TensorFlow coding style.

#### General guidelines and philosophy for contribution

*   Include unit tests when you contribute new features, as they help to a)
    prove that your code works correctly, and b) guard against future breaking
    changes to lower the maintenance cost.
*   Bug fixes also generally require unit tests, because the presence of bugs
    usually indicates insufficient test coverage.

    const char* export_dir, const char* const* tags, int tags_len,
    TF_Graph* graph, TF_Buffer* meta_graph_def, TF_Status* status) {
// TODO(sjr): Remove the IS_MOBILE_PLATFORM guard. This will require ensuring
// that the tensorflow/cc/saved_model:loader build target is mobile friendly.
#if defined(IS_MOBILE_PLATFORM) || defined(IS_SLIM_BUILD)
  status->status = tensorflow::errors::Unimplemented(

*   Add support of local soft device placement for eager op.
*   Add HW acceleration support for `LogSoftMax`.
*   Added a function `nested_value_rowids` for ragged tensors.
*   Add guard to avoid acceleration of L2 Normalization with input rank != 4
*   Add `tf.math.cumulative_logsumexp operation`.
*   Add `tf.ragged.stack`.
*   Fix memory allocation problem when calling `AddNewInputConstantTensor`.

# See: https://github.com/bazelbuild/bazel/issues/5163
build:windows --features=compiler_param_file

# Do not risk cache corruption. See:
# 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