parameters: (vec: Tensor, vec_dim: str or tuple or list or Shape = None)
return_statement: return math.sum_(vec ** 2, dim=vec.shape.channel if vec_dim is None else vec_dim)
docstring: Computes the squared length of `vec`. If `vec_dim` is None, the combined channel dimensions of `vec` are interpreted as a vector.
docstring_summary: Computes the squared length of `vec`. If `vec_dim` is None, the combined channel dimensions of `vec` are interpreted as a vector.
docstring_tokens: Computes the squared length of vec . If vec_dim is None the combined channel dimensions of vec are interpreted as a vector .
function: def vec_squared(vec: Tensor, vec_dim: str or tuple or list or Shape = None):
      """ Computes the squared length of `vec`. If `vec_dim` is None, the combined channel dimensions of `vec` are interpreted as a vector. """
      return math.sum_(vec ** 2, dim=vec.shape.channel if vec_dim is None else vec_dim)
function_tokens: def vec_squared ( vec : Tensor , vec_dim : str or tuple or list or Shape = None ) : return math . sum_ ( vec ** 2 , dim = vec . shape . channel if vec_dim is None else vec_dim )