.4.0 # via dioptra (pyproject.toml) mako==1.3.3 # via alembic @@ -237,8 +272,14 @@ msgpack==1.0.8 # via # distributed # prefect +multidict==6.0.5 + # via + # aiohttp + # yarl multimethod==1.11.2 # via dioptra (pyproject.toml) +multiprocess==0.70.16 + # via datasets mypy-extensions==1.0.0 # via prefect namex==0.0.8 @@ -253,6 +294,7 @@ numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy + # datasets # dioptra (pyproject.toml) # h5py # imageio @@ -281,6 +323,9 @@ numpy==1.24.0 # tensorboard # tensorflow # tifffile + # torchmetrics + # torchvision + # transformers nvidia-cublas-cu12==12.1.3.1 # via # nvidia-cudnn-cu12 @@ -325,18 +370,24 @@ optree==0.11.0 packaging==24.0 # via # dask + # datasets # distributed # docker # gunicorn + # huggingface-hub # lazy-loader + # lightning-utilities # marshmallow # matplotlib # mlflow # prefect # scikit-image # tensorflow + # torchmetrics + # transformers pandas==2.2.2 # via + # datasets # dioptra (pyproject.toml) # mlflow partd==1.4.2 @@ -354,8 +405,11 @@ pillow==10.3.0 # nrtk # scikit-image # smqtk-image-io + # torchvision prefect==1.4.1 # via dioptra (pyproject.toml) +pretty-errors==1.2.25 + # via torchmetrics protobuf==4.25.3 # via # mlflow @@ -367,13 +421,17 @@ psycopg2-binary==2.9.9 # via dioptra (pyproject.toml) pyarrow==15.0.2 # via + # datasets # dioptra (pyproject.toml) # mlflow +pyarrow-hotfix==0.6 + # via datasets pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) + # maite # nrtk pygments==2.18.0 # via rich @@ -405,10 +463,14 @@ pytz==2024.1 pyyaml==6.0.1 # via # dask + # datasets # dioptra (pyproject.toml) # distributed + # huggingface-hub # mlflow # prefect + # timm + # transformers querystring-parser==1.2.4 # via mlflow redis==5.0.4 @@ -419,14 +481,19 @@ referencing==0.35.1 # via # jsonschema # jsonschema-specifications +regex==2024.4.28 + # via transformers requests==2.31.0 # via + # datasets # dioptra (pyproject.toml) # docker + # huggingface-hub # mlflow # prefect # smqtk-dataprovider # tensorflow + # transformers rich==13.7.1 # via # dioptra (pyproject.toml) @@ -440,6 +507,10 @@ rq==1.16.2 # via dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 +safetensors==0.4.3 + # via + # timm + # transformers scikit-image==0.23.2 # via # imgaug @@ -541,6 +612,10 @@ tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum +timm==0.9.16 + # via maite +tokenizers==0.19.1 + # via transformers toml==0.10.2 # via prefect tomlkit==0.12.4 @@ -551,24 +626,45 @@ toolz==0.12.1 # distributed # partd torch==2.3.0 + # via + # maite + # timm + # torchmetrics + # torchvision +torcheval==0.0.7 # via maite +torchmetrics==1.4.0 + # via maite +torchvision==0.18.0 + # via + # maite + # timm tornado==6.4 # via distributed tqdm==4.66.4 # via # adversarial-robustness-toolbox + # datasets + # huggingface-hub + # maite # nrtk + # transformers +transformers==4.40.2 + # via maite triton==2.3.0 # via torch typing-extensions==4.11.0 # via # alembic # dioptra (pyproject.toml) + # huggingface-hub + # lightning-utilities # maite # optree # sqlalchemy # tensorflow # torch + # torcheval tzdata==2024.1 # via # pandas @@ -592,6 +688,10 @@ wheel==0.43.0 # via astunparse wrapt==1.16.0 # via tensorflow +xxhash==3.4.1 + # via datasets +yarl==1.9.4 + # via aiohttp zict==3.0.0 # via distributed zipp==3.18.1 diff --git a/docker/requirements/linux-amd64-py3.11-tensorflow2-gpu-requirements.txt b/docker/requirements/linux-amd64-py3.11-tensorflow2-gpu-requirements.txt index a2829c374..f53cb5d31 100644 --- a/docker/requirements/linux-amd64-py3.11-tensorflow2-gpu-requirements.txt +++ b/docker/requirements/linux-amd64-py3.11-tensorflow2-gpu-requirements.txt @@ -11,6 +11,12 @@ absl-py==2.1.0 # tensorflow adversarial-robustness-toolbox==1.17.1 # via dioptra (pyproject.toml) +aiohttp==3.9.5 + # via + # datasets + # fsspec +aiosignal==1.3.1 + # via aiohttp alembic==1.13.1 # via # dioptra (pyproject.toml) @@ -26,6 +32,7 @@ async-timeout==4.0.3 # via dioptra (pyproject.toml) attrs==23.2.0 # via + # aiohttp # jsonschema # referencing blinker==1.8.2 @@ -58,6 +65,8 @@ cloudpickle==3.0.0 # prefect cmake==3.29.2 # via triton +colorama==0.4.6 + # via pretty-errors contourpy==1.2.1 # via matplotlib croniter==2.0.5 @@ -68,6 +77,12 @@ dask==2024.5.0 # via # distributed # prefect +datasets==2.19.1 + # via maite +dill==0.3.8 + # via + # datasets + # multiprocess distributed==2024.5.0 # via prefect docker==7.0.0 @@ -80,7 +95,10 @@ entrypoints==0.4 # mlflow filelock==3.14.0 # via + # datasets + # huggingface-hub # torch + # transformers # triton flask==3.0.3 # via @@ -111,8 +129,15 @@ flatbuffers==24.3.25 # via tensorflow fonttools==4.51.0 # via matplotlib -fsspec==2024.3.1 - # via dask +frozenlist==1.4.1 + # via + # aiohttp + # aiosignal +fsspec[http]==2024.3.1 + # via + # dask + # datasets + # huggingface-hub gast==0.5.4 # via tensorflow gitdb==4.0.11 @@ -141,8 +166,17 @@ h5py==3.11.0 # via # keras # tensorflow +huggingface-hub==0.23.0 + # via + # datasets + # maite + # timm + # tokenizers + # transformers idna==3.7 - # via requests + # via + # requests + # yarl imageio==2.34.1 # via # imgaug @@ -187,13 +221,15 @@ lazy-loader==0.4 # via scikit-image libclang==18.1.1 # via tensorflow +lightning-utilities==0.11.2 + # via torchmetrics lit==18.1.4 # via triton locket==1.0.0 # via # distributed # partd -maite[all-interop]==0.5.0 +maite[all-interop]==0.4.0 # via dioptra (pyproject.toml) mako==1.3.3 # via alembic @@ -239,8 +275,14 @@ msgpack==1.0.8 # via # distributed # prefect +multidict==6.0.5 + # via + # aiohttp + # yarl multimethod==1.11.2 # via dioptra (pyproject.toml) +multiprocess==0.70.16 + # via datasets mypy-extensions==1.0.0 # via prefect namex==0.0.8 @@ -255,6 +297,7 @@ numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy + # datasets # dioptra (pyproject.toml) # h5py # imageio @@ -283,6 +326,9 @@ numpy==1.24.0 # tensorboard # tensorflow # tifffile + # torchmetrics + # torchvision + # transformers nvidia-cublas-cu11==11.10.3.66 # via # nvidia-cudnn-cu11 @@ -355,18 +401,24 @@ optree==0.11.0 packaging==24.0 # via # dask + # datasets # distributed # docker # gunicorn + # huggingface-hub # lazy-loader + # lightning-utilities # marshmallow # matplotlib # mlflow # prefect # scikit-image # tensorflow + # torchmetrics + # transformers pandas==2.2.2 # via + # datasets # dioptra (pyproject.toml) # mlflow partd==1.4.2 @@ -384,8 +436,11 @@ pillow==10.3.0 # nrtk # scikit-image # smqtk-image-io + # torchvision prefect==1.4.1 # via dioptra (pyproject.toml) +pretty-errors==1.2.25 + # via torchmetrics protobuf==4.25.3 # via # mlflow @@ -397,13 +452,17 @@ psycopg2-binary==2.9.9 # via dioptra (pyproject.toml) pyarrow==15.0.2 # via + # datasets # dioptra (pyproject.toml) # mlflow +pyarrow-hotfix==0.6 + # via datasets pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) + # maite # nrtk pygments==2.18.0 # via rich @@ -435,10 +494,14 @@ pytz==2024.1 pyyaml==6.0.1 # via # dask + # datasets # dioptra (pyproject.toml) # distributed + # huggingface-hub # mlflow # prefect + # timm + # transformers querystring-parser==1.2.4 # via mlflow redis==5.0.4 @@ -449,14 +512,20 @@ referencing==0.35.1 # via # jsonschema # jsonschema-specifications +regex==2024.4.28 + # via transformers requests==2.31.0 # via + # datasets # dioptra (pyproject.toml) # docker + # huggingface-hub # mlflow # prefect # smqtk-dataprovider # tensorflow + # torchvision + # transformers rich==13.7.1 # via # dioptra (pyproject.toml) @@ -470,6 +539,10 @@ rq==1.16.2 # via dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 +safetensors==0.4.3 + # via + # timm + # transformers scikit-image==0.23.2 # via # imgaug @@ -571,6 +644,10 @@ tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum +timm==0.9.16 + # via maite +tokenizers==0.19.1 + # via transformers toml==0.10.2 # via prefect tomlkit==0.12.4 @@ -583,24 +660,44 @@ toolz==0.12.1 torch==2.0.1 # via # maite + # timm + # torchmetrics + # torchvision # triton +torcheval==0.0.7 + # via maite +torchmetrics==1.4.0 + # via maite +torchvision==0.15.2 + # via + # maite + # timm tornado==6.4 # via distributed tqdm==4.66.4 # via # adversarial-robustness-toolbox + # datasets + # huggingface-hub + # maite # nrtk + # transformers +transformers==4.40.2 + # via maite triton==2.0.0 # via torch typing-extensions==4.11.0 # via # alembic # dioptra (pyproject.toml) + # huggingface-hub + # lightning-utilities # maite # optree # sqlalchemy # tensorflow # torch + # torcheval tzdata==2024.1 # via # pandas @@ -631,6 +728,10 @@ wheel==0.43.0 # nvidia-nvtx-cu11 wrapt==1.16.0 # via tensorflow +xxhash==3.4.1 + # via datasets +yarl==1.9.4 + # via aiohttp zict==3.0.0 # via distributed zipp==3.18.1 diff --git a/docker/requirements/linux-arm64-py3.11-pytorch-cpu-requirements.txt b/docker/requirements/linux-arm64-py3.11-pytorch-cpu-requirements.txt index b4a10559f..39158eb36 100644 --- a/docker/requirements/linux-arm64-py3.11-pytorch-cpu-requirements.txt +++ b/docker/requirements/linux-arm64-py3.11-pytorch-cpu-requirements.txt @@ -10,6 +10,12 @@ absl-py==2.1.0 # via tensorboard adversarial-robustness-toolbox==1.17.1 # via dioptra (pyproject.toml) +aiohttp==3.9.5 + # via + # datasets + # fsspec +aiosignal==1.3.1 + # via aiohttp alembic==1.13.1 # via # dioptra (pyproject.toml) @@ -23,6 +29,7 @@ async-timeout==4.0.3 # via dioptra (pyproject.toml) attrs==23.2.0 # via + # aiohttp # jsonschema # referencing blinker==1.8.2 @@ -53,6 +60,8 @@ cloudpickle==3.0.0 # distributed # mlflow # prefect +colorama==0.4.6 + # via pretty-errors contourpy==1.2.1 # via matplotlib croniter==2.0.5 @@ -63,6 +72,12 @@ dask==2024.5.0 # via # distributed # prefect +datasets==2.19.1 + # via maite +dill==0.3.8 + # via + # datasets + # multiprocess distributed==2024.5.0 # via prefect docker==7.0.0 @@ -74,7 +89,11 @@ entrypoints==0.4 # dioptra (pyproject.toml) # mlflow filelock==3.14.0 - # via torch + # via + # datasets + # huggingface-hub + # torch + # transformers flask==3.0.3 # via # dioptra (pyproject.toml) @@ -102,9 +121,15 @@ flask-sqlalchemy==3.1.1 # flask-migrate fonttools==4.51.0 # via matplotlib -fsspec==2024.3.1 +frozenlist==1.4.1 + # via + # aiohttp + # aiosignal +fsspec[http]==2024.3.1 # via # dask + # datasets + # huggingface-hub # torch gitdb==4.0.11 # via gitpython @@ -124,8 +149,17 @@ grpcio==1.63.0 # via tensorboard gunicorn==21.2.0 # via mlflow +huggingface-hub==0.23.0 + # via + # datasets + # maite + # timm + # tokenizers + # transformers idna==3.7 - # via requests + # via + # requests + # yarl imageio==2.34.1 # via # imgaug @@ -166,11 +200,13 @@ kiwisolver==1.4.5 # via matplotlib lazy-loader==0.4 # via scikit-image +lightning-utilities==0.11.2 + # via torchmetrics locket==1.0.0 # via # distributed # partd -maite[all-interop]==0.5.0 +maite[all-interop]==0.4.0 # via dioptra (pyproject.toml) mako==1.3.3 # via alembic @@ -212,8 +248,14 @@ msgpack==1.0.8 # via # distributed # prefect +multidict==6.0.5 + # via + # aiohttp + # yarl multimethod==1.11.2 # via dioptra (pyproject.toml) +multiprocess==0.70.16 + # via datasets mypy-extensions==1.0.0 # via prefect networkx==3.3 @@ -226,6 +268,7 @@ numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy + # datasets # dioptra (pyproject.toml) # imageio # imgaug @@ -249,7 +292,9 @@ numpy==1.24.0 # smqtk-image-io # tensorboard # tifffile + # torchmetrics # torchvision + # transformers opencv-python==4.9.0.80 # via # dioptra (pyproject.toml) @@ -259,17 +304,23 @@ opencv-python==4.9.0.80 packaging==24.0 # via # dask + # datasets # distributed # docker # gunicorn + # huggingface-hub # lazy-loader + # lightning-utilities # marshmallow # matplotlib # mlflow # prefect # scikit-image + # torchmetrics + # transformers pandas==2.2.2 # via + # datasets # dioptra (pyproject.toml) # mlflow partd==1.4.2 @@ -290,6 +341,8 @@ pillow==10.3.0 # torchvision prefect==1.4.1 # via dioptra (pyproject.toml) +pretty-errors==1.2.25 + # via torchmetrics protobuf==5.26.1 # via # mlflow @@ -300,13 +353,17 @@ psycopg2-binary==2.9.9 # via dioptra (pyproject.toml) pyarrow==15.0.2 # via + # datasets # dioptra (pyproject.toml) # mlflow +pyarrow-hotfix==0.6 + # via datasets pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) + # maite # nrtk pygments==2.18.0 # via rich @@ -338,10 +395,14 @@ pytz==2024.1 pyyaml==6.0.1 # via # dask + # datasets # dioptra (pyproject.toml) # distributed + # huggingface-hub # mlflow # prefect + # timm + # transformers querystring-parser==1.2.4 # via mlflow redis==5.0.4 @@ -352,13 +413,18 @@ referencing==0.35.1 # via # jsonschema # jsonschema-specifications +regex==2024.4.28 + # via transformers requests==2.31.0 # via + # datasets # dioptra (pyproject.toml) # docker + # huggingface-hub # mlflow # prefect # smqtk-dataprovider + # transformers rich==13.7.1 # via # dioptra (pyproject.toml) @@ -371,6 +437,10 @@ rq==1.16.2 # via dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 +safetensors==0.4.3 + # via + # timm + # transformers scikit-image==0.23.2 # via # imgaug @@ -461,6 +531,10 @@ tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum +timm==0.9.16 + # via maite +tokenizers==0.19.1 + # via transformers toml==0.10.2 # via prefect tomlkit==0.12.4 @@ -474,25 +548,43 @@ torch==2.2.2 # via # -r requirements-dev-pytorch.in # maite + # timm # torchaudio + # torchmetrics # torchvision torchaudio==2.2.2 # via -r requirements-dev-pytorch.in +torcheval==0.0.7 + # via maite +torchmetrics==1.4.0 + # via maite torchvision==0.17.2 - # via -r requirements-dev-pytorch.in + # via + # -r requirements-dev-pytorch.in + # maite + # timm tornado==6.4 # via distributed tqdm==4.66.4 # via # adversarial-robustness-toolbox + # datasets + # huggingface-hub + # maite # nrtk + # transformers +transformers==4.40.2 + # via maite typing-extensions==4.11.0 # via # alembic # dioptra (pyproject.toml) + # huggingface-hub + # lightning-utilities # maite # sqlalchemy # torch + # torcheval tzdata==2024.1 # via # pandas @@ -512,6 +604,10 @@ werkzeug==3.0.3 # flask-login # flask-restx # tensorboard +xxhash==3.4.1 + # via datasets +yarl==1.9.4 + # via aiohttp zict==3.0.0 # via distributed zipp==3.18.1 diff --git a/docker/requirements/linux-arm64-py3.11-tensorflow2-cpu-requirements.txt b/docker/requirements/linux-arm64-py3.11-tensorflow2-cpu-requirements.txt index 377d6b3d8..c9ba043b6 100644 --- a/docker/requirements/linux-arm64-py3.11-tensorflow2-cpu-requirements.txt +++ b/docker/requirements/linux-arm64-py3.11-tensorflow2-cpu-requirements.txt @@ -11,6 +11,12 @@ absl-py==2.1.0 # tensorflow adversarial-robustness-toolbox==1.17.1 # via dioptra (pyproject.toml) +aiohttp==3.9.5 + # via + # datasets + # fsspec +aiosignal==1.3.1 + # via aiohttp alembic==1.13.1 # via # dioptra (pyproject.toml) @@ -26,6 +32,7 @@ async-timeout==4.0.3 # via dioptra (pyproject.toml) attrs==23.2.0 # via + # aiohttp # jsonschema # referencing blinker==1.8.2 @@ -56,6 +63,8 @@ cloudpickle==3.0.0 # distributed # mlflow # prefect +colorama==0.4.6 + # via pretty-errors contourpy==1.2.1 # via matplotlib croniter==2.0.5 @@ -66,6 +75,12 @@ dask==2024.5.0 # via # distributed # prefect +datasets==2.19.1 + # via maite +dill==0.3.8 + # via + # datasets + # multiprocess distributed==2024.5.0 # via prefect docker==7.0.0 @@ -77,7 +92,11 @@ entrypoints==0.4 # dioptra (pyproject.toml) # mlflow filelock==3.14.0 - # via torch + # via + # datasets + # huggingface-hub + # torch + # transformers flask==3.0.3 # via # dioptra (pyproject.toml) @@ -107,9 +126,15 @@ flatbuffers==24.3.25 # via tensorflow fonttools==4.51.0 # via matplotlib -fsspec==2024.3.1 +frozenlist==1.4.1 + # via + # aiohttp + # aiosignal +fsspec[http]==2024.3.1 # via # dask + # datasets + # huggingface-hub # torch gast==0.5.4 # via tensorflow @@ -139,8 +164,17 @@ h5py==3.11.0 # via # keras # tensorflow +huggingface-hub==0.23.0 + # via + # datasets + # maite + # timm + # tokenizers + # transformers idna==3.7 - # via requests + # via + # requests + # yarl imageio==2.34.1 # via # imgaug @@ -185,11 +219,13 @@ lazy-loader==0.4 # via scikit-image libclang==18.1.1 # via tensorflow +lightning-utilities==0.11.2 + # via torchmetrics locket==1.0.0 # via # distributed # partd -maite[all-interop]==0.5.0 +maite[all-interop]==0.4.0 # via dioptra (pyproject.toml) mako==1.3.3 # via alembic @@ -235,8 +271,14 @@ msgpack==1.0.8 # via # distributed # prefect +multidict==6.0.5 + # via + # aiohttp + # yarl multimethod==1.11.2 # via dioptra (pyproject.toml) +multiprocess==0.70.16 + # via datasets mypy-extensions==1.0.0 # via prefect namex==0.0.8 @@ -251,6 +293,7 @@ numpy==1.24.0 # via # adversarial-robustness-toolbox # contourpy + # datasets # dioptra (pyproject.toml) # h5py # imageio @@ -279,6 +322,9 @@ numpy==1.24.0 # tensorboard # tensorflow # tifffile + # torchmetrics + # torchvision + # transformers opencv-python==4.9.0.80 # via # dioptra (pyproject.toml) @@ -292,18 +338,24 @@ optree==0.11.0 packaging==24.0 # via # dask + # datasets # distributed # docker # gunicorn + # huggingface-hub # lazy-loader + # lightning-utilities # marshmallow # matplotlib # mlflow # prefect # scikit-image # tensorflow + # torchmetrics + # transformers pandas==2.2.2 # via + # datasets # dioptra (pyproject.toml) # mlflow partd==1.4.2 @@ -321,8 +373,11 @@ pillow==10.3.0 # nrtk # scikit-image # smqtk-image-io + # torchvision prefect==1.4.1 # via dioptra (pyproject.toml) +pretty-errors==1.2.25 + # via torchmetrics protobuf==4.25.3 # via # mlflow @@ -334,13 +389,17 @@ psycopg2-binary==2.9.9 # via dioptra (pyproject.toml) pyarrow==15.0.2 # via + # datasets # dioptra (pyproject.toml) # mlflow +pyarrow-hotfix==0.6 + # via datasets pybsm==0.2.0 # via nrtk pycocotools==2.0.7 # via # dioptra (pyproject.toml) + # maite # nrtk pygments==2.18.0 # via rich @@ -372,10 +431,14 @@ pytz==2024.1 pyyaml==6.0.1 # via # dask + # datasets # dioptra (pyproject.toml) # distributed + # huggingface-hub # mlflow # prefect + # timm + # transformers querystring-parser==1.2.4 # via mlflow redis==5.0.4 @@ -386,14 +449,19 @@ referencing==0.35.1 # via # jsonschema # jsonschema-specifications +regex==2024.4.28 + # via transformers requests==2.31.0 # via + # datasets # dioptra (pyproject.toml) # docker + # huggingface-hub # mlflow # prefect # smqtk-dataprovider # tensorflow + # transformers rich==13.7.1 # via # dioptra (pyproject.toml) @@ -407,6 +475,10 @@ rq==1.16.2 # via dioptra (pyproject.toml) s3transfer==0.10.1 # via boto3 +safetensors==0.4.3 + # via + # timm + # transformers scikit-image==0.23.2 # via # imgaug @@ -508,6 +580,10 @@ tifffile==2024.5.3 # via scikit-image time-machine==2.14.1 # via pendulum +timm==0.9.16 + # via maite +tokenizers==0.19.1 + # via transformers toml==0.10.2 # via prefect tomlkit==0.12.4 @@ -518,22 +594,43 @@ toolz==0.12.1 # distributed # partd torch==2.3.0 + # via + # maite + # timm + # torchmetrics + # torchvision +torcheval==0.0.7 # via maite +torchmetrics==1.4.0 + # via maite +torchvision==0.18.0 + # via + # maite + # timm tornado==6.4 # via distributed tqdm==4.66.4 # via # adversarial-robustness-toolbox + # datasets + # huggingface-hub + # maite # nrtk + # transformers +transformers==4.40.2 + # via maite typing-extensions==4.11.0 # via # alembic # dioptra (pyproject.toml) + # huggingface-hub + # lightning-utilities # maite # optree # sqlalchemy # tensorflow # torch + # torcheval tzdata==2024.1 # via # pandas @@ -557,6 +654,10 @@ wheel==0.43.0 # via astunparse wrapt==1.16.0 # via tensorflow +xxhash==3.4.1 + # via datasets +yarl==1.9.4 + # via aiohttp zict==3.0.0 # via distributed zipp==3.18.1 From 33d703ce9b20bef30d62f40e028f28cff2cea437 Mon Sep 17 00:00:00 2001 From: bjpatrick <137509145+bjpatrick@users.noreply.github.com> Date: Tue, 7 May 2024 14:16:14 -0500 Subject: [PATCH 12/18] Update pip-compile.yml --- .github/workflows/pip-compile.yml | 3 --- 1 file changed, 3 deletions(-) diff --git a/.github/workflows/pip-compile.yml b/.github/workflows/pip-compile.yml index ca875275f..3c9084bd0 100644 --- a/.github/workflows/pip-compile.yml +++ b/.github/workflows/pip-compile.yml @@ -19,9 +19,6 @@ name: pip-compile runs on: schedule: - cron: "10 1 * * *" # at 1:10am every day - push: - branches: - - "**" jobs: pip-compile: From 9e97a1b255453ed8f70e14d76819cefe7f883c85 Mon Sep 17 00:00:00 2001 From: bjpatrick <137509145+bjpatrick@users.noreply.github.com> Date: Tue, 16 Jul 2024 17:44:13 -0500 Subject: [PATCH 13/18] Create README.md --- examples/pytorch-maite-nrtk/README.md | 21 +++++++++++++++++++++ 1 file changed, 21 insertions(+) create mode 100644 examples/pytorch-maite-nrtk/README.md diff --git a/examples/pytorch-maite-nrtk/README.md b/examples/pytorch-maite-nrtk/README.md new file mode 100644 index 000000000..d59196c05 --- /dev/null +++ b/examples/pytorch-maite-nrtk/README.md @@ -0,0 +1,21 @@ +# PyTorch MAITE Demo + +The demo provided in the Jupyter notebook `demo.ipynb` uses Dioptra to run experiments that demonstrate compatibility with the MAITE framework to run an attack on datasets and models downloaded from the huggingface repository. + +## Running the example + +To prepare your environment for running this example, follow the linked instructions below: + +1. [Create and activate a Python virtual environment and install the necessary dependencies](../README.md#creating-a-virtual-environment) +2. [Download the MNIST dataset using the download_data.py script.](../README.md#downloading-datasets) +3. [Follow the links in these User Setup instructions](../../README.md#user-setup) to do the following: + - Build the containers + - Use the cookiecutter template to generate the scripts, configuration files, and Docker Compose files you will need to run Dioptra +4. [Edit the docker-compose.yml file to mount the data folder in the worker containers](../README.md#mounting-the-data-folder-in-the-worker-containers) +5. [Initialize and start Dioptra](https://pages.nist.gov/dioptra/getting-started/running-dioptra.html#initializing-the-deployment) +6. [Register the custom task plugins for Dioptra's examples and demos](../README.md#registering-custom-task-plugins) +7. [Register the queues for Dioptra's examples and demos](../README.md#registering-queues) +8. [Start JupyterLab and open `demo.ipynb`](../README.md#starting-jupyter-lab) + +Steps 1–4 and 6–7 only need to be run once. +**Returning users only need to repeat Steps 5 (if you stopped Dioptra using `docker compose down`) and 8 (if you stopped the `jupyter lab` process)**. From 4ac89625b0988e1c083ae5ecfacd6cffa6def75f Mon Sep 17 00:00:00 2001 From: bjpatrick <137509145+bjpatrick@users.noreply.github.com> Date: Tue, 16 Jul 2024 17:44:49 -0500 Subject: [PATCH 14/18] Add files via upload --- .../pytorch-maite-nrtk/maite_nrtk_demo.ipynb | 606 ++++++++++++++++++ 1 file changed, 606 insertions(+) create mode 100644 examples/pytorch-maite-nrtk/maite_nrtk_demo.ipynb diff --git a/examples/pytorch-maite-nrtk/maite_nrtk_demo.ipynb b/examples/pytorch-maite-nrtk/maite_nrtk_demo.ipynb new file mode 100644 index 000000000..9c392d867 --- /dev/null +++ b/examples/pytorch-maite-nrtk/maite_nrtk_demo.ipynb @@ -0,0 +1,606 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Natural Robustness Toolkit (NRTK) demo" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This notebook contains an end-to-end demostration of Dioptra that can be run on any modern laptop." