Dependency node = collectStepTrace.getNode();
                trackingData.add(resolvedArtifact.toString());
                indent += "  ";
                trackingData.add(indent + node + " (" + collectStepTrace.getContext() + ")");
                ListIterator<DependencyNode> iter = collectStepTrace
                        .getPath()
                        .listIterator(collectStepTrace.getPath().size());

      const = 0;
  virtual absl::Status SetInput(size_t index,
                                ImmediateExecutionTensorHandle* input) = 0;

  virtual ImmediateExecutionContext* GetContext() const = 0;

  // Following two methods are used to support custom device.
  // Return true if the inputs contain custom device tensor handle. It means
  // that the argument need to be handled by a custom device.

        LocalMetadataResult result = new LocalMetadataResult(request);

        String path;

        Metadata metadata = request.getMetadata();
        String context = request.getContext();
        RemoteRepository remote = request.getRepository();

        if (remote != null) {
            path = getPathForRemoteMetadata(metadata, remote, context);
        } else {

                return "dependency collection for " + request;
            } else if (data instanceof CollectStepData stepData) {
                String msg = "dependency collection step for " + stepData.getContext();
                if (detailed) {
                    msg += ". Path to offending node from root:\n";
                    msg += stepData.getPath().stream()
                            .map(n -> " -> " + n.toString())

                                           TF_Status* status) {
  Node* node = &output.oper->node;

  mutex_lock l(graph->mu);
  tensorflow::shape_inference::InferenceContext* ic =
      graph->refiner.GetContext(node);
  if (ic == nullptr) {
    status->status =
        InvalidArgument("Node ", node->name(), " was not found in the graph");
    return;
  }

  auto shape_and_type_vec =

        if (request.getRepository() == null) {
            path = getPathForLocalMetadata(metadata);
        } else {
            path = getPathForRemoteMetadata(metadata, request.getRepository(), request.getContext());
        }

        File file = new File(getRepository().getBasedir(), path);

        LocalMetadataResult result = new LocalMetadataResult(request);
        if (file.isFile()) {

  return tensorflow::unwrap(op)->Name().c_str();
}

TFE_Context* TFE_OpGetContext(const TFE_Op* op, TF_Status* status) {
  return tensorflow::wrap(tensorflow::unwrap(op)->GetContext());
}

void TFE_OpSetDevice(TFE_Op* op, const char* device_name, TF_Status* status) {
  status->status = tensorflow::unwrap(op)->SetDeviceName(device_name);
}

ns(null!==n?n:this.element.ownerDocument.documentElement,this.element);if(e.isDefaultPrevented()||!i)return;var s=this.getTipElement(),l=d.getUID(this.constructor.NAME);s.setAttribute("id",l),this.element.setAttribute("aria-describedby",l),this.setContent(),this.config.animation&&o.default(s).addClass(Lt);var r="function"==typeof this.config.placement?this.config.placement.call(this,s,this.element):this.config.placement,u=this._getAttachment(r);this.addAttachmentClass(u);var f=this._getContainer...

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