EXPECT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
  }

  void BuildExpectedGraph(bool grad_inputs_provided,
                          TF_Output* expected_grad_outputs) {
    // The expected graph looks like this if grad_inputs_provided.
    // If grad_inputs_provided is false, Const_0 will be a OnesLike op.
    //      ^             ^
    //    dy|           dx|        // MatMul Gradient Graph
    //      |             |

#endif  // defined(IS_MOBILE_PLATFORM) || defined(IS_SLIM_BUILD)
}

#if !defined(IS_MOBILE_PLATFORM) && !defined(IS_SLIM_BUILD)
namespace {

// TODO(skyewm): make nodes in while loop unfetchable like in Python version
void TF_FinishWhileHelper(const TF_WhileParams* params, TF_Status* status,
                          TF_Output* outputs) {
  if (!ValidateInputWhileParams(*params, status)) return;

// have been executed. Note that "execution" here refers to kernel execution /
// scheduling of copies, etc. Similar to sync execution, it doesn't guarantee
// that lower level device queues (like GPU streams) have been flushed.
//
// This call may not block for execution of ops enqueued concurrently with this
// call.
TF_CAPI_EXPORT extern void TFE_ExecutorWaitForAllPendingNodes(

    to fix this.
-   Once the internal tests pass, we go ahead and merge the code internally as
    well as externally on GitHub.

In a graphical form, the entire lifetime of a PR looks like

![image](https://github.com/tensorflow/tensorflow/assets/52792999/3eea4ca5-daa0-4570-b0b5-2a2b03a724a3)

### Contributor License Agreements

*  `tf.experimental.dtensor`
    * API changes for Relayout. Added a new API, `dtensor.relayout_like`, for relayouting a tensor according to the layout of another tensor.

          if (op_it->second.output_tensor_info[j].GetID() == id) {
            found = true;
            Gradient* ones_like = nullptr;
            TF_RETURN_IF_ERROR(vspace.BuildOnesLike(
                op_it->second.output_tensor_info[j], &ones_like));
            (*result)[id].push_back(ones_like);
            break;
          }
        }
        if (!found) {
          return errors::Internal(

to a banned CUDA dependency when '--define framework_shared_object=false' is set.
This means that a CUDA target was probably included via an is_static condition,
used when targeting platforms like Windows where we build statically instead
of dynamically. Here's the output from bazel query:
EOF
  cat $BATS_TEST_TMPDIR/out
  [[ ! -s $BATS_TEST_TMPDIR/out ]]
}

      'build --copt=/d2ReducedOptimizeHugeFunctions --host_copt=/d2ReducedOptimizeHugeFunctions'
  )

  if get_var(
      environ_cp, 'TF_OVERRIDE_EIGEN_STRONG_INLINE', 'Eigen strong inline',
      True, ('Would you like to override eigen strong inline for some C++ '
             'compilation to reduce the compilation time?'),
      'Eigen strong inline overridden.', 'Not overriding eigen strong inline, '

build:monolithic --define tsl_protobuf_header_only=false
build:monolithic --experimental_link_static_libraries_once=false  # b/229868128

# Please note that MKL on MacOS is still not supported.
# If you would like to use a local MKL instead of downloading, please set the
# environment variable "TF_MKL_ROOT" every time before build.
build:mkl --define=build_with_mkl=true --define=enable_mkl=true