[Archive - Stale] - Documentation Fix to allow unittest to properly run #509

DEKHTIARJonathan · 2018-04-19T12:28:21Z

This PR goes toward many objectives:

Implementing Flake8 coding-style practices
Following PEP8 coding-style practices
Fixing the small errors in the documentation to remove warning from Sphinx.
Adding modules/db to the documentation (if not, it raises an error).

Max Column Length: Changed from 160 to 120 (it was the double of the standard value)

@lgarithm as you pointed out yesterday, we should follow Google coding practices.
It was a good idea, this PR goes in this direction.

…nge are used to prevent updating requirements all the time.

luomai · 2018-04-19T14:19:10Z

@zsdonghao are you happy with changing the max column length to 120?

zsdonghao · 2018-04-19T14:58:04Z

example/tutorial_cifar10.py

-        net = DenseLayer(net, n_units=384, act=tf.nn.relu, W_init=W_init2, b_init=b_init2, name='d1relu')  # output: (batch_size, 384)
-        net = DenseLayer(net, n_units=192, act=tf.nn.relu, W_init=W_init2, b_init=b_init2, name='d2relu')  # output: (batch_size, 192)
-        net = DenseLayer(net, n_units=10, act=tf.identity, W_init=tf.truncated_normal_initializer(stddev=1 / 192.0), name='output')  # output: (batch_size, 10)
+        net = DenseLayer(


need arrange

zsdonghao · 2018-04-19T14:58:12Z

example/tutorial_cifar10.py

+        net = DenseLayer(
+            net, n_units=192, act=tf.nn.relu, W_init=W_init2, b_init=b_init2,
+            name='d2relu')  # output: (batch_size, 192)
+        net = DenseLayer(


need arrange

zsdonghao · 2018-04-19T14:58:17Z

example/tutorial_cifar10.py

-        net = DenseLayer(net, n_units=384, act=tf.nn.relu, W_init=W_init2, b_init=b_init2, name='d1relu')  # output: (batch_size, 384)
-        net = DenseLayer(net, n_units=192, act=tf.nn.relu, W_init=W_init2, b_init=b_init2, name='d2relu')  # output: (batch_size, 192)
-        net = DenseLayer(net, n_units=10, act=tf.identity, W_init=tf.truncated_normal_initializer(stddev=1 / 192.0), name='output')  # output: (batch_size, 10)
+        net = DenseLayer(


need arrange

zsdonghao · 2018-04-19T14:58:29Z

example/tutorial_cifar10.py


 train_params = network.all_params
-train_op = tf.train.AdamOptimizer(learning_rate, beta1=0.9, beta2=0.999, epsilon=1e-08, use_locking=False).minimize(cost, var_list=train_params)
+train_op = tf.train.AdamOptimizer(


need arrange

zsdonghao · 2018-04-19T14:58:39Z

example/tutorial_cifar10_tfrecord.py

-            net = DenseLayer(net, n_units=384, act=tf.nn.relu, W_init=W_init2, b_init=b_init2, name='d1relu')  # output: (batch_size, 384)
-            net = DenseLayer(net, n_units=192, act=tf.nn.relu, W_init=W_init2, b_init=b_init2, name='d2relu')  # output: (batch_size, 192)
-            net = DenseLayer(net, n_units=10, act=tf.identity, W_init=W_init2, name='output')  # output: (batch_size, 10)
+            net = DenseLayer(


need arrange

zsdonghao · 2018-04-19T14:58:45Z

example/tutorial_cifar10_tfrecord.py

-            net = DenseLayer(net, n_units=384, act=tf.nn.relu, W_init=W_init2, b_init=b_init2, name='d1relu')  # output: (batch_size, 384)
-            net = DenseLayer(net, n_units=192, act=tf.nn.relu, W_init=W_init2, b_init=b_init2, name='d2relu')  # output: (batch_size, 192)
-            net = DenseLayer(net, n_units=10, act=tf.identity, W_init=W_init2, name='output')  # output: (batch_size, 10)
+            net = DenseLayer(


need arrange

zsdonghao · 2018-04-19T14:59:00Z

example/tutorial_dorefanet_cifar10_tfrecord.py

-            net = tl.layers.DenseLayer(net, n_units=384, act=tf.nn.relu, W_init=W_init2, b_init=b_init2, name='d1relu')  # output: (batch_size, 384)
-            net = tl.layers.DenseLayer(net, n_units=192, act=tf.nn.relu, W_init=W_init2, b_init=b_init2, name='d2relu')  # output: (batch_size, 192)
-            net = tl.layers.DenseLayer(net, n_units=10, act=tf.identity, W_init=W_init2, name='output')  # output: (batch_size, 10)
+            net = tl.layers.DenseLayer(


need arrange

zsdonghao · 2018-04-19T14:59:10Z

example/tutorial_frozenlake_dqn.py

-predict = tf.argmax(y, 1)  # chose action greedily with reward. in Q-Learning, policy is greedy, so we use "max" to select the next action.
+predict = tf.argmax(
+    y,
+    1)  # chose action greedily with reward. in Q-Learning, policy is greedy, so we use "max" to select the next action.