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Setup" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Below we import the necessary Python modules and ensure the proper environment variables are set so that all the code blocks will work as expected." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "# Import packages from the Python standard library\n", + "import importlib.util\n", + "import os\n", + "import sys\n", + "import pprint\n", + "import time\n", + "import warnings\n", + "from pathlib import Path\n", + "\n", + "\n", + "def register_python_source_file(module_name: str, filepath: Path) -> None:\n", + " \"\"\"Import a source file directly.\n", + "\n", + " Args:\n", + " module_name: The module name to associate with the imported source file.\n", + " filepath: The path to the source file.\n", + "\n", + " Notes:\n", + " Adapted from the following implementation in the Python documentation:\n", + " https://docs.python.org/3/library/importlib.html#importing-a-source-file-directly\n", + " \"\"\"\n", + " spec = importlib.util.spec_from_file_location(module_name, str(filepath))\n", + " module = importlib.util.module_from_spec(spec)\n", + " sys.modules[module_name] = module\n", + " spec.loader.exec_module(module)\n", + "\n", + "\n", + "# Filter out warning messages\n", + "warnings.filterwarnings(\"ignore\")\n", + "\n", + "# Experiment name\n", + "EXPERIMENT_NAME = \"pytorch_maite_nrtk\"\n", + "\n", + "# Default address for accessing the RESTful API service\n", + "RESTAPI_ADDRESS = \"http://localhost:80\"\n", + "\n", + "# Set DIOPTRA_RESTAPI_URI variable if not defined, used to connect to RESTful API service\n", + "os.environ[\"DIOPTRA_RESTAPI_URI\"] = RESTAPI_ADDRESS\n", + "\n", + "# Default address for accessing the MLFlow Tracking server\n", + "MLFLOW_TRACKING_URI = \"http://localhost:35000\"\n", + "\n", + "# Set MLFLOW_TRACKING_URI variable, used to connect to MLFlow Tracking service\n", + "if os.getenv(\"MLFLOW_TRACKING_URI\") is None:\n", + " os.environ[\"MLFLOW_TRACKING_URI\"] = MLFLOW_TRACKING_URI\n", + "\n", + "# Path to workflows archive\n", + "WORKFLOWS_TAR_GZ = Path(\"workflows.tar.gz\")\n", + "\n", + "# Register the examples/scripts directory as a Python module\n", + "register_python_source_file(\"scripts\", Path(\"..\", \"scripts\", \"__init__.py\"))\n", + "\n", + "from scripts.client import DioptraClient\n", + "from scripts.utils import make_tar\n", + "\n", + "# Import third-party Python packages\n", + "import numpy as np\n", + "from mlflow.tracking import MlflowClient\n", + "\n", + "# Create random number generator\n", + "rng = np.random.default_rng(54399264723942495723666216079516778448)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Submit and run jobs" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The entrypoints that we will be running in this example are implemented in the Python source files under `src/` and the `src/MLproject` file.\n", + "To run these entrypoints within Dioptra's architecture, we need to package those files up into an archive and submit it to the Dioptra RESTful API to create a new job.\n", + "For convenience, we provide the `make_tar` helper function defined in `examples/scripts/utils.py`." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "def mlflow_run_id_is_not_known(response_nrtk):\n", + " return response_nrtk[\"mlflowRunId\"] is None and response_nrtk[\"status\"] not in [\n", + " \"failed\",\n", + " \"finished\",\n", + " ]" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "PosixPath('/Users/bhodges/Desktop/Dioptra branches/bjpatrick-dioptra-nrtk/examples/pytorch-obj-detect-nrtk/workflows.tar.gz')" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "make_tar([\"src\"], WORKFLOWS_TAR_GZ)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To connect with the endpoint, we will use a client class defined in the `examples/scripts/client.py` file that is able to connect with the Dioptra RESTful API using the HTTP protocol.\n", + "We connect using the client below.\n", + "The client uses the environment variable `DIOPTRA_RESTAPI_URI`, which we configured at the top of the notebook, to figure out how to connect to the Dioptra RESTful API." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "restapi_client = DioptraClient()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We need to register an experiment under which to collect our job runs.\n", + "The code below checks if the relevant experiment exists.\n", + "If it does, then it just returns info about the experiment, if it doesn't, it then registers the new experiment." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1;36m╭─────────────────────────────────────────────────╮\u001b[0m\n", + "\u001b[1;36m│\u001b[0m\u001b[1;36m \u001b[0m\u001b[1;36mDioptra Examples - Register Custom Task Plugins\u001b[0m\u001b[1;36m \u001b[0m\u001b[1;36m│\u001b[0m\n", + "\u001b[1;36m╰─────────────────────────────────────────────────╯\u001b[0m\n", + " ‣ \u001b[1mplugins_dir:\u001b[0m ..\u001b[35m/\u001b[0m\u001b[95mtask-plugins\u001b[0m\n", + " ‣ \u001b[1mapi_url:\u001b[0m \u001b[4;39mhttp://localhost:80\u001b[0m\n", + " ‣ \u001b[1mforce:\u001b[0m \u001b[3;92mTrue\u001b[0m\n", + " \u001b[1;92m✔\u001b[0m \u001b[1;33mOverwritten.\u001b[0m \u001b[39mRemoved and re-registered the custom task plugin \u001b[0m\u001b[39m'pytorch_mi'\u001b[0m\u001b[39m.\u001b[0m\n", + " \u001b[1;92m✔\u001b[0m \u001b[1;33mOverwritten.\u001b[0m \u001b[39mRemoved and re-registered the custom task plugin \u001b[0m\n", + "\u001b[39m'model_inversion'\u001b[0m\u001b[39m.\u001b[0m\n", + " \u001b[1;92m✔\u001b[0m \u001b[1;33mOverwritten.\u001b[0m \u001b[39mRemoved and re-registered the custom task plugin \u001b[0m\u001b[39m'modelscan'\u001b[0m\u001b[39m.\u001b[0m\n", + " \u001b[1;92m✔\u001b[0m \u001b[1;33mOverwritten.\u001b[0m \u001b[39mRemoved and re-registered the custom task plugin \u001b[0m\n", + "\u001b[39m'custom_poisoning_plugins'\u001b[0m\u001b[39m.\u001b[0m\n", + " \u001b[1;92m✔\u001b[0m \u001b[1;33mOverwritten.\u001b[0m \u001b[39mRemoved and re-registered the custom task plugin \u001b[0m\n", + "\u001b[39m'custom_fgm_plugins'\u001b[0m\u001b[39m.\u001b[0m\n", + " \u001b[1;92m✔\u001b[0m \u001b[1;33mOverwritten.\u001b[0m \u001b[39mRemoved and re-registered the custom task plugin \u001b[0m\n", + "\u001b[39m'pixel_threshold'\u001b[0m\u001b[39m.\u001b[0m\n", + " \u001b[1;92m✔\u001b[0m \u001b[1;33mOverwritten.\u001b[0m \u001b[39mRemoved and re-registered the custom task plugin \u001b[0m\n", + "\u001b[39m'custom_patch_plugins'\u001b[0m\u001b[39m.\u001b[0m\n", + " \u001b[1;92m✔\u001b[0m \u001b[1;33mOverwritten.\u001b[0m \u001b[39mRemoved and re-registered the custom task plugin \u001b[0m\u001b[39m'maite'\u001b[0m\u001b[39m.\u001b[0m\n", + " \u001b[1;92m✔\u001b[0m \u001b[1;33mOverwritten.\u001b[0m \u001b[39mRemoved and re-registered the custom task plugin \u001b[0m\u001b[39m'pytorch_d2'\u001b[0m\u001b[39m.\u001b[0m\n", + " \u001b[1;92m✔\u001b[0m \u001b[1;33mOverwritten.\u001b[0m \u001b[39mRemoved and re-registered the custom task plugin \u001b[0m\u001b[39m'evaluation'\u001b[0m\u001b[39m.\u001b[0m\n", + " \u001b[1;92m✔\u001b[0m \u001b[1;33mOverwritten.\u001b[0m \u001b[39mRemoved and re-registered the custom task plugin \u001b[0m\n", + "\u001b[39m'feature_squeezing'\u001b[0m\u001b[39m.\u001b[0m\n", + " \u001b[1;92m✔\u001b[0m \u001b[1;33mOverwritten.\u001b[0m \u001b[39mRemoved and re-registered the custom task plugin \u001b[0m\u001b[39m'nrtk'\u001b[0m\u001b[39m.\u001b[0m\n", + " \u001b[1;92m✔\u001b[0m Custom task plugin registration is complete.\n" + ] + } + ], + "source": [ + "!python ../scripts/register_task_plugins.py --force --plugins-dir ../task-plugins --api-url http://localhost:80" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'experimentId': 1,\n", + " 'createdOn': '2024-07-13T18:27:57.486712',\n", + " 'lastModified': '2024-07-13T18:27:57.486712',\n", + " 'name': 'pytorch_maite_nrtk'}" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "response_experiment = restapi_client.get_experiment_by_name(name=EXPERIMENT_NAME)\n", + "\n", + "if response_experiment is None or \"Not Found\" in response_experiment.get(\"message\", []):\n", + " response_experiment = restapi_client.register_experiment(name=EXPERIMENT_NAME)\n", + "\n", + "response_experiment" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `full_workflow` entry point tests basic MAITE functionality: load a dataset from huggingface, load a model from huggingface, load a metric from torchvision and run that metric on that model/dataset. It also saves the model into MLFlow." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "response_test_metrics = restapi_client.submit_job(\n", + " workflows_file=WORKFLOWS_TAR_GZ,\n", + " experiment_name=EXPERIMENT_NAME,\n", + " entry_point=\"full_workflow\",\n", + " entry_point_kwargs=\" \".join([\n", + " \"-P dataset_provider_name=torchvision\",\n", + " \"-P dataset_name=voc\",\n", + " \"-P dataset_task=object-detection\",\n", + " \"-P split=val\",\n", + " \"-P model_provider_name=torchvision\",\n", + " \"-P model_name=fasterrcnn_resnet50_fpn\",\n", + " \"-P model_task=object-detection\",\n", + " \"-P metric_provider_name=torchmetrics\",\n", + " \"-P metric_name=MeanAveragePrecision\",\n", + " \"-P metric_task=detection\",\n", + " \"-P classes=46\",\n", + " \"-P batch_size=4\",\n", + " \"-P shape=[800,800]\"\n", + " ]),\n", + " queue=\"pytorch_cpu\",\n", + " timeout=\"1h\",\n", + ")\n", + "pprint.pprint(response_test_metrics)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `save_model` entry point loads a model from huggingface and saves it to MLFlow. In this example, we are pulling this object detection model from huggingface: https://huggingface.co/spaces/lkeab/transfiner/tree/main " + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'createdOn': '2024-07-16T20:41:05.733304',\n", + " 'dependsOn': None,\n", + " 'entryPoint': 'save_model',\n", + " 'entryPointKwargs': '-P model_provider_name=torchvision -P '\n", + " 'model_name=fasterrcnn_resnet50_fpn -P '\n", + " 'model_task=object-detection',\n", + " 'experimentId': 1,\n", + " 'jobId': 'd77bda2f-a610-4bf5-a6c1-4788205eb880',\n", + " 'lastModified': '2024-07-16T20:41:05.733304',\n", + " 'mlflowRunId': None,\n", + " 'queueId': 3,\n", + " 'status': 'queued',\n", + " 'timeout': '1h',\n", + " 'workflowUri': 's3://workflow/4340a0e2bd5e4901adeccd9de152bc5b/workflows.tar.gz'}\n" + ] + } + ], + "source": [ + "response_model = restapi_client.submit_job(\n", + " workflows_file=WORKFLOWS_TAR_GZ,\n", + " experiment_name=EXPERIMENT_NAME,\n", + " entry_point=\"save_model\",\n", + " entry_point_kwargs=\" \".join([\n", + " \"-P model_provider_name=torchvision\",\n", + " \"-P model_name=fasterrcnn_resnet50_fpn\",\n", + " \"-P model_task=object-detection\"\n", + " ]),\n", + " queue=\"pytorch_cpu\",\n", + " timeout=\"1h\",\n", + ")\n", + "pprint.pprint(response_model)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `scan_model` entrypoint loads the previously saved model from MLFlow and uses modelscan to evaluate the model files for insecure or malicious code.