std::vector<int64_t>* shape_arr = &tf_dlm_tensor_ctx->shape;
  std::vector<int64_t>* stride_arr = &tf_dlm_tensor_ctx->strides;
  shape_arr->resize(ndim);
  stride_arr->resize(ndim, 1);
  for (int i = 0; i < ndim; i++) {
    (*shape_arr)[i] = tensor->dim_size(i);
  }
  for (int i = ndim - 2; i >= 0; --i) {
    (*stride_arr)[i] = (*shape_arr)[i + 1] * (*stride_arr)[i + 1];
  }

  virtual tensorflow::Status TensorHandleStatus() const;

  // Returns tensor shape. If tensor has unknown rank, shape remains untouched.
  virtual tensorflow::Status Shape(
      tensorflow::PartialTensorShape* shape) const = 0;

  // Returns tensor (full) type.
  // While there is no immediate plan to deprecate dtype and shape in favor
  // of only using full type type information, this is a future possibility.
  //

// number of dimensions of a parallel tensor.
int ParallelTensorNumDims(void* data, TF_Status* status) {
  const std::vector<int64_t>* shape;
  Status s = reinterpret_cast<ParallelTensor*>(data)->Shape(&shape);
  if (!s.ok()) {
    tsl::Set_TF_Status_from_Status(status, s);
    return -1;
  }
  return shape->size();
}

// Used as an argument to TFE_NewCustomDeviceTensorHandle, for computing a
// dimension of a parallel tensor.

  EXPECT_TRUE(
      std::equal(std::begin(partial_shape), std::end(partial_shape), values));
}

TEST_F(CApiAttributesTest, ShapeList) {
  const int64_t shape_1[] = {1, 3};
  const int64_t shape_2[] = {2, 4, 6};
  const int64_t* list[] = {&shape_1[0], &shape_2[0]};
  const size_t list_size = TF_ARRAYSIZE(list);
  const int ndims[] = {TF_ARRAYSIZE(shape_1), TF_ARRAYSIZE(shape_2)};

                </mxCell>
                <mxCell id="32" value="" style="pointerEvents=1;shadow=0;dashed=0;html=1;fillColor=#505050;labelPosition=center;verticalLabelPosition=bottom;verticalAlign=top;outlineConnect=0;align=center;shape=mxgraph.office.devices.laptop;strokeColor=none;" vertex="1" parent="33">
                    <mxGeometry width="500" height="350" as="geometry"/>
                </mxCell>

                </mxCell>
                <mxCell id="32" value="" style="pointerEvents=1;shadow=0;dashed=0;html=1;fillColor=#505050;labelPosition=center;verticalLabelPosition=bottom;verticalAlign=top;outlineConnect=0;align=center;shape=mxgraph.office.devices.laptop;strokeColor=none;" parent="33" vertex="1">
                    <mxGeometry width="500" height="350" as="geometry"/>
                </mxCell>

                </mxCell>
                <mxCell id="32" value="" style="pointerEvents=1;shadow=0;dashed=0;html=1;fillColor=#505050;labelPosition=center;verticalLabelPosition=bottom;verticalAlign=top;outlineConnect=0;align=center;shape=mxgraph.office.devices.laptop;strokeColor=none;" parent="33" vertex="1">
                    <mxGeometry width="500" height="350" as="geometry"/>
                </mxCell>

// setting a shape of [-1, 2] with an existing shape [2, -1] would set
// a final shape of [2, 2] based on shape merging semantics.
//
// Returns an error into `status` if:
//   * `output` is not in `graph`.
//   * An invalid shape is being set (e.g., the shape being set
//     is incompatible with the existing shape).
TF_CAPI_EXPORT extern void TF_GraphSetTensorShape(TF_Graph* graph,

// Represents a (partially-defined) shape.
typedef struct TF_Shape {
  int num_dims;  // Must be >= -1; -1 represents unknown rank.
  int64_t* dim_sizes;
} TF_Shape;

// Add a new parameter to a TensorFlow Function.
TF_AbstractTensor* TF_AddFunctionParameter(TF_ExecutionContext* func,
                                           TF_DataType dtype, TF_Shape shape,
                                           TF_Status* s);

namespace tensorflow {

// Set the shapes and types of the output's handle.
//
// The lengths of the arrays pointed to by `shapes`, `ranks`, and `types` must
// all be equal to `num_shapes_and_types`. If `ranks[i] != -1`, (i.e., if the
// rank is known), then it must be equal to the length of `shapes[i]`; if
// `ranks[i] == 1`, then `shapes[i]` may be nullptr.
//