return;
      } else if (execution_state_ == ExecutionState::kReadyToExecute) {
        // op_outputs_ may have been std::moved
        op_outputs_ = std::vector<TensorHandlePtr>();
        Execute(context_, operation_name_, std::move(op_inputs_), attributes_,
                expected_max_outputs_, &op_outputs_, status_.get());
        execution_state_ = ExecutionState::kHasResult;
      }
    }

        "first un-packed. Got an un-placed op with an input placed on the "
        "parallel device.");
    return;
  }
  TFE_Context* context = TFE_OpGetContext(original_op, status);
  if (TF_GetCode(status) != TF_OK) return;
  const char* operation_name = TFE_OpGetName(original_op, status);
  if (TF_GetCode(status) != TF_OK) return;
  const TFE_OpAttrs* attributes = TFE_OpGetAttrs(original_op);

  NamedParallelDevice* named_device =

  ASSERT_EQ(TF_OK, TF_GetCode(status));

  const OpDef* expected_op_def;
  TF_ASSERT_OK(OpRegistry::Global()->LookUpOpDef("Add", &expected_op_def));
  string expected_serialized;
  expected_op_def->SerializeToString(&expected_serialized);
  EXPECT_EQ(expected_serialized, actual_string);
  TF_DeleteBuffer(g_buf);
  TF_DeleteBuffer(op_buf);
  TF_DeleteStatus(status);
  TF_DeleteFunctionLibraryDefinition(func);
}

      "      name: 'read0'"
      "      op: 'ReadVariableOp'"
      "      input: 'var'"
      "      device: '/job:localhost/replica:0/task:0/device:CPU:0'"
      "      attr {"
      "        key: 'dtype'"
      "        value {"
      "          type: DT_FLOAT"
      "        }"
      "      }"
      "    }"
      "    node_def {"
      "      name: 'read1'"
      "      op: 'ReadVariableOp'"
      "      input: 'var'"

  TFE_OpAddInput(op, in, status);
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TF_DeleteStatus(status);

  TFE_OpSetAttrType(op, "T", TFE_TensorHandleDataType(in));
  TFE_OpSetAttrInt(op, "group_size", group_size);
  TFE_OpSetAttrInt(op, "group_key", 123);
  TFE_OpSetAttrInt(op, "instance_key", 456);
  TFE_OpSetAttrString(op, "merge_op", "Add", 3);
  TFE_OpSetAttrString(op, "final_op", "Id", 2);

void TFE_DeleteOp(TFE_Op* op) {
  if (op == nullptr) {
    return;
  }

  tensorflow::unwrap(op)->Release();
}

const char* TFE_OpGetName(const TFE_Op* op, TF_Status* status) {
  return tensorflow::unwrap(op)->Name().c_str();
}

TFE_Context* TFE_OpGetContext(const TFE_Op* op, TF_Status* status) {
  return tensorflow::wrap(tensorflow::unwrap(op)->GetContext());
}

  Status Reset(const char* op, const char* raw_device_name) override {
    if (op_) {
      return errors::FailedPrecondition("Reset called on already built op.");
    }
    if (raw_device_name) {
      device_name_ = raw_device_name;
    }
    op_type_ = op;
    return absl::OkStatus();
  }
  Status SetOpName(const char* const op_name) override {
    if (op_) {
      return errors::FailedPrecondition(

namespace tracing {

Status MaybeSetOpName(AbstractOperation* op, const char* op_name) {
  if (isa<TracingOperation>(op)) {
    TF_RETURN_IF_ERROR(dyn_cast<TracingOperation>(op)->SetOpName(op_name));
  }
  if (isa<gradients::TapeOperation>(op)) {
    TF_RETURN_IF_ERROR(MaybeSetOpName(
        dyn_cast<gradients::TapeOperation>(op)->GetBackingOperation(),
        op_name));
  }
  return absl::OkStatus();
}
}  // namespace tracing

                    /*expected_shape*/ make_shape({1, 6}));
  TFE_DeleteOp(reshape_op);
  reshape_op = nullptr;

  TFE_Op* fill_op = TFE_NewOp(tfe_context_, "Fill", status_);
  CHECK_EQ(TF_OK, TF_GetCode(status_)) << TF_Message(status_);
  TFE_OpSetAttrType(fill_op, "T", TF_FLOAT);
  TFE_OpSetAttrType(fill_op, "Tshape", TF_INT32);

  float five = 5.0;

}  // namespace

GradientFunction* AddRegisterer(const ForwardOperation& op) {
  return new AddGradientFunction;
}

GradientFunction* ExpRegisterer(const ForwardOperation& op) {
  return new ExpGradientFunction(op.outputs[0]);
}

GradientFunction* MatMulRegisterer(const ForwardOperation& op) {
  return new MatMulGradientFunction(op.inputs, op.attrs);
}

GradientFunction* SqrtRegisterer(const ForwardOperation& op) {