}
    auto tag = tensorflow::strings::StrCat("Device #", i, " (", name, ")");
    // Copy to device
    TFE_TensorHandle* hdevice =
        TFE_TensorHandleCopyToDevice(hcpu, ctx, name.c_str(), status.get());
    if (TF_GetCode(status.get()) != TF_OK) {
      ADD_FAILURE() << tag << " -- " << TF_Message(status.get());
      continue;
    }
    // Copy from device to the same device.
    TFE_TensorHandle* hdevice2 =

    TF_ImportGraphDefOptions* opts, const char* prefix);

// Set the execution device for nodes in `graph_def`.
// Only applies to nodes where a device was not already explicitly specified.
// `device` is copied and has no lifetime requirements.
TF_CAPI_EXPORT extern void TF_ImportGraphDefOptionsSetDefaultDevice(
    TF_ImportGraphDefOptions* opts, const char* device);

// Set whether to uniquify imported operation names. If true, imported operation

  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  TF_DeleteGraph(graph);
  TF_DeleteStatus(s);
}

// If `device` is non-empty, run Min op on that device.
// Otherwise run it on the default device (CPU).
void RunMinTest(const std::string& device, bool use_XLA) {
  TF_Status* s = TF_NewStatus();
  TF_Graph* graph = TF_NewGraph();

  // Make a placeholder operation.

    subclasses. We've restored that support!


## Version 3.13.0

_2019-02-04_

 *  **This release bumps our minimum requirements to Java 8+ or Android 5+.** Cutting off old
    devices is a serious change and we don't do it lightly! [This post][require_android_5] explains
    why we're doing this and how to upgrade.

                                "schema": {
                                    "type": "array",
                                    "items": {"type": "integer"},
                                    "title": "Device Ids",
                                },
                            }
                        ],
                        "responses": {
                            "200": {

    name = "is_cuda_enabled",
    actual = if_oss(
        "@local_config_cuda//:is_cuda_enabled",
        "@local_config_cuda//cuda:using_config_cuda",
    ),
)

# Config setting that is satisfied when CUDA device code should be compiled
# with clang. It does not imply that CUDA support has been enabled.
alias(
    name = "is_cuda_compiler_clang",
    actual = if_oss(
        "@local_config_cuda//:is_cuda_compiler_clang",

* Allow mounts to run in parallel for non-attachable volumes ([#28939](https://github.com/kubernetes/kubernetes/pull/28939), [@saad-ali](https://github.com/saad-ali))
* add enhanced volume and mount logging for block devices ([#24797](https://github.com/kubernetes/kubernetes/pull/24797), [@screeley44](https://github.com/screeley44))

            // Bind global datepicker mousedown for hiding and
            $(document)
              .on('mousedown.daterangepicker', this._outsideClickProxy)
              // also support mobile devices
              .on('touchend.daterangepicker', this._outsideClickProxy)
              // also explicitly play nice with Bootstrap dropdowns, which stopPropagation when clicking them

    }

    /**
     * Creates highlight information based on screen width.
     * Adjusts fragment size for mobile devices.
     *
     * @return the highlight information
     */
    public HighlightInfo createHighlightInfo() {
        return LaRequestUtil.getOptionalRequest().map(req -> {

    TF_OperationDescription* desc =
        TF_NewOperation(host_graph_, func_name_, func_node_name_);
    for (auto input : inputs) {
      TF_AddInput(desc, input);
    }
    // Set device to CPU because some ops inside the function might not be
    // available on GPU.
    TF_SetDevice(desc, "/cpu:0");
    *op = TF_FinishOperation(desc, s_);
    ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);