it's finished. The default is `False` for backward compatibility. Users of
      `distributed_save` are recommended to set it to `True`.

* `tf.tpu.experimental.embedding.TPUEmbeddingV2`
    * Add `compute_sparse_core_stats` for sparse core users to profile the 
      data with this API to get the `max_ids` and `max_unique_ids`. These

        ":tf_buffer_hdrs",
        ":tf_datatype_hdrs",
        ":tf_status_headers",
        ":tf_tensor_hdrs",
        # TODO: Only include tf_tstring_hdrs. Don't expose the implementation of TF_TString to API
        # users.
        ":tf_tstring",
        "//tensorflow/core:protos_all_cc",
    ],
)

tf_cuda_library(
    name = "c_api_internal",
    hdrs = [
        "c_api.h",
        "c_api_internal.h",

  elif is_windows():
    default_cc_opt_flags = '/arch:AVX'
  else:
    # On all other platforms, no longer use `-march=native` as this can result
    # in instructions that are too modern being generated. Users that want
    # maximum performance should compile TF in their environment and can pass
    # `-march=native` there.
    # See https://github.com/tensorflow/tensorflow/issues/45744 and duplicates

  // If `persistent` is true, GradientTape will not eagerly delete backward
  // functions (and hence the tensors they keep alive). Instead, everything
  // is deleted in ~GradientTape. Persistent GradientTapes are useful when
  // users want to compute multiple gradients over the same tape.
  explicit GradientTape(bool persistent) : persistent_(persistent) {}
  ~GradientTape() {
    for (const auto& pair : op_tape_) {

# reduce the size of the debug info in the binary. This is because if the debug
# sections in the ELF binary are too large, errors can occur. See
# https://github.com/tensorflow/tensorflow/issues/48919.
# Users can still include debug info for a specific kernel, e.g. with:
#     --config=dbg --per_file_copt=+tensorflow/core/kernels/identity_op.*@-g
# Since this .bazelrc file is synced between the tensorflow/tensorflow repo and