Method Run

tensorflow/compiler/xla/service/hlo_verifier.cc:1775–1816

}  // namespace

StatusOr<bool> HloVerifier::Run(HloModule* module) {
  TF_RET_CHECK(!module->name().empty());

  if (module->entry_computation()->IsFusionComputation()) {
    return InvalidArgument(
        "Module entry computation cannot be a fusion computation");
  }

  TF_RETURN_IF_ERROR(VerifyHloStructure(module));
  TF_RETURN_IF_ERROR(VerifyAsynchronousCopies(*module));
  TF_RETURN_IF_ERROR(VerifyChannels(*module));

  std::unique_ptr<ShapeVerifier> shape_verifier =
      target_metadata_->GetVerifier();
  InstructionVerifier instruction_verifier(instruction_can_change_layout_func_);
  for (auto* computation : module->computations()) {
    TF_RETURN_IF_ERROR(computation->Accept(shape_verifier.get()));
    TF_RETURN_IF_ERROR(computation->Accept(&instruction_verifier));
  }

  TF_RETURN_IF_ERROR(shape_verifier->VerifyEntryComputationLayout(*module));
  TF_RETURN_IF_ERROR(VerifyEntryAndExitShapes(*module));

  // If the module has a schedule, it must be valid.
  if (module->has_schedule()) {
    TF_RETURN_IF_ERROR(module->schedule().Verify());
  }

  TF_RETURN_IF_ERROR(module->input_output_alias_config().Verify(
      *module, [this](const Shape& shape) -> int64 {
        if (target_metadata_->IsLayoutSensitive()) {
          return target_metadata_->ShapeSize(shape);
        } else {
          return 0;
        }
      }));

  TF_RETURN_IF_ERROR(module->dynamic_parameter_binding().Verify(*module));
  TF_RETURN_IF_ERROR(VerifyLayoutConstrainedAllReduce(*module));

  return false;
}

}  // namespace xla