remove graph api (#818)

* remove graph api

* changelog

* timeout test

* codacy

* remove graph in tl.models

* increase timeout time

* remove tl in tests

* Additional Cleaning

* Timeout time added

* tests directory refactored

* Tests Fix Update python, 2.6

* YAPF Cleaning

* get_env fix

* Python 2 fix applied

* Python 2 Error fixes

* TL 1.10.1rc0 released

* Doc and YAPF Fix

* Test YAPF Fix

* RTD Lazy Import Fix

* Travis config restored

* Revert "Travis config restored"

This reverts commit 03fe83e.

Author: zsdonghao

.gitignore

@@ -127,3 +127,4 @@ update_tl.py
 *.gz
 *.npz
 venv_doc/
+venv_py2/

.travis.yml

@@ -21,16 +21,12 @@ env:
   # Backward Compatibility in insured for release less than 1 year old.
   # https://pypi.org/project/tensorflow/#history
   matrix:
-    - _TF_VERSION=1.10.0 # Remove on Apr 28, 2019
+    - _TF_VERSION=1.10.1 # Remove on Apr 28, 2019
     - _TF_VERSION=1.9.0 # Remove on Apr 28, 2019
     - _TF_VERSION=1.8.0 # Remove on Apr 28, 2019
     - _TF_VERSION=1.7.1 # Remove on May 08, 2019
     - _TF_VERSION=1.7.0 # Remove on Mar 29, 2019
     - _TF_VERSION=1.6.0 # Remove on Mar 01, 2019
-    # - _TF_VERSION=1.5.1 # Remove on Mar 20, 2019
-    # - _TF_VERSION=1.5.0 # Remove on Jan 26, 2019
-    # - _TF_VERSION=1.4.1 # Remove on Dec 08, 2018
-    # - _TF_VERSION=1.4.0 # Remove on Nov 01, 2018
 
   global:
 
@@ -61,7 +57,7 @@ install:
     if [[ -v _DOC_AND_YAPF_TEST ]]; then
         pip install tensorflow 
         pip install yapf
-        pip install -r requirements/requirements_doc.txt
+        pip install -e .[doc]
     else
         pip install tensorflow==$_TF_VERSION
         pip install -e .[all_cpu_dev]
@@ -97,7 +93,7 @@ deploy:
   on:
     tags: true
     python: '3.6'
-    condition: '$_TF_VERSION = 1.10.0'
+    condition: '$_TF_VERSION = 1.10.1'
 
 # Documentation: https://docs.travis-ci.com/user/deployment/releases/
 - provider: releases
@@ -110,4 +106,4 @@ deploy:
   on:
     tags: true
     python: '3.6'
-    condition: '$_TF_VERSION = 1.10.0'
+    condition: '$_TF_VERSION = 1.10.1'

CHANGELOG.md

@@ -145,6 +145,7 @@ To release a new version, please update the changelog as followed:
 ### Removed
 
   - `conv_layers()`  has been removed in both vgg16 and vgg19(PR #710)
+  - graph API (PR #818)
 
 ### Fixed
 
@@ -171,7 +172,7 @@ To release a new version, please update the changelog as followed:
 - @DEKHTIARJonathan: #739 #747 #750 #754
 - @lgarithm: #705 #700
 - @OwenLiuzZ: #698 #710 #775 #776
-- @zsdonghao: #711 #712 #734 #736 #737 #700 #751 #809
+- @zsdonghao: #711 #712 #734 #736 #737 #700 #751 #809 #818
 - @luomai: #700 #751 #766 #802
 - @XJTUWYD: #735
 - @mutewall: #735

docs/modules/files.rst

@@ -31,13 +31,14 @@ Load benchmark dataset, save and restore model, save and load variables.
    load_and_assign_npz
    save_npz_dict
    load_and_assign_npz_dict
+   save_ckpt
+   load_ckpt
+
+..
    save_graph
    load_graph
    save_graph_and_params
    load_graph_and_params
-   save_ckpt
-   load_ckpt
-
 
    save_any_to_npy
    load_npy_to_any
@@ -183,21 +184,22 @@ Load network from dict (npz)
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 .. autofunction:: load_and_assign_npz_dict
 
