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Commit cb4eb89

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Update TensorLayer (#1148)
1 parent 14ca69e commit cb4eb89

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‎.circleci/config.yml‎

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command: |
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echo "start tag workflow"
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###################################################################################
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###################################################################################
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###################################################################################
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# CircleCI WORKFLOWS #
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###################################################################################
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###################################################################################
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###################################################################################
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workflows:
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version: 2

‎.codacy.yaml‎

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---
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engines:
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bandit:
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enabled: false# FIXME: make it works
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enabled: false
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exclude_paths:
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- scripts/*
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- setup.py

‎.dockerignore‎

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# dockerignore
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.git

‎.github/changelog.yml‎

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- requirements_dev.txt
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- requirements_tf_cpu.txt
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- requirements_tf_gpu.txt
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- requirements_doc.txt
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- requirements_test.txt
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# Configuration Files
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- .travis.yml

‎.gitignore‎

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MANIFEST
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*~
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest

‎.pyup.yml‎

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# Requirements for running unittests
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- requirements/requirements_test.txt
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# add a label to pull requests, default is not set
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# requires private repo permissions, even on public repos
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# default: empty
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#label_prs: update
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# configure the branch prefix the bot is using
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# default: pyup-
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branch_prefix: pyup-

‎.readthedocs.yml‎

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# https://docs.readthedocs.io/en/latest/yaml-config.html
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build:
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image: latest# For python 3.6
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image: latest
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formats:
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- epub

‎CONTRIBUTING.md‎

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# An example of a static model
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# A static model has inputs and outputs with fixed shape.
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inputs = tl.layers.Input([32, 784])
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dense1 = tl.layers.Dense(n_units=800, act=tf.nn.relu, in_channels=784, name='dense1')(inputs)
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dense2 = tl.layers.Dense(n_units=10, act=tf.nn.relu, in_channels=800, name='dense2')(dense1)
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dense1 = tl.layers.Dense(n_units=800, act='relu', in_channels=784, name='dense1')(inputs)
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dense2 = tl.layers.Dense(n_units=10, act='relu', in_channels=800, name='dense2')(dense1)
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model = tl.models.Model(inputs=inputs, outputs=dense2)
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# An example of a dynamic model
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# A dynamic model has more flexibility. The inputs and outputs may be different in different runs.
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class CustomizeModel(tl.models.Model):
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def __init__(self):
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super(CustomizeModel, self).__init__()
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self.dense1 = tl.layers.Dense(n_units=800, act=tf.nn.relu, in_channels=784, name='dense1')
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self.dense2 = tl.layers.Dense(n_units=10, act=tf.nn.relu, in_channels=800, name='dense2')
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self.dense1 = tl.layers.Dense(n_units=800, act='relu', in_channels=784, name='dense1')
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self.dense2 = tl.layers.Dense(n_units=10, act='relu', in_channels=800, name='dense2')
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# a dynamic model allows more flexibility by customising forwarding.
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def forward(self, x, bar=None):

‎README.md‎

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<!--- [![PyUP Updates](https://pyup.io/repos/github/tensorlayer/tensorlayer/shield.svg)](https://pyup.io/repos/github/tensorlayer/tensorlayer/) --->
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[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 advanced AI models quickly, based on this, the community open-sourced mass [tutorials](https://github.com/tensorlayer/tensorlayer/blob/master/examples/reinforcement_learning/README.md) and [applications](https://github.com/tensorlayer). TensorLayer is awarded the 2017 Best Open Source Software by the [ACM Multimedia Society](https://twitter.com/ImperialDSI/status/923928895325442049).
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This project can also be found at [iHub](https://code.ihub.org.cn/projects/328) and [Gitee](https://gitee.com/organizations/TensorLayer).
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This project can also be found at [OpenI](https://git.openi.org.cn/TensorLayer/tensorlayer3.0) and [Gitee](https://gitee.com/organizations/TensorLayer).
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# News
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‎README.rst‎

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====
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If you find this project useful, we would be grateful if you cite the
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TensorLayer paper:
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TensorLayer papers.
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::
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year = {2017}
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}
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@inproceedings{tensorlayer2021,
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title={Tensorlayer 3.0: A Deep Learning Library Compatible With Multiple Backends},
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author={Lai, Cheng and Han, Jiarong and Dong, Hao},
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booktitle={2021 IEEE International Conference on Multimedia \& Expo Workshops (ICMEW)},
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pages={1--3},
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year={2021},
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organization={IEEE}
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License
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=======
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