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CONTRIBUTING.md
```bash bazel run //tensorflow/tools/docs:tf_doctest ``` or ```bash bazel run //tensorflow/tools/docs:tf_doctest -- --module=ops.array_ops ``` The `--module` is relative to `tensorflow.python`. #### Debug builds When [building Tensorflow](https://www.tensorflow.org/install/source), passing
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tensorflow/c/experimental/filesystem/filesystem_interface.h
const TF_TransactionToken* token); /// Returns pointer to an array of available configuration options and their /// current/default values in `options` and number of options in array in /// `num_options`. Ownership of the array is transferred to caller and the /// caller is responsible of freeing the buffers using respective file systems /// allocation API. ///
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tensorflow/c/experimental/gradients/math_grad.cc
#include "tensorflow/c/experimental/gradients/math_grad.h" #include "tensorflow/c/eager/abstract_tensor_handle.h" #include "tensorflow/c/eager/gradients.h" #include "tensorflow/c/experimental/ops/array_ops.h" #include "tensorflow/c/experimental/ops/math_ops.h" #include "tensorflow/c/experimental/ops/nn_ops.h" using std::vector; using tensorflow::ops::AddV2; using tensorflow::ops::Div;
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tensorflow/c/c_api_function_test.cc
* | * | * v */ // Define TF_Tensor* tensor_123 = Int32Tensor({1, 2, 3}); TF_Operation* c = Const(tensor_123, func_graph_, s_, "const_array"); ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_); TF_Operation* split = Split3(c, func_graph_, s_); TF_Operation* add = Add({split, 0}, {split, 2}, func_graph_, s_);
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tensorflow/c/eager/BUILD
":unified_api_testutil", "//tensorflow/c:c_api", "//tensorflow/c:c_test_util", "//tensorflow/c:tf_status_helper", "//tensorflow/c/experimental/gradients:array_grad", "//tensorflow/c/experimental/gradients:math_grad", "//tensorflow/c/experimental/gradients:not_differentiable", "//tensorflow/c/experimental/gradients/tape:tape_context",
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tensorflow/c/experimental/gradients/array_grad.h
#ifndef TENSORFLOW_C_EXPERIMENTAL_GRADIENTS_ARRAY_GRAD_H_ #define TENSORFLOW_C_EXPERIMENTAL_GRADIENTS_ARRAY_GRAD_H_ #include "tensorflow/c/eager/gradients.h" namespace tensorflow { namespace gradients { GradientFunction* IdentityNRegisterer(const ForwardOperation& op); } // namespace gradients } // namespace tensorflow
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RELEASE.md
dataset, in one function call. * **[`timeseries_dataset_from_array`](https://www.tensorflow.org/api_docs/python/tf/keras/preprocessing/timeseries_dataset_from_array)** is a `tf.data.Dataset`-based replacement of the legacy `TimeseriesGenerator`. It takes you from an array of timeseries data to a dataset of shifting windows with their targets. * Added
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tensorflow/c/experimental/gradients/array_grad.cc
See the License for the specific language governing permissions and limitations under the License. ==============================================================================*/ #include "tensorflow/c/experimental/gradients/array_grad.h" #include "tensorflow/c/eager/abstract_context.h" namespace tensorflow { namespace gradients { namespace { class IdentityNGradientFunction : public GradientFunction { public:
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tensorflow/c/experimental/gradients/BUILD
# Library of gradient functions. package( # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"], licenses = ["notice"], ) cc_library( name = "array_grad", srcs = ["array_grad.cc"], hdrs = [ "array_grad.h", ], visibility = [ "//tensorflow:internal", ], deps = [ "//tensorflow/c/eager:abstract_context",
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tensorflow/c/c_api_experimental.cc
delete shape_list; } void TF_DeleteShapeAndTypeListArray(TF_ShapeAndTypeList** shape_list_array, int num_items) { if (shape_list_array == nullptr) return; for (int i = 0; i < num_items; ++i) { TF_DeleteShapeAndTypeList(shape_list_array[i]); } delete[] shape_list_array; } namespace tensorflow { Status TF_TensorToTensor(const TF_Tensor* src, Tensor* dst);
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