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itsmeoliviatensorflower-gardener
itsmeolivia
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tensorflower-gardener
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removing deprecated functions
conv2d dropout and removing moving_average_decay Change: 133718900
1 parent 601b62a commit fe5af7b

8 files changed

Lines changed: 4 additions & 229 deletions

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‎tensorflow/contrib/learn/BUILD‎

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@@ -610,18 +610,6 @@ py_test(
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],
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)
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py_test(
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name = "dropout_ops_test",
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size = "small",
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srcs = ["python/learn/ops/tests/dropout_ops_test.py"],
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srcs_version = "PY2AND3",
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deps = [
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":learn",
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"//tensorflow:tensorflow_py",
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"//tensorflow/python:framework_test_lib",
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],
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)
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py_test(
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name = "seq2seq_ops_test",
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size = "small",

‎tensorflow/contrib/learn/python/learn/ops/__init__.py‎

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@@ -22,9 +22,7 @@
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# pylint: disable=wildcard-import
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from tensorflow.contrib.learn.python.learn.ops.array_ops import *
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from tensorflow.contrib.learn.python.learn.ops.autoencoder_ops import *
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from tensorflow.contrib.learn.python.learn.ops.conv_ops import *
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from tensorflow.contrib.learn.python.learn.ops.dnn_ops import *
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from tensorflow.contrib.learn.python.learn.ops.dropout_ops import *
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from tensorflow.contrib.learn.python.learn.ops.embeddings_ops import *
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from tensorflow.contrib.learn.python.learn.ops.losses_ops import *
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from tensorflow.contrib.learn.python.learn.ops.seq2seq_ops import *

‎tensorflow/contrib/learn/python/learn/ops/conv_ops.py‎

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‎tensorflow/contrib/learn/python/learn/ops/dnn_ops.py‎

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@@ -21,7 +21,6 @@
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from tensorflow.contrib import layers
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from tensorflow.contrib.framework.python.framework.deprecation import deprecated
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from tensorflow.contrib.learn.python.learn.ops import dropout_ops
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from tensorflow.python.framework import ops
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from tensorflow.python.platform import tf_logging as logging

‎tensorflow/contrib/learn/python/learn/ops/dropout_ops.py‎

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‎tensorflow/contrib/learn/python/learn/ops/tests/dropout_ops_test.py‎

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‎tensorflow/contrib/learn/python/learn/ops/tests/ops_test.py‎

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@@ -21,6 +21,7 @@
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import numpy as np
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import tensorflow as tf
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from tensorflow.contrib.layers import conv2d
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from tensorflow.contrib.learn.python.learn import ops
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@@ -70,23 +71,6 @@ def test_categorical_variable(self):
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self.assertEqual(emb1.shape, emb2.shape)
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self.assertAllEqual(np.transpose(emb2, axes=[1, 0, 2]), emb1)
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def test_conv2d(self):
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tf.set_random_seed(42)
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batch_size = 32
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input_shape = (10, 10)
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n_filters = 7
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filter_shape = (5, 5)
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vals = np.random.randn(batch_size, input_shape[0], input_shape[1], 1)
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with self.test_session() as sess:
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tf.add_to_collection("IS_TRAINING", True)
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tensor_in = tf.placeholder(tf.float32, [batch_size, input_shape[0],
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input_shape[1], 1])
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res = ops.conv2d(tensor_in, n_filters, filter_shape, batch_norm=True)
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sess.run(tf.initialize_all_variables())
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conv = sess.run(res, feed_dict={tensor_in.name: vals})
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self.assertEqual(conv.shape, (batch_size, input_shape[0], input_shape[1],
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n_filters))
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def test_one_hot_matrix(self):
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with self.test_session() as sess:
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tensor_in = tf.placeholder(tf.int64, [10, 2])

‎tensorflow/examples/skflow/text_classification_character_cnn.py‎

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import tensorflow as tf
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from tensorflow.contrib import learn
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from tensorflow.contrib.layers import conv2d
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FLAGS = tf.app.flags.FLAGS
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tf.app.flags.DEFINE_bool('test_with_fake_data', False,
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[-1, MAX_DOCUMENT_LENGTH, 256, 1])
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with tf.variable_scope('CNN_Layer1'):
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# Apply Convolution filtering on input sequence.
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conv1 = learn.ops.conv2d(byte_list, N_FILTERS,
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FILTER_SHAPE1, padding='VALID')
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conv1 = conv2d(byte_list, N_FILTERS, FILTER_SHAPE1, padding='VALID')
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# Add a RELU for non linearity.
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conv1 = tf.nn.relu(conv1)
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# Max pooling across output of Convolution+Relu.
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pool1 = tf.transpose(pool1, [0, 1, 3, 2])
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with tf.variable_scope('CNN_Layer2'):
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# Second level of convolution filtering.
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conv2 = learn.ops.conv2d(pool1, N_FILTERS, FILTER_SHAPE2,
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padding='VALID')
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conv2 = conv2d(pool1, N_FILTERS, FILTER_SHAPE2, padding='VALID')
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# Max across each filter to get useful features for classification.
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pool2 = tf.squeeze(tf.reduce_max(conv2, 1), squeeze_dims=[1])
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