diff options
44 files changed, 1904 insertions, 1194 deletions
diff --git a/tensorflow/contrib/layers/python/layers/layers.py b/tensorflow/contrib/layers/python/layers/layers.py index de3d8cefaa..2673495b90 100644 --- a/tensorflow/contrib/layers/python/layers/layers.py +++ b/tensorflow/contrib/layers/python/layers/layers.py @@ -177,7 +177,8 @@ def _fused_batch_norm( Lower `decay` value (recommend trying `decay`=0.9) if model experiences reasonably good training performance but poor validation and/or test performance. - center: If True, subtract `beta`. If False, `beta` is ignored. + center: If True, add offset of `beta` to normalized tensor. If False, + `beta` is ignored. scale: If True, multiply by `gamma`. If False, `gamma` is not used. When the next layer is linear (also e.g. `nn.relu`), this can be disabled since the scaling can be done by the next layer. @@ -408,7 +409,8 @@ def batch_norm( Lower `decay` value (recommend trying `decay`=0.9) if model experiences reasonably good training performance but poor validation and/or test performance. Try zero_debias_moving_mean=True for improved stability. - center: If True, subtract `beta`. If False, `beta` is ignored. + center: If True, add offset of `beta` to normalized tensor. If False, `beta` + is ignored. scale: If True, multiply by `gamma`. If False, `gamma` is not used. When the next layer is linear (also e.g. `nn.relu`), this can be disabled since the scaling can be done by the next layer. @@ -1444,7 +1446,8 @@ def layer_norm(inputs, Args: inputs: a tensor with 2 or more dimensions. The normalization occurs over all but the first dimension. - center: If True, subtract `beta`. If False, `beta` is ignored. + center: If True, add offset of `beta` to normalized tensor. If False, `beta` + is ignored. scale: If True, multiply by `gamma`. If False, `gamma` is not used. When the next layer is linear (also e.g. `nn.relu`), this can be disabled since the scaling can be done by the next layer. diff --git a/tensorflow/contrib/learn/python/learn/estimators/composable_model.py b/tensorflow/contrib/learn/python/learn/estimators/composable_model.py index 74c2c18127..a02c726c74 100644 --- a/tensorflow/contrib/learn/python/learn/estimators/composable_model.py +++ b/tensorflow/contrib/learn/python/learn/estimators/composable_model.py @@ -334,8 +334,8 @@ class DNNComposableModel(_ComposableModel): def _add_hidden_layer_summary(self, value, tag): # TODO(zakaria): Move this code to tf.learn and add test. - summary.scalar("%s:fraction_of_zero_values" % tag, nn.zero_fraction(value)) - summary.histogram("%s:activation" % tag, value) + summary.scalar("%s/fraction_of_zero_values" % tag, nn.zero_fraction(value)) + summary.histogram("%s/activation" % tag, value) def build_model(self, features, feature_columns, is_training): """See base class.""" diff --git a/tensorflow/contrib/learn/python/learn/estimators/dnn_linear_combined.py b/tensorflow/contrib/learn/python/learn/estimators/dnn_linear_combined.py index 9d84d5c3b3..85ab452ee2 100644 --- a/tensorflow/contrib/learn/python/learn/estimators/dnn_linear_combined.py +++ b/tensorflow/contrib/learn/python/learn/estimators/dnn_linear_combined.py @@ -87,9 +87,9 @@ def _linear_learning_rate(num_linear_feature_columns): def _add_hidden_layer_summary(value, tag): - logging_ops.scalar_summary("%s:fraction_of_zero_values" % tag, + logging_ops.scalar_summary("%s/fraction_of_zero_values" % tag, nn.zero_fraction(value)) - logging_ops.histogram_summary("%s:activation" % tag, value) + logging_ops.histogram_summary("%s/activation" % tag, value) def _get_embedding_variable(column, collection_key, input_layer_scope): diff --git a/tensorflow/contrib/learn/python/learn/ops/__init__.py b/tensorflow/contrib/learn/python/learn/ops/__init__.py index 173c894721..33962e34cc 100644 --- a/tensorflow/contrib/learn/python/learn/ops/__init__.py +++ b/tensorflow/contrib/learn/python/learn/ops/__init__.py @@ -20,7 +20,6 @@ from __future__ import division from __future__ import print_function # pylint: disable=wildcard-import -from tensorflow.contrib.learn.python.learn.ops.array_ops import * from tensorflow.contrib.learn.python.learn.ops.embeddings_ops import * from tensorflow.contrib.learn.python.learn.ops.losses_ops import * from tensorflow.contrib.learn.python.learn.ops.seq2seq_ops import * diff --git a/tensorflow/contrib/learn/python/learn/ops/array_ops.py b/tensorflow/contrib/learn/python/learn/ops/array_ops.py deleted file mode 100644 index 9196a9b9ad..0000000000 --- a/tensorflow/contrib/learn/python/learn/ops/array_ops.py +++ /dev/null @@ -1,52 +0,0 @@ -# Copyright 2016 The TensorFlow Authors. All Rights Reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# ============================================================================== - -"""TensorFlow ops for array / tensor manipulation.""" - -from __future__ import absolute_import -from __future__ import division -from __future__ import print_function - -from tensorflow.contrib.framework import deprecated -from tensorflow.python.framework import dtypes -from tensorflow.python.framework import ops -from tensorflow.python.ops import array_ops as array_ops_ -from tensorflow.python.ops import math_ops - - -@deprecated('2016-12-01', 'Use `tf.one_hot` instead.') -def one_hot_matrix(tensor_in, num_classes, on_value=1.0, off_value=0.0, - name=None): - """Encodes indices from given tensor as one-hot tensor. - - TODO(ilblackdragon): Ideally implementation should be - part of TensorFlow with Eigen-native operation. - - Args: - tensor_in: Input `Tensor` of shape [N1, N2]. - num_classes: Number of classes to expand index into. - on_value: `Tensor` or float, value to fill-in given index. - off_value: `Tensor` or float, value to fill-in everything else. - name: Name of the op. - Returns: - `Tensor` of shape `[N1, N2, num_classes]` with 1.0 for each id in original - tensor. - """ - with ops.name_scope( - name, 'one_hot_matrix', - [tensor_in, num_classes, on_value, off_value]) as name_scope: - return array_ops_.one_hot( - math_ops.cast(tensor_in, dtypes.int64), num_classes, on_value, - off_value, name=name_scope) diff --git a/tensorflow/contrib/learn/python/learn/ops/ops_test.py b/tensorflow/contrib/learn/python/learn/ops/ops_test.py index 7ed2ead07e..dd145b9900 100644 --- a/tensorflow/contrib/learn/python/learn/ops/ops_test.py +++ b/tensorflow/contrib/learn/python/learn/ops/ops_test.py @@ -32,8 +32,8 @@ from tensorflow.contrib.learn.python.learn import ops from tensorflow.python.framework import constant_op from tensorflow.python.framework import dtypes from tensorflow.python.framework import random_seed -from tensorflow.python.ops import array_ops from tensorflow.python.ops import variables +from tensorflow.python.ops import array_ops from tensorflow.python.platform import test @@ -80,15 +80,6 @@ class OpsTest(test.TestCase): self.assertEqual(emb1.shape, emb2.shape) self.assertAllEqual(np.transpose(emb2, axes=[1, 0, 2]), emb1) - def test_one_hot_matrix(self): - with self.test_session() as sess: - tensor_in = array_ops.placeholder(dtypes.int64, [10, 2]) - one_hot_tensor = ops.one_hot_matrix(tensor_in, 3) - res = sess.run(ops.one_hot_matrix([[0, 1], [2, 1]], 3)) - self.assertAllEqual(one_hot_tensor.get_shape(), [10, 2, 3]) - self.assertAllEqual(res, [[[1.0, 0, 0], [0, 1.0, 0]], - [[0, 0, 1.0], [0, 1.0, 0]]]) - if __name__ == "__main__": test.main() diff --git a/tensorflow/contrib/learn/python/learn/ops/seq2seq_ops.py b/tensorflow/contrib/learn/python/learn/ops/seq2seq_ops.py index 356bfda30e..0faba7cee5 100644 --- a/tensorflow/contrib/learn/python/learn/ops/seq2seq_ops.py +++ b/tensorflow/contrib/learn/python/learn/ops/seq2seq_ops.py @@ -20,10 +20,9 @@ from __future__ import division from __future__ import print_function from tensorflow.contrib import rnn -from tensorflow.contrib.learn.python.learn.ops import array_ops from tensorflow.python.framework import dtypes from tensorflow.python.framework import ops -from tensorflow.python.ops import array_ops as array_ops_ +from tensorflow.python.ops import array_ops from tensorflow.python.ops import math_ops from tensorflow.python.ops import nn from tensorflow.python.ops import variable_scope as vs @@ -55,7 +54,7 @@ def sequence_classifier(decoding, labels, sampling_decoding=None, name=None): predictions.append(nn.softmax(pred)) xent = math_ops.add_n(xent_list, name="sequence_loss/xent") loss = math_ops.reduce_sum(xent, name="sequence_loss") - return array_ops_.stack(predictions, axis=1), loss + return array_ops.stack(predictions, axis=1), loss def seq2seq_inputs(x, y, input_length, output_length, sentinel=None, name=None): @@ -75,13 +74,13 @@ def seq2seq_inputs(x, y, input_length, output_length, sentinel=None, name=None): Encoder input from x, and decoder inputs and outputs from y. """ with ops.name_scope(name, "seq2seq_inputs", [x, y]): - in_x = array_ops_.unstack(x, axis=1) - y = array_ops_.unstack(y, axis=1) + in_x = array_ops.unstack(x, axis=1) + y = array_ops.unstack(y, axis=1) if not sentinel: # Set to zeros of shape of y[0], using x for batch size. - sentinel_shape = array_ops_.stack( - [array_ops_.shape(x)[0], y[0].get_shape()[1]]) - sentinel = array_ops_.zeros(sentinel_shape) + sentinel_shape = array_ops.stack( + [array_ops.shape(x)[0], y[0].get_shape()[1]]) + sentinel = array_ops.zeros(sentinel_shape) sentinel.set_shape(y[0].get_shape()) in_y = [sentinel] + y out_y = y + [sentinel] diff --git a/tensorflow/core/BUILD b/tensorflow/core/BUILD index 324183c053..d3ffd692b2 100644 --- a/tensorflow/core/BUILD +++ b/tensorflow/core/BUILD @@ -262,6 +262,7 @@ cc_library( "platform/subprocess.h", "platform/thread_annotations.h", "platform/types.h", + "platform/windows/cpu_info.h", ], visibility = ["//visibility:public"], deps = [ diff --git a/tensorflow/core/framework/bfloat16.cc b/tensorflow/core/framework/bfloat16.cc index 33ac0c3cd9..a5ac0e1a8d 100644 --- a/tensorflow/core/framework/bfloat16.cc +++ b/tensorflow/core/framework/bfloat16.cc @@ -20,18 +20,31 @@ namespace tensorflow { void FloatToBFloat16(const float* src, bfloat16* dst, int64 size) { const uint16_t* p = reinterpret_cast<const uint16_t*>(src); uint16_t* q = reinterpret_cast<uint16_t*>(dst); - for (; size; p += 2, q++, size--) { - *q = p[1]; - } +#if __BYTE_ORDER__ == __ORDER_BIG_ENDIAN__ + for (; size != 0; p += 2, q++, size--) { + *q = p[0]; + } +#else + for (; size != 0; p += 2, q++, size--) { + *q = p[1]; + } +#endif } void BFloat16ToFloat(const bfloat16* src, float* dst, int64 size) { const uint16_t* p = reinterpret_cast<const uint16_t*>(src); uint16_t* q = reinterpret_cast<uint16_t*>(dst); - for (; size; p++, q += 2, size--) { - q[0] = 0; - q[1] = *p; - } +#if __BYTE_ORDER__ == __ORDER_BIG_ENDIAN__ + for (; size != 0; p++, q += 2, size--) { + q[0] = *p; + q[1] = 0; + } +#else + for (; size != 0; p++, q += 2, size--) { + q[0] = 0; + q[1] = *p; + } +#endif } } // end namespace tensorflow diff --git a/tensorflow/core/framework/bfloat16.h b/tensorflow/core/framework/bfloat16.h index 90497994c9..b936e899d4 100644 --- a/tensorflow/core/framework/bfloat16.h +++ b/tensorflow/core/framework/bfloat16.h @@ -19,6 +19,10 @@ limitations under the License. #include "tensorflow/core/framework/numeric_types.h" #include "tensorflow/core/platform/types.h" +#if defined(PLATFORM_WINDOWS) +#include "tensorflow/core/platform/windows/cpu_info.h" +#endif + // Compact 16-bit encoding of floating point numbers. This representation uses // 1 bit for the sign, 8 bits for the exponent and 7 bits for the mantissa. It // is assumed that floats are in IEEE 754 format so the representation is just diff --git a/tensorflow/core/kernels/cast_op.h b/tensorflow/core/kernels/cast_op.h index 7bd08cfda6..0def600ac0 100644 --- a/tensorflow/core/kernels/cast_op.h +++ b/tensorflow/core/kernels/cast_op.h @@ -96,11 +96,16 @@ struct scalar_cast_op<::tensorflow::bfloat16, float> { typedef float result_type; EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE float operator()( const ::tensorflow::bfloat16& a) const { - static_assert(::tensorflow::port::kLittleEndian, ""); float ret; uint16_t* p = reinterpret_cast<uint16_t*>(&ret); +#if __BYTE_ORDER__ == __ORDER_BIG_ENDIAN__ + p[0] = a.value; + p[1] = 0; +#else + static_assert(::tensorflow::port::kLittleEndian, "Not a little endian system!"); p[0] = 0; p[1] = a.value; +#endif return ret; } }; @@ -116,9 +121,14 @@ struct scalar_cast_op<float, ::tensorflow::bfloat16> { typedef ::tensorflow::bfloat16 result_type; EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const ::tensorflow::bfloat16 operator()( const float a) const { - static_assert(::tensorflow::port::kLittleEndian, ""); +#if __BYTE_ORDER__ == __ORDER_BIG_ENDIAN__ + const uint16_t* p = reinterpret_cast<const uint16_t*>(&a); + return ::tensorflow::bfloat16(p[0]); +#else + static_assert(::tensorflow::port::kLittleEndian, "Not a little endian system!"); const uint16_t* p = reinterpret_cast<const uint16_t*>(&a); return ::tensorflow::bfloat16(p[1]); +#endif } }; diff --git a/tensorflow/core/kernels/sparse_matmul_op.cc b/tensorflow/core/kernels/sparse_matmul_op.cc index 9545839184..31cca59f50 100644 --- a/tensorflow/core/kernels/sparse_matmul_op.cc +++ b/tensorflow/core/kernels/sparse_matmul_op.cc @@ -258,7 +258,11 @@ static const int kNumOperands = (sizeof(Packet) / sizeof(float)); ALWAYS_INLINE float ConvertBfloat16ToFloat(const bfloat16* src) { float out = 0; auto tmp = reinterpret_cast<bfloat16*>(&out); - tmp[1] = *src; +#if __BYTE_ORDER__ == __ORDER_BIG_ENDIAN__ + tmp[0] = *src; +#else + tmp[1] = *src; +#endif return out; } diff --git a/tensorflow/core/kernels/sparse_matmul_op.h b/tensorflow/core/kernels/sparse_matmul_op.h index 170d4ec18b..61bd6593c3 100644 --- a/tensorflow/core/kernels/sparse_matmul_op.h +++ b/tensorflow/core/kernels/sparse_matmul_op.h @@ -20,6 +20,7 @@ limitations under the License. #include "tensorflow/core/platform/types.h" #if defined(PLATFORM_WINDOWS) +#include "tensorflow/core/platform/windows/cpu_info.h" #include "tensorflow/core/platform/windows/intrinsics_port.h" #endif @@ -30,8 +31,12 @@ namespace internal { // in the lower 16-bits of input template <typename Packet> EIGEN_DEVICE_FUNC inline Packet pexpand_bf16_l(const Packet& from) { - tensorflow::uint32 tmp = - (reinterpret_cast<const tensorflow::uint32&>(from) << 16) & 0xffff0000; + tensorflow::uint32 tmp; +#if __BYTE_ORDER__ == __ORDER_BIG_ENDIAN__ + tmp = (reinterpret_cast<const tensorflow::uint32&>(from) ) & 0xffff0000; +#else + tmp = (reinterpret_cast<const tensorflow::uint32&>(from) << 16) & 0xffff0000; +#endif return reinterpret_cast<const float&>(tmp); } @@ -39,8 +44,12 @@ EIGEN_DEVICE_FUNC inline Packet pexpand_bf16_l(const Packet& from) { // in the upper 16-bits of input template <typename Packet> EIGEN_DEVICE_FUNC inline Packet pexpand_bf16_u(const Packet& from) { - tensorflow::uint32 tmp = - (reinterpret_cast<const tensorflow::uint32&>(from)) & 0xffff0000; + tensorflow::uint32 tmp; +#if __BYTE_ORDER__ == __ORDER_BIG_ENDIAN__ + tmp = (reinterpret_cast<const tensorflow::uint32&>(from) << 16 ) & 0xffff0000; +#else + tmp = (reinterpret_cast<const tensorflow::uint32&>(from)) & 0xffff0000; +#endif return reinterpret_cast<const float&>(tmp); } diff --git a/tensorflow/core/kernels/sparse_matmul_op_test.cc