: filesystem_(std::move(filesystem)),
        ops_(std::move(filesystem_ops)),
        random_access_file_ops_(std::move(random_access_file_ops)),
        writable_file_ops_(std::move(writable_file_ops)),
        read_only_memory_region_ops_(std::move(read_only_memory_region_ops)),
        plugin_memory_allocate_(std::move(plugin_memory_allocate)),
        plugin_memory_free_(std::move(plugin_memory_free)) {}

      xla::PjRtClient::HostBufferSemantics::kImmutableOnlyDuringCall, nullptr,
      c_api_client->pjrt_c_client()->client->addressable_devices()[0]);
  CHECK_OK(buffer.status());

  return new PJRT_Buffer{std::move(*buffer), c_api_client->pjrt_c_client()};
}

TEST(TensorPjRtBufferUtilTest, GetPjRtCBufferFromTensorNoBuffer) {
  auto allocator = std::make_unique<AsyncValueAllocator>();

A downside of this structure is that it is difficult to do focused work on the Gradle UI.

## Decision

Introduce a "UI" architecture module to the core platform, and move the user interaction services to this new module.

This includes:

- Logging and progress services.
- Problem generation services (aka the "problems API").
- User prompting services.
- Build options infrastructure.

    (*var_to_data_type_map)[key] = DataType(entry.dtype());
  }
  // The returned pointers are owned by the caller.
  return std::make_pair(std::move(var_to_shape_map),
                        std::move(var_to_data_type_map));
}

}  // namespace checkpoint

  if (av_tensor == nullptr) {
    TF_ASSIGN_OR_RETURN(
        *tensor, MakeTensorFromPjRtBuffer(tensor->dtype(), tensor->shape(),
                                          std::move(buffer)));
  } else {
    av_tensor->SetBuffer(std::move(buffer));
  }
  return absl::OkStatus();
}

absl::StatusOr<xla::PjRtCApiClient*> GetPjRtCApiClient(
    const DeviceType& device_type) {

  fun invalidatesCache(method: String): Boolean =
    (
      method == "POST" || method == "PATCH" || method == "PUT" ||
        method == "DELETE" || method == "MOVE"
    )

  @JvmStatic // Despite being 'internal', this method is called by popular 3rd party SDKs.
  fun requiresRequestBody(method: String): Boolean =
    (
      method == "POST" || method == "PUT" ||

    }
  }

  TF_DeleteTensor(analytical_tensor);
  delete[] danalytical;
}

Model BuildGradModel(Model forward, GradientRegistry registry) {
  return [forward_model = std::move(forward),
          grad_registry = std::move(registry)](
             AbstractContext* ctx,
             absl::Span<AbstractTensorHandle* const> inputs,
             absl::Span<AbstractTensorHandle*> outputs) -> Status {

	//		outcode(int($1), &$2, 0, &nullgen);
	//	}
	NOP	$4

	//
	// special
	//
	SYSCALL
	BREAK
	SYNC

	//
	// conditional move on zero/nonzero gp value
	//
	CMOVN	R1, R2, R3
	CMOVZ	R1, R2, R3

	//
	// conditional move on fp false/true
	//
	CMOVF	R1, R2
	CMOVT	R1, R2

	//
	// conditional traps
	//
	TEQ	$1, R1, R2
	TEQ	$1, R1


	//

set -euxo pipefail

cd "$TFCI_OUTPUT_DIR"

# Move extra wheel files somewhere out of the way. This script
# expects just one wheel file to exist.
if [[ "$(ls *.whl | wc -l | tr -d ' ')" != "1" ]]; then
  echo "More than one wheel file is present: moving the oldest to"
  echo "$TFCI_OUTPUT_DIR/extra_wheels."
  # List all .whl files by their modification time (ls -t) and move anything

namespace tensorflow {
namespace tracing {
namespace graph {
GraphFunction::GraphFunction(FunctionDef fdef)
    : AbstractFunction(kGraph),
      func_record_(new FunctionRecord(std::move(fdef), {}, true)) {}
GraphFunction::~GraphFunction() {}
Status GraphFunction::GetFunctionDef(const FunctionDef **fdef) {
  *fdef = &(func_record_->fdef());
  return absl::OkStatus();
}
}  // namespace graph