code: def gen_tensor_dims(n, curr):
      """
      Generate a list of tensor dimensions
      :param n:  the number of dimensions
      :param curr: the current counter
      :return: a list of dimension variables and an updated counter
      """
      dims = []
      for _ in range(n):
          dvar, curr = gen_dvar(curr)
          dims.append(dvar)
      return dims, curr
  
imports: from torch.fx.experimental.migrate_gradual_types.constraint import TVar, DVar, BinConstraintD, BVar
  from torch.fx.experimental.migrate_gradual_types.operation import op_leq
label_desc: Use image node_id 4 for calling a global function with example usage: gen_tensor_dims(n, curr) and returns: dims,  curr