-Save network architecture as a graph
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-.. autofunction:: save_graph
+..
+  Save network architecture as a graph
+  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  .. autofunction:: save_graph
 
-Load network architecture from a graph
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-.. autofunction:: load_graph
+  Load network architecture from a graph
+  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  .. autofunction:: load_graph
 
-Save network architecture and parameters
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-.. autofunction:: save_graph_and_params
+  Save network architecture and parameters
+  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  .. autofunction:: save_graph_and_params
 
-Load network architecture and parameters
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-.. autofunction:: load_graph_and_params
+  Load network architecture and parameters
+  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  .. autofunction:: load_graph_and_params
 
 Save network into ckpt
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

setup.py

@@ -89,7 +89,7 @@ def req_file(filename, folder="requirements"):
 
 
 # Readthedocs requires TF 1.5.0 to build properly
-if os.environ.get('READTHEDOCS', None) == 'True':
+if 'READTHEDOCS' in os.environ:
     ext_modules = [
         Extension('install_requirements_for_rtd', []),
     ]

tensorlayer/__init__.py

@@ -2,8 +2,6 @@
 # -*- coding: utf-8 -*-
 """Deep learning and Reinforcement learning library for Researchers and Engineers"""
 
-from __future__ import absolute_import
-
 import os
 from distutils.version import LooseVersion
 

tensorlayer/db.py

@@ -9,7 +9,11 @@
 
 import gridfs
 import pymongo
-from tensorlayer.files import load_graph_and_params, exists_or_mkdir, del_folder
+
+# from tensorlayer.files import load_graph_and_params
+from tensorlayer.files import exists_or_mkdir
+from tensorlayer.files import del_folder
+
 from tensorlayer import logging
 
 import tensorflow as tf

tensorlayer/distributed.py

@@ -107,7 +107,7 @@ def __init__(
             self, training_dataset, build_training_func, optimizer, optimizer_args, batch_size=32, num_epochs=100,
             prefetch_buffer_size=None, shuffle_data=False, shuffle_seed=0, checkpoint_dir=None,
             scaling_learning_rate=True, log_step_size=1, validation_dataset=None, build_validation_func=None,
-            max_iteration=math.inf
+            max_iteration=float('inf')
     ):
         # Initialize Horovod.
         hvd.init()

tensorlayer/files/__init__.py

@@ -67,8 +67,8 @@
     'save_ckpt',
     'save_npz',
     'save_npz_dict',
-    'save_graph',
-    'load_graph',
-    'save_graph_and_params',
-    'load_graph_and_params',
+    #'save_graph',
+    #'load_graph',
+    #'save_graph_and_params',
+    #'load_graph_and_params',
 ]

tensorlayer/files/utils.py

@@ -41,7 +41,8 @@
 
 import tensorflow as tf
 from tensorflow.python.platform import gfile
-import tensorlayer as tl  # it is used in eval() of _graph2net
+
+import tensorlayer as tl
 from tensorlayer import logging
 from tensorlayer import nlp
 from tensorlayer import utils
@@ -71,10 +72,10 @@
     'save_ckpt',
     'save_npz',
     'save_npz_dict',
-    'save_graph',
-    'load_graph',
-    'save_graph_and_params',
-    'load_graph_and_params',
+    #'save_graph',
+    #'load_graph',
+    #'save_graph_and_params',
+    #'load_graph_and_params',
 ]
 
 
@@ -1894,6 +1895,7 @@ def load_ckpt(sess=None, mode_name='model.ckpt', save_dir='checkpoint', var_list
         logging.info("[*] load ckpt fail ...")
 
 
+'''
 def save_graph(network=None, name='graph.pkl'):
     """Save the architecture of TL model into a pickle file. No parameters be saved.
 
