support. Going forward, we will stop testing on Mac GPU systems. We continue
    to welcome patches that maintain Mac GPU support, and we will try to keep
    the Mac GPU build working.

## Changes to contrib APIs

*   The behavior of RNNCells is now stricter due to the transition towards
    making RNNCells act more like Keras layers.

    t.reset(x_raw);
  }

  AbstractOperationPtr check_numerics_op(ctx->CreateOperation());
  ForwardOperation forward_op;
  Status s = Reset(check_numerics_op.get(), "CheckNumerics",
                   /*raw_device_name=*/nullptr, &forward_op);
  ASSERT_EQ(errors::OK, s.code()) << s.message();
  if (isa<TracingOperation>(check_numerics_op.get())) {

Status RunAndMaybeSum(AbstractContext* ctx, Model forward,
                      absl::Span<AbstractTensorHandle* const> inputs,
                      absl::Span<AbstractTensorHandle*> outputs,
                      bool use_function) {
  AbstractTensorHandle* model_outputs[1];

  // Run the model.
  TF_RETURN_IF_ERROR(
      RunModel(forward, ctx, inputs, model_outputs, use_function));

    device_threads_.emplace_back(new DeviceThread(
        devices[device_index].c_str(), is_async, in_flight_nodes_limit));
  }
}

// Necessary for a unique_ptr to a forward-declared type.
ParallelDevice::~ParallelDevice() = default;

std::unique_ptr<ParallelTensor> ParallelDevice::CopyToParallelDevice(
    TFE_Context* context, TFE_TensorHandle* tensor, TF_Status* status) const {

#include "tensorflow/c/tf_tensor.h"
#include "tensorflow/c/tf_tstring.h"

// --------------------------------------------------------------------------
// C API for TensorFlow.
//
// The API leans towards simplicity and uniformity instead of convenience
// since most usage will be by language specific wrappers.
//
// Conventions:
// * We use the prefix TF_ for everything in the API.