Function main

tensorflow/compiler/xla/service/cpu/sample_harness.cc:34–73

#include "tensorflow/core/platform/logging.h"

int main(int argc, char** argv) {
  tensorflow::port::InitMain(argv[0], &argc, &argv);

  xla::LocalClient* client(xla::ClientLibrary::LocalClientOrDie());

  // Transfer parameters.
  xla::Literal param0_literal =
      xla::LiteralUtil::CreateR1<float>({1.1f, 2.2f, 3.3f, 5.5f});
  std::unique_ptr<xla::GlobalData> param0_data =
      client->TransferToServer(param0_literal).ConsumeValueOrDie();

  xla::Literal param1_literal = xla::LiteralUtil::CreateR2<float>(
      {{3.1f, 4.2f, 7.3f, 9.5f}, {1.1f, 2.2f, 3.3f, 4.4f}});
  std::unique_ptr<xla::GlobalData> param1_data =
      client->TransferToServer(param1_literal).ConsumeValueOrDie();

  // Build computation.
  xla::XlaBuilder builder("");
  auto p0 = Parameter(&builder, 0, param0_literal.shape(), "param0");
  auto p1 = Parameter(&builder, 1, param1_literal.shape(), "param1");
  Add(p1, p0, {0});

  xla::StatusOr<xla::XlaComputation> computation_status = builder.Build();
  xla::XlaComputation computation = computation_status.ConsumeValueOrDie();

  // Execute and transfer result of computation.
  xla::ExecutionProfile profile;
  xla::StatusOr<xla::Literal> result = client->ExecuteAndTransfer(
      computation,
      /*arguments=*/{param0_data.get(), param1_data.get()},
      /*execution_options=*/nullptr,
      /*execution_profile=*/&profile);
  xla::Literal actual = result.ConsumeValueOrDie();

  LOG(INFO) << absl::StrFormat("computation took %dns",
                               profile.compute_time_ns());
  LOG(INFO) << actual.ToString();

  return 0;
}