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Jonathan DEKHTIAR
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Documentation fix (#703)
* Update conf.py * Theme RTD removed and added to requirements. * TF 1.9.0rc1 added to Travis * Changelog updated ready for 1.8.6 * Release 1.8.6 * Readme.rst correction * Release date fixed * 1.8.6 changed to 1.9.0
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.travis.yml

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# Backward Compatibility in insured for release less than 1 year old.
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# https://pypi.org/project/tensorflow/#history
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matrix:
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- _TF_VERSION=1.9.0rc0 # Remove on Apr 28, 2019
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- _TF_VERSION=1.9.0rc1 # Remove on Apr 28, 2019
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- _TF_VERSION=1.8.0 # Remove on Apr 28, 2019
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- _TF_VERSION=1.7.1 # Remove on May 08, 2019
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- _TF_VERSION=1.7.0 # Remove on Mar 29, 2019

CHANGELOG.md

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## [Unreleased]
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### Added
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- API:
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- `tl.alphas` and `tl.alphas_like` added following the tf.ones/zeros and tf.zeros_like/ones_like (PR #580)
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- `tl.lazy_imports.LazyImport` to import heavy libraries only when necessary (PR #667)
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- `tl.act.leaky_relu6` and `tl.layers.PRelu6Layer` have been deprecated (PR #686)
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- `tl.act.leaky_twice_relu6` and `tl.layers.PTRelu6Layer` have been deprecated (PR #686)
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- CI Tool:
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- [Stale Probot](https://github.com/probot/stale) added to clean stale issues (PR #573)
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- [Changelog Probot](https://github.com/mikz/probot-changelog) Configuration added (PR #637)
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- Travis Builds now handling a matrix of TF Version from TF==1.6.0 to TF==1.8.0 (PR #644)
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- CircleCI added to build and upload Docker Containers for each PR merged and tag release (PR #648)
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- Decorator:
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- `tl.decorators` API created including `deprecated_alias` and `private_method` (PR #660)
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- `tl.decorators` API enriched with `protected_method` (PR #675)
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- `tl.decorators` API enriched with `deprecated` directly raising warning and modifying documentation (PR #691)
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- Docker:
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- Containers for each release and for each PR merged on master built (PR #648)
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- Containers built in the following configurations (PR #648):
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- py2 + cpu
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- py2 + gpu
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- py3 + cpu
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- py3 + gpu
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- Documentation:
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- Clean README.md (PR #677)
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- Release semantic version added on index page (PR #633)
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- Optimizers page added (PR #636)
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- `AMSGrad` added on Optimizers page added (PR #636)
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- Layer:
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- ElementwiseLambdaLayer added to use custom function to connect multiple layer inputs (PR #579)
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- AtrousDeConv2dLayer added (PR #662)
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- Fix bugs of using `tf.layers` in CNN (PR #686)
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- Optimizer:
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- AMSGrad Optimizer added based on `On the Convergence of Adam and Beyond (ICLR 2018)` (PR #636)
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- Setup:
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- Creation of installation flaggs `all`, `all_cpu`, and `all_gpu` (PR #660)
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- Test:
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- `test_utils_predict.py` added to reproduce and fix issue #288 (PR #566)
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- `Layer_DeformableConvolution_Test` added to reproduce issue #572 with deformable convolution (PR #573)
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- `Array_Op_Alphas_Test` and `Array_Op_Alphas_Like_Test` added to test `tensorlayer/array_ops.py` file (PR #580)
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- `test_optimizer_amsgrad.py` added to test `AMSGrad` optimizer (PR #636)
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- `test_logging.py` added to insure robustness of the logging API (PR #645)
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- `test_decorators.py` added (PR #660)
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- `test_activations.py` added (PR #686)
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- Tutorials:
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- `tutorial_tfslim` has been introduced to show how to use `SlimNetsLayer` (PR #560).
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- add the following to all tutorials (PR #697):
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```python
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tf.logging.set_verbosity(tf.logging.DEBUG)
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tl.logging.set_verbosity(tl.logging.DEBUG)
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```
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### Changed
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- Tensorflow CPU & GPU dependencies moved to separated requirement files in order to allow PyUP.io to parse them (PR #573)
