Merge branch 'master' into quantized_tutorial

Author: Laicheng0830

CHANGELOG.md

@@ -67,7 +67,6 @@ To release a new version, please update the changelog as followed:
 
 <!-- YOU CAN EDIT FROM HERE -->
 
-
 ## [Unreleased]
 
 ### Added
@@ -80,17 +79,38 @@ To release a new version, please update the changelog as followed:
 
 ### Fixed
 
-- Fix README. (#PR 1044)
-- Fix package info. (#PR 1046)
-
 ### Removed
 
 ### Security
 
 ### Contributors
 
-- @luomai (PR #1044, 1046)
+## [2.2.1] - 2020-01-14
+
+TensorLayer 2.2.1 is a maintenance release.
+It contains numerous bug fixes.
+
+### Added
+
+### Changed
+
+### Dependencies Update
+
+### Deprecated
+
+### Fixed
+
+- Fix README. (#1044)
+- Fix package info. (#1046)
+- Fix build test (Using YAPF 0.29) (#1057)
+
+### Removed
+
+### Security
+
+### Contributors
 
+- @luomai (#1044, #1046, #1057)
 
 ## [2.2.0] - 2019-09-13
 
@@ -150,7 +170,7 @@ This release is compatible with TensorFlow 2 RC1.
 - Replace tf.nn.func with tf.nn.func.\_\_name\_\_ in model config. (PR #994)
 - Add Reinforcement learning tutorials. (PR #995)
 - Add RNN layers with simple rnn cell, GRU cell, LSTM cell. (PR #998)
-- Update Seq2seq (#998) 
+- Update Seq2seq (#998)
 - Add Seq2seqLuongAttention model (#998)
 
 ### Fixed
@@ -571,12 +591,13 @@ To many PR for this update, please check [here](https://github.com/tensorlayer/t
 @zsdonghao @luomai @DEKHTIARJonathan
 
 [Unreleased]: https://github.com/tensorlayer/tensorlayer/compare/2.0....master
-[2.2.0]: https://github.com/tensorlayer/tensorlayer/compare/2.2.0...2.2.0
-[2.1.0]: https://github.com/tensorlayer/tensorlayer/compare/2.1.0...2.1.0
-[2.0.2]: https://github.com/tensorlayer/tensorlayer/compare/2.0.2...2.0.2
-[2.0.1]: https://github.com/tensorlayer/tensorlayer/compare/2.0.1...2.0.1
-[2.0.0]: https://github.com/tensorlayer/tensorlayer/compare/2.0.0...2.0.0
-[1.11.1]: https://github.com/tensorlayer/tensorlayer/compare/1.11.0...1.11.0
+[2.2.1]: https://github.com/tensorlayer/tensorlayer/compare/2.2.0...2.2.1
+[2.2.0]: https://github.com/tensorlayer/tensorlayer/compare/2.1.0...2.2.0
+[2.1.0]: https://github.com/tensorlayer/tensorlayer/compare/2.0.2...2.1.0
+[2.0.2]: https://github.com/tensorlayer/tensorlayer/compare/2.0.1...2.0.2
+[2.0.1]: https://github.com/tensorlayer/tensorlayer/compare/2.0.0...2.0.1
+[2.0.0]: https://github.com/tensorlayer/tensorlayer/compare/1.11.1...2.0.0
+[1.11.1]: https://github.com/tensorlayer/tensorlayer/compare/1.11.0...1.11.1
 [1.11.0]: https://github.com/tensorlayer/tensorlayer/compare/1.10.1...1.11.0
 [1.10.1]: https://github.com/tensorlayer/tensorlayer/compare/1.10.0...1.10.1
 [1.10.0]: https://github.com/tensorlayer/tensorlayer/compare/1.9.1...1.10.0

