fixed unused code, error prone and code style #352
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raise not implemented error instead of pass
lgarithm
reviewed
Feb 23, 2018
example/tutorial_vgg16.py
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| def conv_layers_simple_api(net_in): | ||
| with tf.name_scope('preprocess') as scope: | ||
| with tf.name_scope('preprocess'): # as scope: |
luomai
requested changes
Feb 23, 2018
example/tutorial_vgg16.py
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| def conv_layers_simple_api(net_in): | ||
| with tf.name_scope('preprocess') as scope: | ||
| with tf.name_scope('preprocess'): # as scope: |
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remove this comment as users may compensate as a description.
tensorlayer/layers/core.py
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| logging.info("EmbeddingInputlayer %s: (%d, %d)" % (self.name, vocabulary_size, embedding_size)) | ||
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| with tf.variable_scope(name) as vs: | ||
| with tf.variable_scope(name): # as vs: |
tensorlayer/layers/extend.py
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| logging.info("TileLayer %s: multiples:%s" % (self.name, multiples)) | ||
| with tf.variable_scope(name) as vs: | ||
| with tf.variable_scope(name): # as vs: |
tensorlayer/layers/merge.py
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| for l in layers[1:]: | ||
| assert str(self.outputs.get_shape()) == str( | ||
| l.outputs.get_shape()), "Hint: the input shapes should be the same. %s != %s" % (self.outputs.get_shape(), str(l.outputs.get_shape())) | ||
| # assert str(self.outputs.get_shape()) == str( |
tensorlayer/layers/recurrent.py
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| outputs = tf.concat(2, outputs) | ||
| if return_last: | ||
| # [batch_size, 2 * n_hidden] | ||
| raise Exception("Do not support return_last at the moment") |
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shall we actually remove this parameter from the interface?
tensorlayer/layers/stack.py
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| """ | ||
| inputs = layer.outputs | ||
| with tf.variable_scope(name) as vs: | ||
| with tf.variable_scope(name): # as vs: |
| net_new = Layer(inputs, name=whole_name) | ||
| # with tf.name_scope(name): | ||
| with tf.variable_scope(name) as vs: | ||
| with tf.variable_scope(name): # as vs: |
tensorlayer/prepro.py
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| for i in range(len(annotations)): | ||
| class_list.append(annotations[i][0]) | ||
| bbox_list.append(annotations[i][1:]) | ||
| # for i in range(len(annotations)): |
tensorlayer/utils.py
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| elif _platform == "win32": | ||
| logging.info(text2 + "Windows") | ||
| # TODO | ||
| raise NotImplementedError() |
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better to add a string telling "this function is not supported on the Windows platform"
tensorlayer/utils.py
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| elif _platform == "win32": | ||
| logging.info('Windows%s' % text2) | ||
| # TODO | ||
| raise NotImplementedError() |
luomai
requested changes
Feb 23, 2018
tensorlayer/layers/core.py
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| """ | ||
| y = [] | ||
| [y.append(i) for i in x if not i in y] | ||
| # [y.append(i) for i in x if not i in y] |
zsdonghao
changed the title
luomai
requested changes
Feb 23, 2018
tensorlayer/layers/recurrent.py
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| output_keep_prob=out_keep_prob if is_last else 1.0) # out_keep_prob) | ||
| else: | ||
| cell_creator = lambda: rnn_creator() | ||
| # cell_creator = lambda: rnn_creator() |
tensorlayer/nlp.py
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| # assert batch_size % num_skips == 0 | ||
| if batch_size % num_skips != 0: | ||
| raise Exception("batch_size should be able to be divided by num_skips.") | ||
| # assert num_skips <= 2 * skip_window |
tensorlayer/nlp.py
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| assert batch_size % num_skips == 0 | ||
| assert num_skips <= 2 * skip_window | ||
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| # assert batch_size % num_skips == 0 |
tensorlayer/nlp.py
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| logging.info('Limited vocabulary size {}'.format(vocabulary_size)) | ||
| assert len(collections.Counter(words).keys()) >= vocabulary_size, \ | ||
| "the limited vocabulary_size must be less than or equal to the read vocabulary_size" | ||
| # assert len(collections.Counter(words).keys()) >= vocabulary_size, \ |
luomai
approved these changes
Feb 23, 2018
luomai
pushed a commit
that referenced
this pull request
Nov 21, 2018
* raise not implemented error instead of pass * fix unused code * fix pylint issues. * fixed some assert error * fixed unused code * fixed all error prone * fixed most of the code style * yapf * yapf tests * fixed suggestion * yapf * remove unused code * remove unused code * fix
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