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Merge pull request #6139 from gunan/cp
[CMake] Fix support for custom kernels in `tf.contrib.metrics`.
2 parents b8ee14f + 9ff4b1a commit f65c8ce

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-10
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‎tensorflow/contrib/cmake/tf_core_ops.cmake‎

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@@ -46,6 +46,7 @@ GENERATE_CONTRIB_OP_LIBRARY(cudnn_rnn "${tensorflow_source_dir}/tensorflow/contr
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GENERATE_CONTRIB_OP_LIBRARY(factorization_clustering "${tensorflow_source_dir}/tensorflow/contrib/factorization/ops/clustering_ops.cc")
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GENERATE_CONTRIB_OP_LIBRARY(factorization_factorization "${tensorflow_source_dir}/tensorflow/contrib/factorization/ops/factorization_ops.cc")
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GENERATE_CONTRIB_OP_LIBRARY(framework_variable "${tensorflow_source_dir}/tensorflow/contrib/framework/ops/variable_ops.cc")
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GENERATE_CONTRIB_OP_LIBRARY(metrics_set "${tensorflow_source_dir}/tensorflow/contrib/metrics/ops/set_ops.cc")
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GENERATE_CONTRIB_OP_LIBRARY(word2vec "${tensorflow_source_dir}/tensorflow/models/embedding/word2vec_ops.cc")
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########################################################

‎tensorflow/contrib/cmake/tf_python.cmake‎

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@@ -504,6 +504,8 @@ GENERATE_PYTHON_OP_LIB("contrib_factorization_factorization_ops"
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DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/tf_python/tensorflow/contrib/factorization/python/ops/gen_factorization_ops.py)
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GENERATE_PYTHON_OP_LIB("contrib_framework_variable_ops"
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DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/tf_python/tensorflow/contrib/framework/python/ops/gen_variable_ops.py)
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GENERATE_PYTHON_OP_LIB("contrib_metrics_set_ops"
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DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/tf_python/tensorflow/contrib/metrics/python/ops/gen_set_ops.py)
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GENERATE_PYTHON_OP_LIB("contrib_word2vec_ops"
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DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/tf_python/tensorflow/models/embedding/gen_word2vec.py
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SHAPE_FUNCTIONS_NOT_REQUIRED)

‎tensorflow/contrib/cmake/tf_tests.cmake‎

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@@ -119,6 +119,7 @@ if (tensorflow_BUILD_PYTHON_TESTS)
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"${tensorflow_source_dir}/tensorflow/python/training/*_test.py"
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"${tensorflow_source_dir}/tensorflow/tensorboard/*_test.py"
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"${tensorflow_source_dir}/tensorflow/models/*_test.py"
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"${tensorflow_source_dir}/tensorflow/contrib/metrics/*_test.py"
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)
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# exclude the onces we don't want

‎tensorflow/contrib/metrics/BUILD‎

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@@ -35,12 +35,7 @@ tf_gen_op_libs(
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tf_gen_op_wrapper_py(
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name = "set_ops",
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hidden = [
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"DenseToDenseSetOperation",
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"DenseToSparseSetOperation",
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"SparseToSparseSetOperation",
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"SetSize",
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],
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out = "python/ops/gen_set_ops.py",
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deps = [":set_ops_op_lib"],
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)
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‎tensorflow/contrib/metrics/python/ops/set_ops.py‎

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@@ -19,6 +19,7 @@
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from tensorflow.contrib.framework.python.framework import tensor_util
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from tensorflow.contrib.metrics.python.ops import gen_set_ops
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from tensorflow.contrib.util import loader
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from tensorflow.python.framework import dtypes
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from tensorflow.python.framework import ops
@@ -56,7 +57,7 @@ def set_size(a, validate_indices=True):
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if a.values.dtype.base_dtype not in _VALID_DTYPES:
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raise TypeError("Invalid dtype %s." % a.values.dtype)
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# pylint: disable=protected-access
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return _set_ops.set_size(a.indices, a.values, a.shape, validate_indices)
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return gen_set_ops.set_size(a.indices, a.values, a.shape, validate_indices)
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ops.NotDifferentiable("SetSize")
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@@ -100,17 +101,17 @@ def _set_operation(a, b, set_operation, validate_indices=True):
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# pylint: disable=protected-access
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if isinstance(a, sparse_tensor.SparseTensor):
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if isinstance(b, sparse_tensor.SparseTensor):
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indices, values, shape = _set_ops.sparse_to_sparse_set_operation(
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indices, values, shape = gen_set_ops.sparse_to_sparse_set_operation(
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a.indices, a.values, a.shape, b.indices, b.values, b.shape,
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set_operation, validate_indices)
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else:
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raise ValueError("Sparse,Dense is not supported, but Dense,Sparse is. "
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"Please flip the order of your inputs.")
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elif isinstance(b, sparse_tensor.SparseTensor):
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indices, values, shape = _set_ops.dense_to_sparse_set_operation(
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indices, values, shape = gen_set_ops.dense_to_sparse_set_operation(
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a, b.indices, b.values, b.shape, set_operation, validate_indices)
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else:
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indices, values, shape = _set_ops.dense_to_dense_set_operation(
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indices, values, shape = gen_set_ops.dense_to_dense_set_operation(
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a, b, set_operation, validate_indices)
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# pylint: enable=protected-access
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return sparse_tensor.SparseTensor(indices, values, shape)

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