冻结图后的Tensorflow OOM

Question

我正在使用 tf 运行 seq2seq 模型，当使用 tf.train.Saver 从检查点文件加载参数时，推理程序运行良好。但是用freeze_graph.py导出图（使用tf.framework.graph_util.convert_variables_to_constants()），在推理程序中用tf.import_graph_def导入后，出现OOM问题。

这是错误日志的一部分：

W tensorflow/core/common_runtime/bfc_allocator.cc:274] ****************************************************************************************************
W tensorflow/core/common_runtime/bfc_allocator.cc:275] Ran out of memory trying to allocate 4.0KiB.  See logs for memory state.
W tensorflow/core/framework/op_kernel.cc:983] Internal: Dst tensor is not initialized.
E tensorflow/core/common_runtime/executor.cc:594] Executor failed to create kernel. Internal: Dst tensor is not initialized.
     [[Node: embedding_attention_seq2seq/embedding_attention_decoder/attention_decoder/AttnV_0 = Const[dtype=DT_FLOAT, value=Tensor<type: float shape: [1024] values: -0.016628871 -0.2054652 -0.045054652...>, _device="/job:localhost/replica:0/task:0/gpu:0"]()]]
Traceback (most recent call last):
  File "inference.py", line 88, in console_main
    result = list(inference(source_sentence))
  File "inference.py", line 54, in inference
    for sequence in result:
  File "/data/experiment/decoder.py", line 115, in search_best_sequence
    State.batch_predict(self.session, self.model, self.context, beam)
  File "/data/experiment/decoder.py", line 82, in batch_predict
    state_list[0].depth)
  File "/data/experiment/seq2seq_model.py", line 452, in batch_feed_decoder
    log_softmax, attns, state = session.run(output_fetch, input_feed)
  File "/home/.conda/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 767, in run
    run_metadata_ptr)
  File "/home/.conda/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 966, in _run
    feed_dict_string, options, run_metadata)
  File "/home/.conda/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1016, in _do_run
    target_list, options, run_metadata)
  File "/home/.conda/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1036, in _do_call
    raise type(e)(node_def, op, message)
InternalError: Dst tensor is not initialized.
     [[Node: embedding_attention_seq2seq/embedding_attention_decoder/attention_decoder/AttnV_0 = Const[dtype=DT_FLOAT, value=Tensor<type: float shape: [1024] values: -0.016628871 -0.2054652 -0.045054652...>, _device="/job:localhost/replica:0/task:0/gpu:0"]()]]

Caused by op u'embedding_attention_seq2seq/embedding_attention_decoder/attention_decoder/AttnV_0', defined at:
  File "inference.py", line 169, in <module>
    tf.app.run()
  File "/home/.conda/lib/python2.7/site-packages/tensorflow/python/platform/app.py", line 44, in run
    _sys.exit(main(_sys.argv[:1] + flags_passthrough))
  File "inference.py", line 165, in main
    console_main(session)
  File "inference.py", line 66, in console_main
    model = create_model(session, False)
  File "/data/experiment/model.py", line 145, in create_model
    tensor_name_pickle=tensor_name_pickle)
  File "/data/experiment/seq2seq_model.py", line 106, in __init__
    tf.import_graph_def(graph_def, name="")
  File "/home/.conda/lib/python2.7/site-packages/tensorflow/python/framework/importer.py", line 287, in import_graph_def
    op_def=op_def)
  File "/home/.conda/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2395, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "/home/.conda/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1264, in __init__
    self._traceback = _extract_stack()

InternalError (see above for traceback): Dst tensor is not initialized.
     [[Node: embedding_attention_seq2seq/embedding_attention_decoder/attention_decoder/AttnV_0 = Const[dtype=DT_FLOAT, value=Tensor<type: float shape: [1024] values: -0.016628871 -0.2054652 -0.045054652...>, _device="/job:localhost/replica:0/task:0/gpu:0"]()]]

我认为这可能是由tf.Constant 的内存问题引起的。有人遇到过这个问题吗？

Answer 1

我遇到了同样的问题，但是在尝试使用 C API 从 C++ 应用程序加载和运行推理时。经过大量的折腾和测试，罪魁祸首似乎是冻结的图表和freeze_graph.py 本身。这可能是某种错误。实际上在 github 的 TF repo 上有多个问题报告，但由于缺乏活动，它们刚刚关闭，例如here 和 here。我想模型冻结的明显错误不是任何优先事项。

在我的例子中，模型 .pb 文件大约 500mb，运行会话时需要大约 10Gb 的 RAM。它不仅占用了大量的 RAM，而且实际上速度慢了几个数量级。

当我切换到只加载 SavedModel 目录时，一切都正常了。我不确定如何在 python 中实现这一点，但对于 C 代码，我将 TF_GraphImportGraphDef() 调用替换为 TF_LoadSessionFromSavedModel()。

我使用的是 TF v1.14.0。该库是我用 Bazel 构建的，而不是库存版本。如果有人感兴趣，我可以在这里和那里提供一些细节。只是不知道从哪里开始，我经历了很多试验和错误。