b/tensorflow/core/kernels/sparse_matmul_op_test.cc index 1c1035fdcb..42fdde23dd 100644 --- a/tensorflow/core/kernels/sparse_matmul_op_test.cc +++ b/tensorflow/core/kernels/sparse_matmul_op_test.cc @@ -207,8 +207,13 @@ class SparseMatmulOpTest : public ::testing::Test { uint16_t* data3_p = reinterpret_cast<uint16_t*>(&data3[i]); uint16_t* data3_bfloat16_p = reinterpret_cast<uint16_t*>(data3_bfloat16) + i; - data3_p[0] = 0; - data3_bfloat16_p[0] = data3_p[1]; +#if __BYTE_ORDER__ == __ORDER_BIG_ENDIAN__ + data3_p[1] = 0; + data3_bfloat16_p[0] = data3_p[0]; +#else + data3_p[0] = 0; + data3_bfloat16_p[0] = data3_p[1]; +#endif } } diff --git a/tensorflow/core/kernels/sparse_split_op.cc b/tensorflow/core/kernels/sparse_split_op.cc index 2ea986cf7d..9f8ed5ab18 100644 --- a/tensorflow/core/kernels/sparse_split_op.cc +++ b/tensorflow/core/kernels/sparse_split_op.cc @@ -30,7 +30,7 @@ class SparseSplitOp : public OpKernel { } void Compute(OpKernelContext* context) override { - const int32 split_dim = context->input(0).scalar<int>()(); + const int64 split_dim = context->input(0).scalar<int64>()(); const Tensor& input_indices = context->input(1); const Tensor& input_values = context->input(2); const Tensor& input_shape = context->input(3); diff --git a/tensorflow/core/platform/cpu_info.h b/tensorflow/core/platform/cpu_info.h index 5fa58e3759..f6eee478e8 100644 --- a/tensorflow/core/platform/cpu_info.h +++ b/tensorflow/core/platform/cpu_info.h @@ -24,7 +24,7 @@ namespace tensorflow { namespace port { // TODO(jeff,sanjay): Make portable -static const bool kLittleEndian = true; +constexpr bool kLittleEndian = __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__; // Returns an estimate of the number of schedulable CPUs for this // process. Usually, it's constant throughout the lifetime of a diff --git a/tensorflow/examples/android/src/org/tensorflow/demo/ClassifierActivity.java b/tensorflow/examples/android/src/org/tensorflow/demo/ClassifierActivity.java index 263751f03f..387bd3f8fa 100644 --- a/tensorflow/examples/android/src/org/tensorflow/demo/ClassifierActivity.java +++ b/tensorflow/examples/android/src/org/tensorflow/demo/ClassifierActivity.java @@ -48,6 +48,16 @@ public class ClassifierActivity extends CameraActivity implements OnImageAvailab // INPUT_NAME = "Mul:0", and OUTPUT_NAME = "final_result:0". // You'll also need to update the MODEL_FILE and LABEL_FILE paths to point to // the ones you produced. + // + // To use v3 Inception model, strip the DecodeJpeg Op from your retrained + // model first: + // + // python strip_unused.py \ + // --input_graph=<retrained-pb-file> \ + // --output_graph=<your-stripped-pb-file> \ + // --input_node_names="Mul" \ + // --output_node_names="final_result" \ + // --input_binary=true private static final int NUM_CLASSES = 1001; private static final int INPUT_SIZE = 224; private static final int IMAGE_MEAN = 117; diff --git a/tensorflow/examples/tutorials/mnist/mnist_softmax_xla.py b/tensorflow/examples/tutorials/mnist/mnist_softmax_xla.py index ce11b93600..bf3f2fb015 100644 --- a/tensorflow/examples/tutorials/mnist/mnist_softmax_xla.py +++ b/tensorflow/examples/tutorials/mnist/mnist_softmax_xla.py @@ -52,7 +52,8 @@ def main(_): # # So here we use tf.nn.softmax_cross_entropy_with_logits on the raw # outputs of 'y', and then average across the batch. - cross_entropy = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(y, y_)) + cross_entropy = tf.reduce_mean( + tf.nn.softmax_cross_entropy_with_logits(labels=y_, logits=y)) train_step = tf.train.GradientDescentOptimizer(0.5).minimize(cross_entropy) config = tf.ConfigProto() diff --git a/tensorflow/g3doc/api_docs/python/array_ops.md b/tensorflow/g3doc/api_docs/python/array_ops.md index 2dcf6bcca6..a6d950dc6e 100644 --- a/tensorflow/g3doc/api_docs/python/array_ops.md +++ b/tensorflow/g3doc/api_docs/python/array_ops.md @@ -2044,7 +2044,7 @@ The attr `block_size` indicates the input block size and how the data is moved. * Chunks of data of size `block_size * block_size` from depth are rearranged into non-overlapping blocks of size `block_size x block_size` - * The width the output tensor is `input_depth * block_size`, whereas the + * The width the output tensor is `input_width * block_size`, whereas the height is `input_height * block_size`. * The depth of the input tensor must be divisible by `block_size * block_size`. diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.depth_to_space.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.depth_to_space.md index 03dc6bb3b0..ef74b4d54a 100644 --- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.depth_to_space.md +++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.depth_to_space.md @@ -10,7 +10,7 @@ The attr `block_size` indicates the input block size and how the data is moved. * Chunks of data of size `block_size * block_size` from depth are rearranged into non-overlapping blocks of size `block_size x block_size` - * The width the output tensor is `input_depth * block_size`, whereas the + * The width the output tensor is `input_width * block_size`, whereas the height is `input_height * block_size`. * The depth of the input tensor must be divisible by `block_size * block_size`. diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.summary.TaggedRunMetadata.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.summary.TaggedRunMetadata.md index 788d2066ad..8dc62c4c18 100644 --- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.summary.TaggedRunMetadata.md +++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.summary.TaggedRunMetadata.md @@ -1,8 +1,252 @@ - - - +#### `tf.summary.TaggedRunMetadata.ByteSize()` {#TaggedRunMetadata.ByteSize} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.Clear()` {#TaggedRunMetadata.Clear} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.ClearExtension(extension_handle)` {#TaggedRunMetadata.ClearExtension} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.ClearField(field_name)` {#TaggedRunMetadata.ClearField} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.CopyFrom(other_msg)` {#TaggedRunMetadata.CopyFrom} + +Copies the content of the specified message into the current message. + +The method clears the current message and then merges the specified +message using MergeFrom. + +##### Args: + + +* <b>`other_msg`</b>: Message to copy into the current one. + + +- - - + +#### `tf.summary.TaggedRunMetadata.DiscardUnknownFields()` {#TaggedRunMetadata.DiscardUnknownFields} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.FindInitializationErrors()` {#TaggedRunMetadata.FindInitializationErrors} + +Finds required fields which are not initialized. + +##### Returns: + + A list of strings. Each string is a path to an uninitialized field from + the top-level message, e.g. "foo.bar[5].baz". + + +- - - + +#### `tf.summary.TaggedRunMetadata.FromString(s)` {#TaggedRunMetadata.FromString} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.HasExtension(extension_handle)` {#TaggedRunMetadata.HasExtension} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.HasField(field_name)` {#TaggedRunMetadata.HasField} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.IsInitialized(errors=None)` {#TaggedRunMetadata.IsInitialized} + +Checks if all required fields of a message are set. + +##### Args: + + +* <b>`errors`</b>: A list which, if provided, will be populated with the field + paths of all missing required fields. + +##### Returns: + + True iff the specified message has all required fields set. + + +- - - + +#### `tf.summary.TaggedRunMetadata.ListFields()` {#TaggedRunMetadata.ListFields} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.MergeFrom(msg)` {#TaggedRunMetadata.MergeFrom} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.MergeFromString(serialized)` {#TaggedRunMetadata.MergeFromString} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.ParseFromString(serialized)` {#TaggedRunMetadata.ParseFromString} + +Parse serialized protocol buffer data into this message. + +Like MergeFromString(), except we clear the object first and +do not return the value that MergeFromString returns. + + +- - - + +#### `tf.summary.TaggedRunMetadata.RegisterExtension(extension_handle)` {#TaggedRunMetadata.RegisterExtension} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.SerializePartialToString()` {#TaggedRunMetadata.SerializePartialToString} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.SerializeToString()` {#TaggedRunMetadata.SerializeToString} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.SetInParent()` {#TaggedRunMetadata.SetInParent} + +Sets the _cached_byte_size_dirty bit to true, +and propagates this to our listener iff this was a state change. + + +- - - + +#### `tf.summary.TaggedRunMetadata.WhichOneof(oneof_name)` {#TaggedRunMetadata.WhichOneof} + +Returns the name of the currently set field inside a oneof, or None. + + +- - - + +#### `tf.summary.TaggedRunMetadata.__deepcopy__(memo=None)` {#TaggedRunMetadata.__deepcopy__} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.__eq__(other)` {#TaggedRunMetadata.__eq__} + + + + +- - - + #### `tf.summary.TaggedRunMetadata.__getstate__()` {#TaggedRunMetadata.__getstate__} Support the pickle protocol. +- - - + +#### `tf.summary.TaggedRunMetadata.__hash__()` {#TaggedRunMetadata.__hash__} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.__init__(**kwargs)` {#TaggedRunMetadata.__init__} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.__ne__(other_msg)` {#TaggedRunMetadata.__ne__} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.__repr__()` {#TaggedRunMetadata.__repr__} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.__setstate__(state)` {#TaggedRunMetadata.__setstate__} + +Support the pickle protocol. + + +- - - + +#### `tf.summary.TaggedRunMetadata.__str__()` {#TaggedRunMetadata.__str__} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.__unicode__()` {#TaggedRunMetadata.__unicode__} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.run_metadata` {#TaggedRunMetadata.run_metadata} + +Magic attribute generated for "run_metadata" proto field. + + +- - - + +#### `tf.summary.TaggedRunMetadata.tag` {#TaggedRunMetadata.tag} + +Magic attribute generated for "tag" proto field. + + diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.merge_all_summaries.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.merge_all_summaries.md new file mode 100644 index 0000000000..bf17320a5a --- /dev/null +++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.merge_all_summaries.md @@ -0,0 +1,17 @@ +### `tf.merge_all_summaries(*args, **kwargs)` {#merge_all_summaries} + +Merges all summaries collected in the default graph. (deprecated) + +THIS FUNCTION IS DEPRECATED. It will be removed after 2016-11-30. +Instructions for updating: +Please switch to tf.summary.merge_all. + + Args: + key: `GraphKey` used to collect the summaries. Defaults to + `GraphKeys.SUMMARIES`. + + Returns: + If no summaries were collected, returns None. Otherwise returns a scalar + `Tensor` of type `string` containing the serialized `Summary` protocol + buffer resulting from the merging. + diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.image_summary.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.image_summary.md new file mode 100644 index 0000000000..6220d3641b --- /dev/null +++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.image_summary.md @@ -0,0 +1,49 @@ +### `tf.image_summary(*args, **kwargs)` {#image_summary} + +Outputs a `Summary` protocol buffer with images. (deprecated) + +THIS FUNCTION IS DEPRECATED. It will be removed after 2016-11-30. +Instructions for updating: +Please switch to tf.summary.image. Note that tf.summary.histogram uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, the max_images argument was renamed to max_outputs. + + The summary has up to `max_images` summary values containing images. The + images are built from `tensor` which must be 4-D with shape `[batch_size, + height, width, channels]` and where `channels` can be: + + * 1: `tensor` is interpreted as Grayscale. + * 3: `tensor` is interpreted as RGB. + * 4: `tensor` is interpreted as RGBA. + + The images have the same number of channels as the input tensor. For float + input, the values are normalized one image at a time to fit in the range + `[0, 255]`. `uint8` values are unchanged. The op uses two different + normalization algorithms: + + * If the input values are all positive, they are rescaled so the largest one + is 255. + + * If any input value is negative, the values are shifted so input value 0.0 + is at 127. They are then rescaled so that either the smallest value is 0, + or the largest one is 255. + + The `tag` argument is a scalar `Tensor` of type `string`. It is used to + build the `tag` of the summary values: + + * If `max_images` is 1, the summary value tag is '*tag*/image'. + * If `max_images` is greater than 1, the summary value tags are + generated sequentially as '*tag*/image/0', '*tag*/image/1', etc. + + Args: + tag: A scalar `Tensor` of type `string`. Used to build the `tag` + of the summary values. + tensor: A 4-D `uint8` or `float32` `Tensor` of shape `[batch_size, height, + width, channels]` where `channels` is 1, 3, or 4. + max_images: Max number of batch elements to generate images for. + collections: Optional list of ops.GraphKeys. The collections to add the + summary to. Defaults to [ops.GraphKeys.SUMMARIES] + name: A name for the operation (optional). + + Returns: + A scalar `Tensor` of type `string`. The serialized `Summary` protocol + buffer. + diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.summary.SummaryDescription.