*/
  // Define
  TF_Operation* feed = Placeholder(func_graph_, s_);
  Define(-1, {}, {feed}, {feed}, {});

  // Use, run, and verify
  TF_Operation* func_feed = Placeholder(host_graph_, s_);
  TF_Operation* func_op = Use({func_feed});
  Run({{func_feed, Int32Tensor(3)}}, func_op, 3);
  VerifyFDef(empty_, {{"feed_0", DT_INT32}}, {{"feed", DT_INT32}},
             {{"feed_0", "feed"}}, {});
}

  EXPECT_EQ(1, TF_OperationOutputListLength(feed, "output", s));
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  EXPECT_EQ(0, TF_OperationNumInputs(feed));
  EXPECT_EQ(0, TF_OperationOutputNumConsumers(TF_Output{feed, 0}));
  EXPECT_EQ(0, TF_OperationNumControlInputs(feed));
  EXPECT_EQ(0, TF_OperationNumControlOutputs(feed));

  tensorflow::AttrValue attr_value;

// be freed with a call to TF_DeleteDeviceList.
TF_CAPI_EXPORT extern TF_DeviceList* TF_SessionListDevices(TF_Session* session,
                                                           TF_Status* status);

// Lists all devices in a TF_Session.
//
// Caller takes ownership of the returned TF_DeviceList* which must eventually
// be freed with a call to TF_DeleteDeviceList.

    environ_cp['TF_NEED_CUDA'] = '0'
  else:
    environ_cp['TF_NEED_CUDA'] = str(
        int(get_var(environ_cp, 'TF_NEED_CUDA', 'CUDA', False)))
  if (environ_cp.get('TF_NEED_CUDA') == '1' and
      'TF_CUDA_CONFIG_REPO' not in environ_cp):

    set_action_env_var(
        environ_cp,
        'TF_NEED_TENSORRT',
        'TensorRT',
        False,
        bazel_config_name='tensorrt')

        ),
    ] = None,
    include_in_schema: Annotated[
        bool,
        Doc(
            """
            To include (or not) this parameter field in the generated OpenAPI.
            You probably don't need it, but it's available.

            This affects the generated OpenAPI (e.g. visible at `/docs`).
            """
        ),
    ] = True,
    json_schema_extra: Annotated[
        Union[Dict[str, Any], None],

build:tpu --copt=-DLIBTPU_ON_GCE
build:tpu --define=enable_mlir_bridge=true

build:tensorrt --repo_env TF_NEED_TENSORRT=1

build:rocm --crosstool_top=@local_config_rocm//crosstool:toolchain
build:rocm --define=using_rocm_hipcc=true
build:rocm --define=tensorflow_mkldnn_contraction_kernel=0
build:rocm --repo_env TF_NEED_ROCM=1

build:sycl --crosstool_top=@local_config_sycl//crosstool:toolchain
build:sycl --define=using_sycl=true

				// Linux returns InvalidArg for directory O_DIRECT
				// we need to keep this fallback code to return correct
				// errors upwards.
				return nil, dmTime, errFileNotFound
			}
			return nil, dmTime, errUnsupportedDisk
		}
		return nil, dmTime, err
	}

	if discard {
		// This discard is mostly true for DELETEEs
		// so we need to make sure we do not keep
		// page-cache references after.

		//   into memory, any mutation on xl.meta subsequently is
		//   inconsequential to the overall read operation.
		// - xl.meta metadata is still verified for quorum under lock()
		//   however writing the response doesn't need to serialize
		//   concurrent writers
		unlockOnDefer = true
		nsUnlocker = func() { lock.RUnlock(lkctx) }
	}

	fi, metaArr, onlineDisks, err := er.getObjectFileInfo(ctx, bucket, object, opts, true)

}

// addToFlag appends args to flag.
func (p *Package) addToFlag(flag string, args []string) {
	if flag == "CFLAGS" {
		// We'll also need these when preprocessing for dwarf information.
		// However, discard any -g options: we need to be able
		// to parse the debug info, so stick to what we expect.
		for _, arg := range args {
			if !strings.HasPrefix(arg, "-g") {

    }
    Object localValue = value;
    if (localValue != null & !(localValue instanceof SetFuture)) {
      return getDoneValue(localValue);
    }
    // we delay calling nanoTime until we know we will need to either park or spin
    final long endNanos = remainingNanos > 0 ? System.nanoTime() + remainingNanos : 0;
    long_wait_loop:
    if (remainingNanos >= SPIN_THRESHOLD_NANOS) {
      Waiter oldHead = waiters;