char_rnn_model.py 文件源码

def create_tuple_placeholders_with_default(inputs, extra_dims, shape):
  if isinstance(shape, int):
    result = tf.placeholder_with_default(
      inputs, list(extra_dims) + [shape])
  else:
    subplaceholders = [create_tuple_placeholders_with_default(
      subinputs, extra_dims, subshape)
                       for subinputs, subshape in zip(inputs, shape)]
    t = type(shape)
    if t == tuple:
      result = t(subplaceholders)
    else:
      result = t(*subplaceholders)    
  return result