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ci/official/utilities/code_check_changed_files.bats
setup_file() { bazel version # Start the bazel server # Fixes "fatal: detected dubious ownership in repository" for Docker. git config --system --add safe.directory '*' git config --system protocol.file.allow always # Note that you could generate a list of all the affected targets with e.g.: # bazel query $(paste -sd "+" $BATS_FILE_TMPDIR/changed_files) --keep_going
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tensorflow/c/eager/parallel_device/BUILD
cc_library( name = "parallel_device_lib", srcs = [":lib_sources"], hdrs = [":lib_headers"], visibility = ["//tensorflow:internal"], deps = [ "//tensorflow/c:c_api", "//tensorflow/c:safe_ptr", "//tensorflow/c:tf_status_internal", "//tensorflow/c/eager:c_api", "//tensorflow/c/eager:c_api_experimental", "//tensorflow/c/eager:tfe_cancellation_manager_internal",
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tensorflow/c/experimental/filesystem/plugins/gcs/expiring_lru_cache.h
#include "tensorflow/c/tf_status.h" namespace tf_gcs_filesystem { /// \brief An LRU cache of string keys and arbitrary values, with configurable /// max item age (in seconds) and max entries. /// /// This class is thread safe. template <typename T> class ExpiringLRUCache { public: /// A `max_age` of 0 means that nothing is cached. A `max_entries` of 0 means /// that there is no limit on the number of entries in the cache (however, if
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WORKSPACE
) # buildifier: disable=same-origin-load load("@rules_python//python:repositories.bzl", "py_repositories") py_repositories() load("@rules_python//python:repositories.bzl", "python_register_toolchains") # buildifier: disable=same-origin-load load( "//tensorflow/tools/toolchains/python:python_repo.bzl", "python_repository", )
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ci/official/requirements_updater/README.md
for an example. See [this commit](https://github.com/tensorflow/tensorflow/commit/5f7f05a80aac9b01325a78ec3fcff0dbedb1cc23) as a rough example of the steps below. All the files referenced below are located in the same directory as this README, unless indicated otherwise. 1) Add the new version to the `VERSIONS` variable inside `tensorflow/tools/toolchains/python/python_repo.bzl`. \
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tensorflow/c/BUILD
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tensorflow/c/eager/c_api_experimental.h
TF_CAPI_EXPORT TFE_TensorHandle* TFE_NewTensorHandleFromTensor( TFE_Context* ctx, TF_Tensor* t, TF_Status* status); // Create a packed TensorHandle with the given list of TensorHandles. // If `handles` are on the same device, assign the same device to the packed // handle; if `handles` are on different deivces, assign a CompositeDevice to // it. TF_CAPI_EXPORT extern TFE_TensorHandle* TFE_CreatePackedTensorHandle(
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CONTRIBUTING.md
to the core. * As every PR requires several CPU/GPU hours of CI testing, we discourage submitting PRs to fix one typo, one warning,etc. We recommend fixing the same issue at the file level at least (e.g.: fix all typos in a file, fix all compiler warnings in a file, etc.) * Tests should follow the [testing best practices](https://www.tensorflow.org/community/contribute/tests)
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tensorflow/c/eager/gradients.cc
gtl::ArraySlice<AbstractTensorHandle*> output_gradients, absl::Span<AbstractTensorHandle*> result) const override; // Builds a tensor filled with ones with the same shape and dtype as `t`. Status BuildOnesLike(const TapeTensor& t, AbstractTensorHandle** result) const override; // Looks up the ID of a Gradient.
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tensorflow/c/eager/custom_device_test.cc
TFE_Execute(matmul.get(), &retval, &num_retvals, status.get()); ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get()); TFE_DeleteTensorHandle(retval); // Custom device: inputs in same custom device works. matmul.reset(MatMulOp(context.get(), hcustom0.get(), hcustom0.get())); num_retvals = 1; executed = false; TFE_Execute(matmul.get(), &retval, &num_retvals, status.get());
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