Function XLA_TEST_F

tensorflow/compiler/xla/tests/execution_profile_test.cc:28–68

class ExecutionProfileTest : public ClientLibraryTestBase {};

XLA_TEST_F(ExecutionProfileTest, ExecuteWithExecutionProfile) {
  Shape shape = ShapeUtil::MakeShape(F32, {256, 256});

  TF_ASSERT_OK_AND_ASSIGN(
      std::unique_ptr<GlobalData> input,
      client_->TransferToServer(
          LiteralUtil::CreateR2F32Linspace(1e0, 1e5, 256, 256)));

  XlaBuilder b(TestName() + ".add");
  Dot(Parameter(&b, 0, shape, "param_0"), Parameter(&b, 1, shape, "param_1"));
  TF_ASSERT_OK_AND_ASSIGN(XlaComputation dot_product, b.Build());

  ExecutionProfile execution_profile;
  TF_ASSERT_OK_AND_ASSIGN(
      std::unique_ptr<GlobalData> data,
      client_->Execute(dot_product, {input.get(), input.get()},
                       &execution_options_, &execution_profile));

  VLOG(3) << "execution_profile.compute_cycle_count() = "
          << execution_profile.compute_cycle_count();
  VLOG(3) << "execution_profile.compute_and_transfer_time_ns() = "
          << execution_profile.compute_and_transfer_time_ns();
  VLOG(3) << "execution_profile.compute_time_ns() = "
          << execution_profile.compute_time_ns();

  bool hlo_profiling_enabled =
      execution_options_.debug_options().xla_hlo_profile();

  // If HLO profiling is enabled we always expect cycle count to be populated.
  // If HLO profiling is disabled then depending on the backend the cycle count
  // may or may not be populated.
  if (hlo_profiling_enabled) {
    EXPECT_GT(execution_profile.compute_cycle_count(), 0);
  }

  EXPECT_GT(execution_profile.compute_and_transfer_time_ns(), 0);
  EXPECT_GT(execution_profile.compute_time_ns(), 0);

  TF_ASSERT_OK_AND_ASSIGN(auto computed, client_->Transfer(*data, &shape));
  (void)computed;
}

}  // namespace
}  // namespace xla