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- The document of LambdaLayer for linking it with ElementwiseLambdaLayer (PR #587)
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- RTD links point to stable documentation instead of latest used for development (PR #633)
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- TF Version older than 1.6.0 are officially unsupported and raises an exception (PR #644)
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- README.md Badges Updated with Support Python and Tensorflow Versions (PR #644)
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- TL logging API has been consistent with TF logging API and thread-safe (PR #645)
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- Relative Imports changed for absolute imports (PR #657)
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- `tl.files` refactored into a directory with numerous files (PR #657)
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- `tl.files.voc_dataset` fixed because of original Pascal VOC website was down (PR #657)
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- extra requirements hidden inside the library added in the project requirements (PR #657)
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- requirements files refactored in `requirements/` directory (PR #657)
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- README.md and other markdown files have been refactored and cleaned. (PR #639)
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- Ternary Convolution Layer added in unittest (PR #658)
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- Convolution Layers unittests have been cleaned & refactored (PR #658)
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- All the tests are now using a DEBUG level verbosity when run individualy (PR #660)
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- `tf.identity` as activation is **ignored**, thus reducing the size of the graph by removing useless operation (PR #667)
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- argument dictionaries are now checked and saved within the `Layer` Base Class (PR #667)
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- `Layer` Base Class now presenting methods to update faultlessly `all_layers`, `all_params`, and `all_drop` (PR #675)
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- Input Layers have been removed from `tl.layers.core` and added to `tl.layers.inputs` (PR #675)
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- Input Layers are now considered as true layers in the graph (they represent a placeholder), unittests have been updated (PR #675)
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- Layer API is simplified, with automatic feeding `prev_layer` into `self.inputs` (PR #675)
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- Complete Documentation Refactoring and Reorganization (namely Layer APIs) (PR #691)
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### Deprecated
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- `tl.layers.TimeDistributedLayer` argurment `args` is deprecated in favor of `layer_args` (PR #667)
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- `tl.act.leaky_relu` have been deprecated in favor of `tf.nn.leaky_relu` (PR #686)
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### Removed
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- `assert()` calls remove and replaced by `raise AssertionError()` (PR #667)
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- `tl.identity` is removed, not used anymore and deprecated for a long time (PR #667)
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- All Code specific to `TF.__version__ < "1.6"` have been removed (PR #675)
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### Fixed
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- Issue #498 - Deprecation Warning Fix in `tl.layers.RNNLayer` with `inspect` (PR #574)
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- Issue #498 - Deprecation Warning Fix in `tl.files` with truth value of an empty array is ambiguous (PR #575)
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- Issue #565 related to `tl.utils.predict` fixed - `np.hstack` problem in which the results for multiple batches are stacked along `axis=1` (PR #566)
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- Issue #572 with `tl.layers.DeformableConv2d` fixed (PR #573)
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- Issue #664 with `tl.layers.ConvLSTMLayer` fixed (PR #676)
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- Typo of the document of ElementwiseLambdaLayer (PR #588)
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- Error in `tl.layers.TernaryConv2d` fixed - self.inputs not defined (PR #658)
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- Deprecation warning fixed in `tl.layers.binary._compute_threshold()` (PR #658)
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- All references to `tf.logging` replaced by `tl.logging` (PR #661)
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- Duplicated code removed when bias was used (PR #667)
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- `tensorlayer.third_party.roi_pooling.roi_pooling.roi_pooling_ops` is now lazy loaded to prevent systematic error raised (PR #675)
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- Tutorial:
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- `tutorial_word2vec_basic.py` saving issue #476 fixed (PR #635)
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- All tutorials tested and errors have been fixed (PR #635)
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### Security
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### Dependencies Update
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- Update pytest from 3.5.1 to 3.6.0 (PR #647)
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- Update progressbar2 from 3.37.1 to 3.38.0 (PR #651)
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- Update scikit-image from 0.13.1 to 0.14.0 (PR #656)
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- Update keras from 2.1.6 to 2.2.0 (PR #684)
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- Update requests from 2.18.4 to 2.19.0 (PR #695)
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### Contributors
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- @lgarithm: #563
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- @DEKHTIARJonathan: #573 #574 #575 #580 #633 #635 #636 #639 #644 #645 #648 #657 #667 #658 #659 #660 #661 #666 #667 #672 #675 #683 #686 #687 #690 #691 #692
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- @2wins: #560 #566 #662
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- @One-sixth: #579