need arrange

# Conflicts: # tensorlayer/files.py

…nto documentation_cleaning

zsdonghao · 2018-04-20T18:28:40Z

example/tutorial_atari_pong.py

        if reward != 0:
-            print(('episode %d: game %d took %.5fs, reward: %f' % (episode_number, game_number, time.time() - start_time, reward)),
-                  ('' if reward == -1 else ' !!!!!!!!'))
+            print(


need shorten~

zsdonghao · 2018-04-20T18:28:47Z

example/tutorial_binarynet_cifar10_tfrecord.py

                    "label": tf.train.Feature(int64_list=tf.train.Int64List(value=[label])),
                    'img_raw': tf.train.Feature(bytes_list=tf.train.BytesList(value=[img_raw])),
-                }))
+                }


need shorten~

zsdonghao · 2018-04-20T18:28:53Z

example/tutorial_binarynet_cifar10_tfrecord.py

    x_train_batch, y_train_batch = tf.train.shuffle_batch(
-        [x_train_, y_train_], batch_size=batch_size, capacity=2000, min_after_dequeue=1000, num_threads=32)  # set the number of threads here
+        [x_train_, y_train_], batch_size=batch_size, capacity=2000, min_after_dequeue=1000, num_threads=32
+    )  # set the number of threads here


need shorten~

zsdonghao · 2018-04-20T18:29:01Z

example/tutorial_binarynet_cifar10_tfrecord.py

+    )  # set the number of threads here
    # for testing, uses batch instead of shuffle_batch
-    x_test_batch, y_test_batch = tf.train.batch([x_test_, y_test_], batch_size=batch_size, capacity=50000, num_threads=32)
+    x_test_batch, y_test_batch = tf.train.batch(


need shorten~

zsdonghao · 2018-04-20T18:29:11Z

example/tutorial_binarynet_cifar10_tfrecord.py

+            net = tl.layers.LocalResponseNormLayer(
+                net, depth_radius=4, bias=1.0, alpha=0.001 / 9.0, beta=0.75, name='norm1'
+            )
+            net = tl.layers.BinaryConv2d(


need shorten~

DEKHTIARJonathan · 2018-04-20T19:30:28Z

This PR becomes too clumsy. I close it and re-open one

DEKHTIARJonathan added 5 commits April 19, 2018 10:42

Activation Cleaning Docstring Test

864d7cf

Requirements Pinned with range to insure tested versions are used. Ra…

04023ba

…nge are used to prevent updating requirements all the time.

setup.cfg file added with PEP8 configuration

9167833

activation.py refactored

3a4cda7

docstring fixed - ready for documentation unittest

1af0863

DEKHTIARJonathan requested review from lgarithm, luomai and zsdonghao April 19, 2018 12:28

DEKHTIARJonathan and others added 2 commits April 19, 2018 14:46

Merge branch 'master' into requirements_pinning

ea37ed2

Merge branch 'requirements_pinning' into documentation_cleaning

0174a27

DEKHTIARJonathan force-pushed the documentation_cleaning branch from 9048d25 to 0174a27 Compare April 19, 2018 12:50

DEKHTIARJonathan mentioned this pull request Apr 19, 2018

Test documentation #511

Merged

Yapf correction for max_line_length: 120

7ef9e53

tensorlayer deleted a comment Apr 19, 2018

DEKHTIARJonathan force-pushed the documentation_cleaning branch from c16ea57 to aea99c0 Compare April 19, 2018 13:54

tensorlayer deleted a comment Apr 19, 2018

test yapf refactored

dc46dfc

DEKHTIARJonathan force-pushed the documentation_cleaning branch from aea99c0 to dc46dfc Compare April 19, 2018 14:02

Merge branch 'master' into documentation_cleaning

25ecace

tensorlayer deleted a comment Apr 19, 2018

zsdonghao reviewed Apr 19, 2018

View reviewed changes

DEKHTIARJonathan added this to the 1.8.5 milestone Apr 19, 2018

zsdonghao reviewed Apr 19, 2018

View reviewed changes

tl.layers.pooling YAPF reformat

f726da2

tensorlayer deleted a comment Apr 20, 2018

Merge branch 'master' into documentation_cleaning

38f61f2

# Conflicts: # tensorlayer/files.py

tensorlayer deleted a comment Apr 20, 2018

DEKHTIARJonathan changed the title ~~Documentation Fix to allow unittest to properly run~~ [WIP] - Documentation Fix to allow unittest to properly run Apr 20, 2018

DEKHTIARJonathan added 4 commits April 20, 2018 19:13

Merge branch 'master' of https://github.com/tensorlayer/tensorlayer i…

7a6e383

…nto documentation_cleaning

yapf updated

034b3df

gitignore updated

45e4772

YAPF Style Fixing Attempt

e2021f5

zsdonghao reviewed Apr 20, 2018

View reviewed changes

tensorlayer deleted a comment Apr 20, 2018

DEKHTIARJonathan added 2 commits April 20, 2018 20:35

Space Error Fix

4d75516

Style Correction

6092b6c

tensorlayer deleted a comment Apr 20, 2018

Assertion Codacy Errors Corrected

240f0df

tensorlayer deleted a comment Apr 20, 2018

Error Fix

2c97f69

tensorlayer deleted a comment Apr 20, 2018

Assertion Refactored

9966722

tensorlayer deleted a comment Apr 20, 2018

DEKHTIARJonathan closed this Apr 20, 2018

DEKHTIARJonathan changed the title ~~[WIP] - Documentation Fix to allow unittest to properly run~~ [Archive - Stale] - Documentation Fix to allow unittest to properly run Apr 20, 2018

DEKHTIARJonathan mentioned this pull request Apr 20, 2018

[WIP] - Documentation Cleaning and Coding Style #516

Merged

[Archive - Stale] - Documentation Fix to allow unittest to properly run #509

[Archive - Stale] - Documentation Fix to allow unittest to properly run #509

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DEKHTIARJonathan commented Apr 19, 2018 • edited Loading Uh oh! There was an error while loading. Please reload this page.

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DEKHTIARJonathan commented Apr 20, 2018

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DEKHTIARJonathan commented Apr 19, 2018 •

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