int dim1 = 1 << 16;
    int dim2 = 1 << 15;
    assertThat(dim1 * dim2).isLessThan(0);
    testConcatOverflow(dim1, dim2);
  }

  @GwtIncompatible // different overflow behavior; could probably be made to work by using ~~
  public void testConcat_overflow_nonNegative() {
    int dim1 = 1 << 16;
    int dim2 = 1 << 16;
    assertThat(dim1 * dim2).isAtLeast(0);

// Returns the shape of the Tensor referenced by `output` in `graph`
// into `dims`. `dims` must be an array large enough to hold `num_dims`
// entries (e.g., the return value of TF_GraphGetTensorNumDims).
//
// If the number of dimensions in the shape is unknown or the shape is
// a scalar, `dims` will remain untouched. Otherwise, each element of
// `dims` will be set corresponding to the size of the dimension. An

    int dim1 = 1 << 16;
    int dim2 = 1 << 15;
    assertThat(dim1 * dim2).isLessThan(0);
    testConcatOverflow(dim1, dim2);
  }

  @GwtIncompatible // different overflow behavior; could probably be made to work by using ~~
  public void testConcat_overflow_nonNegative() {
    int dim1 = 1 << 16;
    int dim2 = 1 << 16;
    assertThat(dim1 * dim2).isAtLeast(0);

TF_CAPI_EXPORT extern TF_DataType TF_CheckpointReaderGetVariableDataType(
    TF_CheckpointReader* reader, const char* name);
// Read the shape of a variable and write to `dims`
TF_CAPI_EXPORT extern void TF_CheckpointReaderGetVariableShape(
    TF_CheckpointReader* reader, const char* name, int64_t* dims, int num_dims,
    TF_Status* status);
// Get the number of dimension of a variable
TF_CAPI_EXPORT extern int TF_CheckpointReaderGetVariableNumDims(

    int dim1 = 1 << 16;
    int dim2 = 1 << 15;
    assertThat(dim1 * dim2).isLessThan(0);
    testConcatOverflow(dim1, dim2);
  }

  @GwtIncompatible // different overflow behavior; could probably be made to work by using ~~
  public void testConcat_overflow_nonNegative() {
    int dim1 = 1 << 16;
    int dim2 = 1 << 16;
    assertThat(dim1 * dim2).isAtLeast(0);

    int dim1 = 1 << 16;
    int dim2 = 1 << 15;
    assertThat(dim1 * dim2).isLessThan(0);
    testConcatOverflow(dim1, dim2);
  }

  @GwtIncompatible // different overflow behavior; could probably be made to work by using ~~
  public void testConcat_overflow_nonNegative() {
    int dim1 = 1 << 16;
    int dim2 = 1 << 16;
    assertThat(dim1 * dim2).isAtLeast(0);

absl::Status SetAttrType(AbstractOperation*, const char* attr_name,
                         DataType value, ForwardOperation*);
absl::Status SetAttrShape(AbstractOperation*, const char* attr_name,
                          const int64_t* dims, const int num_dims,
                          ForwardOperation*);
absl::Status SetAttrFunction(AbstractOperation*, const char* attr_name,
                             const AbstractOperation* value, ForwardOperation*);

  DLManagedTensor* dlm_tensor = &tf_dlm_tensor_ctx->tensor;
  dlm_tensor->manager_ctx = tf_dlm_tensor_ctx;
  dlm_tensor->deleter = &DLManagedTensorDeleter;
  dlm_tensor->dl_tensor.device = tf_dlm_context;
  int ndim = tensor->dims();
  dlm_tensor->dl_tensor.ndim = ndim;
  dlm_tensor->dl_tensor.data = tf_dlm_data;
  dlm_tensor->dl_tensor.dtype = tf_dlm_type;

  std::vector<int64_t>* shape_arr = &tf_dlm_tensor_ctx->shape;

  static char empty;
  int64_t nelems = 1;
  std::vector<int64_t> dims;
  dims.reserve(shape.dims());
  for (int i = 0; i < shape.dims(); ++i) {
    dims.push_back(shape.dim_size(i));
    nelems *= shape.dim_size(i);
  }
  CHECK_EQ(nelems, 0);
  return TF_NewTensor(
      dtype, reinterpret_cast<const int64_t*>(dims.data()), shape.dims(),
      reinterpret_cast<void*>(&empty), 0, [](void*, size_t, void*) {}, nullptr);

// If the number of dimensions is unknown, `num_dims` must be set to
// -1 and `dims` can be null.  If a dimension is unknown, the
// corresponding entry in the `dims` array must be -1.
TF_CAPI_EXPORT extern void TFE_OpSetAttrShape(TFE_Op* op, const char* attr_name,
                                              const int64_t* dims,
                                              const int num_dims,