ocr.py 文件源码

def inference(images, batch_size, train):
  """Build the ocr model.

  Args:
    images: Images returned from distorted_inputs() or inputs().

  Returns:
    Logits.
  """
  features, timesteps = convolutional_layers(images, batch_size, train)
  logits = get_lstm_layers(features, timesteps, batch_size)
  return logits, timesteps


  # The total loss is defined as the cross entropy loss plus all of the weight
  # decay terms (L2 loss).
  # return tf.add_n(tf.get_collection('losses'), name='total_loss')