\n", + "\n", + "It is important to note that modelscan searches for publicly known vulnerable coding practices, which the tool labels as a CRITICAL vulnerability. If the tool is used to scan models on opensource platforms like HuggingFace, there is a possibility for the tool to report a critical finding. Use caution when engaging with models that produce critical scan reports and ensure the model is published by a trusted source. " + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'createdOn': '2024-07-16T20:44:08.019447',\n", + " 'dependsOn': 'd77bda2f-a610-4bf5-a6c1-4788205eb880',\n", + " 'entryPoint': 'scan_model',\n", + " 'entryPointKwargs': '-P mlflow_run_id=fe5b0db1fee14cb294e8c1c87acf7720',\n", + " 'experimentId': 1,\n", + " 'jobId': 'f4b45e7f-f60e-4004-8a72-a95d119d66db',\n", + " 'lastModified': '2024-07-16T20:44:08.019447',\n", + " 'mlflowRunId': None,\n", + " 'queueId': 3,\n", + " 'status': 'queued',\n", + " 'timeout': '1h',\n", + " 'workflowUri': 's3://workflow/1d40de8c18b649ddb230a2d88ebf9a99/workflows.tar.gz'}\n" + ] + } + ], + "source": [ + "while mlflow_run_id_is_not_known(response_model):\n", + " time.sleep(1)\n", + " response_model = restapi_client.get_job_by_id(response_model[\"jobId\"])\n", + "\n", + "response_scan_model = restapi_client.submit_job(\n", + " workflows_file=WORKFLOWS_TAR_GZ,\n", + " experiment_name=EXPERIMENT_NAME,\n", + " entry_point=\"scan_model\",\n", + " entry_point_kwargs=\" \".join([\n", + " f\"-P mlflow_run_id={response_model['mlflowRunId']}\",\n", + " ]),\n", + " queue=\"pytorch_cpu\",\n", + " timeout=\"1h\",\n", + " depends_on=response_model[\"jobId\"],\n", + ")\n", + "pprint.pprint(response_scan_model)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `test_model` entrypoint loads the previously saved model from MLFlow into a MAITE-readable format, and then uses maite to test metrics and a dataset on it." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "while mlflow_run_id_is_not_known(response_model):\n", + " time.sleep(1)\n", + " response_model = restapi_client.get_job_by_id(response_model[\"jobId\"])\n", + "\n", + "response_use_model = restapi_client.submit_job(\n", + " workflows_file=WORKFLOWS_TAR_GZ,\n", + " experiment_name=EXPERIMENT_NAME,\n", + " entry_point=\"test_model\",\n", + " entry_point_kwargs=\" \".join([\n", + " \"-P model_name=loaded_model\",\n", + " \"-P model_version=1\",\n", + " \"-P model_task=object-detection\", \n", + " \"-P dataset_provider_name=huggingface\",\n", + " \"-P dataset_name=detection-datasets/fashionpedia\",\n", + " \"-P dataset_task=object-detection\",\n", + " \"-P split=val\",\n", + " \"-P metric_provider_name=torchmetrics\",\n", + " \"-P metric_name=MeanAveragePrecision\", \n", + " \"-P metric_task=detection\",\n", + " \"-P classes=80\",\n", + " \"-P batch_size=4\",\n", + " \"-P shape=[800,800]\"\n", + " ]),\n", + " queue=\"pytorch_cpu\",\n", + " timeout=\"1h\",\n", + ")\n", + "#HuggingFace datasets:\n", + "#detection-datasets/fashionpedia; classes=46; TEST STATUS=Success\n", + "#detection-datasets/coco; classes=80; TEST STATUS=Success" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `load_dataset` entrypoint loads a dataset from disk, puts it into maite format, then loads a model and metric using maite and runs it on that dataset." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "response_load_dataset = restapi_client.submit_job(\n", + " workflows_file=WORKFLOWS_TAR_GZ,\n", + " experiment_name=EXPERIMENT_NAME,\n", + " entry_point=\"load_dataset\",\n", + " entry_point_kwargs=\" \".join([\n", + " \"-P subset=400\"\n", + " ]),\n", + " queue=\"pytorch_cpu\",\n", + " timeout=\"1h\",\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `gen_nrtk` entrypoint loads a dataset using MAITE, applies a NRTK perturbations on it, creates a new `perturbed_dataset` and registers it to MLFlow as an artifact. \n", + "\n", + "Currently, Dioptra's NRTK custom plugin is configured to apply skimage and PIL perturbations to object detection datasets. For more insight into NRTK's perturbations, please refer to their documentation. Parameters for this example were derived from NRTK's perturbation jupyter notebook example here: https://github.com/Kitware/nrtk/blob/main/examples/perturbers.ipynb." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "response_gen_nrtk = restapi_client.submit_job(\n", + " workflows_file=WORKFLOWS_TAR_GZ,\n", + " experiment_name=EXPERIMENT_NAME,\n", + " entry_point=\"gen_nrtk\",\n", + " entry_point_kwargs=\" \".join([\n", + " \"-P dataset_provider_name=huggingface\",\n", + " \"-P dataset_name=detection-datasets/fashionpedia\",\n", + " \"-P dataset_task=object-detection\",\n", + " \"-P split=val\",\n", + " \"-P perturbation=SaltNoisePerturber\",\n", + " \"-P seed=42\",\n", + " \"-P amount=0.25\"\n", + " ]),\n", + " queue=\"pytorch_cpu\",\n", + " timeout=\"1h\",\n", + ")\n", + "#Tested datasets\n", + "#dataset_provider_name=huggingface; dataset_name=detection-datasets/coco\n", + "#dataset_provider_name=huggingface; dataset_name=detection-datasets/fashionpedia" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `infer_nrtk` entrypoint takes the previously generated `perturbed_dataset` results and runs it against a given model and metric. It is included here as a function and tested against 4 models on huggingface from different authors. Note that not all targeted models on huggingface are compatible for various reasons - missing `config.json`, different requirements for data formatting, etc. The examples included below worked at the time of testing.\n", + "\n", + "Although MAITE supports torchvision as a provider as well, torchvision does not seem to provide pretrained CIFAR10 models. An ImageNET example may be more suited to cross-testing torchvision and huggingface models." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "def test_nrtk_dataset(provider, model):\n", + " global response_gen_nrtk\n", + " while mlflow_run_id_is_not_known(response_gen_nrtk):\n", + " time.sleep(1)\n", + " response_gen_nrtk = restapi_client.get_job_by_id(response_gen_nrtk[\"jobId\"])\n", + " response_infer_nrtk = restapi_client.submit_job(\n", + " workflows_file=WORKFLOWS_TAR_GZ,\n", + " experiment_name=EXPERIMENT_NAME,\n", + " entry_point=\"infer_nrtk\",\n", + " entry_point_kwargs=\" \".join([\n", + " f\"-P run_id={response_gen_nrtk['mlflowRunId']}\",\n", + " f\"-P model_provider_name={provider}\",\n", + " f\"-P model_name={model}\",\n", + " f\"-P model_task=image-classification\"\n", + " ]),\n", + " queue=\"pytorch_cpu\",\n", + " timeout=\"1h\",\n", + " depends_on=response_gen_nrtk[\"jobId\"],\n", + " )\n", + " return response_infer_nrtk" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'jobId': '005bdf2e-ec0f-4947-a3eb-c13d8d4a82ed',\n", + " 'mlflowRunId': None,\n", + " 'experimentId': 1,\n", + " 'queueId': 3,\n", + " 'createdOn': '2024-07-16T22:13:32.531231',\n", + " 'lastModified': '2024-07-16T22:13:32.531231',\n", + " 'timeout': '1h',\n", + " 'workflowUri': 's3://workflow/cfb8540537e84152a3f8d1189ed92c6c/workflows.tar.gz',\n", + " 'entryPoint': 'infer_nrtk',\n", + " 'entryPointKwargs': '-P run_id=171fdfd812a848278e5d35bab2960e72 -P model_provider_name=torchvision -P model_name=fasterrcnn_resnet50_fpn -P model_task=object-detection',\n", + " 'dependsOn': 'a32b9497-2f92-4112-9f2c-da54ff4d7521',\n", + " 'status': 'queued'}" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "test_perturbed_dataset_nrtk(\"torchvision\",\"fasterrcnn_resnet50_fpn\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "test_perturbed_dataset_nrtk(\"huggingface\",\"facebook/detr-resnet-50\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "interpreter": { + "hash": "edee40310913f16e2ca02c1d37887bcb7f07f00399ca119bb7e27de7d632ea99" + }, + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.0" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} From 100cfabc0ec1d8a000044e3718a78adb401e33ac Mon Sep 17 00:00:00 2001 From: bjpatrick <137509145+bjpatrick@users.noreply.github.com> Date: Tue, 16 Jul 2024 17:45:58 -0500 Subject: [PATCH 15/18] Create MLproject --- examples/pytorch-maite-nrtk/src/MLproject | 187 ++++++++++++++++++++++ 1 file changed, 187 insertions(+) create mode 100644 examples/pytorch-maite-nrtk/src/MLproject diff --git a/examples/pytorch-maite-nrtk/src/MLproject b/examples/pytorch-maite-nrtk/src/MLproject new file mode 100644 index 000000000..401908850 --- /dev/null +++ b/examples/pytorch-maite-nrtk/src/MLproject @@ -0,0 +1,187 @@ +# This Software (Dioptra) is being made available as a public service by the +# National Institute of Standards and Technology (NIST), an Agency of the United +# States Department of Commerce. This software was developed in part by employees of +# NIST and in part by NIST contractors. Copyright in portions of this software that +# were developed by NIST contractors has been licensed or assigned to NIST. Pursuant +# to Title 17 United States Code Section 105, works of NIST employees are not +# subject to copyright protection in the United States. However, NIST may hold +# international copyright in software created by its employees and domestic +# copyright (or licensing rights) in portions of software that were assigned or +# licensed to NIST. To the extent that NIST holds copyright in this software, it is +# being made available under the Creative Commons Attribution 4.0 International +# license (CC BY 4.0). The disclaimers of the CC BY 4.0 license apply to all parts +# of the software developed or licensed by NIST. +# +# ACCESS THE FULL CC BY 4.0 LICENSE HERE: +# https://creativecommons.org/licenses/by/4.0/legalcode +name: pytorch-obj-detect-nrtk + +entry_points: + full_workflow: + parameters: + dataset_provider_name: { type: string, default: "huggingface" } + dataset_name: { type: string, default: "detection-datasets/coco" } + dataset_task: { type: string, default: "object-detection" } + split: { type: string, default: "test" } + model_provider_name: { type: string, default: "torchvision" } + model_name: { type: string, default: "fasterrcnn_resnet50_fpn" } + model_task: { type: string, default: "object-detection" } + metric_provider_name: { type: string, default: "torchmetrics" } + metric_name: { type: string, default: "Accuracy" } + metric_task: { type: string, default: "multiclass" } + classes: { type: int, default: 80 } + batch_size: { type: int, default: 32 } + shape: { type: string, default: "[800,800]" } + subset: { type: int, default: 0 } + command: > + PYTHONPATH=$DIOPTRA_PLUGIN_DIR validate-experiment full_workflow.yml && PYTHONPATH=$DIOPTRA_PLUGIN_DIR run-experiment full_workflow.yml + -P dataset_provider_name={dataset_provider_name} + -P dataset_name={dataset_name} + -P dataset_task={dataset_task} + -P split={split} + -P model_provider_name={model_provider_name} + -P model_name={model_name} + -P model_task={model_task} + -P metric_provider_name={metric_provider_name} + -P metric_name={metric_name} + -P metric_task={metric_task} + -P classes={classes} + -P batch_size={batch_size} + -P shape={shape} + -P subset={subset} + save_model: + parameters: + model_provider_name: { type: string, default: "huggingface" } + model_name: { type: string, default: "fasterrcnn_resnet50_fpn"} + model_task: { type: string, default: "object-detection" } + register_model: { type: string, default: "loaded_model" } + command: > + PYTHONPATH=$DIOPTRA_PLUGIN_DIR validate-experiment save_model.yml && PYTHONPATH=$DIOPTRA_PLUGIN_DIR run-experiment save_model.yml + -P model_provider_name={model_provider_name} + -P model_name={model_name} + -P model_task={model_task} + -P register_model={register_model} + scan_model: + parameters: + mlflow_run_id: { type: string} + command: > + PYTHONPATH=$DIOPTRA_PLUGIN_DIR validate-experiment scan_model.yml && PYTHONPATH=$DIOPTRA_PLUGIN_DIR run-experiment scan_model.yml + -P mlflow_run_id={mlflow_run_id} + test_model: + parameters: + dataset_provider_name: { type: string, default: "huggingface" } + dataset_name: { type: string, default: "detection-datasets/coco" } + dataset_task: { type: string, default: "object-detection" } + split: { type: string, default: "test" } + model_name: { type: string, default: "loaded_model" } + model_version: { type: int, default: 1 } + model_task: { type: string, default: "object-detection" } + metric_provider_name: { type: string, default: "torchmetrics" } + metric_name: { type: string, default: "MeanAveragePrecision" } + metric_task: { type: string, default: "detection" } + classes: { type: int, default: 80 } + batch_size: { type: int, default: 8 } + shape: { type: string, default: "[800,800]" } + subset: { type: int, default: 0 } + command: > + PYTHONPATH=$DIOPTRA_PLUGIN_DIR validate-experiment test_model.yml && PYTHONPATH=$DIOPTRA_PLUGIN_DIR run-experiment test_model.yml + -P dataset_provider_name={dataset_provider_name} + -P dataset_name={dataset_name} + -P dataset_task={dataset_task} + -P split={split} + -P model_name={model_name} + -P model_version={model_version} + -P model_task={model_task} + -P metric_provider_name={metric_provider_name} + -P metric_name={metric_name} + -P metric_task={metric_task} + -P classes={classes} + -P batch_size={batch_size} + -P shape={shape} + -P subset={subset} + load_dataset: + parameters: + testing_dir: { type: string, default: "/dioptra/data/Mnist/testing" } + validation_split: { type: int, default: 0.3 } + image_size: { type: string, default: "[28,28,3]" } + new_size: { type: integer, default: 224 } + model_provider_name: { type: string, default: "huggingface" } + model_name: { type: string, default: "farleyknight-org-username/vit-base-mnist" } + model_task: { type: string, default: "object-detection" } + metric_provider_name: { type: string, default: "torchmetrics" } + metric_name: { type: string, default: "Accuracy" } + metric_task: { type: string, default: "multiclass" } + classes: { type: int, default: 10 } + batch_size: { type: int, default: 32 } + shape: { type: string, default: "[3,224,224]" } + subset: { type: int, default: 0 } + command: > + PYTHONPATH=$DIOPTRA_PLUGIN_DIR validate-experiment load_dataset.yml && PYTHONPATH=$DIOPTRA_PLUGIN_DIR run-experiment load_dataset.yml + -P testing_dir={testing_dir} + -P validation_split={validation_split} + -P image_size={image_size} + -P new_size={new_size} + -P model_provider_name={model_provider_name} + -P model_name={model_name} + -P model_task={model_task} + -P metric_provider_name={metric_provider_name} + -P metric_name={metric_name} + -P metric_task={metric_task} + -P classes={classes} + -P batch_size={batch_size} + -P shape={shape} + -P subset={subset} + gen_nrtk: + parameters: + dataset_provider_name: { type: string, default: "huggingface" } + dataset_name: { type: string, default: "detection-datasets/coco" } + dataset_task: { type: string, default: "object-detection" } + split: { type: string, default: "test" } + perturbation: { type: string, default: "SaltNoisePerturber" } + seed: { type: int, default: 42 } + amount: { type: float, default: 0.25 } + salt_vs_pepper: { type: float, default: 0.5 } + var: { type: float, default: 0.05 } + mean: { type: int, default: 0 } + ksize: { type: int, default: 7 } + factor: { type: float, default: 0.25 } + command: > + PYTHONPATH=$DIOPTRA_PLUGIN_DIR validate-experiment gen_nrtk.yml && PYTHONPATH=$DIOPTRA_PLUGIN_DIR run-experiment gen_nrtk.yml + -P split={split} + -P dataset_provider_name={dataset_provider_name} + -P dataset_name={dataset_name} + -P dataset_task={dataset_task} + -P perturbation={perturbation} + -P seed={seed} + -P amount={amount} + -P salt_vs_pepper={salt_vs_pepper} + -P var={var} + -P mean={mean} + -P ksize={ksize} + -P factor={amount} + infer_nrtk: + parameters: + mlflow_run_id: { type: string } + model_provider_name: { type: string, default: "torchvision" } + model_name: { type: string, default: "fasterrcnn_resnet50_fpn"} + model_task: { type: string, default: "object-detection" } + metric_provider_name: { type: string, default: "torchmetrics" } + metric_name: { type: string, default: "MeanAveragePrecision" } + metric_task: { type: string, default: "detection" } + classes: { type: int, default: 46 } + batch_size: { type: int, default: 4 } + shape: { type: string, default: "[800,800]" } + subset: { type: int, default: 0 } + command: > + PYTHONPATH=$DIOPTRA_PLUGIN_DIR validate-experiment infer_nrtk.yml && PYTHONPATH=$DIOPTRA_PLUGIN_DIR run-experiment infer_nrtk.yml + -P mlflow_run_id={mlflow_run_id} + -P model_provider_name={model_provider_name} + -P model_name={model_name} + -P model_task={model_task} + -P metric_provider_name={metric_provider_name} + -P metric_name={metric_name} + -P metric_task={metric_task} + -P classes={classes} + -P batch_size={batch_size} + -P shape={shape} + -P subset={subset} From 43998c997879912963d2ac87b71b602ef69ea3a6 Mon Sep 17 00:00:00 2001 From: bjpatrick <137509145+bjpatrick@users.noreply.github.com> Date: Tue, 16 Jul 2024 17:47:50 -0500 Subject: [PATCH 16/18] Upload entry points for maite-nrtk example --- .../pytorch-maite-nrtk/src/full_workflow.yml | 157 ++++++++++++++++ examples/pytorch-maite-nrtk/src/gen_nrtk.yml | 115 ++++++++++++ .../pytorch-maite-nrtk/src/infer_nrtk.yml | 148 +++++++++++++++ .../pytorch-maite-nrtk/src/load_dataset.yml | 177 ++++++++++++++++++ .../pytorch-maite-nrtk/src/save_model.yml | 82 ++++++++ .../pytorch-maite-nrtk/src/scan_model.yml | 73 ++++++++ .../pytorch-maite-nrtk/src/test_model.yml | 157 ++++++++++++++++ 7 files changed, 909 insertions(+) create mode 100644 examples/pytorch-maite-nrtk/src/full_workflow.yml create mode 100644 examples/pytorch-maite-nrtk/src/gen_nrtk.yml create mode 100644 examples/pytorch-maite-nrtk/src/infer_nrtk.yml create mode 100644 examples/pytorch-maite-nrtk/src/load_dataset.yml create mode 100644 examples/pytorch-maite-nrtk/src/save_model.yml create mode 100644 examples/pytorch-maite-nrtk/src/scan_model.yml create mode 100644 examples/pytorch-maite-nrtk/src/test_model.yml diff --git a/examples/pytorch-maite-nrtk/src/full_workflow.yml b/examples/pytorch-maite-nrtk/src/full_workflow.yml new file mode 100644 index 000000000..b7632634d --- /dev/null +++ b/examples/pytorch-maite-nrtk/src/full_workflow.yml @@ -0,0 +1,157 @@ +types: + callback: + dataset: + directoryiterator: + functiontype: + kerasclassifier: + metric: + mlflowrun: + tuple: + model: + modelversion: + np.ndarray: + optimizer: + path: + dataframe: + rngenerator: + sequential: + tarfile: + list_tuple_string_any: + list: tuple_string_any + list_union_metric_functiontype: + list: union_metric_functiontype + list_union_string_path: + list: union_string_path + list_mapping_string_string: + list: mapping_string_string + mapping_string_any: + mapping: [string, any] + mapping_string_number: + mapping: [string, number] + mapping_string_string: + mapping: [string, string] + tuple_integer_integer: + tuple: [integer, integer] + tuple_integer_integer_integer: + tuple: [integer, integer, integer] + tuple_string_any: + tuple: [string, any] + union_integer_number_string: + union: [integer, number, string] + union_integer_any: + union: [integer, any] + union_metric_functiontype: + union: [metric, functiontype] + union_null_list_tuple_string_any: + union: [list_tuple_string_any , "null"] + union_null_mapping_string_any: + union: [mapping_string_any, "null"] + union_null_modelversion: + union: [modelversion, "null"] + union_null_number: + union: [number, "null"] + union_null_string: + union: [string, "null"] + union_null_union_integer_any: + union: [union_integer_any, "null"] + union_string_path: + union: [string, path] + union_null_union_string_path: + union: [union_string_path, "null"] +parameters: + dataset_provider_name: huggingface + dataset_name: cifar10 + dataset_task: image-classification + split: test + model_provider_name: huggingface + model_name: aaraki/vit-base-patch16-224-in21k-finetuned-cifar10 + model_task: image-classification + metric_provider_name: torchmetrics + metric_name: Accuracy + metric_task: multiclass + classes: 10 + batch_size: 32 + shape: [224, 224] + subset: 0 +tasks: + get_dataset: + plugin: dioptra_custom.maite.maite.get_dataset + inputs: + - provider_name: string + - dataset_name: string + - task: string + - split: string + outputs: + dataset: dataset + get_model: + plugin: dioptra_custom.maite.maite.get_model + inputs: + - provider_name: string + - model_name: string + - task: string + outputs: + model: model + get_metric: + plugin: dioptra_custom.maite.maite.get_metric + inputs: + - provider_name: string + - metric_name: string + - task: string + - classes: integer + outputs: + metric: metric + transform_tensor: + plugin: dioptra_custom.maite.maite.transform_tensor + inputs: + - dataset: dataset + - shape: any + - name: totensor + type: boolean + required: false + - name: subset + type: integer + required: false + outputs: + dataset: dataset + compute_metric: + plugin: dioptra_custom.maite.maite.compute_metric + inputs: + - dataset: dataset + - model: model + - metric: metric + - task: string + - batch_size: integer + outputs: + computed: mapping_string_number +graph: + dataset: + get_dataset: + provider_name: $dataset_provider_name + dataset_name: $dataset_name + task: $dataset_task + split: $split + model: + get_model: + provider_name: $model_provider_name + model_name: $model_name + task: $model_task + metric: + get_metric: + provider_name: $metric_provider_name + metric_name: $metric_name + task: $metric_task + classes: $classes + transformed_dataset: + transform_tensor: + dataset: $dataset + shape: $shape + subset: $subset + totensor: true + metric_results: + compute_metric: + dataset: $transformed_dataset.dataset + model: $model + metric: $metric + task: $model_task + batch_size: $batch_size + dependencies: [transformed_dataset, model, metric] diff --git a/examples/pytorch-maite-nrtk/src/gen_nrtk.yml b/examples/pytorch-maite-nrtk/src/gen_nrtk.yml new file mode 100644 index 000000000..0b52ba6cc --- /dev/null +++ b/examples/pytorch-maite-nrtk/src/gen_nrtk.yml @@ -0,0 +1,115 @@ +types: + callback: + dataset: + directoryiterator: + functiontype: + kerasclassifier: + metric: + mlflowrun: + tuple: + model: + modelversion: + np.ndarray: + optimizer: + path: + dataframe: + rngenerator: + sequential: + tarfile: + list_tuple_string_any: + list: tuple_string_any + list_union_metric_functiontype: + list: union_metric_functiontype + list_union_string_path: + list: union_string_path + list_mapping_string_string: + list: mapping_string_string + mapping_string_any: + mapping: [string, any] + mapping_string_number: + mapping: [string, number] + mapping_string_string: + mapping: [string, string] + tuple_integer_integer: + tuple: [integer, integer] + tuple_integer_integer_integer: + tuple: [integer, integer, integer] + tuple_string_any: + tuple: [string, any] + union_integer_number_string: + union: [integer, number, string] + union_integer_any: + union: [integer, any] + union_metric_functiontype: + union: [metric, functiontype] + union_null_list_tuple_string_any: + union: [list_tuple_string_any , "null"] + union_null_mapping_string_any: + union: [mapping_string_any, "null"] + union_null_modelversion: + union: [modelversion, "null"] + union_null_number: + union: [number, "null"] + union_null_string: + union: [string, "null"] + union_null_union_integer_any: + union: [union_integer_any, "null"] + union_string_path: + union: [string, path] + union_null_union_string_path: + union: [union_string_path, "null"] +parameters: + dataset_provider_name: huggingface + dataset_name: detection-datasets/coco + dataset_task: object-detection + split: val + perturbation: SaltNoisePerturber + seed: 42 + amount: 0.25 + salt_vs_pepper: 0.5 + var: 0.05 + mean: 0 + ksize: 7 + factor: 0.25 +tasks: + get_dataset: + plugin: dioptra_custom.maite.maite.get_dataset + inputs: + - provider_name: string + - dataset_name: string + - task: string + - split: string + outputs: + dataset: dataset + perturb_images: + plugin: dioptra_custom.nrtk.nrtk.perturb_images + inputs: + - dataset: dataset + - perturbation: string + - seed: integer + - amount: number + - salt_vs_pepper: number + - var: number + - mean: integer + - ksize: integer + - factor: number + outputs: + dataset: dataset +graph: + dataset: + get_dataset: + provider_name: $dataset_provider_name + dataset_name: $dataset_name + task: $dataset_task + split: $split + create_nrtk_dataset_from_hf_dataset: + perturb_images: + dataset: $dataset + perturbation: $perturbation + seed: $seed + amount: $amount + salt_vs_pepper: $salt_vs_pepper + var: $var + mean: $mean + ksize: $ksize + factor: $factor \ No newline at end of file diff --git a/examples/pytorch-maite-nrtk/src/infer_nrtk.yml b/examples/pytorch-maite-nrtk/src/infer_nrtk.yml new file mode 100644 index 000000000..905a9c28c --- /dev/null +++ b/examples/pytorch-maite-nrtk/src/infer_nrtk.yml @@ -0,0 +1,148 @@ +types: + callback: + dataset: + directoryiterator: + functiontype: + kerasclassifier: + metric: + mlflowrun: + tuple: + model: + modelversion: + np.ndarray: + optimizer: + path: + dataframe: + rngenerator: + sequential: + tarfile: + list_tuple_string_any: + list: tuple_string_any + list_union_metric_functiontype: + list: union_metric_functiontype + list_union_string_path: + list: union_string_path + list_mapping_string_string: + list: mapping_string_string + mapping_string_any: + mapping: [string, any] + mapping_string_number: + mapping: [string, number] + mapping_string_string: + mapping: [string, string] + tuple_integer_integer: + tuple: [integer, integer] + tuple_integer_integer_integer: + tuple: [integer, integer, integer] + tuple_string_any: + tuple: [string, any] + union_integer_number_string: + union: [integer, number, string] + union_integer_any: + union: [integer, any] + union_metric_functiontype: + union: [metric, functiontype] + union_null_list_tuple_string_any: + union: [list_tuple_string_any , "null"] + union_null_mapping_string_any: + union: [mapping_string_any, "null"] + union_null_modelversion: + union: [modelversion, "null"] + union_null_number: + union: [number, "null"] + union_null_string: + union: [string, "null"] + union_null_union_integer_any: + union: [union_integer_any, "null"] + union_string_path: + union: [string, path] + union_null_union_string_path: + union: [union_string_path, "null"] +parameters: + mlflow_run_id: string + model_provider_name: torchvision + model_name: fasterrcnn_resnet50_fpn + model_task: object-detection + metric_provider_name: torchmetrics + metric_name: MeanAveragePrecision + metric_task: detection + classes: 80 + batch_size: 32 + shape: [800,800] + subset: 0 +tasks: + get_dataset: + plugin: dioptra_custom.nrtk.nrtk.get_perturbed_dataset + inputs: + - mlflow_run_id: string + outputs: + dataset: dataset + get_model: + plugin: dioptra_custom.maite.maite.get_model + inputs: + - provider_name: string + - model_name: string + - task: string + outputs: + model: model + get_metric: + plugin: dioptra_custom.maite.maite.get_metric + inputs: + - provider_name: string + - metric_name: string + - task: string + - classes: integer + outputs: + metric: metric + transform_tensor: + plugin: dioptra_custom.maite.maite.transform_tensor + inputs: + - dataset: dataset + - shape: any + - name: totensor + type: boolean + required: false + - name: subset + type: integer + required: false + outputs: + dataset: dataset + compute_metric: + plugin: dioptra_custom.maite.maite.compute_metric + inputs: + - dataset: dataset + - model: model + - metric: metric + - task: string + - batch_size: integer + outputs: + computed: mapping_string_number +graph: + dataset: + get_dataset: + mlflow_run_id: $mlflow_run_id + model: + get_model: + provider_name: $model_provider_name + model_name: $model_name + task: $model_task + metric: + get_metric: + provider_name: $metric_provider_name + metric_name: $metric_name + task: $metric_task + classes: $classes + transformed_dataset: + transform_tensor: + dataset: $dataset + shape: $shape + subset: $subset + totensor: true + metric_results: + compute_metric: + dataset: $transformed_dataset.dataset + model: $model + metric: $metric + task: $model_task + batch_size: $batch_size + dependencies: [transformed_dataset, model, metric] \ No newline at end of file diff --git a/examples/pytorch-maite-nrtk/src/load_dataset.yml b/examples/pytorch-maite-nrtk/src/load_dataset.yml new file mode 100644 index 000000000..2cb4469a5 --- /dev/null +++ b/examples/pytorch-maite-nrtk/src/load_dataset.yml @@ -0,0 +1,177 @@ +types: + callback: + dataset: + directoryiterator: + functiontype: + kerasclassifier: + metric: + mlflowrun: + tuple: + model: + modelversion: + np.ndarray: + optimizer: + path: + dataframe: + rngenerator: + sequential: + tarfile: + list_tuple_string_any: + list: tuple_string_any + list_union_metric_functiontype: + list: union_metric_functiontype + list_union_string_path: + list: union_string_path + list_mapping_string_string: + list: mapping_string_string + mapping_string_any: + mapping: [string, any] + mapping_string_number: + mapping: [string, number] + mapping_string_string: + mapping: [string, string] + tuple_integer_integer: + tuple: [integer, integer] + tuple_integer_integer_integer: + tuple: [integer, integer, integer] + tuple_string_any: + tuple: [string, any] + union_integer_number_string: + union: [integer, number, string] + union_integer_any: + union: [integer, any] + union_metric_functiontype: + union: [metric, functiontype] + union_null_list_tuple_string_any: + union: [list_tuple_string_any , "null"] + union_null_mapping_string_any: + union: [mapping_string_any, "null"] + union_null_modelversion: + union: [modelversion, "null"] + union_null_number: + union: [number, "null"] + union_null_string: + union: [string, "null"] + union_null_union_integer_any: + union: [union_integer_any, "null"] + union_string_path: + union: [string, path] + union_null_union_string_path: + union: [union_string_path, "null"] +parameters: + testing_dir: /dioptra/data/Mnist/testing + validation_split: 0.3 + image_size: [28,28,3] + new_size: 224 + model_provider_name: huggingface + model_name: road-signs-6ih4y + model_task: object-detection + metric_provider_name: torchmetrics + metric_name: mAP + metric_task: detection + classes: 22 + batch_size: 8 + shape: [640,640] + subset: 0 +tasks: + create_image_dataset: + plugin: dioptra_custom.maite.maite.create_image_dataset + inputs: + - data_dir: string + - image_size: tuple_integer_integer_integer + - name: new_size + type: integer + required: false + - name: validation_split + type: union_null_number + required: false + - name: batch_size + type: integer + required: false + - name: label_mode + type: string + required: false + outputs: + - dataset_a: dataset + - dataset_b: dataset + get_dataset: + plugin: dioptra_custom.maite.maite.get_dataset + inputs: + - provider_name: string + - dataset_name: string + - task: string + - split: string + outputs: + dataset: dataset + get_model: + plugin: dioptra_custom.maite.maite.get_model + inputs: + - provider_name: string + - model_name: string + - task: string + outputs: + model: model + get_metric: + plugin: dioptra_custom.maite.maite.get_metric + inputs: + - provider_name: string + - metric_name: string + - task: string + - classes: integer + outputs: + metric: metric + transform_tensor: + plugin: dioptra_custom.maite.maite.transform_tensor + inputs: + - dataset: dataset + - shape: any + - name: totensor + type: boolean + required: false + - name: subset + type: integer + required: false + outputs: + dataset: dataset + compute_metric: + plugin: dioptra_custom.maite.maite.compute_metric + inputs: + - dataset: dataset + - model: model + - metric: metric + - task: string + - batch_size: integer + outputs: + computed: mapping_string_number +graph: + dataset: + create_image_dataset: + data_dir: $testing_dir + validation_split: $validation_split + batch_size: $batch_size + image_size: $image_size + new_size: $new_size + model: + get_model: + provider_name: $model_provider_name + model_name: $model_name + task: $model_task + metric: + get_metric: + provider_name: $metric_provider_name + metric_name: $metric_name + task: $metric_task + classes: $classes + transformed_dataset: + transform_tensor: + dataset: $dataset.dataset_a + shape: $shape + subset: $subset + metric_results: + compute_metric: + dataset: $transformed_dataset.dataset + model: $model + metric: $metric + task: $model_task + batch_size: $batch_size + dependencies: [transformed_dataset, model, metric] diff --git a/examples/pytorch-maite-nrtk/src/save_model.yml b/examples/pytorch-maite-nrtk/src/save_model.yml new file mode 100644 index 000000000..3daf3df20 --- /dev/null +++ b/examples/pytorch-maite-nrtk/src/save_model.yml @@ -0,0 +1,82 @@ +types: + callback: + dataset: + directoryiterator: + functiontype: + kerasclassifier: + metric: + mlflowrun: + tuple: + model: + modelversion: + np.ndarray: + optimizer: + path: + dataframe: + rngenerator: + sequential: + tarfile: + list_tuple_string_any: + list: tuple_string_any + list_union_metric_functiontype: + list: union_metric_functiontype + list_union_string_path: + list: union_string_path + list_mapping_string_string: + list: mapping_string_string + mapping_string_any: + mapping: [string, any] + mapping_string_number: + mapping: [string, number] + mapping_string_string: + mapping: [string, string] + tuple_integer_integer: + tuple: [integer, integer] + tuple_integer_integer_integer: + tuple: [integer, integer, integer] + tuple_string_any: + tuple: [string, any] + union_integer_number_string: + union: [integer, number, string] + union_integer_any: + union: [integer, any] + union_metric_functiontype: + union: [metric, functiontype] + union_null_list_tuple_string_any: + union: [list_tuple_string_any , "null"] + union_null_mapping_string_any: + union: [mapping_string_any, "null"] + union_null_modelversion: + union: [modelversion, "null"] + union_null_number: + union: [number, "null"] + union_null_string: + union: [string, "null"] + union_null_union_integer_any: + union: [union_integer_any, "null"] + union_string_path: + union: [string, path] + union_null_union_string_path: + union: [union_string_path, "null"] +parameters: + model_provider_name: torchvision + model_name: fasterrcnn_resnet50_fpn + model_task: object-detection + register_model: loaded_model +tasks: + get_model: + plugin: dioptra_custom.maite.maite.get_model + inputs: + - provider_name: string + - model_name: string + - task: string + - register_model_name: string + outputs: + model: model +graph: + model: + get_model: + provider_name: $model_provider_name + model_name: $model_name + task: $model_task + register_model_name: $register_model diff --git a/examples/pytorch-maite-nrtk/src/scan_model.yml b/examples/pytorch-maite-nrtk/src/scan_model.yml new file mode 100644 index 000000000..8233ac7e3 --- /dev/null +++ b/examples/pytorch-maite-nrtk/src/scan_model.yml @@ -0,0 +1,73 @@ +types: + callback: + dataset: + directoryiterator: + functiontype: + kerasclassifier: + metric: + mlflowrun: + tuple: + model: + modelversion: + np.ndarray: + optimizer: + path: + dataframe: + rngenerator: + sequential: + tarfile: + list_tuple_string_any: + list: tuple_string_any + list_union_metric_functiontype: + list: union_metric_functiontype + list_union_string_path: + list: union_string_path + list_mapping_string_string: + list: mapping_string_string + mapping_string_any: + mapping: [string, any] + mapping_string_number: + mapping: [string, number] + mapping_string_string: + mapping: [string, string] + tuple_integer_integer: + tuple: [integer, integer] + tuple_integer_integer_integer: + tuple: [integer, integer, integer] + tuple_string_any: + tuple: [string, any] + union_integer_number_string: + union: [integer, number, string] + union_integer_any: + union: [integer, any] + union_metric_functiontype: + union: [metric, functiontype] + union_null_list_tuple_string_any: + union: [list_tuple_string_any , "null"] + union_null_mapping_string_any: + union: [mapping_string_any, "null"] + union_null_modelversion: + union: [modelversion, "null"] + union_null_number: + union: [number, "null"] + union_null_string: + union: [string, "null"] + union_null_union_integer_any: + union: [union_integer_any, "null"] + union_string_path: + union: [string, path] + union_null_union_string_path: + union: [union_string_path, "null"] +parameters: + mlflow_run_id: string +tasks: + scan_model: + plugin: dioptra_custom.modelscan.modelscan.scan_model + inputs: + - mlflow_run_id: string + outputs: + scan_results: string +graph: + model: + scan_model: + mlflow_run_id: $mlflow_run_id diff --git a/examples/pytorch-maite-nrtk/src/test_model.yml b/examples/pytorch-maite-nrtk/src/test_model.yml new file mode 100644 index 000000000..7ed129130 --- /dev/null +++ b/examples/pytorch-maite-nrtk/src/test_model.yml @@ -0,0 +1,157 @@ +types: + callback: + dataset: + directoryiterator: + functiontype: + kerasclassifier: + metric: + mlflowrun: + tuple: + model: + modelversion: + np.ndarray: + optimizer: + path: + dataframe: + rngenerator: + sequential: + tarfile: + list_tuple_string_any: + list: tuple_string_any + list_union_metric_functiontype: + list: union_metric_functiontype + list_union_string_path: + list: union_string_path + list_mapping_string_string: + list: mapping_string_string + mapping_string_any: + mapping: [string, any] + mapping_string_number: + mapping: [string, number] + mapping_string_string: + mapping: [string, string] + tuple_integer_integer: + tuple: [integer, integer] + tuple_integer_integer_integer: + tuple: [integer, integer, integer] + tuple_string_any: + tuple: [string, any] + union_integer_number_string: + union: [integer, number, string] + union_integer_any: + union: [integer, any] + union_metric_functiontype: + union: [metric, functiontype] + union_null_list_tuple_string_any: + union: [list_tuple_string_any , "null"] + union_null_mapping_string_any: + union: [mapping_string_any, "null"] + union_null_modelversion: + union: [modelversion, "null"] + union_null_number: + union: [number, "null"] + union_null_string: + union: [string, "null"] + union_null_union_integer_any: + union: [union_integer_any, "null"] + union_string_path: + union: [string, path] + union_null_union_string_path: + union: [union_string_path, "null"] +parameters: + dataset_provider_name: huggingface + dataset_name: cifar10 + dataset_task: image-classification + split: test + model_name: loaded_model + model_version: 1 + model_task: object-detection + metric_provider_name: torchmetrics + metric_name: MeanAveragePrecision + metric_task: detection + classes: 80 + batch_size: 32 + shape: [800, 800] + subset: 0 +tasks: + get_dataset: + plugin: dioptra_custom.maite.maite.get_dataset + inputs: + - provider_name: string + - dataset_name: string + - task: string + - split: string + outputs: + dataset: dataset + get_metric: + plugin: dioptra_custom.maite.maite.get_metric + inputs: + - provider_name: string + - metric_name: string + - task: string + - classes: integer + outputs: + metric: metric + transform_tensor: + plugin: dioptra_custom.maite.maite.transform_tensor + inputs: + - dataset: dataset + - shape: any + - name: totensor + type: boolean + required: false + - name: subset + type: integer + required: false + outputs: + dataset: dataset + compute_metric: + plugin: dioptra_custom.maite.maite.compute_metric + inputs: + - dataset: dataset + - model: model + - metric: metric + - task: string + - batch_size: integer + outputs: + computed: mapping_string_number + load_pytorch_classifier: + inputs: + - name: name + type: string + required: true + - version: integer + outputs: + ret: model + plugin: dioptra_custom.pytorch_d2.registry_mlflow_detectron2.load_pytorch_classifier +graph: + model: + load_pytorch_classifier: + name: $model_name + version: $model_version + dataset: + get_dataset: + provider_name: $dataset_provider_name + dataset_name: $dataset_name + task: $dataset_task + split: $split + metric: + get_metric: + provider_name: $metric_provider_name + metric_name: $metric_name + task: $metric_task + classes: $classes + transformed_dataset: + transform_tensor: + dataset: $dataset + shape: $shape + subset: $subset + totensor: true + metric_results: + compute_metric: + dataset: $transformed_dataset.dataset + model: $model + metric: $metric + task: $model_task + batch_size: $batch_size + dependencies: [transformed_dataset, model, metric] From e078fec00f4cd929409cfb703efc955a7ba342c5 Mon Sep 17 00:00:00 2001 From: bjpatrick <137509145+bjpatrick@users.noreply.github.com> Date: Tue, 16 Jul 2024 17:49:21 -0500 Subject: [PATCH 17/18] Upload NRTK custom task plugin --- task-plugins/dioptra_builtins/nrtk/nrtk.py | 249 +++++++++++++++++++++ 1 file changed, 249 insertions(+) create mode 100644 task-plugins/dioptra_builtins/nrtk/nrtk.py diff --git a/task-plugins/dioptra_builtins/nrtk/nrtk.py b/task-plugins/dioptra_builtins/nrtk/nrtk.py new file mode 100644 index 000000000..54caec290 --- /dev/null +++ b/task-plugins/dioptra_builtins/nrtk/nrtk.py @@ -0,0 +1,249 @@ +# This Software (Dioptra) is being made available as a public service by the +# National Institute of Standards and Technology (NIST), an Agency of the United +# States Department of Commerce. This software was developed in part by employees of +# NIST and in part by NIST contractors. Copyright in portions of this software that +# were developed by NIST contractors has been licensed or assigned to NIST. Pursuant +# to Title 17 United States Code Section 105, works of NIST employees are not +# subject to copyright protection in the United States. However, NIST may hold +# international copyright in software created by its employees and domestic +# copyright (or licensing rights) in portions of software that were assigned or +# licensed to NIST. To the extent that NIST holds copyright in this software, it is +# being made available under the Creative Commons Attribution 4.0 International +# license (CC BY 4.0). The disclaimers of the CC BY 4.0 license apply to all parts +# of the software developed or licensed by NIST. +# +# ACCESS THE FULL CC BY 4.0 LICENSE HERE: +# https://creativecommons.org/licenses/by/4.0/legalcode +from __future__ import annotations + +from pathlib import Path +from typing import Any +import numpy as np +from PIL import Image +import os +import json +from io import BytesIO +import base64 +import shutil +import random + +import mlflow +import tempfile +from mlflow.entities import Run as MlflowRun +from mlflow.tracking import MlflowClient + +import torch +from torchvision.transforms import functional as F +from torch.utils.data import Dataset + +import nrtk +from nrtk.impls.perturb_image.generic.skimage.random_noise import ( + SaltNoisePerturber, + PepperNoisePerturber, + SaltAndPepperNoisePerturber, + GaussianNoisePerturber, + SpeckleNoisePerturber +) +#from nrtk.impls.perturb_image.generic.cv2.blur import ( +# AverageBlurPerturber, +# GaussianBlurPerturber, +# MedianBlurPerturber +#) +from nrtk.impls.perturb_image.generic.PIL.enhance import ( + BrightnessPerturber, + ColorPerturber, + ContrastPerturber, + SharpnessPerturber +) + +from dioptra import pyplugs + +############################################################ +# CREATE PERTURBED DATASET # +############################################################ + +def image_to_base64(image: Image.Image) -> str: + buffered = BytesIO() + image.save(buffered, format="PNG") + return base64.b64encode(buffered.getvalue()).decode("utf-8") + +def image_to_numpy(image: Image.Image) -> np.array: + return np.array(image) + +def numpy_to_image(array: np.ndarray) -> Image.Image: + return Image.fromarray(array) + +def get_perturber(perturbation: str, seed: int, amount: float, salt_vs_pepper: float, var: float, mean: int, ksize: int, factor: float): + perturber_mapping = { + "SaltNoisePerturber": SaltNoisePerturber(rng=seed, amount=amount), + "PepperNoisePerturber": PepperNoisePerturber(rng=seed, amount=amount), + "SaltAndPepperNoisePerturber": SaltAndPepperNoisePerturber(rng=seed, amount=amount, salt_vs_pepper=salt_vs_pepper), + "GaussianNoisePerturber": GaussianNoisePerturber(rng=seed, mean=mean, var=var), + "SpeckleNoisePerturber": SpeckleNoisePerturber(rng=seed, mean=mean, var=var), + #"AverageBlurPerturber": AverageBlurPerturber(ksize=ksize), + #"GaussianBlurPerturber": GaussianBlurPerturber(ksize=ksize), + #"MedianBlurPerturber": MedianBlurPerturber(ksize=ksize), + "BrightnessPerturber": BrightnessPerturber(factor=factor), + "ColorPerturber": ColorPerturber(factor=factor), + "ContrastPerturber": ContrastPerturber(factor=factor), + "SharpnessPerturber": SharpnessPerturber(factor=factor), + } + return perturber_mapping.get(perturbation) + +def serialize_metadata(metadata): + if isinstance(metadata, dict): + return metadata + elif hasattr(metadata, '__dict__'): + return metadata.__dict__ + else: + return str(metadata) + +@pyplugs.register +def perturb_images(dataset: Any, perturbation: str, seed: int, amount: float, salt_vs_pepper: float, var: float, mean: int, ksize: int, factor: float) -> Any: + + perturber = get_perturber(perturbation, seed, amount, salt_vs_pepper, var, mean, ksize, factor) + + if perturber is None: + raise ValueError(f"Unknown perturbation type: {perturbation}") + + def apply_perturbation(original_dataset): + original_image = image_to_numpy(original_dataset['image']) + perturbed_image = perturber(original_image) + original_dataset['image'] = numpy_to_image(perturbed_image) + return original_dataset + + perturbed_dataset = [apply_perturbation(img_data) for img_data in dataset] + + with tempfile.TemporaryDirectory() as tmp_dir: + annotations = [] + for i, perturbed_image in enumerate(perturbed_dataset): + image_path = os.path.join(tmp_dir, f"perturbed_image_{i}.png") + perturbed_image['image'].save(image_path) + + metadata_serializable = {key: serialize_metadata(value) for key, value in perturbed_image.items() if key != 'image'} + metadata_serializable['image_path'] = image_path + annotations.append(metadata_serializable) + + annotations_path = os.path.join(tmp_dir, 'annotations.json') + with open(annotations_path, 'w') as f: + json.dump(annotations, f) + + mlflow.log_artifacts(tmp_dir, artifact_path="perturbed_dataset") + + return perturbed_dataset + +############################################################ +# CREATE OBJECT DETECTION DATASET CLASS # +############################################################ + +class ObjectDetectionDataset(Dataset): + def __init__(self, annotations, images, transform=None): + self.annotations = annotations + self.images = images + self.transform = transform + + def __len__(self): + return len(self.annotations) + + def __getitem__(self, idx): + annotation = self.annotations[idx] + image_filename = os.path.basename(annotation['image_path']) + image = self.images[image_filename] + + objects = annotation['objects'] + boxes = objects['boxes'] + labels = objects['labels'] + bbox_id = objects.get('bbox_id', []) + area = objects.get('area', []) + + data = { + "image": image, + "objects": { + "boxes": boxes, + "labels": labels, + "bbox_id": bbox_id, + "area": area + } + } + + if self.transform: + data = self.transform(data) + + return data + + def set_transform(self, transform): + self.transform = transform + +def to_tensor(image): + return F.to_tensor(image) + +def transform_function(data, shape, totensor=False): + image = data['image'].convert("RGB") + if totensor: + image = to_tensor(image.resize(shape)) + else: + image = image.resize(shape) + + data["image"] = image + data["objects"]["boxes"] = torch.tensor(data["objects"]["boxes"], dtype=torch.float32) if totensor else data["objects"]["boxes"] + return data + +def set_transform(dataset, shape, totensor=False): + def transform(data): + return transform_function(data, shape, totensor) + dataset.set_transform(transform) + +############################################################ +# PULL PERTURBED DATASET ARTIFACT # +############################################################ + +@pyplugs.register +def get_perturbed_dataset(mlflow_run_id: str) -> Any: + """Pulls a perturbed image dataset from mlflow and converts it into a MAITE readable + object detection dataset. + + Args: + mlflow_run_id: A string representing the run_id from the job that perturbed the original + dataset and registered the perturbed images into mlflow. + + Returns: + One ObjectDetectionDataset populated with NRTK perturbed images. + """ + client = MlflowClient() + run_id = mlflow_run_id + artifact_path = "perturbed_dataset" + artifact_uri = client.get_run(run_id).info.artifact_uri + dataset_artifact_path = f"{artifact_uri}/{artifact_path}" + + with tempfile.TemporaryDirectory() as tmpdir: + data_annotation_path = mlflow.artifacts.download_artifacts(run_id=run_id, artifact_path=artifact_path, dst_path=tmpdir) + + images_dir = os.path.join(tmpdir, 'images') + if not os.path.exists(images_dir): + os.makedirs(images_dir) + + annotations_file = None + + for filename in os.listdir(data_annotation_path): + file_path = os.path.join(data_annotation_path, filename) + if filename == 'annotations.json': + annotations_file = file_path + elif filename.endswith('.png') or filename.endswith('.jpg') or filename.endswith('.jpeg'): + shutil.move(file_path, images_dir) + + if annotations_file is None: + raise FileNotFoundError("Annotations file not found in the artifact path.") + + with open(annotations_file, 'r') as f: + annotations = json.load(f) + + images = {} + for annotation in annotations: + image_filename = annotation['image_path'].split('/')[-1] + image_path = os.path.join(images_dir, image_filename) + image = Image.open(image_path) + images[image_filename] = image + + perturbed_dataset = ObjectDetectionDataset(annotations, images) + + return perturbed_dataset From eadd804b47075050b92a620186d175a840f45101 Mon Sep 17 00:00:00 2001 From: bjpatrick <137509145+bjpatrick@users.noreply.github.com> Date: Tue, 16 Jul 2024 17:50:25 -0500 Subject: [PATCH 18/18] Upload modelscan custom task plugin --- .../dioptra_builtins/modelscan/modelscan.py | 110 ++++++++++++++++++ 1 file changed, 110 insertions(+) create mode 100644 task-plugins/dioptra_builtins/modelscan/modelscan.py diff --git a/task-plugins/dioptra_builtins/modelscan/modelscan.py b/task-plugins/dioptra_builtins/modelscan/modelscan.py new file mode 100644 index 000000000..2b47ddf7b --- /dev/null +++ b/task-plugins/dioptra_builtins/modelscan/modelscan.py @@ -0,0 +1,110 @@ +# This Software (Dioptra) is being made available as a public service by the +# National Institute of Standards and Technology (NIST), an Agency of the United +# States Department of Commerce. This software was developed in part by employees of +# NIST and in part by NIST contractors. Copyright in portions of this software that +# were developed by NIST contractors has been licensed or assigned to NIST. Pursuant +# to Title 17 United States Code Section 105, works of NIST employees are not +# subject to copyright protection in the United States. However, NIST may hold +# international copyright in software created by its employees and domestic +# copyright (or licensing rights) in portions of software that were assigned or +# licensed to NIST. To the extent that NIST holds copyright in this software, it is +# being made available under the Creative Commons Attribution 4.0 International +# license (CC BY 4.0). The disclaimers of the CC BY 4.0 license apply to all parts +# of the software developed or licensed by NIST. +# +# ACCESS THE FULL CC BY 4.0 LICENSE HERE: +# https://creativecommons.org/licenses/by/4.0/legalcode +from __future__ import annotations + +from types import FunctionType +from typing import Any, Dict, List, Union + +import mlflow +import modelscan +import os +import re +import structlog +import subprocess +import tempfile +from structlog.stdlib import BoundLogger + +from dioptra import pyplugs +from dioptra.sdk.utilities.decorators import require_package +from mlflow.tracking import MlflowClient + +LOGGER: BoundLogger = structlog.stdlib.get_logger() + +def trim_key(key): + return key.replace('-', '').strip() +def convert_to_int(value): + try: + value = int(value) + return value + except ValueError: + return value +@pyplugs.register +def scan_model(mlflow_run_id: str) -> Any: + """ + Run the modelscan library on a model stored in MlFlow. + + Parameters: + mlflow_run_id (str): The run_id of the job that stored a model in MlFlow. + + Returns: + result (dict): A dictionary storing the modelscan results: + output (str): The standard output from the modelscan command. The output will be logged in MlFlow. + error (str): The standard error from the modelscan command. + return_code (int): The return code of the modelscan command. + """ + + #get the artifact_path for the huggingface model just stored in mlflow + client = MlflowClient() + run_id = mlflow_run_id + artifact_path = "model/data" + artifact_uri = client.get_run(mlflow_run_id).info.artifact_uri + model_artifact_path = f"{artifact_uri}/{artifact_path}" + print(model_artifact_path) + + #download the model file to a localized temp file + with tempfile.TemporaryDirectory() as tmpdir: + local_path = mlflow.artifacts.download_artifacts(run_id=run_id, artifact_path=artifact_path, dst_path=tmpdir) + model_file_path = os.path.join(local_path, "model.pth") + + if os.path.exists(model_file_path): + scan_command = ["modelscan", "--path", model_file_path, "--show-skipped"] + + try: + result = subprocess.run(scan_command, capture_output=True, text=True) + output = result.stdout + error = result.stderr + return_code = result.returncode + + #record scan results as metrics and artifacts in mlflow + with open("scan_output.txt", "w") as f: + f.write(output) + + mlflow.log_artifact("scan_output.txt") + result = {} + + for line in output.split('\n'): + if ': ' in line: + key, value = line.split(': ') + result[key.strip(' .')] = value.strip() + + for key, value in result.items(): + trimmed_key = trim_key(key) + result[key] = convert_to_int(value) + if isinstance(result[key], int) == True: + mlflow.log_metric(trimmed_key, value) + + total_skipped = int(re.search(r"Total skipped:\s+(\d+)", output).group(1)) + mlflow.log_metric("total_skipped", total_skipped) + mlflow.log_metric("return_code", return_code) + + except Exception as e: + raise Exception(f"An error occurred while running modelscan: {str(e)}") + + else: + print("Error: Model file path does not exist.") + + return result