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.summary.SummaryDescription.md index 19532f7cc3..bce704ef4f 100644 --- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.summary.SummaryDescription.md +++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.summary.SummaryDescription.md @@ -1,8 +1,245 @@ - - - +#### `tf.summary.SummaryDescription.ByteSize()` {#SummaryDescription.ByteSize} + + + + +- - - + +#### `tf.summary.SummaryDescription.Clear()` {#SummaryDescription.Clear} + + + + +- - - + +#### `tf.summary.SummaryDescription.ClearExtension(extension_handle)` {#SummaryDescription.ClearExtension} + + + + +- - - + +#### `tf.summary.SummaryDescription.ClearField(field_name)` {#SummaryDescription.ClearField} + + + + +- - - + +#### `tf.summary.SummaryDescription.CopyFrom(other_msg)` {#SummaryDescription.CopyFrom} + +Copies the content of the specified message into the current message. + +The method clears the current message and then merges the specified +message using MergeFrom. + +##### Args: + + +* <b>`other_msg`</b>: Message to copy into the current one. + + +- - - + +#### `tf.summary.SummaryDescription.DiscardUnknownFields()` {#SummaryDescription.DiscardUnknownFields} + + + + +- - - + +#### `tf.summary.SummaryDescription.FindInitializationErrors()` {#SummaryDescription.FindInitializationErrors} + +Finds required fields which are not initialized. + +##### Returns: + + A list of strings. Each string is a path to an uninitialized field from + the top-level message, e.g. "foo.bar[5].baz". + + +- - - + +#### `tf.summary.SummaryDescription.FromString(s)` {#SummaryDescription.FromString} + + + + +- - - + +#### `tf.summary.SummaryDescription.HasExtension(extension_handle)` {#SummaryDescription.HasExtension} + + + + +- - - + +#### `tf.summary.SummaryDescription.HasField(field_name)` {#SummaryDescription.HasField} + + + + +- - - + +#### `tf.summary.SummaryDescription.IsInitialized(errors=None)` {#SummaryDescription.IsInitialized} + +Checks if all required fields of a message are set. + +##### Args: + + +* <b>`errors`</b>: A list which, if provided, will be populated with the field + paths of all missing required fields. + +##### Returns: + + True iff the specified message has all required fields set. + + +- - - + +#### `tf.summary.SummaryDescription.ListFields()` {#SummaryDescription.ListFields} + + + + +- - - + +#### `tf.summary.SummaryDescription.MergeFrom(msg)` {#SummaryDescription.MergeFrom} + + + + +- - - + +#### `tf.summary.SummaryDescription.MergeFromString(serialized)` {#SummaryDescription.MergeFromString} + + + + +- - - + +#### `tf.summary.SummaryDescription.ParseFromString(serialized)` {#SummaryDescription.ParseFromString} + +Parse serialized protocol buffer data into this message. + +Like MergeFromString(), except we clear the object first and +do not return the value that MergeFromString returns. + + +- - - + +#### `tf.summary.SummaryDescription.RegisterExtension(extension_handle)` {#SummaryDescription.RegisterExtension} + + + + +- - - + +#### `tf.summary.SummaryDescription.SerializePartialToString()` {#SummaryDescription.SerializePartialToString} + + + + +- - - + +#### `tf.summary.SummaryDescription.SerializeToString()` {#SummaryDescription.SerializeToString} + + + + +- - - + +#### `tf.summary.SummaryDescription.SetInParent()` {#SummaryDescription.SetInParent} + +Sets the _cached_byte_size_dirty bit to true, +and propagates this to our listener iff this was a state change. + + +- - - + +#### `tf.summary.SummaryDescription.WhichOneof(oneof_name)` {#SummaryDescription.WhichOneof} + +Returns the name of the currently set field inside a oneof, or None. + + +- - - + +#### `tf.summary.SummaryDescription.__deepcopy__(memo=None)` {#SummaryDescription.__deepcopy__} + + + + +- - - + +#### `tf.summary.SummaryDescription.__eq__(other)` {#SummaryDescription.__eq__} + + + + +- - - + #### `tf.summary.SummaryDescription.__getstate__()` {#SummaryDescription.__getstate__} Support the pickle protocol. +- - - + +#### `tf.summary.SummaryDescription.__hash__()` {#SummaryDescription.__hash__} + + + + +- - - + +#### `tf.summary.SummaryDescription.__init__(**kwargs)` {#SummaryDescription.__init__} + + + + +- - - + +#### `tf.summary.SummaryDescription.__ne__(other_msg)` {#SummaryDescription.__ne__} + + + + +- - - + +#### `tf.summary.SummaryDescription.__repr__()` {#SummaryDescription.__repr__} + + + + +- - - + +#### `tf.summary.SummaryDescription.__setstate__(state)` {#SummaryDescription.__setstate__} + +Support the pickle protocol. + + +- - - + +#### `tf.summary.SummaryDescription.__str__()` {#SummaryDescription.__str__} + + + + +- - - + +#### `tf.summary.SummaryDescription.__unicode__()` {#SummaryDescription.__unicode__} + + + + +- - - + +#### `tf.summary.SummaryDescription.type_hint` {#SummaryDescription.type_hint} + +Magic attribute generated for "type_hint" proto field. + + diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.test.TestCase.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.test.TestCase.md index e9e8a2684c..4d4330488f 100644 --- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.test.TestCase.md +++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.test.TestCase.md @@ -175,125 +175,6 @@ Checks that for all elements of farray1 and farray2 - - - -#### `tf.test.TestCase.assertBetween(value, minv, maxv, msg=None)` {#TestCase.assertBetween} - -Asserts that value is between minv and maxv (inclusive). - - -- - - - -#### `tf.test.TestCase.assertCommandFails(command, regexes, env=None, close_fds=True, msg=None)` {#TestCase.assertCommandFails} - -Asserts a shell command fails and the error matches a regex in a list. - -##### Args: - - -* <b>`command`</b>: List or string representing the command to run. -* <b>`regexes`</b>: the list of regular expression strings. -* <b>`env`</b>: Dictionary of environment variable settings. -* <b>`close_fds`</b>: Whether or not to close all open fd's in the child after - forking. -* <b>`msg`</b>: Optional message to report on failure. - - -- - - - -#### `tf.test.TestCase.assertCommandSucceeds(command, regexes=('',), env=None, close_fds=True, msg=None)` {#TestCase.assertCommandSucceeds} - -Asserts that a shell command succeeds (i.e. exits with code 0). - -##### Args: - - -* <b>`command`</b>: List or string representing the command to run. -* <b>`regexes`</b>: List of regular expression byte strings that match success. -* <b>`env`</b>: Dictionary of environment variable settings. -* <b>`close_fds`</b>: Whether or not to close all open fd's in the child after - forking. -* <b>`msg`</b>: Optional message to report on failure. - - -- - - - -#### `tf.test.TestCase.assertContainsExactSubsequence(container, subsequence, msg=None)` {#TestCase.assertContainsExactSubsequence} - -Assert that "container" contains "subsequence" as an exact subsequence. - -Asserts that "container" contains all the elements of "subsequence", in -order, and without other elements interspersed. For example, [1, 2, 3] is an -exact subsequence of [0, 0, 1, 2, 3, 0] but not of [0, 0, 1, 2, 0, 3, 0]. - -##### Args: - - -* <b>`container`</b>: the list we're testing for subsequence inclusion. -* <b>`subsequence`</b>: the list we hope will be an exact subsequence of container. -* <b>`msg`</b>: Optional message to report on failure. - - -- - - - -#### `tf.test.TestCase.assertContainsInOrder(strings, target, msg=None)` {#TestCase.assertContainsInOrder} - -Asserts that the strings provided are found in the target in order. - -This may be useful for checking HTML output. - -##### Args: - - -* <b>`strings`</b>: A list of strings, such as [ 'fox', 'dog' ] -* <b>`target`</b>: A target string in which to look for the strings, such as - 'The quick brown fox jumped over the lazy dog'. -* <b>`msg`</b>: Optional message to report on failure. - - -- - - - -#### `tf.test.TestCase.assertContainsSubsequence(container, subsequence, msg=None)` {#TestCase.assertContainsSubsequence} - -Assert that "container" contains "subsequence" as a subsequence. - -Asserts that "container" contains all the elements of "subsequence", in -order, but possibly with other elements interspersed. For example, [1, 2, 3] -is a subsequence of [0, 0, 1, 2, 0, 3, 0] but not of [0, 0, 1, 3, 0, 2, 0]. - -##### Args: - - -* <b>`container`</b>: the list we're testing for subsequence inclusion. -* <b>`subsequence`</b>: the list we hope will be a subsequence of container. -* <b>`msg`</b>: Optional message to report on failure. - - -- - - - -#### `tf.test.TestCase.assertContainsSubset(expected_subset, actual_set, msg=None)` {#TestCase.assertContainsSubset} - -Checks whether actual iterable is a superset of expected iterable. - - -- - - - -#### `tf.test.TestCase.assertCountEqual(*args, **kwargs)` {#TestCase.assertCountEqual} - -An unordered sequence specific comparison. - -Equivalent to assertItemsEqual(). This method is a compatibility layer -for Python 3k, since 2to3 does not convert assertItemsEqual() calls into -assertCountEqual() calls. - -##### Args: - - -* <b>`expected_seq`</b>: A sequence containing elements we are expecting. -* <b>`actual_seq`</b>: The sequence that we are testing. -* <b>`msg`</b>: The message to be printed if the test fails. - - -- - - - #### `tf.test.TestCase.assertDeviceEqual(device1, device2)` {#TestCase.assertDeviceEqual} Asserts that the two given devices are the same. @@ -314,49 +195,10 @@ Checks whether actual is a superset of expected. - - - -#### `tf.test.TestCase.assertDictEqual(a, b, msg=None)` {#TestCase.assertDictEqual} +#### `tf.test.TestCase.assertDictEqual(d1, d2, msg=None)` {#TestCase.assertDictEqual} -Raises AssertionError if a and b are not equal dictionaries. - -##### Args: - - -* <b>`a`</b>: A dict, the expected value. -* <b>`b`</b>: A dict, the actual value. -* <b>`msg`</b>: An optional str, the associated message. - -##### Raises: - - -* <b>`AssertionError`</b>: if the dictionaries are not equal. - - -- - - - -#### `tf.test.TestCase.assertEmpty(container, msg=None)` {#TestCase.assertEmpty} - -Assert that an object has zero length. - -##### Args: - - -* <b>`container`</b>: Anything that implements the collections.Sized interface. -* <b>`msg`</b>: Optional message to report on failure. -- - - - -#### `tf.test.TestCase.assertEndsWith(actual, expected_end, msg=None)` {#TestCase.assertEndsWith} - -Assert that actual.endswith(expected_end) is True. - -##### Args: - - -* <b>`actual`</b>: str -* <b>`expected_end`</b>: str -* <b>`msg`</b>: Optional message to report on failure. - - - - @@ -440,11 +282,10 @@ Included for symmetry with assertIsNone. - - - -#### `tf.test.TestCase.assertItemsEqual(*args, **kwargs)` {#TestCase.assertItemsEqual} - -An unordered sequence specific comparison. +#### `tf.test.TestCase.assertItemsEqual(expected_seq, actual_seq, msg=None)` {#TestCase.assertItemsEqual} -It asserts that actual_seq and expected_seq have the same element counts. +An unordered sequence specific comparison. It asserts that +actual_seq and expected_seq have the same element counts. Equivalent to:: self.assertEqual(Counter(iter(actual_seq)), @@ -457,30 +298,6 @@ Asserts that each element has the same count in both sequences. - [0, 1, 1] and [1, 0, 1] compare equal. - [0, 0, 1] and [0, 1] compare unequal. -##### Args: - - -* <b>`expected_seq`</b>: A sequence containing elements we are expecting. -* <b>`actual_seq`</b>: The sequence that we are testing. -* <b>`msg`</b>: The message to be printed if the test fails. - - -- - - - -#### `tf.test.TestCase.assertJsonEqual(first, second, msg=None)` {#TestCase.assertJsonEqual} - -Asserts that the JSON objects defined in two strings are equal. - -A summary of the differences will be included in the failure message -using assertSameStructure. - -##### Args: - - -* <b>`first`</b>: A string contining JSON to decode and compare to second. -* <b>`second`</b>: A string contining JSON to decode and compare to first. -* <b>`msg`</b>: Additional text to include in the failure message. - - - - @@ -552,13 +369,6 @@ if not. - - - -#### `tf.test.TestCase.assertNoCommonElements(expected_seq, actual_seq, msg=None)` {#TestCase.assertNoCommonElements} - -Checks whether actual iterable and expected iterable are disjoint. - - -- - - - #### `tf.test.TestCase.assertNotAlmostEqual(first, second, places=None, msg=None, delta=None)` {#TestCase.assertNotAlmostEqual} Fail if the two objects are equal as determined by their @@ -589,33 +399,6 @@ Objects that are equal automatically fail. - - - -#### `tf.test.TestCase.assertNotEmpty(container, msg=None)` {#TestCase.assertNotEmpty} - -Assert that an object has non-zero length. - -##### Args: - - -* <b>`container`</b>: Anything that implements the collections.Sized interface. -* <b>`msg`</b>: Optional message to report on failure. - - -- - - - -#### `tf.test.TestCase.assertNotEndsWith(actual, unexpected_end, msg=None)` {#TestCase.assertNotEndsWith} - -Assert that actual.endswith(unexpected_end) is False. - -##### Args: - - -* <b>`actual`</b>: str -* <b>`unexpected_end`</b>: str -* <b>`msg`</b>: Optional message to report on failure. - - -- - - - #### `tf.test.TestCase.assertNotEqual(first, second, msg=None)` {#TestCase.assertNotEqual} Fail if the two objects are equal as determined by the '!=' @@ -653,20 +436,6 @@ Fail the test if the text matches the regular expression. - - - -#### `tf.test.TestCase.assertNotStartsWith(actual, unexpected_start, msg=None)` {#TestCase.assertNotStartsWith} - -Assert that actual.startswith(unexpected_start) is False. - -##### Args: - - -* <b>`actual`</b>: str -* <b>`unexpected_start`</b>: str -* <b>`msg`</b>: Optional message to report on failure. - - -- - - - #### `tf.test.TestCase.assertProtoEquals(expected_message_maybe_ascii, message)` {#TestCase.assertProtoEquals} Asserts that message is same as parsed expected_message_ascii. @@ -741,38 +510,6 @@ Asserts that the message in a raised exception matches a regexp. - - - -#### `tf.test.TestCase.assertRaisesWithLiteralMatch(expected_exception, expected_exception_message, callable_obj=None, *args, **kwargs)` {#TestCase.assertRaisesWithLiteralMatch} - -Asserts that the message in a raised exception equals the given string. - -Unlike assertRaisesRegexp, this method takes a literal string, not -a regular expression. - -with self.assertRaisesWithLiteralMatch(ExType, 'message'): - DoSomething() - -##### Args: - - -* <b>`expected_exception`</b>: Exception class expected to be raised. -* <b>`expected_exception_message`</b>: String message expected in the raised - exception. For a raise exception e, expected_exception_message must - equal str(e). -* <b>`callable_obj`</b>: Function to be called, or None to return a context. -* <b>`args`</b>: Extra args. -* <b>`kwargs`</b>: Extra kwargs. - -##### Returns: - - A context manager if callable_obj is None. Otherwise, None. - -##### Raises: - - self.failureException if callable_obj does not raise a macthing exception. - - -- - - - #### `tf.test.TestCase.assertRaisesWithPredicateMatch(exception_type, expected_err_re_or_predicate)` {#TestCase.assertRaisesWithPredicateMatch} Returns a context manager to enclose code expected to raise an exception. @@ -797,71 +534,6 @@ predicate search. - - - -#### `tf.test.TestCase.assertRaisesWithRegexpMatch(expected_exception, expected_regexp, callable_obj=None, *args, **kwargs)` {#TestCase.assertRaisesWithRegexpMatch} - -Asserts that the message in a raised exception matches the given regexp. - -This is just a wrapper around assertRaisesRegexp. Please use -assertRaisesRegexp instead of assertRaisesWithRegexpMatch. - -##### Args: - - -* <b>`expected_exception`</b>: Exception class expected to be raised. -* <b>`expected_regexp`</b>: Regexp (re pattern object or string) expected to be - found in error message. -* <b>`callable_obj`</b>: Function to be called, or None to return a context. -* <b>`args`</b>: Extra args. -* <b>`kwargs`</b>: Extra keyword args. - -##### Returns: - - A context manager if callable_obj is None. Otherwise, None. - -##### Raises: - - self.failureException if callable_obj does not raise a macthing exception. - - -- - - - -#### `tf.test.TestCase.assertRegexMatch(actual_str, regexes, message=None)` {#TestCase.assertRegexMatch} - -Asserts that at least one regex in regexes matches str. - - If possible you should use assertRegexpMatches, which is a simpler - version of this method. assertRegexpMatches takes a single regular - expression (a string or re compiled object) instead of a list. - - Notes: - 1. This function uses substring matching, i.e. the matching - succeeds if *any* substring of the error message matches *any* - regex in the list. This is more convenient for the user than - full-string matching. - - 2. If regexes is the empty list, the matching will always fail. - - 3. Use regexes=[''] for a regex that will always pass. - - 4. '.' matches any single character *except* the newline. To - match any character, use '(.| -)'. - - 5. '^' matches the beginning of each line, not just the beginning - of the string. Similarly, '$' matches the end of each line. - - 6. An exception will be thrown if regexes contains an invalid - regex. - - Args: - actual_str: The string we try to match with the items in regexes. - regexes: The regular expressions we want to match against str. - See "Notes" above for detailed notes on how this is interpreted. - message: The message to be printed if the test fails. - - -- - - - #### `tf.test.TestCase.assertRegexpMatches(text, expected_regexp, msg=None)` {#TestCase.assertRegexpMatches} Fail the test unless the text matches the regular expression. @@ -869,79 +541,6 @@ Fail the test unless the text matches the regular expression. - - - -#### `tf.test.TestCase.assertSameElements(expected_seq, actual_seq, msg=None)` {#TestCase.assertSameElements} - -Assert that two sequences have the same elements (in any order). - -This method, unlike assertItemsEqual, doesn't care about any -duplicates in the expected and actual sequences. - - >> assertSameElements([1, 1, 1, 0, 0, 0], [0, 1]) - # Doesn't raise an AssertionError - -If possible, you should use assertItemsEqual instead of -assertSameElements. - -##### Args: - - -* <b>`expected_seq`</b>: A sequence containing elements we are expecting. -* <b>`actual_seq`</b>: The sequence that we are testing. -* <b>`msg`</b>: The message to be printed if the test fails. - - -- - - - -#### `tf.test.TestCase.assertSameStructure(a, b, aname='a', bname='b', msg=None)` {#TestCase.assertSameStructure} - -Asserts that two values contain the same structural content. - -The two arguments should be data trees consisting of trees of dicts and -lists. They will be deeply compared by walking into the contents of dicts -and lists; other items will be compared using the == operator. -If the two structures differ in content, the failure message will indicate -the location within the structures where the first difference is found. -This may be helpful when comparing large structures. - -##### Args: - - -* <b>`a`</b>: The first structure to compare. -* <b>`b`</b>: The second structure to compare. -* <b>`aname`</b>: Variable name to use for the first structure in assertion messages. -* <b>`bname`</b>: Variable name to use for the second structure. -* <b>`msg`</b>: Additional text to include in the failure message. - - -- - - - -#### `tf.test.TestCase.assertSequenceAlmostEqual(expected_seq, actual_seq, places=None, msg=None, delta=None)` {#TestCase.assertSequenceAlmostEqual} - -An approximate equality assertion for ordered sequences. - -Fail if the two sequences are unequal as determined by their value -differences rounded to the given number of decimal places (default 7) and -comparing to zero, or by comparing that the difference between each value -in the two sequences is more than the given delta. - -Note that decimal places (from zero) are usually not the same as significant -digits (measured from the most signficant digit). - -If the two sequences compare equal then they will automatically compare -almost equal. - -##### Args: - - -* <b>`expected_seq`</b>: A sequence containing elements we are expecting. -* <b>`actual_seq`</b>: The sequence that we are testing. -* <b>`places`</b>: The number of decimal places to compare. -* <b>`msg`</b>: The message to be printed if the test fails. -* <b>`delta`</b>: The OK difference between compared values. - - -- - - - #### `tf.test.TestCase.assertSequenceEqual(seq1, seq2, msg=None, seq_type=None)` {#TestCase.assertSequenceEqual} An equality assertion for ordered sequences (like lists and tuples). @@ -962,26 +561,6 @@ which can be indexed, has a length, and has an equality operator. - - - -#### `tf.test.TestCase.assertSequenceStartsWith(prefix, whole, msg=None)` {#TestCase.assertSequenceStartsWith} - -An equality assertion for the beginning of ordered sequences. - -If prefix is an empty sequence, it will raise an error unless whole is also -an empty sequence. - -If prefix is not a sequence, it will raise an error if the first element of -whole does not match. - -##### Args: - - -* <b>`prefix`</b>: A sequence expected at the beginning of the whole parameter. -* <b>`whole`</b>: The sequence in which to look for prefix. -* <b>`msg`</b>: Optional message to report on failure. - - -- - - - #### `tf.test.TestCase.assertSetEqual(set1, set2, msg=None)` {#TestCase.assertSetEqual} A set-specific equality assertion. @@ -1033,51 +612,6 @@ Assert that actual.startswith(expected_start) is True. - - - -#### `tf.test.TestCase.assertTotallyOrdered(*groups, **kwargs)` {#TestCase.assertTotallyOrdered} - -Asserts that total ordering has been implemented correctly. - -For example, say you have a class A that compares only on its attribute x. -Comparators other than __lt__ are omitted for brevity. - -class A(object): - def __init__(self, x, y): - self.x = x - self.y = y - - def __hash__(self): - return hash(self.x) - - def __lt__(self, other): - try: - return self.x < other.x - except AttributeError: - return NotImplemented - -assertTotallyOrdered will check that instances can be ordered correctly. -For example, - -self.assertTotallyOrdered( - [None], # None should come before everything else. - [1], # Integers sort earlier. - [A(1, 'a')], - [A(2, 'b')], # 2 is after 1. - [A(3, 'c'), A(3, 'd')], # The second argument is irrelevant. - [A(4, 'z')], - ['foo']) # Strings sort last. - -##### Args: - - -* <b>`*groups`</b>: A list of groups of elements. Each group of elements is a list - of objects that are equal. The elements in each group must be less than - the elements in the group after it. For example, these groups are - totally ordered: [None], [1], [2, 2], [3]. -* <b>`**kwargs`</b>: optional msg keyword argument can be passed. - - -- - - - #### `tf.test.TestCase.assertTrue(expr, msg=None)` {#TestCase.assertTrue} Check that the expression is true. @@ -1100,13 +634,6 @@ A tuple-specific equality assertion. - - - -#### `tf.test.TestCase.assertUrlEqual(a, b, msg=None)` {#TestCase.assertUrlEqual} - -Asserts that urls are equal, ignoring ordering of query params. - - -- - - - #### `tf.test.TestCase.assert_(expr, msg=None)` {#TestCase.assert_} Check that the expression is true. @@ -1166,9 +693,9 @@ tearDown. - - - -#### `tf.test.TestCase.fail(msg=None, prefix=None)` {#TestCase.fail} +#### `tf.test.TestCase.fail(msg=None)` {#TestCase.fail} -Fail immediately with the given message, optionally prefixed. +Fail immediately, with the given message. - - - @@ -1222,13 +749,6 @@ Fail immediately with the given message, optionally prefixed. - - - -#### `tf.test.TestCase.getRecordedProperties()` {#TestCase.getRecordedProperties} - -Return any properties that the user has recorded. - - -- - - - #### `tf.test.TestCase.get_temp_dir()` {#TestCase.get_temp_dir} Returns a unique temporary directory for the test to use. @@ -1251,20 +771,6 @@ pollute each others environment. - - - -#### `tf.test.TestCase.recordProperty(property_name, property_value)` {#TestCase.recordProperty} - -Record an arbitrary property for later use. - -##### Args: - - -* <b>`property_name`</b>: str, name of property to record; must be a valid XML - attribute name -* <b>`property_value`</b>: value of property; must be valid XML attribute value - - -- - - - #### `tf.test.TestCase.run(result=None)` {#TestCase.run} @@ -1288,18 +794,11 @@ Hook method for setting up class fixture before running tests in the class. #### `tf.test.TestCase.shortDescription()` {#TestCase.shortDescription} -Format both the test method name and the first line of its docstring. - -If no docstring is given, only returns the method name. - -This method overrides unittest.TestCase.shortDescription(), which -only returns the first line of the docstring, obscuring the name -of the test upon failure. - -##### Returns: - +Returns a one-line description of the test, or None if no +description has been provided. -* <b>`desc`</b>: A short description of a test method. +The default implementation of this method returns the first line of +the specified test method's docstring. - - - diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.scalar_summary.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.scalar_summary.md new file mode 100644 index 0000000000..3ffd9260c7 --- /dev/null +++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.scalar_summary.md @@ -0,0 +1,22 @@ +### `tf.scalar_summary(*args, **kwargs)` {#scalar_summary} + +Outputs a `Summary` protocol buffer with scalar values. (deprecated) + +THIS FUNCTION IS DEPRECATED. It will be removed after 2016-11-30. +Instructions for updating: +Please switch to tf.summary.scalar. Note that tf.summary.scalar uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, passing a tensor or list of tags to a scalar summary op is no longer supported. + + The input `tags` and `values` must have the same shape. The generated + summary has a summary value for each tag-value pair in `tags` and `values`. + + Args: + tags: A `string` `Tensor`. Tags for the summaries. + values: A real numeric Tensor. Values for the summaries. + collections: Optional list of graph collections keys. The new summary op is + added to these collections. Defaults to `[GraphKeys.SUMMARIES]`. + name: A name for the operation (optional). + + Returns: + A scalar `Tensor` of type `string`. The serialized `Summary` protocol + buffer. + diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.summary.SummaryDescription.RegisterExtension.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.summary.SummaryDescription.RegisterExtension.md new file mode 100644 index 0000000000..3cfd7103d7 --- /dev/null +++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.summary.SummaryDescription.RegisterExtension.md @@ -0,0 +1,4 @@ +#### `tf.summary.SummaryDescription.RegisterExtension(extension_handle)` {#SummaryDescription.RegisterExtension} + + + diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.histogram_summary.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.histogram_summary.md new file mode 100644 index 0000000000..570d7b712c --- /dev/null +++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.histogram_summary.md @@ -0,0 +1,26 @@ +### `tf.histogram_summary(*args, **kwargs)` {#histogram_summary} + +Outputs a `Summary` protocol buffer with a histogram. (deprecated) + +THIS FUNCTION IS DEPRECATED. It will be removed after 2016-11-30. +Instructions for updating: +Please switch to tf.summary.histogram. Note that tf.summary.histogram uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on their scope. + + The generated + [`Summary`](https://www.tensorflow.org/code/tensorflow/core/framework/summary.proto) + has one summary value containing a histogram for `values`. + + This op reports an `InvalidArgument` error if any value is not finite. + + Args: + tag: A `string` `Tensor`. 0-D. Tag to use for the summary value. + values: A real numeric `Tensor`. Any shape. Values to use to + build the histogram. + collections: Optional list of graph collections keys. The new summary op is + added to these collections. Defaults to `[GraphKeys.SUMMARIES]`. + name: A name for the operation (optional). + + Returns: + A scalar `Tensor` of type `string`. The serialized `Summary` protocol + buffer. + diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.merge_summary.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.merge_summary.md new file mode 100644 index 0000000000..ccb984f5ab --- /dev/null +++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.merge_summary.md @@ -0,0 +1,27 @@ +### `tf.merge_summary(*args, **kwargs)` {#merge_summary} + +Merges summaries. (deprecated) + +THIS FUNCTION IS DEPRECATED. It will be removed after 2016-11-30. +Instructions for updating: +Please switch to tf.summary.merge. + + This op creates a + [`Summary`](https://www.tensorflow.org/code/tensorflow/core/framework/summary.proto) + protocol buffer that contains the union of all the values in the input + summaries. + + When the Op is run, it reports an `InvalidArgument` error if multiple values + in the summaries to merge use the same tag. + + Args: + inputs: A list of `string` `Tensor` objects containing serialized `Summary` + protocol buffers. + collections: Optional list of graph collections keys. The new summary op is + added to these collections. Defaults to `[GraphKeys.SUMMARIES]`. + name: A name for the operation (optional). + + Returns: + A scalar `Tensor` of type `string`. The serialized `Summary` protocol + buffer resulting from the merging. + diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.summary.SummaryDescription.FromString.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.summary.SummaryDescription.FromString.md new file mode 100644 index 0000000000..24a3b3f10c --- /dev/null +++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.summary.SummaryDescription.FromString.md @@ -0,0 +1,4 @@ +#### `tf.summary.SummaryDescription.FromString(s)` {#SummaryDescription.FromString} + + + diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.summary.TaggedRunMetadata.RegisterExtension.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.summary.TaggedRunMetadata.RegisterExtension.md new file mode 100644 index 0000000000..f2d0c042d7 --- /dev/null +++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.summary.TaggedRunMetadata.RegisterExtension.md @@ -0,0 +1,4 @@ +#### `tf.summary.TaggedRunMetadata.RegisterExtension(extension_handle)` {#TaggedRunMetadata.RegisterExtension} + + + diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.train.SummaryWriter.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.train.SummaryWriter.md new file mode 100644 index 0000000000..e9bdda200f --- /dev/null +++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.train.SummaryWriter.md @@ -0,0 +1,207 @@ + +- - - + +#### `tf.train.SummaryWriter.__init__(*args, **kwargs)` {#SummaryWriter.__init__} + +Creates a `SummaryWriter` and an event file. (deprecated) + +THIS FUNCTION IS DEPRECATED. It will be removed after 2016-11-30. +Instructions for updating: +Please switch to tf.summary.FileWriter. The interface and behavior is the same; this is just a rename. + + This class is deprecated, and should be replaced with tf.summary.FileWriter. + + On construction the summary writer creates a new event file in `logdir`. + This event file will contain `Event` protocol buffers constructed when you + call one of the following functions: `add_summary()`, `add_session_log()`, + `add_event()`, or `add_graph()`. + + If you pass a `Graph` to the constructor it is added to + the event file. (This is equivalent to calling `add_graph()` later). + + TensorBoard will pick the graph from the file and display it graphically so + you can interactively explore the graph you built. You will usually pass + the graph from the session in which you launched it: + + ```python + ...create a graph... + # Launch the graph in a session. + sess = tf.Session() + # Create a summary writer, add the 'graph' to the event file. + writer = tf.train.SummaryWriter(<some-directory>, sess.graph) + ``` + + The other arguments to the constructor control the asynchronous writes to + the event file: + + * `flush_secs`: How often, in seconds, to flush the added summaries + and events to disk. + * `max_queue`: Maximum number of summaries or events pending to be + written to disk before one of the 'add' calls block. + + Args: + logdir: A string. Directory where event file will be written. + graph: A `Graph` object, such as `sess.graph`. + max_queue: Integer. Size of the queue for pending events and summaries. + flush_secs: Number. How often, in seconds, to flush the + pending events and summaries to disk. + graph_def: DEPRECATED: Use the `graph` argument instead. + + +- - - + +#### `tf.train.SummaryWriter.add_event(event)` {#SummaryWriter.add_event} + +Adds an event to the event file. + +##### Args: + + +* <b>`event`</b>: An `Event` protocol buffer. + + +- - - + +#### `tf.train.SummaryWriter.add_graph(graph, global_step=None, graph_def=None)` {#SummaryWriter.add_graph} + +Adds a `Graph` to the event file. + +The graph described by the protocol buffer will be displayed by +TensorBoard. Most users pass a graph in the constructor instead. + +##### Args: + + +* <b>`graph`</b>: A `Graph` object, such as `sess.graph`. +* <b>`global_step`</b>: Number. Optional global step counter to record with the + graph. +* <b>`graph_def`</b>: DEPRECATED. Use the `graph` parameter instead. + +##### Raises: + + +* <b>`ValueError`</b>: If both graph and graph_def are passed to the method. + + +- - - + +#### `tf.train.SummaryWriter.add_meta_graph(meta_graph_def, global_step=None)` {#SummaryWriter.add_meta_graph} + +Adds a `MetaGraphDef` to the event file. + +The `MetaGraphDef` allows running the given graph via +`saver.import_meta_graph()`. + +##### Args: + + +* <b>`meta_graph_def`</b>: A `MetaGraphDef` object, often as retured by + `saver.export_meta_graph()`. +* <b>`global_step`</b>: Number. Optional global step counter to record with the + graph. + +##### Raises: + + +* <b>`TypeError`</b>: If both `meta_graph_def` is not an instance of `MetaGraphDef`. + + +- - - + +#### `tf.train.SummaryWriter.add_run_metadata(run_metadata, tag, global_step=None)` {#SummaryWriter.add_run_metadata} + +Adds a metadata information for a single session.run() call. + +##### Args: + + +* <b>`run_metadata`</b>: A `RunMetadata` protobuf object. +* <b>`tag`</b>: The tag name for this metadata. +* <b>`global_step`</b>: Number. Optional global step counter to record with the + StepStats. + +##### Raises: + + +* <b>`ValueError`</b>: If the provided tag was already used for this type of event. + + +- - - + +#### `tf.train.SummaryWriter.add_session_log(session_log, global_step=None)` {#SummaryWriter.add_session_log} + +Adds a `SessionLog` protocol buffer to the event file. + +This method wraps the provided session in an `Event` protocol buffer +and adds it to the event file. + +##### Args: + + +* <b>`session_log`</b>: A `SessionLog` protocol buffer. +* <b>`global_step`</b>: Number. Optional global step value to record with the + summary. + + +- - - + +#### `tf.train.SummaryWriter.add_summary(summary, global_step=None)` {#SummaryWriter.add_summary} + +Adds a `Summary` protocol buffer to the event file. + +This method wraps the provided summary in an `Event` protocol buffer +and adds it to the event file. + +You can pass the result of evaluating any summary op, using +[`Session.run()`](client.md#Session.run) or +[`Tensor.eval()`](framework.md#Tensor.eval), to this +function. Alternatively, you can pass a `tf.Summary` protocol +buffer that you populate with your own data. The latter is +commonly done to report evaluation results in event files. + +##### Args: + + +* <b>`summary`</b>: A `Summary` protocol buffer, optionally serialized as a string. +* <b>`global_step`</b>: Number. Optional global step value to record with the + summary. + + +- - - + +#### `tf.train.SummaryWriter.close()` {#SummaryWriter.close} + +Flushes the event file to disk and close the file. + +Call this method when you do not need the summary writer anymore. + + +- - - + +#### `tf.train.SummaryWriter.flush()` {#SummaryWriter.flush} + +Flushes the event file to disk. + +Call this method to make sure that all pending events have been written to +disk. + + +- - - + +#### `tf.train.SummaryWriter.get_logdir()` {#SummaryWriter.get_logdir} + +Returns the directory where event file will be written. + + +- - - + +#### `tf.train.SummaryWriter.reopen()` {#SummaryWriter.reopen} + +Reopens the EventFileWriter. + +Can be called after `close()` to add more events in the same directory. +The events will go into a new events file. + +Does nothing if the EventFileWriter was not closed. + + diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.audio_summary.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.audio_summary.md new file mode 100644 index 0000000000..c5830ab550 --- /dev/null +++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.audio_summary.md @@ -0,0 +1,37 @@ +### `tf.audio_summary(*args, **kwargs)` {#audio_summary} + +Outputs a `Summary` protocol buffer with audio. (deprecated) + +THIS FUNCTION IS DEPRECATED. It will be removed after 2016-11-30. +Instructions for updating: +Please switch to tf.summary.audio. Note that tf.summary.histogram uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on the scope they are created in. + + The summary has up to `max_outputs` summary values containing audio. The + audio is built from `tensor` which must be 3-D with shape `[batch_size, + frames, channels]` or 2-D with shape `[batch_size, frames]`. The values are + assumed to be in the range of `[-1.0, 1.0]` with a sample rate of + `sample_rate`. + + The `tag` argument is a scalar `Tensor` of type `string`. It is used to + build the `tag` of the summary values: + + * If `max_outputs` is 1, the summary value tag is '*tag*/audio'. + * If `max_outputs` is greater than 1, the summary value tags are + generated sequentially as '*tag*/audio/0', '*tag*/audio/1', etc. + + Args: + tag: A scalar `Tensor` of type `string`. Used to build the `tag` + of the summary values. + tensor: A 3-D `float32` `Tensor` of shape `[batch_size, frames, channels]` + or a 2-D `float32` `Tensor` of shape `[batch_size, frames]`. + sample_rate: A Scalar `float32` `Tensor` indicating the sample rate of the + signal in hertz. + max_outputs: Max number of batch elements to generate audio for. + collections: Optional list of ops.GraphKeys. The collections to add the + summary to. Defaults to [ops.GraphKeys.SUMMARIES] + name: A name for the operation (optional). + + Returns: + A scalar `Tensor` of type `string`. The serialized `Summary` protocol + buffer. + diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.summary.TaggedRunMetadata.FromString.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.summary.TaggedRunMetadata.FromString.md new file mode 100644 index 0000000000..613f4ebd73 --- /dev/null +++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.summary.TaggedRunMetadata.FromString.md @@ -0,0 +1,4 @@ +#### `tf.summary.TaggedRunMetadata.FromString(s)` {#TaggedRunMetadata.FromString} + + + diff --git a/tensorflow/g3doc/api_docs/python/summary.md b/tensorflow/g3doc/api_docs/python/summary.md index 8d344036db..be029f4290 100644 --- a/tensorflow/g3doc/api_docs/python/summary.md +++ b/tensorflow/g3doc/api_docs/python/summary.md @@ -487,11 +487,248 @@ metadata is stored in its NodeDef. This method retrieves the description. - - - +#### `tf.summary.SummaryDescription.ByteSize()` {#SummaryDescription.ByteSize} + + + + +- - - + +#### `tf.summary.SummaryDescription.Clear()` {#SummaryDescription.Clear} + + + + +- - - + +#### `tf.summary.SummaryDescription.ClearExtension(extension_handle)` {#SummaryDescription.ClearExtension} + + + + +- - - + +#### `tf.summary.SummaryDescription.ClearField(field_name)` {#SummaryDescription.ClearField} + + + + +- - - + +#### `tf.summary.SummaryDescription.CopyFrom(other_msg)` {#SummaryDescription.CopyFrom} + +Copies the content of the specified message into the current message. + +The method clears the current message and then merges the specified +message using MergeFrom. + +##### Args: + + +* <b>`other_msg`</b>: Message to copy into the current one. + + +- - - + +#### `tf.summary.SummaryDescription.DiscardUnknownFields()` {#SummaryDescription.DiscardUnknownFields} + + + + +- - - + +#### `tf.summary.SummaryDescription.FindInitializationErrors()` {#SummaryDescription.FindInitializationErrors} + +Finds required fields which are not initialized. + +##### Returns: + + A list of strings. Each string is a path to an uninitialized field from + the top-level message, e.g. "foo.bar[5].baz". + + +- - - + +#### `tf.summary.SummaryDescription.FromString(s)` {#SummaryDescription.FromString} + + + + +- - - + +#### `tf.summary.SummaryDescription.HasExtension(extension_handle)` {#SummaryDescription.HasExtension} + + + + +- - - + +#### `tf.summary.SummaryDescription.HasField(field_name)` {#SummaryDescription.HasField} + + + + +- - - + +#### `tf.summary.SummaryDescription.IsInitialized(errors=None)` {#SummaryDescription.IsInitialized} + +Checks if all required fields of a message are set. + +##### Args: + + +* <b>`errors`</b>: A list which, if provided, will be populated with the field + paths of all missing required fields. + +##### Returns: + + True iff the specified message has all required fields set. + + +- - - + +#### `tf.summary.SummaryDescription.ListFields()` {#SummaryDescription.ListFields} + + + + +- - - + +#### `tf.summary.SummaryDescription.MergeFrom(msg)` {#SummaryDescription.MergeFrom} + + + + +- - - + +#### `tf.summary.SummaryDescription.MergeFromString(serialized)` {#SummaryDescription.MergeFromString} + + + + +- - - + +#### `tf.summary.SummaryDescription.ParseFromString(serialized)` {#SummaryDescription.ParseFromString} + +Parse serialized protocol buffer data into this message. + +Like MergeFromString(), except we clear the object first and +do not return the value that MergeFromString returns. + + +- - - + +#### `tf.summary.SummaryDescription.RegisterExtension(extension_handle)` {#SummaryDescription.RegisterExtension} + + + + +- - - + +#### `tf.summary.SummaryDescription.SerializePartialToString()` {#SummaryDescription.SerializePartialToString} + + + + +- - - + +#### `tf.summary.SummaryDescription.SerializeToString()` {#SummaryDescription.SerializeToString} + + + + +- - - + +#### `tf.summary.SummaryDescription.SetInParent()` {#SummaryDescription.SetInParent} + +Sets the _cached_byte_size_dirty bit to true, +and propagates this to our listener iff this was a state change. + + +- - - + +#### `tf.summary.SummaryDescription.WhichOneof(oneof_name)` {#SummaryDescription.WhichOneof} + +Returns the name of the currently set field inside a oneof, or None. + + +- - - + +#### `tf.summary.SummaryDescription.__deepcopy__(memo=None)` {#SummaryDescription.__deepcopy__} + + + + +- - - + +#### `tf.summary.SummaryDescription.__eq__(other)` {#SummaryDescription.__eq__} + + + + +- - - + #### `tf.summary.SummaryDescription.__getstate__()` {#SummaryDescription.__getstate__} Support the pickle protocol. +- - - + +#### `tf.summary.SummaryDescription.__hash__()` {#SummaryDescription.__hash__} + + + + +- - - + +#### `tf.summary.SummaryDescription.__init__(**kwargs)` {#SummaryDescription.__init__} + + + + +- - - + +#### `tf.summary.SummaryDescription.__ne__(other_msg)` {#SummaryDescription.__ne__} + + + + +- - - + +#### `tf.summary.SummaryDescription.__repr__()` {#SummaryDescription.__repr__} + + + + +- - - + +#### `tf.summary.SummaryDescription.__setstate__(state)` {#SummaryDescription.__setstate__} + +Support the pickle protocol. + + +- - - + +#### `tf.summary.SummaryDescription.__str__()` {#SummaryDescription.__str__} + + + + +- - - + +#### `tf.summary.SummaryDescription.__unicode__()` {#SummaryDescription.__unicode__} + + + + +- - - + +#### `tf.summary.SummaryDescription.type_hint` {#SummaryDescription.type_hint} + +Magic attribute generated for "type_hint" proto field. + + - - - @@ -500,9 +737,253 @@ Support the pickle protocol. - - - +#### `tf.summary.TaggedRunMetadata.ByteSize()` {#TaggedRunMetadata.ByteSize} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.Clear()` {#TaggedRunMetadata.Clear} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.ClearExtension(extension_handle)` {#TaggedRunMetadata.ClearExtension} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.ClearField(field_name)` {#TaggedRunMetadata.ClearField} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.CopyFrom(other_msg)` {#TaggedRunMetadata.CopyFrom} + +Copies the content of the specified message into the current message. + +The method clears the current message and then merges the specified +message using MergeFrom. + +##### Args: + + +* <b>`other_msg`</b>: Message to copy into the current one. + + +- - - + +#### `tf.summary.TaggedRunMetadata.DiscardUnknownFields()` {#TaggedRunMetadata.DiscardUnknownFields} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.FindInitializationErrors()` {#TaggedRunMetadata.FindInitializationErrors} + +Finds required fields which are not initialized. + +##### Returns: + + A list of strings. Each string is a path to an uninitialized field from + the top-level message, e.g. "foo.bar[5].baz". + + +- - - + +#### `tf.summary.TaggedRunMetadata.FromString(s)` {#TaggedRunMetadata.FromString} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.HasExtension(extension_handle)` {#TaggedRunMetadata.HasExtension} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.HasField(field_name)` {#TaggedRunMetadata.HasField} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.IsInitialized(errors=None)` {#TaggedRunMetadata.IsInitialized} + +Checks if all required fields of a message are set. + +##### Args: + + +* <b>`errors`</b>: A list which, if provided, will be populated with the field + paths of all missing required fields. + +##### Returns: + + True iff the specified message has all required fields set. + + +- - - + +#### `tf.summary.TaggedRunMetadata.ListFields()` {#TaggedRunMetadata.ListFields} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.MergeFrom(msg)` {#TaggedRunMetadata.MergeFrom} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.MergeFromString(serialized)` {#TaggedRunMetadata.MergeFromString} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.ParseFromString(serialized)` {#TaggedRunMetadata.ParseFromString} + +Parse serialized protocol buffer data into this message. + +Like MergeFromString(), except we clear the object first and +do not return the value that MergeFromString returns. + + +- - - + +#### `tf.summary.TaggedRunMetadata.RegisterExtension(extension_handle)` {#TaggedRunMetadata.RegisterExtension} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.SerializePartialToString()` {#TaggedRunMetadata.SerializePartialToString} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.SerializeToString()` {#TaggedRunMetadata.SerializeToString} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.SetInParent()` {#TaggedRunMetadata.SetInParent} + +Sets the _cached_byte_size_dirty bit to true, +and propagates this to our listener iff this was a state change. + + +- - - + +#### `tf.summary.TaggedRunMetadata.WhichOneof(oneof_name)` {#TaggedRunMetadata.WhichOneof} + +Returns the name of the currently set field inside a oneof, or None. + + +- - - + +#### `tf.summary.TaggedRunMetadata.__deepcopy__(memo=None)` {#TaggedRunMetadata.__deepcopy__} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.__eq__(other)` {#TaggedRunMetadata.__eq__} + + + + +- - - + #### `tf.summary.TaggedRunMetadata.__getstate__()` {#TaggedRunMetadata.__getstate__} Support the pickle protocol. +- - - + +#### `tf.summary.TaggedRunMetadata.__hash__()` {#TaggedRunMetadata.__hash__} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.__init__(**kwargs)` {#TaggedRunMetadata.__init__} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.__ne__(other_msg)` {#TaggedRunMetadata.__ne__} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.__repr__()` {#TaggedRunMetadata.__repr__} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.__setstate__(state)` {#TaggedRunMetadata.__setstate__} + +Support the pickle protocol. + + +- - - + +#### `tf.summary.TaggedRunMetadata.__str__()` {#TaggedRunMetadata.__str__} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.__unicode__()` {#TaggedRunMetadata.__unicode__} + + + + +- - - + +#### `tf.summary.TaggedRunMetadata.run_metadata` {#TaggedRunMetadata.run_metadata} + +Magic attribute generated for "run_metadata" proto field. + + +- - - + +#### `tf.summary.TaggedRunMetadata.tag` {#TaggedRunMetadata.tag} + +Magic attribute generated for "tag" proto field. + + diff --git a/tensorflow/g3doc/api_docs/python/test.md b/tensorflow/g3doc/api_docs/python/test.md index c95f971889..265e4028d0 100644 --- a/tensorflow/g3doc/api_docs/python/test.md +++ b/tensorflow/g3doc/api_docs/python/test.md @@ -215,125 +215,6 @@ Checks that for all elements of farray1 and farray2 - - - -#### `tf.test.TestCase.assertBetween(value, minv, maxv, msg=None)` {#TestCase.assertBetween} - -Asserts that value is between minv and maxv (inclusive). - - -- - - - -#### `tf.test.TestCase.assertCommandFails(command, regexes, env=None, close_fds=True, msg=None)` {#TestCase.assertCommandFails} - -Asserts a shell command fails and the error matches a regex in a list. - -##### Args: - - -* <b>`command`</b>: List or string representing the command to run. -* <b>`regexes`</b>: the list of regular expression strings. -* <b>`env`</b>: Dictionary of environment variable settings. -* <b>`close_fds`</b>: Whether or not to close all open fd's in the child after - forking. -* <b>`msg`</b>: Optional message to report on failure. - - -- - - - -#### `tf.test.TestCase.assertCommandSucceeds(command, regexes=('',), env=None, close_fds=True, msg=None)` {#TestCase.assertCommandSucceeds} - -Asserts that a shell command succeeds (i.e. exits with code 0). - -##### Args: - - -* <b>`command`</b>: List or string representing the command to run. -* <b>`regexes`</b>: List of regular expression byte strings that match success. -* <b>`env`</b>: Dictionary of environment variable settings. -* <b>`close_fds`</b>: Whether or not to close all open fd's in the child after - forking. -* <b>`msg`</b>: Optional message to report on failure. - - -- - - - -#### `tf.test.TestCase.assertContainsExactSubsequence(container, subsequence, msg=None)` {#TestCase.assertContainsExactSubsequence} - -Assert that "container" contains "subsequence" as an exact subsequence. - -Asserts that "container" contains all the elements of "subsequence", in -order, and without other elements interspersed. For example, [1, 2, 3] is an -exact subsequence of [0, 0, 1, 2, 3, 0] but not of [0, 0, 1, 2, 0, 3, 0]. - -##### Args: - - -* <b>`container`</b>: the list we're testing for subsequence inclusion. -* <b>`subsequence`</b>: the list we hope will be an exact subsequence of container. -* <b>`msg`</b>: Optional message to report on failure. - - -- - - - -#### `tf.test.TestCase.assertContainsInOrder(strings, target, msg=None)` {#TestCase.assertContainsInOrder} - -Asserts that the strings provided are found in the target in order. - -This may be useful for checking HTML output. - -##### Args: - - -* <b>`strings`</b>: A list of strings, such as [ 'fox', 'dog' ] -* <b>`target`</b>: A target string in which to look for the strings, such as - 'The quick brown fox jumped over the lazy dog'. -* <b>`msg`</b>: Optional message to report on failure. - - -- - - - -#### `tf.test.TestCase.assertContainsSubsequence(container, subsequence, msg=None)` {#TestCase.assertContainsSubsequence} - -Assert that "container" contains "subsequence" as a subsequence. - -Asserts that "container" contains all the elements of "subsequence", in -order, but possibly with other elements interspersed. For example, [1, 2, 3] -is a subsequence of [0, 0, 1, 2, 0, 3, 0] but not of [0, 0, 1, 3, 0, 2, 0]. - -##### Args: - - -* <b>`container`</b>: the list we're testing for subsequence inclusion. -* <b>`subsequence`</b>: the list we hope will be a subsequence of container. -* <b>`msg`</b>: Optional message to report on failure. - - -- - - - -#### `tf.test.TestCase.assertContainsSubset(expected_subset, actual_set, msg=None)` {#TestCase.assertContainsSubset} - -Checks whether actual iterable is a superset of expected iterable. - - -- - - - -#### `tf.test.TestCase.assertCountEqual(*args, **kwargs)` {#TestCase.assertCountEqual} - -An unordered sequence specific comparison. - -Equivalent to assertItemsEqual(). This method is a compatibility layer -for Python 3k, since 2to3 does not convert assertItemsEqual() calls into -assertCountEqual() calls. - -##### Args: - - -* <b>`expected_seq`</b>: A sequence containing elements we are expecting. -* <b>`actual_seq`</b>: The sequence that we are testing. -* <b>`msg`</b>: The message to be printed if the test fails. - - -- - - - #### `tf.test.TestCase.assertDeviceEqual(device1, device2)` {#TestCase.assertDeviceEqual} Asserts that the two given devices are the same. @@ -354,49 +235,10 @@ Checks whether actual is a superset of expected. - - - -#### `tf.test.TestCase.assertDictEqual(a, b, msg=None)` {#TestCase.assertDictEqual} +#### `tf.test.TestCase.assertDictEqual(d1, d2, msg=None)` {#TestCase.assertDictEqual} -Raises AssertionError if a and b are not equal dictionaries. - -##### Args: - - -* <b>`a`</b>: A dict, the expected value. -* <b>`b`</b>: A dict, the actual value. -* <b>`msg`</b>: An optional str, the associated message. - -##### Raises: - - -* <b>`AssertionError`</b>: if the dictionaries are not equal. - - -- - - - -#### `tf.test.TestCase.assertEmpty(container, msg=None)` {#TestCase.assertEmpty} - -Assert that an object has zero length. - -##### Args: - - -* <b>`container`</b>: Anything that implements the collections.Sized interface. -* <b>`msg`</b>: Optional message to report on failure. -- - - - -#### `tf.test.TestCase.assertEndsWith(actual, expected_end, msg=None)` {#TestCase.assertEndsWith} - -Assert that actual.endswith(expected_end) is True. - -##### Args: - - -* <b>`actual`</b>: str -* <b>`expected_end`</b>: str -* <b>`msg`</b>: Optional message to report on failure. - - - - @@ -480,11 +322,10 @@ Included for symmetry with assertIsNone. - - - -#### `tf.test.TestCase.assertItemsEqual(*args, **kwargs)` {#TestCase.assertItemsEqual} - -An unordered sequence specific comparison. +#### `tf.test.TestCase.assertItemsEqual(expected_seq, actual_seq, msg=None)` {#TestCase.assertItemsEqual} -It asserts that actual_seq and expected_seq have the same element counts. +An unordered sequence specific comparison. It asserts that +actual_seq and expected_seq have the same element counts. Equivalent to:: self.assertEqual(Counter(iter(actual_seq)), @@ -497,30 +338,6 @@ Asserts that each element has the same count in both sequences. - [0, 1, 1] and [1, 0, 1] compare equal. - [0, 0, 1] and [0, 1] compare unequal. -##### Args: - - -* <b>`expected_seq`</b>: A sequence containing elements we are expecting. -* <b>`actual_seq`</b>: The sequence that we are testing. -* <b>`msg`</b>: The message to be printed if the test fails. - - -- - - - -#### `tf.test.TestCase.assertJsonEqual(first, second, msg=None)` {#TestCase.assertJsonEqual} - -Asserts that the JSON objects defined in two strings are equal. - -A summary of the differences will be included in the failure message -using assertSameStructure. - -##### Args: - - -* <b>`first`</b>: A string contining JSON to decode and compare to second. -* <b>`second`</b>: A string contining JSON to decode and compare to first. -* <b>`msg`</b>: Additional text to include in the failure message. - - - - @@ -592,13 +409,6 @@ if not. - - - -#### `tf.test.TestCase.assertNoCommonElements(expected_seq, actual_seq, msg=None)` {#TestCase.assertNoCommonElements} - -Checks whether actual iterable and expected iterable are disjoint. - - -- - - - #### `tf.test.TestCase.assertNotAlmostEqual(first, second, places=None, msg=None, delta=None)` {#TestCase.assertNotAlmostEqual} Fail if the two objects are equal as determined by their @@ -629,33 +439,6 @@ Objects that are equal automatically fail. - - - -#### `tf.test.TestCase.assertNotEmpty(container, msg=None)` {#TestCase.assertNotEmpty} - -Assert that an object has non-zero length. - -##### Args: - - -* <b>`container`</b>: Anything that implements the collections.Sized interface. -* <b>`msg`</b>: Optional message to report on failure. - - -- - - - -#### `tf.test.TestCase.assertNotEndsWith(actual, unexpected_end, msg=None)` {#TestCase.assertNotEndsWith} - -Assert that actual.endswith(unexpected_end) is False. - -##### Args: - - -* <b>`actual`</b>: str -* <b>`unexpected_end`</b>: str -* <b>`msg`</b>: Optional message to report on failure. - - -- - - - #### `tf.test.TestCase.assertNotEqual(first, second, msg=None)` {#TestCase.assertNotEqual} Fail if the two objects are equal as determined by the '!=' @@ -693,20 +476,6 @@ Fail the test if the text matches the regular expression. - - - -#### `tf.test.TestCase.assertNotStartsWith(actual, unexpected_start, msg=None)` {#TestCase.assertNotStartsWith} - -Assert that actual.startswith(unexpected_start) is False. - -##### Args: - - -* <b>`actual`</b>: str -* <b>`unexpected_start`</b>: str -* <b>`msg`</b>: Optional message to report on failure. - - -- - - - #### `tf.test.TestCase.assertProtoEquals(expected_message_maybe_ascii, message)` {#TestCase.assertProtoEquals} Asserts that message is same as parsed expected_message_ascii. @@ -781,38 +550,6 @@ Asserts that the message in a raised exception matches a regexp. - - - -#### `tf.test.TestCase.assertRaisesWithLiteralMatch(expected_exception, expected_exception_message, callable_obj=None, *args, **kwargs)` {#TestCase.assertRaisesWithLiteralMatch} - -Asserts that the message in a raised exception equals the given string. - -Unlike assertRaisesRegexp, this method takes a literal string, not -a regular expression. - -with self.assertRaisesWithLiteralMatch(ExType, 'message'): - DoSomething() - -##### Args: - - -* <b>`expected_exception`</b>: Exception class expected to be raised. -* <b>`expected_exception_message`</b>: String message expected in the raised - exception. For a raise exception e, expected_exception_message must - equal str(e). -* <b>`callable_obj`</b>: Function to be called, or None to return a context. -* <b>`args`</b>: Extra args. -* <b>`kwargs`</b>: Extra kwargs. - -##### Returns: - - A context manager if callable_obj is None. Otherwise, None. - -##### Raises: - - self.failureException if callable_obj does not raise a macthing exception. - - -- - - - #### `tf.test.TestCase.assertRaisesWithPredicateMatch(exception_type, expected_err_re_or_predicate)` {#TestCase.assertRaisesWithPredicateMatch} Returns a context manager to enclose code expected to raise an exception. @@ -837,71 +574,6 @@ predicate search. - - - -#### `tf.test.TestCase.assertRaisesWithRegexpMatch(expected_exception, expected_regexp, callable_obj=None, *args, **kwargs)` {#TestCase.assertRaisesWithRegexpMatch} - -Asserts that the message in a raised exception matches the given regexp. - -This is just a wrapper around assertRaisesRegexp. Please use -assertRaisesRegexp instead of assertRaisesWithRegexpMatch. - -##### Args: - - -* <b>`expected_exception`</b>: Exception class expected to be raised. -* <b>`expected_regexp`</b>: Regexp (re pattern object or string) expected to be - found in error message. -* <b>`callable_obj`</b>: Function to be called, or None to return a context. -* <b>`args`</b>: Extra args. -* <b>`kwargs`</b>: Extra keyword args. - -##### Returns: - - A context manager if callable_obj is None. Otherwise, None. - -##### Raises: - - self.failureException if callable_obj does not raise a macthing exception. - - -- - - - -#### `tf.test.TestCase.assertRegexMatch(actual_str, regexes, message=None)` {#TestCase.assertRegexMatch} - -Asserts that at least one regex in regexes matches str. - - If possible you should use assertRegexpMatches, which is a simpler - version of this method. assertRegexpMatches takes a single regular - expression (a string or re compiled object) instead of a list. - - Notes: - 1. This function uses substring matching, i.e. the matching - succeeds if *any* substring of the error message matches *any* - regex in the list. This is more convenient for the user than - full-string matching. - - 2. If regexes is the empty list, the matching will always fail. - - 3. Use regexes=[''] for a regex that will always pass. - - 4. '.' matches any single character *except* the newline. To - match any character, use '(.| -)'. - - 5. '^' matches the beginning of each line, not just the beginning - of the string. Similarly, '$' matches the end of each line. - - 6. An exception will be thrown if regexes contains an invalid - regex. - - Args: - actual_str: The string we try to match with the items in regexes. - regexes: The regular expressions we want to match against str. - See "Notes" above for detailed notes on how this is interpreted. - message: The message to be printed if the test fails. - - -- - - - #### `tf.test.TestCase.assertRegexpMatches(text, expected_regexp, msg=None)` {#TestCase.assertRegexpMatches} Fail the test unless the text matches the regular expression. @@ -909,79 +581,6 @@ Fail the test unless the text matches the regular expression. - - - -#### `tf.test.TestCase.assertSameElements(expected_seq, actual_seq, msg=None)` {#TestCase.assertSameElements} - -Assert that two sequences have the same elements (in any order). - -This method, unlike assertItemsEqual, doesn't care about any -duplicates in the expected and actual sequences. - - >> assertSameElements([1, 1, 1, 0, 0, 0], [0, 1]) - # Doesn't raise an AssertionError - -If possible, you should use assertItemsEqual instead of -assertSameElements. - -##### Args: - - -* <b>`expected_seq`</b>: A sequence containing elements we are expecting. -* <b>`actual_seq`</b>: The sequence that we are testing. -* <b>`msg`</b>: The message to be printed if the test fails. - - -- - - - -#### `tf.test.TestCase.assertSameStructure(a, b, aname='a', bname='b', msg=None)` {#TestCase.assertSameStructure} - -Asserts that two values contain the same structural content. - -The two arguments should be data trees consisting of trees of dicts and -lists. They will be deeply compared by walking into the contents of dicts -and lists; other items will be compared using the == operator. -If the two structures differ in content, the failure message will indicate -the location within the structures where the first difference is found. -This may be helpful when comparing large structures. - -##### Args: - - -* <b>`a`</b>: The first structure to compare. -* <b>`b`</b>: The second structure to compare. -* <b>`aname`</b>: Variable name to use for the first structure in assertion messages. -* <b>`bname`</b>: Variable name to use for the second structure. -* <b>`msg`</b>: Additional text to include in the failure message. - - -- - - - -#### `tf.test.TestCase.assertSequenceAlmostEqual(expected_seq, actual_seq, places=None, msg=None, delta=None)` {#TestCase.assertSequenceAlmostEqual} - -An approximate equality assertion for ordered sequences. - -Fail if the two sequences are unequal as determined by their value -differences rounded to the given number of decimal places (default 7) and -comparing to zero, or by comparing that the difference between each value -in the two sequences is more than the given delta. - -Note that decimal places (from zero) are usually not the same as significant -digits (measured from the most signficant digit). - -If the two sequences compare equal then they will automatically compare -almost equal. - -##### Args: - - -* <b>`expected_seq`</b>: A sequence containing elements we are expecting. -* <b>`actual_seq`</b>: The sequence that we are testing. -* <b>`places`</b>: The number of decimal places to compare. -* <b>`msg`</b>: The message to be printed if the test fails. -* <b>`delta`</b>: The OK difference between compared values. - - -- - - - #### `tf.test.TestCase.assertSequenceEqual(seq1, seq2, msg=None, seq_type=None)` {#TestCase.assertSequenceEqual} An equality assertion for ordered sequences (like lists and tuples). @@ -1002,26 +601,6 @@ which can be indexed, has a length, and has an equality operator. - - - -#### `tf.test.TestCase.assertSequenceStartsWith(prefix, whole, msg=None)` {#TestCase.assertSequenceStartsWith} - -An equality assertion for the beginning of ordered sequences. - -If prefix is an empty sequence, it will raise an error unless whole is also -an empty sequence. - -If prefix is not a sequence, it will raise an error if the first element of -whole does not match. - -##### Args: - - -* <b>`prefix`</b>: A sequence expected at the beginning of the whole parameter. -* <b>`whole`</b>: The sequence in which to look for prefix. -* <b>`msg`</b>: Optional message to report on failure. - - -- - - - #### `tf.test.TestCase.assertSetEqual(set1, set2, msg=None)` {#TestCase.assertSetEqual} A set-specific equality assertion. @@ -1073,51 +652,6 @@ Assert that actual.startswith(expected_start) is True. - - - -#### `tf.test.TestCase.assertTotallyOrdered(*groups, **kwargs)` {#TestCase.assertTotallyOrdered} - -Asserts that total ordering has been implemented correctly. - -For example, say you have a class A that compares only on its attribute x. -Comparators other than __lt__ are omitted for brevity. - -class A(object): - def __init__(self, x, y): - self.x = x - self.y = y - - def __hash__(self): - return hash(self.x) - - def __lt__(self, other): - try: - return self.x < other.x - except AttributeError: - return NotImplemented - -assertTotallyOrdered will check that instances can be ordered correctly. -For example, - -self.assertTotallyOrdered( - [None], # None should come before everything else. - [1], # Integers sort earlier. - [A(1, 'a')], - [A(2, 'b')], # 2 is after 1. - [A(3, 'c'), A(3, 'd')], # The second argument is irrelevant. - [A(4, 'z')], - ['foo']) # Strings sort last. - -##### Args: - - -* <b>`*groups`</b>: A list of groups of elements. Each group of elements is a list - of objects that are equal. The elements in each group must be less than - the elements in the group after it. For example, these groups are - totally ordered: [None], [1], [2, 2], [3]. -* <b>`**kwargs`</b>: optional msg keyword argument can be passed. - - -- - - - #### `tf.test.TestCase.assertTrue(expr, msg=None)` {#TestCase.assertTrue} Check that the expression is true. @@ -1140,13 +674,6 @@ A tuple-specific equality assertion. - - - -#### `tf.test.TestCase.assertUrlEqual(a, b, msg=None)` {#TestCase.assertUrlEqual} - -Asserts that urls are equal, ignoring ordering of query params. - - -- - - - #### `tf.test.TestCase.assert_(expr, msg=None)` {#TestCase.assert_} Check that the expression is true. @@ -1206,9 +733,9 @@ tearDown. - - - -#### `tf.test.TestCase.fail(msg=None, prefix=None)` {#TestCase.fail} +#### `tf.test.TestCase.fail(msg=None)` {#TestCase.fail} -Fail immediately with the given message, optionally prefixed. +Fail immediately, with the given message. - - - @@ -1262,13 +789,6 @@ Fail immediately with the given message, optionally prefixed. - - - -#### `tf.test.TestCase.getRecordedProperties()` {#TestCase.getRecordedProperties} - -Return any properties that the user has recorded. - - -- - - - #### `tf.test.TestCase.get_temp_dir()` {#TestCase.get_temp_dir} Returns a unique temporary directory for the test to use. @@ -1291,20 +811,6 @@ pollute each others environment. - - - -#### `tf.test.TestCase.recordProperty(property_name, property_value)` {#TestCase.recordProperty} - -Record an arbitrary property for later use. - -##### Args: - - -* <b>`property_name`</b>: str, name of property to record; must be a valid XML - attribute name -* <b>`property_value`</b>: value of property; must be valid XML attribute value - - -- - - - #### `tf.test.TestCase.run(result=None)` {#TestCase.run} @@ -1328,18 +834,11 @@ Hook method for setting up class fixture before running tests in the class. #### `tf.test.TestCase.shortDescription()` {#TestCase.shortDescription} -Format both the test method name and the first line of its docstring. - -If no docstring is given, only returns the method name. - -This method overrides unittest.TestCase.shortDescription(), which -only returns the first line of the docstring, obscuring the name -of the test upon failure. - -##### Returns: - +Returns a one-line description of the test, or None if no +description has been provided. -* <b>`desc`</b>: A short description of a test method. +The default implementation of this method returns the first line of +the specified test method's docstring. - - - diff --git a/tensorflow/python/framework/tensor_util_test.py b/tensorflow/python/framework/tensor_util_test.py index 16aab707e7..b5dab1ebff 100644 --- a/tensorflow/python/framework/tensor_util_test.py +++ b/tensorflow/python/framework/tensor_util_test.py @@ -19,6 +19,7 @@ from __future__ import division from __future__ import print_function import numpy as np +import sys from tensorflow.python.framework import constant_op from tensorflow.python.framework import dtypes @@ -46,33 +47,54 @@ class TensorUtilTest(test.TestCase): def testFloatN(self): t = tensor_util.make_tensor_proto([10.0, 20.0, 30.0]) - self.assertProtoEquals(""" - dtype: DT_FLOAT - tensor_shape { dim { size: 3 } } - tensor_content: "\000\000 A\000\000\240A\000\000\360A" - """, t) + if sys.byteorder == "big": + self.assertProtoEquals(""" + dtype: DT_FLOAT + tensor_shape { dim { size: 3 } } + tensor_content: "A \000\000A\240\000\000A\360\000\000" + """, t) + else: + self.assertProtoEquals(""" + dtype: DT_FLOAT + tensor_shape { dim { size: 3 } } + tensor_content: "\000\000 A\000\000\240A\000\000\360A" + """, t) a = tensor_util.MakeNdarray(t) self.assertEquals(np.float32, a.dtype) self.assertAllClose(np.array([10.0, 20.0, 30.0], dtype=np.float32), a) def testFloatTyped(self): t = tensor_util.make_tensor_proto([10.0, 20.0, 30.0], dtype=dtypes.float32) - self.assertProtoEquals(""" - dtype: DT_FLOAT - tensor_shape { dim { size: 3 } } - tensor_content: "\000\000 A\000\000\240A\000\000\360A" - """, t) + if sys.byteorder == "big": + self.assertProtoEquals(""" + dtype: DT_FLOAT + tensor_shape { dim { size: 3 } } + tensor_content: "A \000\000A\240\000\000A\360\000\000" + """, t) + else: + self.assertProtoEquals(""" + dtype: DT_FLOAT + tensor_shape { dim { size: 3 } } + tensor_content: "\000\000 A\000\000\240A\000\000\360A" + """, t) a = tensor_util.MakeNdarray(t) self.assertEquals(np.float32, a.dtype) self.assertAllClose(np.array([10.0, 20.0, 30.0], dtype=np.float32), a) def testFloatTypeCoerce(self): t = tensor_util.make_tensor_proto([10, 20, 30], dtype=dtypes.float32) - self.assertProtoEquals(""" - dtype: DT_FLOAT - tensor_shape { dim { size: 3 } } - tensor_content: "\000\000 A\000\000\240A\000\000\360A" - """, t) + if sys.byteorder == "big": + self.assertProtoEquals(""" + dtype: DT_FLOAT + tensor_shape { dim { size: 3 } } + tensor_content: "A \000\000A\240\000\000A\360\000\000" + """, t) + else: + self.assertProtoEquals(""" + dtype: DT_FLOAT + tensor_shape { dim { size: 3 } } + tensor_content: "\000\000 A\000\000\240A\000\000\360A" + """, t) a = tensor_util.MakeNdarray(t) self.assertEquals(np.float32, a.dtype) self.assertAllClose(np.array([10.0, 20.0, 30.0], dtype=np.float32), a) @@ -80,33 +102,54 @@ class TensorUtilTest(test.TestCase): def testFloatTypeCoerceNdarray(self): arr = np.asarray([10, 20, 30], dtype="int") t = tensor_util.make_tensor_proto(arr, dtype=dtypes.float32) - self.assertProtoEquals(""" - dtype: DT_FLOAT - tensor_shape { dim { size: 3 } } - tensor_content: "\000\000 A\000\000\240A\000\000\360A" - """, t) + if sys.byteorder == "big": + self.assertProtoEquals(""" + dtype: DT_FLOAT + tensor_shape { dim { size: 3 } } + tensor_content: "A \000\000A\240\000\000A\360\000\000" + """, t) + else: + self.assertProtoEquals(""" + dtype: DT_FLOAT + tensor_shape { dim { size: 3 } } + tensor_content: "\000\000 A\000\000\240A\000\000\360A" + """, t) a = tensor_util.MakeNdarray(t) self.assertEquals(np.float32, a.dtype) self.assertAllClose(np.array([10.0, 20.0, 30.0], dtype=np.float32), a) def testFloatSizes(self): t = tensor_util.make_tensor_proto([10.0, 20.0, 30.0], shape=[1, 3]) - self.assertProtoEquals(""" - dtype: DT_FLOAT - tensor_shape { dim { size: 1 } dim { size: 3 } } - tensor_content: "\000\000 A\000\000\240A\000\000\360A" - """, t) + if sys.byteorder == "big": + self.assertProtoEquals(""" + dtype: DT_FLOAT + tensor_shape { dim { size: 1 } dim { size: 3 } } + tensor_content: "A \000\000A\240\000\000A\360\000\000" + """, t) + else: + self.assertProtoEquals(""" + dtype: DT_FLOAT + tensor_shape { dim { size: 1 } dim { size: 3 } } + tensor_content: "\000\000 A\000\000\240A\000\000\360A" + """, t) a = tensor_util.MakeNdarray(t) self.assertEquals(np.float32, a.dtype) self.assertAllClose(np.array([[10.0, 20.0, 30.0]], dtype=np.float32), a) def testFloatSizes2(self): t = tensor_util.make_tensor_proto([10.0, 20.0, 30.0], shape=[3, 1]) - self.assertProtoEquals(""" - dtype: DT_FLOAT - tensor_shape { dim { size: 3 } dim { size: 1 } } - tensor_content: "\000\000 A\000\000\240A\000\000\360A" - """, t) + if sys.byteorder == "big": + self.assertProtoEquals(""" + dtype: DT_FLOAT + tensor_shape { dim { size: 3 } dim { size: 1 } } + tensor_content: "A \000\000A\240\000\000A\360\000\000" + """, t) + else: + self.assertProtoEquals(""" + dtype: DT_FLOAT + tensor_shape { dim { size: 3 } dim { size: 1 } } + tensor_content: "\000\000 A\000\000\240A\000\000\360A" + """, t) a = tensor_util.MakeNdarray(t) self.assertEquals(np.float32, a.dtype) self.assertAllClose(np.array([[10.0], [20.0], [30.0]], dtype=np.float32), a) @@ -123,11 +166,18 @@ class TensorUtilTest(test.TestCase): def testFloatNpArrayFloat64(self): t = tensor_util.make_tensor_proto( np.array([[10.0, 20.0, 30.0]], dtype=np.float64)) - self.assertProtoEquals(""" - dtype: DT_DOUBLE - tensor_shape { dim { size: 1 } dim { size: 3 } } - tensor_content: "\000\000\000\000\000\000$@\000\000\000\000\000\0004@\000\000\000\000\000\000>@" - """, t) + if sys.byteorder == "big": + self.assertProtoEquals(""" + dtype: DT_DOUBLE + tensor_shape { dim { size: 1 } dim { size: 3 } } + tensor_content: "@$\000\000\000\000\000\000@4\000\000\000\000\000\000@>\000\000\000\000\000\000" + """, t) + else: + self.assertProtoEquals(""" + dtype: DT_DOUBLE + tensor_shape { dim { size: 1 } dim { size: 3 } } + tensor_content: "\000\000\000\000\000\000$@\000\000\000\000\000\0004@\000\000\000\000\000\000>@" + """, t) a = tensor_util.MakeNdarray(t) self.assertEquals(np.float64, a.dtype) self.assertAllClose( @@ -207,11 +257,18 @@ class TensorUtilTest(test.TestCase): def testIntNDefaultType(self): t = tensor_util.make_tensor_proto([10, 20, 30, 40], shape=[2, 2]) - self.assertProtoEquals(""" - dtype: DT_INT32 - tensor_shape { dim { size: 2 } dim { size: 2 } } - tensor_content: "\\n\000\000\000\024\000\000\000\036\000\000\000(\000\000\000" - """, t) + if sys.byteorder == "big": + self.assertProtoEquals(""" + dtype: DT_INT32 + tensor_shape { dim { size: 2 } dim { size: 2 } } + tensor_content: "\000\000\000\\n\000\000\000\024\000\000\000\036\000\000\000(" + """, t) + else: + self.assertProtoEquals(""" + dtype: DT_INT32 + tensor_shape { dim { size: 2 } dim { size: 2 } } + tensor_content: "\\n\000\000\000\024\000\000\000\036\000\000\000(\000\000\000" + """, t) a = tensor_util.MakeNdarray(t) self.assertEquals(np.int32, a.dtype) self.assertAllClose(np.array([[10, 20], [30, 40]], dtype=np.int32), a) @@ -270,22 +327,36 @@ class TensorUtilTest(test.TestCase): def testLongN(self): t = tensor_util.make_tensor_proto( [10, 20, 30], shape=[1, 3], dtype=dtypes.int64) - self.assertProtoEquals(""" - dtype: DT_INT64 - tensor_shape { dim { size: 1 } dim { size: 3 } } - tensor_content: "\\n\000\000\000\000\000\000\000\024\000\000\000\000\000\000\000\036\000\000\000\000\000\000\000" - """, t) + if sys.byteorder == "big": + self.assertProtoEquals(""" + dtype: DT_INT64 + tensor_shape { dim { size: 1 } dim { size: 3 } } + tensor_content: "\000\000\000\000\000\000\000\\n\000\000\000\000\000\000\000\024\000\000\000\000\000\000\000\036" + """, t) + else: + self.assertProtoEquals(""" + dtype: DT_INT64 + tensor_shape { dim { size: 1 } dim { size: 3 } } + tensor_content: "\\n\000\000\000\000\000\000\000\024\000\000\000\000\000\000\000\036\000\000\000\000\000\000\000" + """, t) a = tensor_util.MakeNdarray(t) self.assertEquals(np.int64, a.dtype) self.assertAllClose(np.array([[10, 20, 30]], dtype=np.int64), a) def testLongNpArray(self): t = tensor_util.make_tensor_proto(np.array([10, 20, 30])) - self.assertProtoEquals(""" - dtype: DT_INT64 - tensor_shape { dim { size: 3 } } - tensor_content: "\\n\000\000\000\000\000\000\000\024\000\000\000\000\000\000\000\036\000\000\000\000\000\000\000" - """, t) + if sys.byteorder == "big": + self.assertProtoEquals(""" + dtype: DT_INT64 + tensor_shape { dim { size: 3 } } + tensor_content: "\000\000\000\000\000\000\000\\n\000\000\000\000\000\000\000\024\000\000\000\000\000\000\000\036" + """, t) + else: + self.assertProtoEquals(""" + dtype: DT_INT64 + tensor_shape { dim { size: 3 } } + tensor_content: "\\n\000\000\000\000\000\000\000\024\000\000\000\000\000\000\000\036\000\000\000\000\000\000\000" + """, t) a = tensor_util.MakeNdarray(t) self.assertEquals(np.int64, a.dtype) self.assertAllClose(np.array([10, 20, 30], dtype=np.int64), a) @@ -295,11 +366,18 @@ class TensorUtilTest(test.TestCase): data = [(21,), (22,), (23,)] t = tensor_util.make_tensor_proto(data, dtype=dtypes.qint32) - self.assertProtoEquals(""" - dtype: DT_QINT32 - tensor_shape { dim { size: 3 } } - tensor_content: "\025\000\000\000\026\000\000\000\027\000\000\000" - """, t) + if sys.byteorder == "big": + self.assertProtoEquals(""" + dtype: DT_QINT32 + tensor_shape { dim { size: 3 } } + tensor_content: "\000\000\000\025\000\000\000\026\000\000\000\027" + """, t) + else: + self.assertProtoEquals(""" + dtype: DT_QINT32 + tensor_shape { dim { size: 3 } } + tensor_content: "\025\000\000\000\026\000\000\000\027\000\000\000" + """, t) a = tensor_util.MakeNdarray(t) self.assertEquals(dtypes.qint32.as_numpy_dtype, a.dtype) self.assertAllEqual(np.array(data, dtype=a.dtype), a) @@ -325,21 +403,35 @@ class TensorUtilTest(test.TestCase): self.assertAllEqual(np.array(data, dtype=a.dtype), a) t = tensor_util.make_tensor_proto(data, dtype=dtypes.quint16) - self.assertProtoEquals(""" - dtype: DT_QUINT16 - tensor_shape { dim { size: 3 } } - tensor_content: "\025\000\026\000\027\000" - """, t) + if sys.byteorder == "big": + self.assertProtoEquals(""" + dtype: DT_QUINT16 + tensor_shape { dim { size: 3 } } + tensor_content: "\000\025\000\026\000\027" + """, t) + else: + self.assertProtoEquals(""" + dtype: DT_QUINT16 + tensor_shape { dim { size: 3 } } + tensor_content: "\025\000\026\000\027\000" + """, t) a = tensor_util.MakeNdarray(t) self.assertEquals(dtypes.quint16.as_numpy_dtype, a.dtype) self.assertAllEqual(np.array(data, dtype=a.dtype), a) t = tensor_util.make_tensor_proto(data, dtype=dtypes.qint16) - self.assertProtoEquals(""" - dtype: DT_QINT16 - tensor_shape { dim { size: 3 } } - tensor_content: "\025\000\026\000\027\000" - """, t) + if sys.byteorder == "big": + self.assertProtoEquals(""" + dtype: DT_QINT16 + tensor_shape { dim { size: 3 } } + tensor_content: "\000\025\000\026\000\027" + """, t) + else: + self.assertProtoEquals(""" + dtype: DT_QINT16 + tensor_shape { dim { size: 3 } } + tensor_content: "\025\000\026\000\027\000" + """, t) a = tensor_util.MakeNdarray(t) self.assertEquals(dtypes.qint16.as_numpy_dtype, a.dtype) self.assertAllEqual(np.array(data, dtype=a.dtype), a) diff --git a/tensorflow/python/kernel_tests/cast_op_test.py b/tensorflow/python/kernel_tests/cast_op_test.py index 30416a8bc6..17771e0572 100644 --- a/tensorflow/python/kernel_tests/cast_op_test.py +++ b/tensorflow/python/kernel_tests/cast_op_test.py @@ -19,6 +19,7 @@ from __future__ import division from __future__ import print_function import numpy as np +import sys from tensorflow.python.framework import constant_op from tensorflow.python.framework import dtypes @@ -142,8 +143,12 @@ class CastOpTest(test.TestCase): self._compare(np.inf, np.float32, np.inf, False) self._compare(np.inf, np.float64, np.inf, False) - self._compare(np.inf, np.int32, i4.min, False) - self._compare(np.inf, np.int64, i8.min, False) + if sys.byteorder == "big": + self._compare(np.inf, np.int32, i4.max, False) + self._compare(np.inf, np.int64, i8.max, False) + else: + self._compare(np.inf, np.int32, i4.min, False) + self._compare(np.inf, np.int64, i8.min, False) self._compare(-np.inf, np.float32, -np.inf, False) self._compare(-np.inf, np.float64, -np.inf, False) self._compare(-np.inf, np.int32, i4.min, False) diff --git a/tensorflow/python/layers/normalization.py b/tensorflow/python/layers/normalization.py index ac5aef7de9..fcbc69f2c5 100644 --- a/tensorflow/python/layers/normalization.py +++ b/tensorflow/python/layers/normalization.py @@ -55,7 +55,8 @@ class BatchNormalization(base._Layer): # pylint: disable=protected-access `data_format="channels_first"`, set `axis=1` in `BatchNormalization`. momentum: Momentum for the moving average. epsilon: Small float added to variance to avoid dividing by zero. - center: If True, subtract `beta`. If False, `beta` is ignored. + center: If True, add offset of `beta` to normalized tensor. If False, `beta` + is ignored. scale: If True, multiply by `gamma`. If False, `gamma` is not used. When the next layer is linear (also e.g. `nn.relu`), this can be disabled since the scaling can be done by the next layer. @@ -273,7 +274,8 @@ def batch_normalization(inputs, `data_format="channels_first"`, set `axis=1` in `BatchNormalization`. momentum: Momentum for the moving average. epsilon: Small float added to variance to avoid dividing by zero. - center: If True, subtract `beta`. If False, `beta` is ignored. + center: If True, add offset of `beta` to normalized tensor. If False, `beta` + is ignored. scale: If True, multiply by `gamma`. If False, `gamma` is not used. When the next layer is linear (also e.g. `nn.relu`), this can be disabled since the scaling can be done by the next layer. diff --git a/tensorflow/python/ops/image_ops.py b/tensorflow/python/ops/image_ops.py index f11db98ed3..f97a240acb 100644 --- a/tensorflow/python/ops/image_ops.py +++ b/tensorflow/python/ops/image_ops.py @@ -162,6 +162,10 @@ type and representation (RGB or HSV). @@draw_bounding_boxes @@non_max_suppression @@sample_distorted_bounding_box + +## Denoising + +@@total_variation """ from __future__ import absolute_import from __future__ import division diff --git a/tensorflow/python/ops/image_ops_impl.py b/tensorflow/python/ops/image_ops_impl.py index 2ca9be6187..d2f373ed12 100644 --- a/tensorflow/python/ops/image_ops_impl.py +++ b/tensorflow/python/ops/image_ops_impl.py @@ -1269,3 +1269,73 @@ def decode_image(contents, channels=None, name=None): is_jpeg = math_ops.equal(substr, b'\xff\xd8\xff\xe0', name='is_jpeg') return control_flow_ops.cond(is_jpeg, _jpeg, check_png, name='cond_jpeg') + + +def total_variation(images, name=None): + """Calculate and return the total variation for one or more images. + + The total variation is the sum of the absolute differences for neighboring + pixel-values in the input images. This measures how much noise is in the + images. + + This can be used as a loss-function during optimization so as to suppress + noise in images. If you have a batch of images, then you should calculate + the scalar loss-value as the sum: + `loss = tf.reduce_sum(tf.image.total_variation(images))` + + This implements the anisotropic 2-D version of the formula described here: + + https://en.wikipedia.org/wiki/Total_variation_denoising + + Args: + images: 4-D Tensor of shape `[batch, height, width, channels]` or + 3-D Tensor of shape `[height, width, channels]`. + + name: A name for the operation (optional). + + Raises: + ValueError: if images.shape is not a 3-D or 4-D vector. + + Returns: + The total variation of `images`. + + If `images` was 4-D, return a 1-D float Tensor of shape `[batch]` with the + total variation for each image in the batch. + If `images` was 3-D, return a scalar float with the total variation for + that image. + """ + + with ops.name_scope(name, 'total_variation'): + ndims = images.get_shape().ndims + + if ndims == 3: + # The input is a single image with shape [height, width, channels]. + + # Calculate the difference of neighboring pixel-values. + # The images are shifted one pixel along the height and width by slicing. + pixel_dif1 = images[1:, :, :] - images[:-1, :, :] + pixel_dif2 = images[:, 1:, :] - images[:, :-1, :] + + # Sum for all axis. (None is an alias for all axis.) + sum_axis = None + elif ndims == 4: + # The input is a batch of images with shape: + # [batch, height, width, channels]. + + # Calculate the difference of neighboring pixel-values. + # The images are shifted one pixel along the height and width by slicing. + pixel_dif1 = images[:, 1:, :, :] - images[:, :-1, :, :] + pixel_dif2 = images[:, :, 1:, :] - images[:, :, :-1, :] + + # Only sum for the last 3 axis. + # This results in a 1-D tensor with the total variation for each image. + sum_axis = [1, 2, 3] + else: + raise ValueError('\'images\' must be either 3 or 4-dimensional.') + + # Calculate the total variation by taking the absolute value of the + # pixel-differences and summing over the appropriate axis. + tot_var = math_ops.reduce_sum(math_ops.abs(pixel_dif1), axis=sum_axis) + \ + math_ops.reduce_sum(math_ops.abs(pixel_dif2), axis=sum_axis) + + return tot_var diff --git a/tensorflow/python/ops/image_ops_test.py b/tensorflow/python/ops/image_ops_test.py index 03cf74ae21..b6da60770d 100644 --- a/tensorflow/python/ops/image_ops_test.py +++ b/tensorflow/python/ops/image_ops_test.py @@ -2405,5 +2405,186 @@ class ConvertImageTest(test_util.TensorFlowTestCase): [0, 255 * 256]) +class TotalVariationTest(test_util.TensorFlowTestCase): + """Tests the function total_variation() in image_ops. + + We test a few small handmade examples, as well as + some larger examples using an equivalent numpy + implementation of the total_variation() function. + + We do NOT test for overflows and invalid / edge-case arguments. + """ + + def _test(self, x_np, y_np): + """Test that the TensorFlow implementation of + total_variation(x_np) calculates the values in y_np. + + Note that these may be float-numbers so we only test + for approximate equality within some narrow error-bound. + """ + + # Create a TensorFlow session. + with self.test_session(use_gpu=True): + # Add a constant to the TensorFlow graph that holds the input. + x_tf = constant_op.constant(x_np, shape=x_np.shape) + + # Add ops for calculating the total variation using TensorFlow. + y = image_ops.total_variation(images=x_tf) + + # Run the TensorFlow session to calculate the result. + y_tf = y.eval() + + # Assert that the results are as expected within + # some small error-bound in case they are float-values. + self.assertAllClose(y_tf, y_np) + + def _total_variation_np(self, x_np): + """Calculate the total variation of x_np using numpy. + This implements the same function as TensorFlow but + using numpy instead. + + Args: + x_np: Numpy array with 3 or 4 dimensions. + """ + + dim = len(x_np.shape) + + if dim == 3: + # Calculate differences for neighboring pixel-values using slices. + dif1 = x_np[1:, :, :] - x_np[:-1, :, :] + dif2 = x_np[:, 1:, :] - x_np[:, :-1, :] + + # Sum for all axis. + sum_axis = None + elif dim == 4: + # Calculate differences for neighboring pixel-values using slices. + dif1 = x_np[:, 1:, :, :] - x_np[:, :-1, :, :] + dif2 = x_np[:, :, 1:, :] - x_np[:, :, :-1, :] + + # Only sum for the last 3 axis. + sum_axis = (1, 2, 3) + else: + # This should not occur in this test-code. + pass + + tot_var = np.sum(np.abs(dif1), axis=sum_axis) + \ + np.sum(np.abs(dif2), axis=sum_axis) + + return tot_var + + def _test_tensorflow_vs_numpy(self, x_np): + """Test the TensorFlow implementation against a numpy implementation. + + Args: + x_np: Numpy array with 3 or 4 dimensions. + """ + + # Calculate the y-values using the numpy implementation. + y_np = self._total_variation_np(x_np) + + self._test(x_np, y_np) + + def _generateArray(self, shape): + """Generate an array of the given shape for use in testing. + The numbers are calculated as the cumulative sum, which + causes the difference between neighboring numbers to vary.""" + + # Flattened length of the array. + flat_len = np.prod(shape) + + a = np.array(range(flat_len), dtype=int) + a = np.cumsum(a) + a = a.reshape(shape) + + return a + + def testTotalVariationNumpy(self): + """Test the TensorFlow implementation against a numpy implementation. + The two implementations are very similar so it is possible that both + have the same bug, which would not be detected by this test. It is + therefore necessary to test with manually crafted data as well.""" + + # Generate a test-array. + # This is an 'image' with 100x80 pixels and 3 color channels. + a = self._generateArray(shape=(100, 80, 3)) + + # Test the TensorFlow implementation vs. numpy implementation. + # We use a numpy implementation to check the results that are + # calculated using TensorFlow are correct. + self._test_tensorflow_vs_numpy(a) + self._test_tensorflow_vs_numpy(a + 1) + self._test_tensorflow_vs_numpy(-a) + self._test_tensorflow_vs_numpy(1.1 * a) + + # Expand to a 4-dim array. + b = a[np.newaxis, :] + + # Combine several variations of the image into a single 4-dim array. + multi = np.vstack((b, b + 1, -b, 1.1 * b)) + + # Test that the TensorFlow function can also handle 4-dim arrays. + self._test_tensorflow_vs_numpy(multi) + + def testTotalVariationHandmade(self): + """Test the total variation for a few handmade examples.""" + + # We create an image that is 2x2 pixels with 3 color channels. + # The image is very small so we can check the result by hand. + + # Red color channel. + # The following are the sum of absolute differences between the pixels. + # sum row dif = (4-1) + (7-2) = 3 + 5 = 8 + # sum col dif = (2-1) + (7-4) = 1 + 3 = 4 + r = [[1, 2], + [4, 7]] + + # Blue color channel. + # sum row dif = 18 + 29 = 47 + # sum col dif = 7 + 18 = 25 + g = [[11, 18], + [29, 47]] + + # Green color channel. + # sum row dif = 120 + 193 = 313 + # sum col dif = 47 + 120 = 167 + b = [[73, 120], + [193, 313]] + + # Combine the 3 color channels into a single 3-dim array. + # The shape is (2, 2, 3) corresponding to (height, width and color). + a = np.dstack((r, g, b)) + + # Total variation for this image. + # Sum of all pixel differences = 8 + 4 + 47 + 25 + 313 + 167 = 564 + tot_var = 564 + + # Calculate the total variation using TensorFlow and assert it is correct. + self._test(a, tot_var) + + # If we add 1 to all pixel-values then the total variation is unchanged. + self._test(a + 1, tot_var) + + # If we negate all pixel-values then the total variation is unchanged. + self._test(-a, tot_var) + + # Scale the pixel-values by a float. This scales the total variation as well. + b = 1.1 * a + self._test(b, 1.1 * tot_var) + + # Scale by another float. + c = 1.2 * a + self._test(c, 1.2 * tot_var) + + # Combine these 3 images into a single array of shape (3, 2, 2, 3) + # where the first dimension is for the image-number. + multi = np.vstack((a[np.newaxis, :], + b[np.newaxis, :], + c[np.newaxis, :])) + + # Check that TensorFlow correctly calculates the total variation + # for each image individually and returns the correct array. + self._test(multi, tot_var * np.array([1.0, 1.1, 1.2])) + + if __name__ == '__main__': googletest.main() diff --git a/tensorflow/python/ops/math_grad.py b/tensorflow/python/ops/math_grad.py index 6f4473885e..e0232b35f0 100644 --- a/tensorflow/python/ops/math_grad.py +++ b/tensorflow/python/ops/math_grad.py @@ -628,7 +628,7 @@ def _DivGrad(op, grad): y = math_ops.conj(y) return (array_ops.reshape(math_ops.reduce_sum(math_ops.div(grad, y), rx), sx), array_ops.reshape( - math_ops.reduce_sum(grad * math_ops.div(-x, math_ops.square(y)), + math_ops.reduce_sum(grad * math_ops.div(math_ops.div(-x, y), y), ry), sy)) @@ -658,7 +658,7 @@ def _RealDivGrad(op, grad): return (array_ops.reshape( math_ops.reduce_sum(math_ops.realdiv(grad, y), rx), sx), array_ops.reshape( - math_ops.reduce_sum(grad * math_ops.realdiv(-x, math_ops.square(y)), + math_ops.reduce_sum(grad * math_ops.realdiv(math_ops.realdiv(-x, y), y), ry), sy)) diff --git a/third_party/eigen3/unsupported/Eigen/CXX11/FixedPoint b/third_party/eigen3/unsupported/Eigen/CXX11/FixedPoint index 8e55a1f3e8..b0a73aac79 100644 --- a/third_party/eigen3/unsupported/Eigen/CXX11/FixedPoint +++ b/third_party/eigen3/unsupported/Eigen/CXX11/FixedPoint @@ -32,14 +32,12 @@ // Use optimized implementations whenever available #ifdef EIGEN_VECTORIZE_AVX512 -#include "src/Tensor/TensorContractionThreadPool.h" #include "src/FixedPoint/PacketMathAVX512.h" #include "src/FixedPoint/TypeCastingAVX512.h" #elif defined EIGEN_VECTORIZE_AVX2 #define EIGEN_USE_OPTIMIZED_INT8_UINT8_MAT_MAT_PRODUCT #define EIGEN_USE_OPTIMIZED_INT16_INT16_MAT_MAT_PRODUCT -#include "src/Tensor/TensorContractionThreadPool.h" #include "src/FixedPoint/PacketMathAVX2.h" #include "src/FixedPoint/MatMatProductAVX2.h" #include "src/FixedPoint/TypeCastingAVX2.h" |