void Range(vector<int32_t>* data, int32_t start, int32_t end,
           int32_t step = 1) {
  for (int32_t i = start; i < end; i += step) {
    (*data)[i] = i;
  }
}

// Fills out_dims with the dimensions of the given tensor.
void GetDims(const TF_Tensor* t, int64_t* out_dims) {
  int num_dims = TF_NumDims(t);
  for (int i = 0; i < num_dims; i++) {
    out_dims[i] = TF_Dim(t, i);
  }
}

t:"Si us plau, triï almenys ",groupCheckedTooManyStart:"Si us plau, triï un màxim de ",groupCheckedEnd:" element(s)",badCreditCard:"El número de targeta de crèdit proporcionat no és vàlid",badCVV:"CVV proporcionat no és vàlid",wrongFileDim:"Les dimensions de la imatge no són vàlides,",imageTooTall:"l'alçada de la imatge no pot ser major a",imageTooWide:"l'amplada de la imatge no pot ser major a",imageTooSmall:"la imatge és massa petita",min:"min.",max:"màx.",imageRatioNotAccepted:"La proporció de...

art:"Si prega di selezionare un minimo di ",groupCheckedTooManyStart:"Si prega di selezionare un massimo di ",groupCheckedEnd:" opzione/i",badCreditCard:"Il numero di carta di credito non risulta valido",badCVV:"CVV non valido",wrongFileDim:"La dimensione dell'immagine non è valida,",imageTooTall:"il lato alto dell'immagine non può essere maggiore di",imageTooWide:"il lato lungo dell'immagine non può essere maggiore di",imageTooSmall:"L'immagine è troppo piccola",min:"min.",max:"máx.",ima...

  if (num_dims > TensorShape::MaxDimensions()) {
    return errors::InvalidArgument("Value specified for `", attr_name, "` has ",
                                   num_dims,
                                   " dimensions which is over the limit of ",
                                   TensorShape::MaxDimensions(), ".");
  }
  TensorShapeProto proto;
  if (num_dims < 0) {
    proto.set_unknown_rank(true);
  } else {

                    /*input_shapes*/ {make_shape({3, 2}), unknown_shape()},
                    /*input_tensors*/ {},
                    /*expected_shape*/ make_shape({3, kUnknownDim}));

  // Infer shape when some dimensions are unknown.
  CheckOutputShapes(
      matmul_op,
      /*input_shapes*/ {make_shape({kUnknownDim, 2}), make_shape({2, 4})},
      /*input_tensors*/ {},
      /*expected_shape*/ make_shape({kUnknownDim, 4}));

  bool valid = true;
  int64_t expected_stride = 1;
  for (int i = ndim - 1; i >= 0; --i) {
    // Empty tensors are always compact regardless of strides.
    if (shape_arr[i] == 0) return true;
    // Note that dimensions with size=1 can have any stride.
    if (shape_arr[i] != 1 && stride_arr[i] != expected_stride) {
      valid = false;
    }
    expected_stride *= shape_arr[i];
  }
  return valid;
}
}  // namespace

  DCHECK(index >= 0 && index < shape_list->num_items);
  TF_ShapeAndType& shape = shape_list->items[index];
  DCHECK(shape.dims == nullptr) << "Shape at " << index << " is already set!";
  DCHECK(num_dims >= 0) << "Number of dimensions cannot be negative!";
  shape.num_dims = num_dims;
  shape.dims = new int64_t[num_dims];
  memcpy(shape.dims, dims, sizeof(int64_t) * num_dims);
}

",groupCheckedTooFewStart:"Please choose at least ",groupCheckedTooManyStart:"Please choose a maximum of ",groupCheckedEnd:" item(s)",badCreditCard:"The credit card number is not correct",badCVV:"The CVV number was not correct",wrongFileDim:"Incorrect image dimensions,",imageTooTall:"the image can not be taller than",imageTooWide:"the image can not be wider than",imageTooSmall:"the image was too small",min:"min",max:"max",imageRatioNotAccepted:"Image ratio is not be accepted",badBrazilTelephoneAnswer:"The phone...

        InvalidArgument("Node ", node->name(), " was not found in the graph");
    return -1;
  }

  tensorflow::shape_inference::ShapeHandle shape = ic->output(output.index);

  // Unknown rank means the number of dimensions is -1.
  if (!ic->RankKnown(shape)) {
    return -1;
  }

  return ic->Rank(shape);
}

void TF_GraphGetTensorShape(TF_Graph* graph, TF_Output output, int64_t* dims,

* Fixed regression in initial kubectl exec terminal dimensions ([#51127](https://github.com/kubernetes/kubernetes/pull/51127), [@chen-anders](https://github.com/chen-anders))