<la:text styleClass="query form-control" property="q"
                                             title="Search" size="50" maxlength="1000"
                                             placeholder="Type a search query"/>
                                </div>
                                <div class="form-group ml-sm-2">
                                    <button type="submit" class="btn btn-primary" id="submit"

                                            </c:set>
                                            <la:text styleId="sessionIdSearchBtn" property="sessionId"
                                                     styleClass="form-control" placeholder="${ph_session_id}"></la:text>
                                        </div>
                                        <div class="form-group ml-sm-2">

TF_Tensor* Int32Tensor(const std::vector<int32_t>& values);

TF_Tensor* Int32Tensor(int32_t v);

TF_Tensor* DoubleTensor(double v);

TF_Tensor* FloatTensor(float v);

TF_Operation* Placeholder(TF_Graph* graph, TF_Status* s,
                          const char* name = "feed",
                          TF_DataType dtype = TF_INT32,
                          const std::vector<int64_t>& dims = {});

      TF_NewGraph(), TF_DeleteGraph);
  std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> s(TF_NewStatus(),
                                                           TF_DeleteStatus);

  TF_Operation* feed = Placeholder(func_graph.get(), s.get());
  TF_Operation* neg = Neg(feed, func_graph.get(), s.get());

  TF_Output inputs[] = {{feed, 0}};
  TF_Output outputs[] = {{neg, 0}};

        in flux. This can make the feature you're suggesting much clearer to us.

  - type: textarea
    attributes:
      label: (Optional) What would the method signatures for your feature look like?
      placeholder: |
        e.g.,
        public static <E> ImmutableList<E> of();
        public static <E> ImmutableList<E> of(E element);
        public static <E> ImmutableList<E> of(E e1, E e2);
        ...
      render: java

		t.Fatalf("failed to find updated user, got %v", err)
	}

	if err := DB.Model(User{Model: user3.Model}).Save(&struct {
		gorm.Model
		Placeholder string
		Name        string
	}{
		Model:       user3.Model,
		Placeholder: "placeholder",
		Name:        "save3__",
	}).Error; err != nil {
		t.Fatalf("failed to update user, got %v", err)
	}

	var result3 User

    if (copy.isEmpty()) {
      // Having no services causes the manager to behave strangely. Notably, listeners are never
      // fired. To avoid this we substitute a placeholder service.
      logger
          .get()
          .log(
              Level.WARNING,
              "ServiceManager configured with no services.  Is your application configured"
                  + " properly?",

    if (copy.isEmpty()) {
      // Having no services causes the manager to behave strangely. Notably, listeners are never
      // fired. To avoid this we substitute a placeholder service.
      logger
          .get()
          .log(
              Level.WARNING,
              "ServiceManager configured with no services.  Is your application configured"
                  + " properly?",

              --input $(location :tensorflow_def_file) \\
              --output $@
          """,
        "//conditions:default": "touch $@",  # Just a placeholder for Unix platforms
    }),
    tools = ["@local_config_def_file_filter//:def_file_filter"],
    visibility = ["//visibility:public"],
)

// `tensor_id`, associated with `session`. There must be a graph node named
// "fifo_queue_enqueue_<tensor_id>", to be executed by this API call. It reads
// from a placeholder node "arg_tensor_enqueue_<tensor_id>".
//
// `tensor` is still owned by the caller. This call will be blocked if the queue
// has reached its capacity, and will be unblocked when the queued tensors again