Makefile

@@ -14,16 +14,17 @@ test:
 	python3 tests/files/test_utils_saveload.py
 
 format:
-	autoflake -i examples/*.py
-	autoflake -i tensorlayer/*.py
-	autoflake -i tensorlayer/**/*.py
+	autoflake -ir examples
+	autoflake -ir tensorlayer
+	autoflake -ir tests
 
 	isort -rc examples
 	isort -rc tensorlayer
+	isort -rc tests
 
-	yapf -i examples/*.py
-	yapf -i tensorlayer/*.py
-	yapf -i tensorlayer/**/*.py
+	yapf -ir examples
+	yapf -ir tensorlayer
+	yapf -ir tests
 
 install3:
 	pip3 install -U . --user

README.md

@@ -20,7 +20,7 @@
 <!---  [![Documentation Status](https://readthedocs.org/projects/tensorlayercn/badge/)](https://tensorlayercn.readthedocs.io/)
 <!---  [![PyUP Updates](https://pyup.io/repos/github/tensorlayer/tensorlayer/shield.svg)](https://pyup.io/repos/github/tensorlayer/tensorlayer/) --->
 
-TensorLayer is a novel TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers. It provides an extensive collection of customizable neural layers to build complex AI models. TensorLayer is awarded the 2017 Best Open Source Software by the [ACM Multimedia Society](https://twitter.com/ImperialDSI/status/923928895325442049). 
+[TensorLayer](https://tensorlayer.readthedocs.io) is a novel TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers. It provides an extensive collection of customizable neural layers to build complex AI models. TensorLayer is awarded the 2017 Best Open Source Software by the [ACM Multimedia Society](https://twitter.com/ImperialDSI/status/923928895325442049). 
 TensorLayer can also be found at [iHub](https://code.ihub.org.cn/projects/328) and [Gitee](https://gitee.com/organizations/TensorLayer).
 
 # News
@@ -158,7 +158,7 @@ We suggest users to report bugs using Github issues. Users can also discuss how
 
 <br/>
 
-<a href="https://join.slack.com/t/tensorlayer/shared_invite/enQtMjUyMjczMzU2Njg4LWI0MWU0MDFkOWY2YjQ4YjVhMzI5M2VlZmE4YTNhNGY1NjZhMzUwMmQ2MTc0YWRjMjQzMjdjMTg2MWQ2ZWJhYzc" target="\_blank">
+<a href="https://join.slack.com/t/tensorlayer/shared_invite/enQtODk1NTQ5NTY1OTM5LTQyMGZhN2UzZDBhM2I3YjYzZDBkNGExYzcyZDNmOGQzNmYzNjc3ZjE3MzhiMjlkMmNiMmM3Nzc4ZDY2YmNkMTY" target="\_blank">
 	<div align="center">
 		<img src="img/join_slack.png" width="40%"/>
 	</div>
@@ -178,4 +178,4 @@ If you find TensorLayer useful for your project, please cite the following paper
     url     = {http://tensorlayer.org},
     year    = {2017}
 }
-```
+```

docs/user/get_involved.rst

@@ -9,9 +9,10 @@ Ph.D. Postition @ PKU
 
 
 Hi, I am `Hao Dong <https://zsdonghao.github.io/>`__, the founder of this project and a new faculty member in EECS, Peking University. I now have a few Ph.D. positions per year open for international students who would like to study AI. If you or your friends are interested in it, feel free to contact me.
-PKU is a top 30 university in the global ranking. The application is competitive, apply early is recommended. For the application of next year, please note that the DDL of Chinese Government Scholarship is in the end of each year, please check this `link <http://www.isd.pku.edu.cn/info/1503/5676.htm>`__ for more details.
+PKU is a top 30 university in the global ranking. The application is competitive, apply early is recommended. Please check the following links for more details.
 
-My homepage: `https://zsdonghao.github.io <https://zsdonghao.github.io/>`__
+- `About the International Elite Ph.D. Program in Computer Science <https://cs.pku.edu.cn/info/1115/2233.htm>`__
+- `My homepage <https://zsdonghao.github.io/>`__
 
 Contact: hao.dong [AT] pku.edu.cn
 

docs/user/installation.rst

@@ -35,6 +35,8 @@ For stable version:
 .. code-block:: bash
 
   pip3 install tensorlayer
+  
+  pip install tensorlayer -i https://pypi.tuna.tsinghua.edu.cn/simple  (faster in China)
 
 For latest version, please install from Github.
 
@@ -60,7 +62,7 @@ Alternatively, you can build from the source.
   cd tensorlayer
 
   # Install virtualenv if necessary
-  pip install virtualenv
+  sudo pip3 install virtualenv
   # Then create a virtualenv called `venv`
   virtualenv venv
 
@@ -73,29 +75,29 @@ Alternatively, you can build from the source.
   venv\Scripts\activate.bat
 
   # basic installation
-  pip install .
+  pip3 install .
 
   # ============= IF TENSORFLOW IS NOT ALREADY INSTALLED ============= #
 
   # for a machine **without** an NVIDIA GPU
-  pip install -e ".[all_cpu_dev]"
+  pip3 install -e ".[all_cpu_dev]"
 
   # for a machine **with** an NVIDIA GPU
-  pip install -e ".[all_gpu_dev]"
+  pip3 install -e ".[all_gpu_dev]"
 
 If you want install TensorLayer 1.X, the simplest way to install TensorLayer 1.X is as follow. It will also install the numpy and matplotlib automatically.
 
 .. code-block:: bash
 
-  [stable version] pip install tensorlayer==1.x.x
+  [stable version] pip3 install tensorlayer==1.x.x
 
 However, if you want to modify or extend TensorLayer 1.X, you can download the repository from
 `Github`_ and install it as follow.
 
 .. code-block:: bash
 
   cd to the root of the git tree
-  pip install -e .
+  pip3 install -e .
 
 This command will run the ``setup.py`` to install TensorLayer. The ``-e`` reflects
 editable, then you can edit the source code in ``tensorlayer`` folder, and ``import`` the edited
@@ -194,9 +196,9 @@ For TensorLayer, please refer to the steps mentioned above.
 
 .. code-block:: bash
 
-  pip install tensorflow        #CPU version
-  pip install tensorflow-gpu    #GPU version (GPU version and CPU version just choose one)
-  pip install tensorlayer       #Install tensorlayer
+  pip3 install tensorflow        #CPU version
+  pip3 install tensorflow-gpu    #GPU version (GPU version and CPU version just choose one)
+  pip3 install tensorlayer       #Install tensorlayer
 
 
 

examples/basic_tutorials/tutorial_cifar10_cnn_static.py

@@ -1,10 +1,12 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 
+import multiprocessing
 import time
+
 import numpy as np
-import multiprocessing
 import tensorflow as tf
+
 import tensorlayer as tl
 from tensorlayer.layers import (BatchNorm, Conv2d, Dense, Flatten, Input, LocalResponseNorm, MaxPool2d)
 from tensorlayer.models import Model
@@ -122,7 +124,7 @@ def _map_fn_train(img, target):
 
 def _map_fn_test(img, target):
     # 1. Crop the central [height, width] of the image.
-    img = tf.image.resize_with_crop_or_pad(img, 24, 24)
+    img = tf.image.resize_with_pad(img, 24, 24)
     # 2. Subtract off the mean and divide by the variance of the pixels.
     img = tf.image.per_image_standardization(img)
     img = tf.reshape(img, (24, 24, 3))

examples/basic_tutorials/tutorial_mnist_mlp_dynamic.py

@@ -1,6 +1,8 @@
 import time
+
 import numpy as np
 import tensorflow as tf
+
 import tensorlayer as tl
 from tensorlayer.layers import Dense, Dropout, Input
 from tensorlayer.models import Model

examples/basic_tutorials/tutorial_mnist_mlp_dynamic_2.py

@@ -1,6 +1,8 @@
 import time
+
 import numpy as np
 import tensorflow as tf
+
 import tensorlayer as tl
 from tensorlayer.layers import Dense, Dropout, Input, LayerList
 from tensorlayer.models import Model

examples/basic_tutorials/tutorial_mnist_mlp_static.py

@@ -1,6 +1,9 @@
+import pprint
 import time
+
 import numpy as np
 import tensorflow as tf
+
 import tensorlayer as tl
 from tensorlayer.layers import Dense, Dropout, Input
 from tensorlayer.models import Model
@@ -29,7 +32,6 @@ def get_model(inputs_shape):
 