@@ -2058,6 +2060,7 @@ def load_graph_and_params(name='model', sess=None):
     network = load_graph(name=os.path.join(name, 'graph.pkl'))
     load_and_assign_npz(sess=sess, name=os.path.join(name, 'params.npz'), network=network)
     return network
+'''
 
 
 def save_any_to_npy(save_dict=None, name='file.npy'):

tensorlayer/layers/core.py

@@ -116,13 +116,9 @@ def __init__(self, prev_layer, act=None, name=None, *args, **kwargs):
 
         self.inputs = None
         self.outputs = None
-        self.graph = {}
         self.all_layers = list()
         self.all_params = list()
         self.all_drop = dict()
-        self.all_graphs = list()
-
-        self.layer_args = self._get_init_args(skip=4)
 
         if name is None:
             raise ValueError('Layer must have a name.')
@@ -146,7 +142,6 @@ def __init__(self, prev_layer, act=None, name=None, *args, **kwargs):
             self._add_layers(prev_layer.all_layers)
             self._add_params(prev_layer.all_params)
             self._add_dropout_layers(prev_layer.all_drop)
-            self._add_graphs(prev_layer.all_graphs)
 
         elif isinstance(prev_layer, list):
             # 2. for layer have multiply inputs i.e. ConcatLayer
@@ -156,7 +151,6 @@ def __init__(self, prev_layer, act=None, name=None, *args, **kwargs):
             self._add_layers(sum([l.all_layers for l in prev_layer], []))
             self._add_params(sum([l.all_params for l in prev_layer], []))
             self._add_dropout_layers(sum([list(l.all_drop.items()) for l in prev_layer], []))
-            self._add_graphs(sum([l.all_graphs for l in prev_layer], []))
 
         elif isinstance(prev_layer, tf.Tensor) or isinstance(prev_layer, tf.Variable):  # placeholders
             if self.__class__.__name__ not in ['InputLayer', 'OneHotInputLayer', 'Word2vecEmbeddingInputlayer',
@@ -165,49 +159,15 @@ def __init__(self, prev_layer, act=None, name=None, *args, **kwargs):
 
             self.inputs = prev_layer
 
-            self._add_graphs(
-                (
-                    self.inputs.name,  # .split(':')[0],
-                    {
-                        'shape': self.inputs.get_shape().as_list(),
-                        'dtype': self.inputs.dtype.name,
-                        'class': 'placeholder',
-                        'prev_layer': None
-                    }
-                )
-            )
-
         elif prev_layer is not None:
             # 4. tl.models
             self._add_layers(prev_layer.all_layers)
             self._add_params(prev_layer.all_params)
             self._add_dropout_layers(prev_layer.all_drop)
-            self._add_graphs(prev_layer.all_graphs)
 
             if hasattr(prev_layer, "outputs"):
                 self.inputs = prev_layer.outputs
 
-        # TL Graph
-        if isinstance(prev_layer, list):  # e.g. ConcatLayer, ElementwiseLayer have multiply previous layers
-            _list = []
-            for layer in prev_layer:
-                _list.append(layer.name)
-            self.graph.update({'class': self.__class__.__name__.split('.')[-1], 'prev_layer': _list})
-        elif prev_layer is None:  #
-            self.graph.update({'class': self.__class__.__name__.split('.')[-1], 'prev_layer': None})
-        else:  # normal layers e.g. Conv2d
-            self.graph.update({'class': self.__class__.__name__.split('.')[-1], 'prev_layer': prev_layer.name})
-        # if act:  ## convert activation from function to string
-        #     try:
-        #         act = act.__name__
-        #     except:
-        #         pass
-        #     self.graph.update({'act': act})
-        # print(self.layer_args)
-        self.graph.update(self.layer_args)
-        # print(self.graph)
-        self._add_graphs((self.name, self.graph))
-
     def print_params(self, details=True, session=None):
         """Print all info of parameters in the network"""
         for i, p in enumerate(self.all_params):
@@ -278,7 +238,6 @@ def __getitem__(self, key):
         net_new._add_layers(net_new.outputs)
 
         net_new._add_params(self.all_params)
-        net_new._add_graphs(self.all_graphs)
         net_new._add_dropout_layers(self.all_drop)
 
         return net_new
@@ -353,17 +312,6 @@ def _add_params(self, params):
 
         self.all_params = list_remove_repeat(self.all_params)
 
-    @protected_method
-    def _add_graphs(self, graphs):
-
-        if isinstance(graphs, list):
-            self.all_graphs.extend(list(graphs))
-
-        else:
-            self.all_graphs.append(graphs)
-
-        # self.all_graphs = list_remove_repeat(self.all_graphs) # cannot repeat
-
     @protected_method
     def _add_dropout_layers(self, drop_layers):
         if isinstance(drop_layers, dict) or isinstance(drop_layers, list):

tensorlayer/layers/utils.py

@@ -296,23 +296,19 @@ def merge_networks(layers=None):
 
     all_params = []
     all_layers = []
-    all_graphs = []
     all_drop = {}
 
     for l in layers:
         all_params.extend(l.all_params)
         all_layers.extend(l.all_layers)
-        all_graphs.extend(l.all_graphs)
         all_drop.update(l.all_drop)
 
     layer.all_params = list(all_params)
     layer.all_layers = list(all_layers)
-    layer.all_graphs = list(all_graphs)
     layer.all_drop = dict(all_drop)
 
     layer.all_layers = list_remove_repeat(layer.all_layers)
     layer.all_params = list_remove_repeat(layer.all_params)
-    layer.all_graphs = list_remove_repeat(layer.all_graphs)
 
     return layer
 

tensorlayer/lazy_imports.py

@@ -17,6 +17,7 @@
 Commonly used nitime lazy imports are also defined in :mod:`nitime.lazy`, so
 they can be reused throughout nitime.
 """
+import os
 import sys
 import types
 
@@ -76,7 +77,7 @@ def __repr__(self):
         return "<module '%s' will be lazily loaded>" % object.__getattribute__(self, '__name__')
 
 
-if 'sphinx' in sys.modules:
+if 'READTHEDOCS' in os.environ:
     lazy_doc = """
                WARNING: To get Sphinx documentation to build we disable
                LazyImports, which makes Sphinx incorrectly report this

tensorlayer/models/mobilenetv1.py

@@ -90,7 +90,6 @@ def __init__(self, x, end_with='out', is_train=False, reuse=None):
         self.all_params = list(self.net.all_params)
         self.all_layers = list(self.net.all_layers)
         self.all_drop = dict(self.net.all_drop)
-        self.all_graphs = list(self.net.all_graphs)
         self.print_layers = self.net.print_layers
         self.print_params = self.net.print_params
 

tensorlayer/models/squeezenetv1.py

@@ -91,7 +91,6 @@ def __init__(self, x, end_with='output', is_train=False, reuse=None):
         self.all_params = list(self.net.all_params)
         self.all_layers = list(self.net.all_layers)
         self.all_drop = dict(self.net.all_drop)
-        self.all_graphs = list(self.net.all_graphs)
         self.print_layers = self.net.print_layers
         self.print_params = self.net.print_params
 

tensorlayer/models/vgg16.py

@@ -214,7 +214,6 @@ def __init__(self, x, end_with='fc3_relu', reuse=None):
             self.all_params = list(self.net.all_params)
             self.all_layers = list(self.net.all_layers)
             self.all_drop = dict(self.net.all_drop)
-            self.all_graphs = list(self.net.all_graphs)
 
             self.print_layers = self.net.print_layers
             self.print_params = self.net.print_params

tensorlayer/models/vgg19.py

@@ -256,6 +256,5 @@ def __init__(self, x, end_with='fc3_relu', reuse=None):
             self.all_params = self.net.all_params
             self.all_layers = self.net.all_layers
             self.all_drop = self.net.all_drop
-            self.all_graphs = list(self.net.all_graphs)
             self.print_layers = self.net.print_layers
             self.print_params = self.net.print_params

tensorlayer/package_info.py

@@ -3,7 +3,7 @@
 """Deep learning and Reinforcement learning library for Researchers and Engineers"""
 
 # Use the following formatting: (major, minor, patch, prerelease)
-VERSION = (1, 10, 0, "")
+VERSION = (1, 10, 1, "rc0")
 __shortversion__ = '.'.join(map(str, VERSION[:3]))
 __version__ = '.'.join(map(str, VERSION[:3])) + "".join(VERSION[3:])