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- @zsdonghao: #587 #588 #639 #685 #697
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- @luomai: #639 #677
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- @dengyueyun666: #676
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## [1.8.6] - 2018-06-02
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## [1.9.0] - 2018-06-16
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### Added
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- API:
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- Decorator:
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- `tl.decorators` API created including `deprecated_alias` and `private_method` (PR #660)
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- `tl.decorators` API enriched with `protected_method` (PR #675)
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- `tl.decorators` API enriched with `deprecated` directly raising warning and modifying documentation (PR #691)
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- Docker:
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- Containers for each release and for each PR merged on master built (PR #648)
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- Containers built in the following configurations (PR #648):
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- `test_activations.py` added (PR #686)
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- Tutorials:
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- `tutorial_tfslim` has been introduced to show how to use `SlimNetsLayer` (PR #560).
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- add the following to all tutorials (PR #697):
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```python
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tf.logging.set_verbosity(tf.logging.DEBUG)
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tl.logging.set_verbosity(tl.logging.DEBUG)
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```
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### Changed
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- Tensorflow CPU & GPU dependencies moved to separated requirement files in order to allow PyUP.io to parse them (PR #573)
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- Input Layers have been removed from `tl.layers.core` and added to `tl.layers.inputs` (PR #675)
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- Input Layers are now considered as true layers in the graph (they represent a placeholder), unittests have been updated (PR #675)
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- Layer API is simplified, with automatic feeding `prev_layer` into `self.inputs` (PR #675)
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- Complete Documentation Refactoring and Reorganization (namely Layer APIs) (PR #691)
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### Deprecated
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- `tl.layers.TimeDistributedLayer` argurment `args` is deprecated in favor of `layer_args` (PR #667)
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- All references to `tf.logging` replaced by `tl.logging` (PR #661)
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- Duplicated code removed when bias was used (PR #667)
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- `tensorlayer.third_party.roi_pooling.roi_pooling.roi_pooling_ops` is now lazy loaded to prevent systematic error raised (PR #675)
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- Documentation not build in RTD due to old version of theme in docs directory fixed (PR #703)
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- Tutorial:
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- `tutorial_word2vec_basic.py` saving issue #476 fixed (PR #635)
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- All tutorials tested and errors have been fixed (PR #635)
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### Security
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### Dependencies Update
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- Update pytest from 3.5.1 to 3.6.0 (PR #647)
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- Update progressbar2 from 3.37.1 to 3.38.0 (PR #651)
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- Update requests from 2.18.4 to 2.19.0 (PR #695)
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### Contributors
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- @lgarithm (#563)
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- @DEKHTIARJonathan (#573 #574 #575 #580 #633 #635 #636 #639 #644 #645 #648 #657 #667 #658 #659 #660 #661 #666 #667 #672 #675 #683 #686 #687 #690 #692)
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- @2wins (#560 #566 #662)
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- @One-sixth (#579)
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- @zsdonghao (#587 #588 #639 #685)
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- @luomai (#639 #677)
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- @dengyueyun666 (#676)
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- @lgarithm: #563
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- @DEKHTIARJonathan: #573 #574 #575 #580 #633 #635 #636 #639 #644 #645 #648 #657 #667 #658 #659 #660 #661 #666 #667 #672 #675 #683 #686 #687 #690 #691 #692 #703
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- @2wins: #560 #566 #662
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- @One-sixth: #579
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- @zsdonghao: #587 #588 #639 #685 #697
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- @luomai: #639 #677
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- @dengyueyun666: #676
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## [1.8.5] - 2018-05-09
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### Contributors
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@zsdonghao @luomai @DEKHTIARJonathan
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[Unreleased]: https://github.com/tensorlayer/tensorlayer/compare/1.8.5...master
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[1.8.6]: https://github.com/tensorlayer/tensorlayer/compare/1.8.6rc6...1.8.5
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[1.8.5]: https://github.com/tensorlayer/tensorlayer/compare/1.8.4...1.8.5
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[Unreleased]: https://github.com/tensorlayer/tensorlayer/compare/1.9.0...master
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[1.9.0]: https://github.com/tensorlayer/tensorlayer/compare/1.9.0...1.8.5
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[1.8.5]: https://github.com/tensorlayer/tensorlayer/compare/1.8.4...1.8.5