 
 MLP = get_model([None, 784])
-import pprint
 pprint.pprint(MLP.config)
 
 ## start training

examples/basic_tutorials/tutorial_mnist_mlp_static_2.py

@@ -1,6 +1,8 @@
 import time
+
 import numpy as np
 import tensorflow as tf
+
 import tensorlayer as tl
 from tensorlayer.layers import Dense, Dropout, Input
 from tensorlayer.models import Model

examples/basic_tutorials/tutorial_mnist_siamese.py

@@ -14,8 +14,8 @@
 import time
 
 import numpy as np
-
 import tensorflow as tf
+
 import tensorlayer as tl
 from tensorlayer.layers import Dense, Dropout, Flatten, Input
 from tensorlayer.models import Model

examples/basic_tutorials/tutorial_mnist_simple.py

@@ -2,8 +2,8 @@
 # -*- coding: utf-8 -*-
 
 import numpy as np
-
 import tensorflow as tf
+
 import tensorlayer as tl
 
 tl.logging.set_verbosity(tl.logging.DEBUG)

examples/data_process/tutorial_fast_affine_transform.py

@@ -9,9 +9,9 @@
 import time
 
 import numpy as np
+import tensorflow as tf
 
 import cv2
-import tensorflow as tf
 import tensorlayer as tl
 
 # tl.logging.set_verbosity(tl.logging.DEBUG)
@@ -98,7 +98,6 @@ def _map_fn(image_path, target):
     st = time.time()
     for img, target in dataset:
         n_step += 1
-        pass
     assert n_step == n_epoch * n_data / batch_size
     print("dataset APIs took %fs for each image" % ((time.time() - st) / batch_size / n_step))  # CPU ~ 100%
 

examples/data_process/tutorial_tf_dataset_voc.py

@@ -13,8 +13,8 @@
 import time
 
 import numpy as np
-
 import tensorflow as tf
+
 import tensorlayer as tl
 
 # tf.logging.set_verbosity(tf.logging.DEBUG)

examples/data_process/tutorial_tfrecord.py

@@ -22,9 +22,9 @@
 import os
 
 import numpy as np
+import tensorflow as tf
 from PIL import Image
 
-import tensorflow as tf
 import tensorlayer as tl
 
 ## Save data ==================================================================

examples/data_process/tutorial_tfrecord2.py

@@ -14,10 +14,10 @@
 import os
 
 import numpy as np
-
 # import matplotlib
 # matplotlib.use('GTK')
 import tensorflow as tf
+
 import tensorlayer as tl
 
 # Download data, and convert to TFRecord format, see ```tutorial_tfrecord.py```

examples/data_process/tutorial_tfrecord3.py

@@ -19,9 +19,9 @@
 import os
 
 import numpy as np
+import tensorflow as tf
 from PIL import Image
 
-import tensorflow as tf
 import tensorlayer as tl
 
 
@@ -231,8 +231,8 @@ def distort_image(image, thread_id):
 
 
 def prefetch_input_data(
-        reader, file_pattern, is_training, batch_size, values_per_shard, input_queue_capacity_factor=16,
-        num_reader_threads=1, shard_queue_name="filename_queue", value_queue_name="input_queue"
+    reader, file_pattern, is_training, batch_size, values_per_shard, input_queue_capacity_factor=16,
+    num_reader_threads=1, shard_queue_name="filename_queue", value_queue_name="input_queue"
 ):
     """Prefetches string values from disk into an input queue.
 

examples/database/dispatch_tasks.py

@@ -6,6 +6,7 @@
 import time
 
 import tensorflow as tf
+
 import tensorlayer as tl
 
 tl.logging.set_verbosity(tl.logging.DEBUG)

examples/database/task_script.py

@@ -1,6 +1,7 @@
 """Sample task script."""
 
 import tensorflow as tf
+
 import tensorlayer as tl
 
 # tf.logging.set_verbosity(tf.logging.DEBUG)