parameters: (tensor, tensor_slicing)
return_statement: return tensor[_parse_slices(tensor_slicing)]
docstring: Call eval on the slicing of a tensor, with validation.
  
    Args:
      tensor: (numpy ndarray) The tensor value.
      tensor_slicing: (str or None) Slicing of the tensor, e.g., "[:, 1]". If
        None, no slicing will be performed on the tensor.
  
    Returns:
      (numpy ndarray) The sliced tensor.
  
    Raises:
      ValueError: If tensor_slicing is not a valid numpy ndarray slicing str.
docstring_summary: Call eval on the slicing of a tensor, with validation.
docstring_tokens: Call eval on the slicing of a tensor with validation .
function: def evaluate_tensor_slice(tensor, tensor_slicing):
    """Call eval on the slicing of a tensor, with validation.
  
    Args:
      tensor: (numpy ndarray) The tensor value.
      tensor_slicing: (str or None) Slicing of the tensor, e.g., "[:, 1]". If
        None, no slicing will be performed on the tensor.
  
    Returns:
      (numpy ndarray) The sliced tensor.
  
    Raises:
      ValueError: If tensor_slicing is not a valid numpy ndarray slicing str.
    """
  
    _ = tensor
  
    if not validate_slicing_string(tensor_slicing):
      raise ValueError("Invalid tensor-slicing string.")
  
    return tensor[_parse_slices(tensor_slicing)]
function_tokens: def evaluate_tensor_slice ( tensor , tensor_slicing ) : _ = tensor if not validate_slicing_string ( tensor_slicing ) : raise ValueError ( "Invalid tensor-slicing string." ) return tensor [ _parse_slices ( tensor_slicing ) ]