"//tensorflow:windows": """
              $(location @local_config_def_file_filter//:def_file_filter) \\
              --input $(location :tensorflow_def_file) \\
              --output $@
          """,
        "//conditions:default": "touch $@",  # Just a placeholder for Unix platforms
    }),
    tools = ["@local_config_def_file_filter//:def_file_filter"],
    visibility = ["//visibility:public"],
)

  ///    placed in `out`.
  /// 4) `TF_OK` otherwise (i.e. the read succeeded, and at least one byte was
  /// placed
  ///    in `buffer`).
  ///
  /// Caller is responsible for allocating memory for `buffer`.
  /// `buffer` will be left unchanged in case of errors.
  int64_t Read(const std::string& filename, size_t offset, size_t n,
               char* buffer, TF_Status* status);

}

// Registers filesystem at `index`, if plugin is providing valid information.
//
// Extracted to a separate function so that pointers inside `info` are freed
// by the caller regardless of whether validation/registration failed or not.
//
// Must be called only with `index` a valid index in `info->ops`.
static Status ValidateAndRegisterFilesystems(

              bool expect_failure = false) {
    DefineT(num_opers, opers, ToOutput(inputs), ToOutput(outputs), output_names,
            expect_failure);
  }

  // Caller must delete[] the returned value
  static const char** ToArray(const std::vector<string>& strs) {
    const char** ptr = nullptr;
    if (!strs.empty()) {
      ptr = new const char*[strs.size()];

    *   Added a new field, `filter_parallelization`, to `tf.data.experimental.OptimizationOptions`. If it is set to `True`, tf.data will run `Filter` transformation with multiple threads. Its default value is `False` if not specified.

*   `tf.keras`:

      console.log(resp_assign);
      throw "Error adding assignee to PR";
    }
  }
  return `PR Updated successfully with Labels: ${labels} with Assignees: ${assignees}`;
};

module.exports = {
  filter: filter_action,
  get_email_domain

// The returned string is heap-allocated, and caller should call free() on it.
TF_CAPI_EXPORT extern const char* TF_GraphDebugString(TF_Graph* graph,
                                                      size_t* len);

// Returns the function content in a human-readable format, with length set in
// `len`. The format is subject to change in the future.
// The returned string is heap-allocated, and caller should call free() on it.
//

      const std::vector<int64_t>& unneeded_gradients,
      gtl::ArraySlice<Gradient*> output_gradients,
      absl::Span<Gradient*> result) const = 0;

  // Builds a tensor filled with ones with the same shape and dtype as `t`.
  virtual Status BuildOnesLike(const TapeTensor& t,
                               Gradient** result) const = 0;

  // Looks up the ID of a Gradient.

  // scheduled on that same threadpool, causing a deadlock in cases where the
  // caller of event_mgr->ThenExecute() blocks on the completion of the callback
  // (as in the case of ConstOp kernel creation on GPU, which involves copying a
  // CPU tensor to GPU).
  // Setting a larger thread pool does not help with the Swift caller, as we use
  // a different TFE context for each thread of execution (for running graph

# https://github.com/bazelbuild/bazel/issues/3360
build:linux --experimental_guard_against_concurrent_changes

# Configure short or long logs
build:short_logs --output_filter=DONT_MATCH_ANYTHING
build:verbose_logs --output_filter=

# Instruction set optimizations
# TODO(gunan): Create a feature in toolchains for avx/avx2 to
#   avoid having to define linux/win separately.
build:avx_linux --copt=-mavx