README.md

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![PyPI Stable Version](http://ec2-35-178-47-120.eu-west-2.compute.amazonaws.com/github/release/tensorlayer/tensorlayer.svg?label=PyPI%20-%20Release)
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![PyPI RC Version](http://ec2-35-178-47-120.eu-west-2.compute.amazonaws.com/github/release/tensorlayer/tensorlayer/all.svg?label=PyPI%20-%20Pre-Release)
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[![Github commits (since latest release)](http://ec2-35-178-47-120.eu-west-2.compute.amazonaws.com/github/commits-since/tensorlayer/tensorlayer/latest.svg)](https://github.com/tensorlayer/tensorlayer/compare/1.8.6rc6...master)
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[![Github commits (since latest release)](http://ec2-35-178-47-120.eu-west-2.compute.amazonaws.com/github/commits-since/tensorlayer/tensorlayer/latest.svg)](https://github.com/tensorlayer/tensorlayer/compare/1.9.0...master)
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[![PyPI - Python Version](http://ec2-35-178-47-120.eu-west-2.compute.amazonaws.com/pypi/pyversions/tensorlayer.svg)](https://pypi.org/project/tensorlayer/)
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[![Supported TF Version](http://ec2-35-178-47-120.eu-west-2.compute.amazonaws.com/badge/tensorflow-1.6.0+-blue.svg)](https://github.com/tensorflow/tensorflow/releases)
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# Why another deep learning library: TensorLayer
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As deep learning practitioners, we have been looking for a library that can address various development
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purposes. This library is easy to adopt by providing diverse examples, tutorials and pre-trained models.
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purposes. This library is easy to adopt by providing diverse examples, tutorials and pre-trained models.
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Also, it allow users to easily fine-tune TensorFlow; while being suitable for production deployment. TensorLayer aims to satisfy all these purposes. It has three key features:
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- ***Simplicity*** : TensorLayer lifts the low-level dataflow interface of TensorFlow to *high-level* layers / models. It is very easy to learn through the rich [example codes](https://github.com/tensorlayer/awesome-tensorlayer) contributed by a wide community.
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TensorLayer stands at a unique spot in the library landscape. Other wrapper libraries like Keras and TFLearn also provide high-level abstractions. They, however, often
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hide the underlying engine from users, which make them hard to customize
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and fine-tune. On the contrary, TensorLayer APIs are generally flexible and transparent.
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hide the underlying engine from users, which make them hard to customize
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and fine-tune. On the contrary, TensorLayer APIs are generally flexible and transparent.
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Users often find it easy to start with the examples and tutorials, and then dive
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into TensorFlow seamlessly. In addition, TensorLayer does not create library lock-in through native supports for importing components from Keras, TFSlim and TFLearn.
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README.rst

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:target: http://www.broadview.com.cn/book/5059/
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.. |Downloads| image:: http://pepy.tech/badge/tensorlayer
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.. |PyPI-Prerelease| image:: http://ec2-35-178-47-120.eu-west-2.compute.amazonaws.com/github/release/tensorlayer/tensorlayer/all.svg?label=PyPI%20-%20Pre-Release
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:target: https://github.com/tensorlayer/tensorlayer/compare/1.9.0...master
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.. |Docker| image:: http://ec2-35-178-47-120.eu-west-2.compute.amazonaws.com/circleci/project/github/tensorlayer/tensorlayer/master.svg?label=Docker%20Build

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