//        |         |
    //      Const_0    Const_1
    //
    const float const0_val[] = {1.0, 2.0, 3.0, 4.0};
    const float const1_val[] = {1.0, 0.0, 0.0, 1.0};
    TF_Operation* const0 = FloatConst2x2(graph_, s_, const0_val, "Const_0");
    TF_Operation* const1 = FloatConst2x2(graph_, s_, const1_val, "Const_1");
    TF_Operation* matmul = MatMul(graph_, s_, const0, const1, "MatMul");
    inputs[0] = TF_Output{const0, 0};

after touch\nconst SWIPE_THRESHOLD = 40\n\nconst CLASS_NAME_CAROUSEL = 'carousel'\nconst CLASS_NAME_ACTIVE = 'active'\nconst CLASS_NAME_SLIDE = 'slide'\nconst CLASS_NAME_RIGHT = 'carousel-item-right'\nconst CLASS_NAME_LEFT = 'carousel-item-left'\nconst CLASS_NAME_NEXT = 'carousel-item-next'\nconst CLASS_NAME_PREV = 'carousel-item-prev'\nconst CLASS_NAME_POINTER_EVENT = 'pointer-event'\n\nconst DIRECTION_NEXT = 'next'\nconst DIRECTION_PREV = 'prev'\nconst DIRECTION_LEFT = 'left'\nconst DIRECTION_RIGHT...

====================================================\n */\n\nconst NAME = 'CardRefresh'\nconst DATA_KEY = 'lte.cardrefresh'\nconst EVENT_KEY = `.${DATA_KEY}`\nconst JQUERY_NO_CONFLICT = $.fn[NAME]\n\nconst EVENT_LOADED = `loaded${EVENT_KEY}`\nconst EVENT_OVERLAY_ADDED = `overlay.added${EVENT_KEY}`\nconst EVENT_OVERLAY_REMOVED = `overlay.removed${EVENT_KEY}`\n\nconst CLASS_NAME_CARD = 'card'\n\nconst SELECTOR_CARD = `.${CLASS_NAME_CARD}`\nconst SELECTOR_DATA_REFRESH = '[data-card-widget=\"card-refresh\"]'\n\nconst...

                                            TF_Status* status) const;

  // The number of devices operations run on.
  size_t num_underlying_devices() const { return underlying_devices_.size(); }

  // The devices operations run on.
  const std::vector<std::string>& underlying_devices() const {
    return underlying_devices_;
  }

  // Takes a description of a single operation being executed on the

getOffsetRectRelativeToArbitraryNode(children, parent, fixedPosition = false) {\n  const isIE10 = runIsIE(10);\n  const isHTML = parent.nodeName === 'HTML';\n  const childrenRect = getBoundingClientRect(children);\n  const parentRect = getBoundingClientRect(parent);\n  const scrollParent = getScrollParent(children);\n\n  const styles = getStyleComputedProperty(parent);\n  const borderTopWidth = parseFloat(styles.borderTopWidth);\n  const borderLeftWidth = parseFloat(styles.borderLeftWidth);\n\n  // In cases...

}

void TF_AttrBuilderSetTypeList(TF_AttrBuilder* builder, const char* attr_name,
                               const TF_DataType* values, int num_values) {
  auto iter = builder->attr_names.insert(attr_name).first;
  builder->Set(*iter, tensorflow::gtl::ArraySlice<const tensorflow::DataType>(
                          reinterpret_cast<const tensorflow::DataType*>(values),
                          num_values));
}

			}
		case []interface{}: // Handle array types.
			if len(condt) != 3 { // Return error if we have insufficient elements.
				return parsedPolicy, fmt.Errorf("Malformed conditional fields %s of type %s found in POST policy form", condt, reflect.TypeOf(condt).String())
			}
			switch toLowerString(condt[0]) {
			case policyCondEqual, policyCondStartsWith:
				for _, v := range condt { // Pre-check all values for type.
					if !isString(v) {

	"github.com/minio/minio/internal/event"
	"github.com/minio/minio/internal/logger"
	"github.com/minio/minio/internal/once"
	"github.com/minio/minio/internal/store"
	xnet "github.com/minio/pkg/v3/net"
)

const (
	psqlTableExists          = `SELECT 1 FROM %s;`
	psqlCreateNamespaceTable = `CREATE TABLE %s (key VARCHAR PRIMARY KEY, value JSONB);`

  virtual absl::Status SetAttrInt(const char* attr_name, int64_t value) = 0;
  virtual absl::Status SetAttrFloat(const char* attr_name, float value) = 0;
  virtual absl::Status SetAttrBool(const char* attr_name, bool value) = 0;
  virtual absl::Status SetAttrType(const char* attr_name, DataType value) = 0;
  virtual absl::Status SetAttrShape(const char* attr_name, const int64_t* dims,
                                    const int num_dims) = 0;

    const TF_Operation* const* opers, int ninputs, const TF_Output* inputs,
    int noutputs, const TF_Output* outputs, const char* const* output_names,
    int ncontrol_outputs, const TF_Operation* const* control_outputs,
    const char* const* control_output_names, const TF_FunctionOptions* opts,
    const char* description, TF_Status* status) {
  tensorflow::mutex_lock l(fn_body->mu);

  // Process inputs.