inputs.py 文件源码

def auto_placeholder(dtype, shape, name, feed_data, preprocess_offset=None):
  placeholder_shape = [None, None] + list(shape)[1:] if shape else shape
  placeholder = tf.placeholder(dtype, placeholder_shape, name)
  placeholder.required_feeds = RequiredFeeds(placeholder)
  placeholder.feed_data = feed_data

  tensor = preprocess_offset(placeholder) if preprocess_offset else placeholder

  def offset_data(t, name):
    input_len = shape[0]
    if not hasattr(placeholder, 'zero_offset'):
      placeholder.zero_offset = tf.placeholder_with_default(
          input_len - 1,  # If no zero_offset is given assume that t = 0
          (),
          name + '/zero_offset')

    end = t + 1
    start = end - input_len
    zero_offset = placeholder.zero_offset
    offset_tensor = tensor[:, start + zero_offset:end + zero_offset]

    input_range = np.arange(start, end)
    offset_tensor.required_feeds = RequiredFeeds(placeholder, input_range)

    return tf.reshape(offset_tensor, [-1] + shape, name)

  placeholder.offset_data = offset_data
  return placeholder