Question

我正在尝试从我使用TensorFlow tutorials训练的模型中恢复图形，然后我尝试恢复模型：

import tensorflow as tf
import reader
from ptb_word_lm import PTBInput, PTBModel, get_config, run_epoch

def main(_):
    checkpoint_path = "/Users/roger/data/ptb_out"
    checkpoint_path = tf.train.latest_checkpoint(checkpoint_path)

    raw_data = reader.ptb_raw_data("/Users/roger/data/simple-examples/small_data")
    train_data, valid_data, test_data, _ = raw_data

    config = get_config()
    eval_config = get_config()
    eval_config.batch_size = 1
    eval_config.num_steps = 1


    with tf.Session() as session:
        initializer = tf.random_uniform_initializer(-config.init_scale,
                                                config.init_scale)

        saver = tf.train.import_meta_graph(checkpoint_path + ".meta")
        saver.restore(session, checkpoint_path)

        with tf.name_scope("Test"):
            test_input = PTBInput(config=eval_config, data=test_data, name="TestInput")
            with tf.variable_scope("Model", reuse=True, initializer=initializer):
                mtest = PTBModel(is_training=False, config=eval_config,
                                input_=test_input)
            test_perplexity = run_epoch(session, mtest)
            print("Test Perplexity: %.3f" % test_perplexity)

if __name__ == "__main__":
  tf.app.run()

但是，我发现创建here的Varible Model/embedding未从图中恢复。所以我得到这样的错误：

 ValueError: Variable Model/embedding does not exist, or was not created with tf.get_variable(). Did you mean to set reuse=None in VarScope?

那我怎样才能正确恢复模型呢？

Answer 1

我认为，既然你在变量范围中设置了reuse = True，它会在你调用PTBModel（）时尝试找到该变量而不是创建它。如果在范围中使用带有reuse = True的get_variable（），它将永远不会创建变量。

使用import_meta_graph恢复图时不会创建变量？

1 个答案: