diff options
31 files changed, 371 insertions, 50 deletions
@@ -23,13 +23,8 @@ function bazel_clean_and_fetch() { # TODO(pcloudy): Re-enable it after bazel clean --expunge is fixed. if ! is_windows; then bazel clean --expunge - # TODO(https://github.com/bazelbuild/bazel/issues/2220) Remove the nested `bazel query`. - bazel fetch $(bazel query "//tensorflow/... -//tensorflow/examples/android/...") - else - # TODO(pcloudy): Also filter out //tensorflow/examples/android/... on Windows after - # https://github.com/bazelbuild/bazel/issues/2248 is fixed. - bazel fetch //tensorflow/... fi + bazel fetch "//tensorflow/... -//tensorflow/examples/android/..." } ## Set up python-related environment settings diff --git a/tensorflow/contrib/cmake/tf_core_kernels.cmake b/tensorflow/contrib/cmake/tf_core_kernels.cmake index 50eba857ad..911e52604e 100644 --- a/tensorflow/contrib/cmake/tf_core_kernels.cmake +++ b/tensorflow/contrib/cmake/tf_core_kernels.cmake @@ -102,6 +102,24 @@ file(GLOB_RECURSE tf_core_gpu_kernels_srcs "${tensorflow_source_dir}/tensorflow/contrib/rnn/kernels/*.cu.cc" ) +if(WIN32 AND tensorflow_ENABLE_GPU) + file(GLOB_RECURSE tf_core_kernels_cpu_only_srcs + # GPU implementation not working on Windows yet. + "${tensorflow_source_dir}/tensorflow/core/kernels/matrix_diag_op.cc" + "${tensorflow_source_dir}/tensorflow/core/kernels/one_hot_op.cc") + list(REMOVE_ITEM tf_core_kernels_srcs ${tf_core_kernels_cpu_only_srcs}) + add_library(tf_core_kernels_cpu_only OBJECT ${tf_core_kernels_cpu_only_srcs}) + add_dependencies(tf_core_kernels_cpu_only tf_core_cpu) + # Undefine GOOGLE_CUDA to avoid registering unsupported GPU kernel symbols. + get_target_property(target_compile_flags tf_core_kernels_cpu_only COMPILE_FLAGS) + if(target_compile_flags STREQUAL "target_compile_flags-NOTFOUND") + set(target_compile_flags "/UGOOGLE_CUDA") + else() + set(target_compile_flags "${target_compile_flags} /UGOOGLE_CUDA") + endif() + set_target_properties(tf_core_kernels_cpu_only PROPERTIES COMPILE_FLAGS ${target_compile_flags}) +endif(WIN32 AND tensorflow_ENABLE_GPU) + add_library(tf_core_kernels OBJECT ${tf_core_kernels_srcs}) add_dependencies(tf_core_kernels tf_core_cpu) diff --git a/tensorflow/contrib/cmake/tf_python.cmake b/tensorflow/contrib/cmake/tf_python.cmake index d7d3d54003..6fe83bf83e 100644 --- a/tensorflow/contrib/cmake/tf_python.cmake +++ b/tensorflow/contrib/cmake/tf_python.cmake @@ -584,6 +584,7 @@ add_library(pywrap_tensorflow SHARED $<TARGET_OBJECTS:tf_core_direct_session> $<$<BOOL:${tensorflow_ENABLE_GRPC_SUPPORT}>:$<TARGET_OBJECTS:tf_core_distributed_runtime>> $<TARGET_OBJECTS:tf_core_kernels> + $<$<BOOL:${tensorflow_ENABLE_GPU}>:$<TARGET_OBJECTS:tf_core_kernels_cpu_only>> $<$<BOOL:${tensorflow_ENABLE_GPU}>:$<TARGET_OBJECTS:tf_stream_executor>> ) target_include_directories(pywrap_tensorflow PUBLIC diff --git a/tensorflow/contrib/cmake/tf_tests.cmake b/tensorflow/contrib/cmake/tf_tests.cmake index 081a7a7ce3..0909b61ba9 100644 --- a/tensorflow/contrib/cmake/tf_tests.cmake +++ b/tensorflow/contrib/cmake/tf_tests.cmake @@ -148,13 +148,10 @@ if (tensorflow_BUILD_PYTHON_TESTS) "${tensorflow_source_dir}/tensorflow/python/kernel_tests/variable_scope_test.py" "${tensorflow_source_dir}/tensorflow/python/kernel_tests/reshape_op_test.py" "${tensorflow_source_dir}/tensorflow/tensorboard/backend/server_test.py" + "${tensorflow_source_dir}/tensorflow/python/kernel_tests/diag_op_test.py" # Silently failing with GPU kernel disabled. # int32/int64 mixup "${tensorflow_source_dir}/tensorflow/python/kernel_tests/functional_ops_test.py" "${tensorflow_source_dir}/tensorflow/python/kernel_tests/py_func_test.py" - # cuda launch failed - "${tensorflow_source_dir}/tensorflow/python/kernel_tests/diag_op_test.py" - "${tensorflow_source_dir}/tensorflow/python/kernel_tests/trace_op_test.py" - "${tensorflow_source_dir}/tensorflow/python/kernel_tests/one_hot_op_test.py" # gpu, T=uint8 # training tests "${tensorflow_source_dir}/tensorflow/python/training/basic_session_run_hooks_test.py" # Needs tf.contrib fix. "${tensorflow_source_dir}/tensorflow/python/training/localhost_cluster_performance_test.py" # Needs portpicker. diff --git a/tensorflow/contrib/distributions/python/ops/exponential.py b/tensorflow/contrib/distributions/python/ops/exponential.py index cd6e5c2d1a..d0245bf445 100644 --- a/tensorflow/contrib/distributions/python/ops/exponential.py +++ b/tensorflow/contrib/distributions/python/ops/exponential.py @@ -74,7 +74,7 @@ class Exponential(gamma.Gamma): allow_nan_stats=allow_nan_stats, validate_args=validate_args, name=ns) - # While the Gamma distribution is not reparameterizeable, the + # While the Gamma distribution is not re-parameterizable, the # exponential distribution is. self._is_reparameterized = True self._parameters = parameters diff --git a/tensorflow/contrib/makefile/Makefile b/tensorflow/contrib/makefile/Makefile index bb22586264..284a5894cf 100644 --- a/tensorflow/contrib/makefile/Makefile +++ b/tensorflow/contrib/makefile/Makefile @@ -294,6 +294,7 @@ ifeq ($(TARGET),IOS) ifeq ($(IOS_ARCH),ARMV7) CXXFLAGS += -miphoneos-version-min=$(MIN_SDK_VERSION) \ -arch armv7 \ + -fembed-bitcode \ -D__thread= \ -DUSE_GEMM_FOR_CONV \ -Wno-c++11-narrowing \ @@ -304,6 +305,7 @@ ifeq ($(TARGET),IOS) -isysroot \ ${IPHONEOS_SYSROOT} LDFLAGS := -arch armv7 \ + -fembed-bitcode \ -miphoneos-version-min=${MIN_SDK_VERSION} \ -framework Accelerate \ -Xlinker -S \ @@ -316,6 +318,7 @@ ifeq ($(TARGET),IOS) ifeq ($(IOS_ARCH),ARMV7S) CXXFLAGS += -miphoneos-version-min=$(MIN_SDK_VERSION) \ -arch armv7s \ + -fembed-bitcode \ -D__thread= \ -DUSE_GEMM_FOR_CONV \ -Wno-c++11-narrowing \ @@ -326,6 +329,7 @@ ifeq ($(TARGET),IOS) -isysroot \ ${IPHONEOS_SYSROOT} LDFLAGS := -arch armv7s \ + -fembed-bitcode \ -miphoneos-version-min=${MIN_SDK_VERSION} \ -framework Accelerate \ -Xlinker -S \ @@ -338,6 +342,7 @@ ifeq ($(TARGET),IOS) ifeq ($(IOS_ARCH),ARM64) CXXFLAGS += -miphoneos-version-min=$(MIN_SDK_VERSION) \ -arch arm64 \ + -fembed-bitcode \ -D__thread= \ -DUSE_GEMM_FOR_CONV \ -Wno-c++11-narrowing \ @@ -347,6 +352,7 @@ ifeq ($(TARGET),IOS) -isysroot \ ${IPHONEOS_SYSROOT} LDFLAGS := -arch arm64 \ + -fembed-bitcode \ -miphoneos-version-min=${MIN_SDK_VERSION} \ -framework Accelerate \ -Xlinker -S \ @@ -359,6 +365,7 @@ ifeq ($(TARGET),IOS) ifeq ($(IOS_ARCH),I386) CXXFLAGS += -mios-simulator-version-min=$(MIN_SDK_VERSION) \ -arch i386 \ + -fembed-bitcode \ -D__thread= \ -DUSE_GEMM_FOR_CONV \ -Wno-c++11-narrowing \ @@ -368,6 +375,7 @@ ifeq ($(TARGET),IOS) -isysroot \ ${IPHONESIMULATOR_SYSROOT} LDFLAGS := -arch i386 \ + -fembed-bitcode \ -mios-simulator-version-min=${MIN_SDK_VERSION} \ -framework Accelerate \ -Xlinker -S \ @@ -380,6 +388,7 @@ ifeq ($(TARGET),IOS) ifeq ($(IOS_ARCH),X86_64) CXXFLAGS += -mios-simulator-version-min=$(MIN_SDK_VERSION) \ -arch x86_64 \ + -fembed-bitcode \ -D__thread= \ -DUSE_GEMM_FOR_CONV \ -Wno-c++11-narrowing \ @@ -389,6 +398,7 @@ ifeq ($(TARGET),IOS) -isysroot \ ${IPHONESIMULATOR_SYSROOT} LDFLAGS := -arch x86_64 \ + -fembed-bitcode \ -mios-simulator-version-min=${MIN_SDK_VERSION} \ -framework Accelerate \ -Xlinker -S \ diff --git a/tensorflow/contrib/makefile/build_all_ios.sh b/tensorflow/contrib/makefile/build_all_ios.sh index 4d9ce077ba..344bf49dcf 100755 --- a/tensorflow/contrib/makefile/build_all_ios.sh +++ b/tensorflow/contrib/makefile/build_all_ios.sh @@ -32,6 +32,13 @@ cd ${SCRIPT_DIR}/../../../ make -f tensorflow/contrib/makefile/Makefile clean rm -rf tensorflow/contrib/makefile/downloads +# Setting a deployment target is required for building with bitcode, +# otherwise linking will fail with: +# +# ld: -bind_at_load and -bitcode_bundle (Xcode setting ENABLE_BITCODE=YES) cannot be used together +# +export MACOSX_DEPLOYMENT_TARGET="10.10" + # Pull down the required versions of the frameworks we need. tensorflow/contrib/makefile/download_dependencies.sh diff --git a/tensorflow/contrib/makefile/compile_ios_protobuf.sh b/tensorflow/contrib/makefile/compile_ios_protobuf.sh index c413924538..12f34b38d0 100755 --- a/tensorflow/contrib/makefile/compile_ios_protobuf.sh +++ b/tensorflow/contrib/makefile/compile_ios_protobuf.sh @@ -76,14 +76,17 @@ make distclean "CFLAGS=${CFLAGS} \ -mios-simulator-version-min=${MIN_SDK_VERSION} \ -arch i386 \ +-fembed-bitcode \ -isysroot ${IPHONESIMULATOR_SYSROOT}" \ "CXX=${CXX}" \ "CXXFLAGS=${CXXFLAGS} \ -mios-simulator-version-min=${MIN_SDK_VERSION} \ -arch i386 \ +-fembed-bitcode \ -isysroot \ ${IPHONESIMULATOR_SYSROOT}" \ LDFLAGS="-arch i386 \ +-fembed-bitcode \ -mios-simulator-version-min=${MIN_SDK_VERSION} \ ${LDFLAGS} \ -L${IPHONESIMULATOR_SYSROOT}/usr/lib/ \ @@ -103,14 +106,17 @@ make distclean "CFLAGS=${CFLAGS} \ -mios-simulator-version-min=${MIN_SDK_VERSION} \ -arch x86_64 \ +-fembed-bitcode \ -isysroot ${IPHONESIMULATOR_SYSROOT}" \ "CXX=${CXX}" \ "CXXFLAGS=${CXXFLAGS} \ -mios-simulator-version-min=${MIN_SDK_VERSION} \ -arch x86_64 \ +-fembed-bitcode \ -isysroot \ ${IPHONESIMULATOR_SYSROOT}" \ LDFLAGS="-arch x86_64 \ +-fembed-bitcode \ -mios-simulator-version-min=${MIN_SDK_VERSION} \ ${LDFLAGS} \ -L${IPHONESIMULATOR_SYSROOT}/usr/lib/ \ @@ -129,13 +135,16 @@ make distclean "CFLAGS=${CFLAGS} \ -miphoneos-version-min=${MIN_SDK_VERSION} \ -arch armv7 \ +-fembed-bitcode \ -isysroot ${IPHONEOS_SYSROOT}" \ "CXX=${CXX}" \ "CXXFLAGS=${CXXFLAGS} \ -miphoneos-version-min=${MIN_SDK_VERSION} \ -arch armv7 \ +-fembed-bitcode \ -isysroot ${IPHONEOS_SYSROOT}" \ LDFLAGS="-arch armv7 \ +-fembed-bitcode \ -miphoneos-version-min=${MIN_SDK_VERSION} \ ${LDFLAGS}" \ "LIBS=${LIBS}" @@ -152,13 +161,16 @@ make distclean "CFLAGS=${CFLAGS} \ -miphoneos-version-min=${MIN_SDK_VERSION} \ -arch armv7s \ +-fembed-bitcode \ -isysroot ${IPHONEOS_SYSROOT}" \ "CXX=${CXX}" \ "CXXFLAGS=${CXXFLAGS} \ -miphoneos-version-min=${MIN_SDK_VERSION} \ -arch armv7s \ +-fembed-bitcode \ -isysroot ${IPHONEOS_SYSROOT}" \ LDFLAGS="-arch armv7s \ +-fembed-bitcode \ -miphoneos-version-min=${MIN_SDK_VERSION} \ ${LDFLAGS}" \ "LIBS=${LIBS}" @@ -175,12 +187,15 @@ make distclean "CFLAGS=${CFLAGS} \ -miphoneos-version-min=${MIN_SDK_VERSION} \ -arch arm64 \ +-fembed-bitcode \ -isysroot ${IPHONEOS_SYSROOT}" \ "CXXFLAGS=${CXXFLAGS} \ -miphoneos-version-min=${MIN_SDK_VERSION} \ -arch arm64 \ +-fembed-bitcode \ -isysroot ${IPHONEOS_SYSROOT}" \ LDFLAGS="-arch arm64 \ +-fembed-bitcode \ -miphoneos-version-min=${MIN_SDK_VERSION} \ ${LDFLAGS}" \ "LIBS=${LIBS}" diff --git a/tensorflow/contrib/rnn/python/ops/lstm_ops.py b/tensorflow/contrib/rnn/python/ops/lstm_ops.py index c1578f7da9..d1d547b952 100644 --- a/tensorflow/contrib/rnn/python/ops/lstm_ops.py +++ b/tensorflow/contrib/rnn/python/ops/lstm_ops.py @@ -635,7 +635,7 @@ class LSTMBlockFusedCell(LSTMBlockWrapper): wci = wco = wcf = array_ops.zeros([self._num_units], dtype=dtype) if sequence_length is None: - max_seq_len = time_len + max_seq_len = math_ops.to_int64(time_len) else: max_seq_len = math_ops.to_int64(math_ops.reduce_max(sequence_length)) diff --git a/tensorflow/contrib/seq2seq/BUILD b/tensorflow/contrib/seq2seq/BUILD index 9566d03211..3c314e2f28 100644 --- a/tensorflow/contrib/seq2seq/BUILD +++ b/tensorflow/contrib/seq2seq/BUILD @@ -41,6 +41,18 @@ cuda_py_test( ) cuda_py_test( + name = "loss_test", + size = "medium", + srcs = ["python/kernel_tests/loss_test.py"], + additional_deps = [ + ":seq2seq_py", + "//tensorflow:tensorflow_py", + "//tensorflow/python:framework_test_lib", + "//tensorflow/python:platform_test", + ], +) + +cuda_py_test( name = "seq2seq_test", size = "medium", srcs = ["python/kernel_tests/seq2seq_test.py"], diff --git a/tensorflow/contrib/seq2seq/python/kernel_tests/loss_test.py b/tensorflow/contrib/seq2seq/python/kernel_tests/loss_test.py index f99de76f17..95560fb254 100644 --- a/tensorflow/contrib/seq2seq/python/kernel_tests/loss_test.py +++ b/tensorflow/contrib/seq2seq/python/kernel_tests/loss_test.py @@ -20,14 +20,58 @@ from __future__ import division from __future__ import print_function # pylint: enable=unused-import +import numpy as np import tensorflow as tf - class LossTest(tf.test.TestCase): - def testLoss(self): - pass + def testSequenceLoss(self): + with self.test_session() as sess: + with tf.variable_scope("root", + initializer=tf.constant_initializer(0.5)) as varscope: + batch_size = 2 + sequence_length = 3 + number_of_classes = 5 + logits = [tf.constant(i + 0.5, shape=[batch_size, number_of_classes]) + for i in range(sequence_length)] + logits = tf.stack(logits, axis=1) + targets = [tf.constant(i, tf.int32, shape=[batch_size]) for i in + range(sequence_length)] + targets = tf.stack(targets, axis=1) + weights = [tf.constant(1.0, shape=[batch_size]) for i in + range(sequence_length)] + weights = tf.stack(weights, axis=1) + + average_loss_per_example = tf.contrib.seq2seq.sequence_loss( + logits, targets, weights, + average_across_timesteps=True, + average_across_batch=True) + res = sess.run(average_loss_per_example) + self.assertAllClose(1.60944, res) + + average_loss_per_sequence = tf.contrib.seq2seq.sequence_loss( + logits, targets, weights, + average_across_timesteps=False, + average_across_batch=True) + res = sess.run(average_loss_per_sequence) + compare_per_sequence = np.ones((sequence_length)) * 1.60944 + self.assertAllClose(compare_per_sequence, res) + + average_loss_per_batch = tf.contrib.seq2seq.sequence_loss( + logits, targets, weights, + average_across_timesteps=True, + average_across_batch=False) + res = sess.run(average_loss_per_batch) + compare_per_batch = np.ones((batch_size)) * 1.60944 + self.assertAllClose(compare_per_batch, res) + total_loss = tf.contrib.seq2seq.sequence_loss( + logits, targets, weights, + average_across_timesteps=False, + average_across_batch=False) + res = sess.run(total_loss) + compare_total = np.ones((batch_size, sequence_length)) * 1.60944 + self.assertAllClose(compare_total, res) if __name__ == '__main__': tf.test.main() diff --git a/tensorflow/contrib/seq2seq/python/ops/loss.py b/tensorflow/contrib/seq2seq/python/ops/loss.py index b8a33b3f6f..bb87111266 100644 --- a/tensorflow/contrib/seq2seq/python/ops/loss.py +++ b/tensorflow/contrib/seq2seq/python/ops/loss.py @@ -13,18 +13,88 @@ # limitations under the License. # ============================================================================== -"""Seq2seq loss operations for use in neural networks. +"""Seq2seq loss operations for use in sequence models. """ from __future__ import absolute_import from __future__ import division from __future__ import print_function +from tensorflow.python.framework import ops from tensorflow.python.ops import array_ops +from tensorflow.python.ops import nn_ops +from tensorflow.python.ops import math_ops +__all__ = ["sequence_loss"] -__all__ = ["seq2seq_loss"] +def sequence_loss(logits, targets, weights, + average_across_timesteps=True, average_across_batch=True, + softmax_loss_function=None, name=None): + """Weighted cross-entropy loss for a sequence of logits (per example). + Args: + logits: A 3D Tensor of shape + [batch_size x sequence_length x num_decoder_symbols] and dtype float. + The logits correspond to the prediction across all classes at each + timestep. + targets: A 2D Tensor of shape [batch_size x sequence_length] and dtype + int. The target represents the true class at each timestep. + weights: A 2D Tensor of shape [batch_size x sequence_length] and dtype + float. Weights constitutes the weighting of each prediction in the + sequence. When using weights as masking set all valid timesteps to 1 and + all padded timesteps to 0. + average_across_timesteps: If set, sum the cost across the sequence + dimension and divide by the cost by the total label weight across + timesteps. + average_across_batch: If set, sum the cost across the batch dimension and + divide the returned cost by the batch size. + softmax_loss_function: Function (inputs-batch, labels-batch) -> loss-batch + to be used instead of the standard softmax (the default if this is None). + name: Optional name for this operation, defaults to "sequence_loss". -def seq2seq_loss(*args, **kwargs): - pass + Returns: + A scalar float Tensor: The average log-perplexity per symbol (weighted). + + Raises: + ValueError: logits does not have 3 dimensions or targets does not have 2 + dimensions or weights does not have 2 dimensions. + """ + if len(logits.get_shape()) != 3: + raise ValueError("Logits must be a " + "[batch_size x sequence_length x logits] tensor") + if len(targets.get_shape()) != 2: + raise ValueError("Targets must be a [batch_size x sequence_length] " + "tensor") + if len(weights.get_shape()) != 2: + raise ValueError("Weights must be a [batch_size x sequence_length] " + "tensor") + with ops.name_scope(name, "sequence_loss", [logits, targets, weights]): + num_classes = array_ops.shape(logits)[2] + probs_flat = array_ops.reshape(logits, [-1, num_classes]) + targets = array_ops.reshape(targets, [-1]) + if softmax_loss_function is None: + crossent = nn_ops.sparse_softmax_cross_entropy_with_logits( + labels=targets, logits=probs_flat) + else: + crossent = softmax_loss_function(probs_flat, targets) + crossent = crossent * array_ops.reshape(weights, [-1]) + if average_across_timesteps and average_across_batch: + crossent = math_ops.reduce_sum(crossent) + total_size = math_ops.reduce_sum(weights) + total_size += 1e-12 # to avoid division by 0 for all-0 weights + crossent /= total_size + else: + batch_size = array_ops.shape(logits)[0] + sequence_length = array_ops.shape(logits)[1] + crossent = array_ops.reshape(crossent, [batch_size, sequence_length]) + if average_across_timesteps and not average_across_batch: + crossent = math_ops.reduce_sum(crossent, axis=[1]) + total_size = math_ops.reduce_sum(weights, axis=[1]) + total_size += 1e-12 # to avoid division by 0 for all-0 weights + crossent /= total_size + if not average_across_timesteps and average_across_batch: + crossent = math_ops.reduce_sum(crossent, axis=[0]) + total_size = math_ops.reduce_sum(weights, axis=[0]) + total_size += 1e-12 # to avoid division by 0 for all-0 weights + crossent /= total_size + return crossent diff --git a/tensorflow/contrib/slim/python/slim/data/parallel_reader.py b/tensorflow/contrib/slim/python/slim/data/parallel_reader.py index 170c5899b9..6082af008a 100644 --- a/tensorflow/contrib/slim/python/slim/data/parallel_reader.py +++ b/tensorflow/contrib/slim/python/slim/data/parallel_reader.py @@ -210,7 +210,8 @@ def parallel_read(data_sources, data_files = get_data_files(data_sources) with ops.name_scope(scope, 'parallel_read'): filename_queue = tf_input.string_input_producer( - data_files, num_epochs=num_epochs, shuffle=shuffle, name='filenames') + data_files, num_epochs=num_epochs, shuffle=shuffle, seed=seed, + name='filenames') dtypes = dtypes or [tf_dtypes.string, tf_dtypes.string] if shuffle: common_queue = data_flow_ops.RandomShuffleQueue( diff --git a/tensorflow/core/common_runtime/simple_placer.cc b/tensorflow/core/common_runtime/simple_placer.cc index d3110cba04..f6e6bf0692 100644 --- a/tensorflow/core/common_runtime/simple_placer.cc +++ b/tensorflow/core/common_runtime/simple_placer.cc @@ -605,7 +605,7 @@ bool IsMetadataNode(const Node* node) { // outputs that are connected to nodes in the same colocation group. bool IsGeneratorNode(const Node* node) { return node->num_inputs() == 0 && node->num_outputs() == 1 && - node->out_edges().size() == 1 && !IsRefType(node->output_type(0)); + !IsRefType(node->output_type(0)); } } // namespace @@ -730,9 +730,9 @@ Status SimplePlacer::Run() { // Heuristic A: prefer to place "generators" with their only // consumers. // - // If this is a node with no inputs and a single (non-ref) - // consumer, we save this for a second pass, so that the - // consumer's placement is chosen. + // If this is a node with no inputs and one output, we save + // this for a second pass, so that the consumer's placement + // is chosen. if (IsGeneratorNode(node)) { second_pass.push_back(node); continue; @@ -794,7 +794,15 @@ Status SimplePlacer::Run() { if (IsGeneratorNode(node)) { const Node* output = (*node->out_edges().begin())->dst(); const string& output_device_name = output->assigned_device_name(); - if (CanAssignToDevice(output_device_name, devices)) { + + const bool consumers_on_same_device = std::all_of( + node->out_edges().begin(), node->out_edges().end(), + [output_device_name](const Edge* e) { + return e->dst()->assigned_device_name() == output_device_name; + }); + + if (consumers_on_same_device && + CanAssignToDevice(output_device_name, devices)) { assigned_device = output_device_name; } } diff --git a/tensorflow/core/common_runtime/simple_placer_test.cc b/tensorflow/core/common_runtime/simple_placer_test.cc index 06267d71ae..c73ed041ed 100644 --- a/tensorflow/core/common_runtime/simple_placer_test.cc +++ b/tensorflow/core/common_runtime/simple_placer_test.cc @@ -1226,5 +1226,76 @@ TEST_F(SimplePlacerTest, TestUnsatisfiableConstraintWithReferenceConnections) { .contains("Cannot colocate nodes 'var' and 'assign'")); } +// Test that a generator node follows its consumers (where there are several +// consumer nodes on the same devices). +TEST_F(SimplePlacerTest, TestGeneratorNodeFollowsConsumerNode) { + Graph g(OpRegistry::Global()); + { // Scope for temporary variables used to construct g. + GraphDefBuilder b(GraphDefBuilder::kFailImmediately); + + // A variable is only on CPU + Node* var1_cpu = + ops::SourceOp("VariableCPU", b.opts().WithName("var1_cpu")); + Node* var2_cpu = + ops::SourceOp("VariableCPU", b.opts().WithName("var2_cpu")); + + // The constant to be assigned can be on both GPU or CPU. + // + // Because of the heuristic, it gets placed on CPU to avoid a + // copy. + Node* input = ops::SourceOp("TestCPUGPUOutput", b.opts().WithName("in")); + + // The assigns are bound to CPU by the reference edge. + ops::BinaryOp("TestAssign", var1_cpu, input, b.opts().WithName("assign1")); + ops::BinaryOp("TestAssign", var2_cpu, input, b.opts().WithName("assign2")); + + TF_EXPECT_OK(BuildGraph(b, &g)); + } + + TF_EXPECT_OK(Place(&g)); + EXPECT_COLOCATED(g, "var1_cpu", "in"); + EXPECT_COLOCATED(g, "assign1", "in"); + EXPECT_COLOCATED(g, "var2_cpu", "in"); + EXPECT_COLOCATED(g, "assign2", "in"); +} + +// Test that a generator node does not follow its consumers (where there are +// several consumers on different devices). +TEST_F(SimplePlacerTest, TestGeneratorNodeDoesntFollowNonColocatedConsumers) { + Graph g(OpRegistry::Global()); + { // Scope for temporary variables used to construct g. + GraphDefBuilder b(GraphDefBuilder::kFailImmediately); + + // A variable is only on CPU + Node* var1_cpu = + ops::SourceOp("VariableCPU", b.opts().WithName("var1_cpu")); + Node* var2_cpu = + ops::SourceOp("VariableCPU", b.opts().WithName("var2_cpu")); + + // The constant to be assigned can be on both GPU or CPU. + // + // Because of the heuristic, it ought to be on the GPU (cannot be + // co-located with both consumers, so goes to the 'standard' place) + Node* input = ops::SourceOp("TestCPUGPUOutput", b.opts().WithName("in")); + + // The assigns are bound to CPU by the reference