lstm_crf_train.py 文件源码

def read_csv(batch_size, file_name):
    filename_queue = tf.train.string_input_producer([file_name])
    reader = tf.TextLineReader(skip_header_lines=0)
    key, value = reader.read(filename_queue)
    # decode_csv will convert a Tensor from type string (the text line) in
    # a tuple of tensor columns with the specified defaults, which also
    # sets the data type for each column
    decoded = tf.decode_csv(
        value,
        field_delim=' ',
        record_defaults=[[0] for i in range(FLAGS.max_sentence_len * 2)])

    # batch actually reads the file and loads "batch_size" rows in a single tensor
    return tf.train.shuffle_batch(decoded,
                                  batch_size=batch_size,
                                  capacity=batch_size * 50,
                                  min_after_dequeue=batch_size)