}

TFE_TensorHandle* TFE_NewTensorHandleFromScalar(TF_DataType data_type,
                                                void* data, size_t len,
                                                TF_Status* status) {
  auto dtype = static_cast<tensorflow::DataType>(data_type);
  DCHECK(tensorflow::DataTypeCanUseMemcpy(dtype));

  tensorflow::Tensor tensor(dtype, tensorflow::TensorShape({}));

    TF_Status* status);

// Information about the shape of a Tensor and its type.
struct TF_ShapeAndType {
  // Number of dimensions. -1 indicates unknown rank.
  int num_dims;
  // Array of dimensions. -1 indicates unknown dim.
  int64_t* dims;
  // The data type. May be 0 to denote unknown type.
  TF_DataType dtype;
};

typedef struct TF_ShapeAndType TF_ShapeAndType;

}

// getSigningKey hmac seed to calculate final signature.
func getSigningKey(secretKey string, t time.Time, region string, stype serviceType) []byte {
	date := sumHMAC([]byte("AWS4"+secretKey), []byte(t.Format(yyyymmdd)))
	regionBytes := sumHMAC(date, []byte(region))
	service := sumHMAC(regionBytes, []byte(stype))
	signingKey := sumHMAC(service, []byte("aws4_request"))
	return signingKey
}

  for (int i = 0; i < num_devices; ++i) {
    const string dev_type(TF_DeviceListType(devices, i, status.get()));
    CHECK_EQ(TF_GetCode(status.get()), TF_OK) << TF_Message(status.get());
    const string dev_name(TF_DeviceListName(devices, i, status.get()));
    CHECK_EQ(TF_GetCode(status.get()), TF_OK) << TF_Message(status.get());
    if (dev_type == device_type) {
      *device_name = dev_name;

// guessIsMetricsReq - returns true if incoming request looks
// like metrics request
func guessIsMetricsReq(req *http.Request) bool {
	if req == nil {
		return false
	}
	aType := getRequestAuthType(req)
	return (aType == authTypeAnonymous || aType == authTypeJWT) &&
		req.URL.Path == minioReservedBucketPath+prometheusMetricsPathLegacy ||
		req.URL.Path == minioReservedBucketPath+prometheusMetricsV2ClusterPath ||

// Value represents a value of restricted type reduced from an
// expression represented by an ASTNode. Only one of the fields is
// non-nil.
//
// In cases where we are fetching data from a data source (like csv),
// the type may not be determined yet. In these cases, a byte-slice is
// used.
type Value struct {
	value interface{}
}

// Missing is used to indicate a non-existing value.
type Missing struct{}

      TFE_NewOp(context.get(), "VarHandleOp", status.get()), TFE_DeleteOp);
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  TFE_OpSetAttrType(op.get(), "dtype", TF_FLOAT);
  TFE_OpSetAttrShape(op.get(), "shape", {}, 0, status.get());
  TFE_OpSetAttrString(op.get(), "container", "", 0);
  TFE_OpSetAttrString(op.get(), "shared_name", "", 0);

      gtl::ArraySlice<AbstractTensorHandle*> gradient_tensors) const override;

  // Calls the passed-in backward function.
  // op_type is the op's name provided in RecordOperation.
  Status CallBackwardFunction(
      const string& op_type, GradientFunction* gradient_function,
      const std::vector<int64_t>& unneeded_gradients,
      gtl::ArraySlice<AbstractTensorHandle*> output_gradients,

      },
      "favorite_count": {
        "type": "long"
      },
      "filename": {
        "type": "keyword"
      },
      "filetype": {
        "type": "keyword"
      },
      "host": {
        "type": "keyword"
      },
      "lang": {
        "type": "keyword"
      },
      "last_modified": {
        "type": "date",
        "format": "date_optional_time"
      },

      },
      "favorite_count": {
        "type": "long"
      },
      "filename": {
        "type": "keyword"
      },
      "filetype": {
        "type": "keyword"
      },
      "host": {
        "type": "keyword"
      },
      "lang": {
        "type": "keyword"
      },
      "last_modified": {
        "type": "date",
        "format": "date_optional_time"
      },