edge. + ops::BinaryOp("TestAssign", var1_cpu, input, b.opts().WithName("assign1")); + ops::BinaryOp("TestAssign", var2_cpu, input, b.opts().WithName("assign2")); + + TF_EXPECT_OK(BuildGraph(b, &g)); + + GetNodeByName(g, "var1_cpu") + ->set_assigned_device_name("/job:a/replica:0/task:0/device:fakecpu:1"); + + GetNodeByName(g, "var2_cpu") + ->set_assigned_device_name("/job:a/replica:0/task:0/device:fakecpu:2"); + } + + TF_EXPECT_OK(Place(&g)); + EXPECT_COLOCATED(g, "assign1", "var1_cpu"); + EXPECT_COLOCATED(g, "assign2", "var2_cpu"); + EXPECT_DEVICE_TYPE(g, "in", "FakeGPU"); +} + } // namespace } // namespace tensorflow diff --git a/tensorflow/core/kernels/BUILD b/tensorflow/core/kernels/BUILD index e7854ac0db..5137156107 100644 --- a/tensorflow/core/kernels/BUILD +++ b/tensorflow/core/kernels/BUILD @@ -439,7 +439,6 @@ ARRAY_DEPS = [ cc_library( name = "array_not_windows", deps = [ - ":debug_ops", ":immutable_constant_op", ], ) @@ -478,6 +477,7 @@ cc_library( ":bitcast_op", ":concat_op", ":constant_op", + ":debug_ops", ":depth_space_ops", ":diag_op", ":edit_distance_op", diff --git a/tensorflow/core/kernels/debug_ops.h b/tensorflow/core/kernels/debug_ops.h index aa47315f55..0a4dc45205 100644 --- a/tensorflow/core/kernels/debug_ops.h +++ b/tensorflow/core/kernels/debug_ops.h @@ -127,7 +127,7 @@ class DebugNanCountOp : public OpKernel { const T* input_flat = input.template flat<T>().data(); for (int64 i = 0; i < input_shape.num_elements(); ++i) { - if (Eigen::numext::isnan(input_flat[i])) { + if (Eigen::numext::isnan(static_cast<double>(input_flat[i]))) { nan_count++; } } diff --git a/tensorflow/core/platform/windows/windows_file_system.cc b/tensorflow/core/platform/windows/windows_file_system.cc index 670abf3fdf..facadc7f57 100644 --- a/tensorflow/core/platform/windows/windows_file_system.cc +++ b/tensorflow/core/platform/windows/windows_file_system.cc @@ -72,7 +72,9 @@ SSIZE_T pread(HANDLE hfile, char* src, size_t num_bytes, uint64_t offset) { BOOL read_result = ::ReadFile(hfile, src, static_cast<DWORD>(num_bytes), &bytes_read, &overlapped); - if ((FALSE == read_result) && + if (TRUE == read_result) { + result = bytes_read; + } else if ((FALSE == read_result) && ((last_error = GetLastError()) != ERROR_IO_PENDING)) { result = (last_error == ERROR_HANDLE_EOF) ? 0 : -1; } else { diff --git a/tensorflow/examples/how_tos/reading_data/convert_to_records.py b/tensorflow/examples/how_tos/reading_data/convert_to_records.py index 5457b27eca..d14c1f7c86 100644 --- a/tensorflow/examples/how_tos/reading_data/convert_to_records.py +++ b/tensorflow/examples/how_tos/reading_data/convert_to_records.py @@ -26,14 +26,6 @@ import tensorflow as tf from tensorflow.contrib.learn.python.learn.datasets import mnist -SOURCE_URL = 'http://yann.lecun.com/exdb/mnist/' - -TRAIN_IMAGES = 'train-images-idx3-ubyte.gz' # MNIST filenames -TRAIN_LABELS = 'train-labels-idx1-ubyte.gz' -TEST_IMAGES = 't10k-images-idx3-ubyte.gz' -TEST_LABELS = 't10k-labels-idx1-ubyte.gz' - - FLAGS = None diff --git a/tensorflow/examples/udacity/README.md b/tensorflow/examples/udacity/README.md index 6e40c3bae6..143a75a3e9 100644 --- a/tensorflow/examples/udacity/README.md +++ b/tensorflow/examples/udacity/README.md @@ -54,6 +54,15 @@ to get the ip of the new virtual machine. To switch from default virtual machine Note that `docker-machine env tensorflow` outputs some environment variables such like `DOCKER_HOST`. Then your docker client is now connected to the docker host in virtual machine `tensorflow` +* **I'm getting a TLS connection error.** + +If you get an error about the TLS connection of your docker, run the command below to confirm the problem. + + docker-machine ip tensorflow + +Then if it is the case use the instructions on [this page](https://docs.docker.com/toolbox/faqs/troubleshoot/) to solve the issue. + + * **I'm getting the error - docker: Cannot connect to the Docker daemon. Is the docker daemon running on this host? - when I run 'docker run'.** This is a permissions issue, and a popular answer is provided for Linux and Max OSX [here](http://stackoverflow.com/questions/21871479/docker-cant-connect-to-docker-daemon) on StackOverflow. diff --git a/tensorflow/g3doc/how_tos/quantization/index.md b/tensorflow/g3doc/how_tos/quantization/index.md index 340d70f93e..fa61cadcea 100644 --- a/tensorflow/g3doc/how_tos/quantization/index.md +++ b/tensorflow/g3doc/how_tos/quantization/index.md @@ -91,11 +91,11 @@ eight-bit computations: ```sh curl http://download.tensorflow.org/models/image/imagenet/inception-2015-12-05.tgz -o /tmp/inceptionv3.tgz tar xzf /tmp/inceptionv3.tgz -C /tmp/ -bazel build tensorflow/contrib/quantization/tools:quantize_graph -bazel-bin/tensorflow/contrib/quantization/tools/quantize_graph \ ---input=/tmp/classify_image_graph_def.pb \ ---output_node_names="softmax" --output=/tmp/quantized_graph.pb \ ---mode=eightbit +bazel build tensorflow/tools/quantization/tools:quantize_graph +bazel-bin/tensorflow/tools/quantization/tools/quantize_graph \ + --input=/tmp/classify_image_graph_def.pb \ + --output_node_names="softmax" --output=/tmp/quantized_graph.pb \ + --mode=eightbit ``` This will produce a new model that runs the same operations as the original, but diff --git a/tensorflow/python/debug/cli/analyzer_cli_test.py b/tensorflow/python/debug/cli/analyzer_cli_test.py index d6b5c3a097..5d3f1aed2f 100644 --- a/tensorflow/python/debug/cli/analyzer_cli_test.py +++ b/tensorflow/python/debug/cli/analyzer_cli_test.py @@ -1608,7 +1608,8 @@ class AnalyzerCLIWhileLoopTest(test_util.TensorFlowTestCase): self.assertEqual(" dtype: int32", output.lines[1]) self.assertEqual(" shape: ()", output.lines[2]) self.assertEqual("", output.lines[3]) - self.assertEqual("array(%d, dtype=int32)" % i, output.lines[4]) + self.assertTrue(output.lines[4].startswith("array(%d" % i)) + self.assertTrue(output.lines[4].endswith(")")) def testMultipleDumpsPrintTensorInvalidNumber(self): output = self._registry.dispatch_command("pt", diff --git a/tensorflow/python/debug/debug_data.py b/tensorflow/python/debug/debug_data.py index 3e638c6f04..e010e8f3fc 100644 --- a/tensorflow/python/debug/debug_data.py +++ b/tensorflow/python/debug/debug_data.py @@ -312,7 +312,7 @@ class DebugTensorDatum(object): self._debug_op = base.split("_")[-2] self._output_slot = int(base.split("_")[-3]) - namespace = os.path.dirname(debug_dump_rel_path) + namespace = os.path.dirname(debug_dump_rel_path).replace("\\", "/") node_base_name = "_".join(base.split("_")[:-3]) if not namespace or namespace == ".": self._node_name = node_base_name diff --git a/tensorflow/python/debug/debug_data_test.py b/tensorflow/python/debug/debug_data_test.py index 9910244ad3..753b76358b 100644 --- a/tensorflow/python/debug/debug_data_test.py +++ b/tensorflow/python/debug/debug_data_test.py @@ -133,7 +133,7 @@ class HasNanOrInfTest(test_util.TensorFlowTestCase): a = np.array([1j, 3j, 3j, 7j], dtype=np.complex128) self.assertFalse(debug_data.has_inf_or_nan(self._dummy_datum, a)) - b = np.array([1j, 3j, 3j, 7j, np.nan], dtype=np.complex256) + b = np.array([1j, 3j, 3j, 7j, np.nan], dtype=np.complex128) self.assertTrue(debug_data.has_inf_or_nan(self._dummy_datum, b)) def testDTypeIntegerWorks(self): diff --git a/tensorflow/python/framework/graph_io.py b/tensorflow/python/framework/graph_io.py index 85a00efd74..0033a37088 100644 --- a/tensorflow/python/framework/graph_io.py +++ b/tensorflow/python/framework/graph_io.py @@ -50,6 +50,9 @@ def write_graph(graph_or_graph_def, logdir, name, as_text=True): filesystems, such as Google Cloud Storage (GCS). name: Filename for the graph. as_text: If `True`, writes the graph as an ASCII proto. + + Returns: + The path of the output proto file. """ if isinstance(graph_or_graph_def, ops.Graph): graph_def = graph_or_graph_def.as_graph_def() @@ -64,3 +67,4 @@ def write_graph(graph_or_graph_def, logdir, name, as_text=True): file_io.atomic_write_string_to_file(path, str(graph_def)) else: file_io.atomic_write_string_to_file(path, graph_def.SerializeToString()) + return path diff --git a/tensorflow/python/ops/special_math_ops.py b/tensorflow/python/ops/special_math_ops.py index a2d995030f..bf4d198209 100644 --- a/tensorflow/python/ops/special_math_ops.py +++ b/tensorflow/python/ops/special_math_ops.py @@ -340,6 +340,22 @@ def _einsum_reduction(t0, t0_axis_labels, t1, t1_axis_labels, axes_to_sum): t0_shape[:len(preserved_axes)+len(broadcast_axes[0])] + t1_shape[len(t1_shape)-len(broadcast_axes[1]):] ) + + # Check the number of None values and replace them with Tensors containing + # corresponding dimensions if there exist two or more None values + num_none_dims = sum(1 for d in uncompacted_shape if d is None) + if num_none_dims > 1: + uncompacted_shape = list(uncompacted_shape) + for i in xrange(len(uncompacted_shape)): + if uncompacted_shape[i] is None: + if i < len(preserved_axes) + len(broadcast_axes[0]): + uncompacted_shape[i] = array_ops.shape(inputs[0])[i] + else: + idx = (i - len(preserved_axes) - len(broadcast_axes[0]) + + len(t1_shape) - len(broadcast_axes[1])) + uncompacted_shape[i] = array_ops.shape(inputs[1])[idx] + uncompacted_shape = tuple(uncompacted_shape) + product = _reshape_if_necessary(product, uncompacted_shape) product_axes = ( diff --git a/tensorflow/python/ops/special_math_ops_test.py b/tensorflow/python/ops/special_math_ops_test.py index d17bb80d4b..3d289bcc9a 100644 --- a/tensorflow/python/ops/special_math_ops_test.py +++ b/tensorflow/python/ops/special_math_ops_test.py @@ -283,6 +283,43 @@ class EinsumTest(test.TestCase): } np.testing.assert_almost_equal([7], sess.run(out, feed_dict=feed_dict)) + # Tests for placeholders which have two or more None values + with ops.Graph().as_default(): + m0 = array_ops.placeholder(dtypes.int32, shape=(None, None, 2)) + m1 = array_ops.placeholder(dtypes.int32, shape=(2, 1)) + out = special_math_ops.einsum('ijk,kl->ijl', m0, m1) + with session.Session() as sess: + feed_dict = { + m0: [[[1,2]]], + m1: [[3], [2]], + } + np.testing.assert_almost_equal( + [[[7]]], sess.run(out, feed_dict=feed_dict)) + + with ops.Graph().as_default(): + m0 = array_ops.placeholder(dtypes.int32, shape=(2, 1)) + m1 = array_ops.placeholder(dtypes.int32, shape=(None, None, 2)) + out = special_math_ops.einsum('kl,ijk->ijl', m0, m1) + with session.Session() as sess: + feed_dict = { + m0: [[3], [2]], + m1: [[[1,2]]], + } + np.testing.assert_almost_equal( + [[[7]]], sess.run(out, feed_dict=feed_dict)) + + with ops.Graph().as_default(): + m0 = array_ops.placeholder(dtypes.int32, shape=(None, None, 2)) + m1 = array_ops.placeholder(dtypes.int32, shape=(2,)) + out = special_math_ops.einsum('ijk,k->ij', m0, m1) + with session.Session() as sess: + feed_dict = { + m0: [[[1, 2]]], + m1: [3, 2], + } + np.testing.assert_almost_equal( + [[7]], sess.run(out, feed_dict=feed_dict)) + if __name__ == '__main__': test.main() diff --git a/tensorflow/python/ops/variable_scope.py b/tensorflow/python/ops/variable_scope.py index 5897f94f9d..ddba73f7e9 100644 --- a/tensorflow/python/ops/variable_scope.py +++ b/tensorflow/python/ops/variable_scope.py @@ -998,7 +998,7 @@ for an extensive description of how reusing works. Here is a basic example: with tf.variable_scope("foo"): v = tf.get_variable("v", [1]) # v.name == "foo/v:0" w = tf.get_variable("w", [1]) # w.name == "foo/w:0" -with tf.variable_scope("foo", reuse=True) +with tf.variable_scope("foo", reuse=True): v1 = tf.get_variable("v") # The same as v above. ``` diff --git a/tensorflow/python/training/saver_test.py b/tensorflow/python/training/saver_test.py index 03d1c06476..af9f13f438 100644 --- a/tensorflow/python/training/saver_test.py +++ b/tensorflow/python/training/saver_test.py @@ -1837,14 +1837,22 @@ class WriteGraphTest(test.TestCase): def testWriteGraph(self): test_dir = _TestDir("write_graph_dir") variables.Variable([[1, 2, 3], [4, 5, 6]], dtype=dtypes.float32, name="v0") - graph_io.write_graph(ops_lib.get_default_graph(), - "/".join([test_dir, "l1"]), "graph.pbtxt") + path = graph_io.write_graph(ops_lib.get_default_graph(), + os.path.join(test_dir, "l1"), "graph.pbtxt") + truth = os.path.join(test_dir, "l1", "graph.pbtxt") + self.assertEqual(path, truth) + self.assertTrue(os.path.exists(path)) + def testRecursiveCreate(self): test_dir = _TestDir("deep_dir") variables.Variable([[1, 2, 3], [4, 5, 6]], dtype=dtypes.float32, name="v0") - graph_io.write_graph(ops_lib.get_default_graph().as_graph_def(), - "/".join([test_dir, "l1/l2/l3"]), "graph.pbtxt") + path = graph_io.write_graph(ops_lib.get_default_graph().as_graph_def(), + os.path.join(test_dir, "l1", "l2", "l3"), + "graph.pbtxt") + truth = os.path.join(test_dir, 'l1', 'l2', 'l3', "graph.pbtxt") + self.assertEqual(path, truth) + self.assertTrue(os.path.exists(path)) class SaverUtilsTest(test.TestCase): diff --git a/tensorflow/tools/ci_build/builds/android_full.sh b/tensorflow/tools/ci_build/builds/android_full.sh index fce2ed7504..241f28ef9c 100755 --- a/tensorflow/tools/ci_build/builds/android_full.sh +++ b/tensorflow/tools/ci_build/builds/android_full.sh @@ -67,4 +67,7 @@ cp bazel-bin/tensorflow/examples/android/tensorflow_demo.apk \ bazel-bin/tensorflow/contrib/android/libandroid_tensorflow_inference_java.jar ${OUT_DIR} # Test Makefile build just to make sure it still works. +if [ -z "$NDK_ROOT" ]; then + export NDK_ROOT=${ANDROID_NDK_HOME} +fi tensorflow/contrib/makefile/build_all_android.sh diff --git a/tensorflow/tools/ci_build/windows/bazel/bazel_test_lib.sh b/tensorflow/tools/ci_build/windows/bazel/bazel_test_lib.sh index e809e89a41..a3b7ee786b 100644 --- a/tensorflow/tools/ci_build/windows/bazel/bazel_test_lib.sh +++ b/tensorflow/tools/ci_build/windows/bazel/bazel_test_lib.sh @@ -121,7 +121,7 @@ function get_failing_cpu_py_tests() { //$1/tensorflow/python:session_test + \ //$1/tensorflow/python:supervisor_test + \ //$1/tensorflow/python:sync_replicas_optimizer_test + \ - //$1/tensorflow/python/debug/... + \ + //$1/tensorflow/python/debug:curses_ui_test + \ //$1/tensorflow/python/kernel_tests:as_string_op_test + \ //$1/tensorflow/python/kernel_tests:benchmark_test + \ //$1/tensorflow/python/kernel_tests:cast_op_test + \ |