Fix for migration

.github/workflows/test_AMDShark.yml

@@ -29,11 +29,11 @@ jobs:
         with:
           python-version: ${{matrix.version}}
 
-      - name: "Checkout AMDShark"
+      - name: "Checkout AMD-Shark"
         uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
         with:
-          repository: "nod-ai/AMDShark.git"
-          path: AMDShark
+          repository: "nod-ai/AMD-Shark.git"
+          path: AMD-Shark
           ref: "main"
 
       - name: "Checkout iree-turbine"

README.md

@@ -9,7 +9,7 @@ were developed, including:
 * [Torch-MLIR ONNX Importer](https://github.com/llvm/torch-mlir/blob/main/python/torch_mlir/extras/onnx_importer.py)
 * [Torch-MLIR's ONNX C Importer](https://github.com/llvm/torch-mlir/tree/main/projects/onnx_c_importer)
 * [IREE Turbine](https://github.com/iree-org/iree-turbine)
-* [AMDSharktank and Shortfin](https://github.com/nod-ai/AMDSharktank)
+* [AMDSharktank and Shortfin](https://github.com/nod-ai/Sharktank)
 
 As these have all found upstream homes, this repo is a bit bare. We will
 continue to use it as a staging ground for things that don't have a

models/README.md

@@ -14,8 +14,8 @@ YOUR_HF_TOKEN="insert token for headless"
 
 # clone and install dependencies
 sudo apt install -y git
-git clone https://github.com/nod-ai/AMDShark-Turbine.git
-cd AMDShark-Turbine
+git clone https://github.com/nod-ai/AMD-Shark-ModelDev.git
+cd AMD-Shark-ModelDev
 pip install -r core/requirements.txt
 pip install -r models/requirements.txt
 

models/requirements.txt

@@ -4,7 +4,7 @@ transformers==4.50.0
 torchsde
 accelerate
 peft
-diffusers @ git+https://github.com/nod-ai/[email protected]AMDShark
+diffusers @ git+https://github.com/nod-ai/[email protected]Shark
 brevitas @ git+https://github.com/Xilinx/brevitas.git@6695e8df7f6a2c7715b9ed69c4b78157376bb60b
 # turbine tank downloading/uploading
 azure-storage-blob
@@ -13,4 +13,4 @@ einops
 pytest
 scipy
 iree-turbine @ git+https://github.com/iree-org/iree-turbine.git@main
--e git+https://github.com/nod-ai/AMDSharktank.git@main#egg=AMDSharktank&subdirectory=AMDSharktank
+-e git+https://github.com/nod-ai/Sharktank.git@main#egg=Sharktank&subdirectory=Sharktank

models/setup.py

@@ -40,7 +40,7 @@ def load_version_info():
     description="AMDShark Turbine Machine Learning Model Zoo",
     long_description=README,
     long_description_content_type="text/markdown",
-    url="https://github.com/nod-ai/AMDShark-Turbine",
+    url="https://github.com/nod-ai/AMD-SHARK-ModelDev",
     license="Apache-2.0",
     classifiers=[
         "Development Status :: 3 - Alpha",

models/turbine_models/custom_models/README.md

@@ -2,8 +2,8 @@
 
 Clone and install AMDShark-Turbine
 ```
-git clone https://github.com/nod-ai/AMDShark-Turbine.git
-cd AMDShark-Turbine
+git clone https://github.com/nod-ai/AMD-SHARK-ModelDev.git
+cd AMD-SHARK-ModelDev
 python -m venv turbine_venv && source turbine_venv/bin/activate
 
 pip install --index-url https://download.pytorch.org/whl/cpu \

models/turbine_models/custom_models/llama_benchmark/README.md

@@ -2,8 +2,8 @@
 
 Clone and install AMDShark-Turbine
 ```
-git clone https://github.com/nod-ai/AMDShark-Turbine.git
-cd AMDShark-Turbine
+git clone https://github.com/nod-ai/AMD-SHARK-ModelDev.git
+cd AMD-SHARK-ModelDev
 python -m venv turbine_venv && source turbine_venv/bin/activate
 
 pip install --upgrade -r requirements.txt

models/turbine_models/custom_models/llm_optimizations/streaming_llm/README.md

@@ -27,6 +27,6 @@ python python/turbine_models/custom_models/llm_runner.py --vmfb_path=/path/to/Ll
 ```
 
 ## Future Work:
-- [ ] Make window size configurable through python, everything is there but we'd need to initialize with a default value which would only be possible after we let `_create_initial_value` to take in initial value from GlobalAttribute somewhere [here](https://github.com/nod-ai/AMDShark-Turbine/blob/18e8a4100b61adfd9425dd32f780dc5f90017813/python/AMDShark_turbine/aot/support/ir_utils.py#L284-L316) . 
+- [ ] Make window size configurable through python, everything is there but we'd need to initialize with a default value which would only be possible after we let `_create_initial_value` to take in initial value from GlobalAttribute somewhere [here](https://github.com/nod-ai/AMD-SHARK-ModelDev/blob/18e8a4100b61adfd9425dd32f780dc5f90017813/python/AMDShark_turbine/aot/support/ir_utils.py#L284-L316) . 
 - [ ] Get flow.move to enable overlap of sliding window and src of data. (Currently need to evict when it's at least 2x size of window) For example by default our streamingLLM window_size is 256, so we evict at ~600(slightly more than 2x for safety) token.
-- [ ] Introduce Rerotation of RoPE to as seen [here](https://github.com/huggingface/transformers/blob/c2d283a64a7f33547952e3eb0fa6533fc375bcdd/src/transformers/cache_utils.py#L213-L218) to remove invasive modification of LlamaAttention module for streamingLLM.
+- [ ] Introduce Rerotation of RoPE to as seen [here](https://github.com/huggingface/transformers/blob/c2d283a64a7f33547952e3eb0fa6533fc375bcdd/src/transformers/cache_utils.py#L213-L218) to remove invasive modification of LlamaAttention module for streamingLLM.

models/turbine_models/tests/stateless_llama_test.py

@@ -76,7 +76,7 @@ def tearDownClass(cls):
         cls.tokenizer = None
         cls.mod = None
 
-    # See: https://github.com/nod-ai/AMDShark-Turbine/issues/601
+    # See: https://github.com/nod-ai/AMD-SHARK-ModelDev/issues/601
     # Developed issues related to the pytorch 2.3 upgrade.
     @unittest.expectedFailure
     def test_vmfb_comparison(self):
@@ -139,7 +139,7 @@ def test_vmfb_comparison(self):
             new_blob_name = new_blob_name[0] + "-pass.mlir"
             turbine_tank.changeBlobName(blob_name, new_blob_name)
 
-    # See: https://github.com/nod-ai/AMDShark-Turbine/issues/601
+    # See: https://github.com/nod-ai/AMD-SHARK-ModelDev/issues/601
     # Developed issues related to the pytorch 2.3 upgrade.
     @unittest.expectedFailure
     def test_streaming_vmfb_comparison(self):