speech_input.py 文件源码

def __init__(self, input_size, batch_size, data_generator_creator, max_steps=None):

    super().__init__(input_size)
    self.batch_size = batch_size
    self.data_generator_creator = data_generator_creator
    self.steps_left = max_steps

    with tf.device("/cpu:0"):
      # Define input and label placeholders
      # inputs is of dimension [batch_size, max_time, input_size]
      self.inputs = tf.placeholder(tf.float32, [batch_size, None, input_size], name='inputs')
      self.sequence_lengths = tf.placeholder(tf.int32, [batch_size], name='sequence_lengths')
      self.labels = tf.sparse_placeholder(tf.int32, name='labels')

      # Queue for inputs and labels
      self.queue = tf.FIFOQueue(dtypes=[tf.float32, tf.int32, tf.string],
                                capacity=100)

      # queues do not support sparse tensors yet, we need to serialize...
      serialized_labels = tf.serialize_many_sparse(self.labels)

      self.enqueue_op = self.queue.enqueue([self.inputs,
                                            self.sequence_lengths,
                                            serialized_labels])