BERT-BiLSTM-CRF-NER 关于在cpu服务器上启动报错模型使用的是gpu服务器生成的pb模型文件。

关于在cpu服务器上启动报错模型使用的是gpu服务器生成的pb模型文件。

Open ljyoungs opened this issue 4 years ago • 9 comments

I:VENTILATOR:new config request req id: 0 client: b'e4d5dbdc-97ff-4ec5-8bd3-96e0c11d5c60' Process BertWorker-3: Traceback (most recent call last): File "d:\app\python\python37\lib\multiprocessing\process.py", line 297, in bootstrap self.run() File "d:\app\python\python37\lib\site-packages\bert_base\server_init.py", line 487, in run self.run() File "d:\app\python\python37\lib\site-packages\zmq\decorators.py", line 75, in wrapper return func(*args, **kwargs) File "d:\app\python\python37\lib\site-packages\bert_base\server\zmq_decor.py", line 27, in wrapper return func(*args, **kwargs) File "d:\app\python\python37\lib\site-packages\bert_base\server_init.py", line 505, in _run for r in estimator.predict(input_fn=self.input_fn_builder(receivers, tf), yield_single_examples=False): File "d:\app\python\python37\lib\site-packages\tensorflow_estimator\python\estimator\estimator.py", line 611, in predict features, None, model_fn_lib.ModeKeys.PREDICT, self.config) File "d:\app\python\python37\lib\site-packages\tensorflow_estimator\python\estimator\estimator.py", line 1112, in _call_model_fn model_fn_results = self.model_fn(features=features, **kwargs) File "d:\app\python\python37\lib\site-packages\bert_base\server_init.py", line 463, in classification_model_fn pred_probs = tf.import_graph_def(graph_def, name='', input_map=input_map, return_elements=['pred_prob:0']) File "d:\app\python\python37\lib\site-packages\tensorflow\python\util\deprecation.py", line 507, in new_func return func(*args, **kwargs) File "d:\app\python\python37\lib\site-packages\tensorflow\python\framework\importer.py", line 426, in import_graph_def graph._c_graph, serialized, options) # pylint: disable=protected-access tensorflow.python.framework.errors_impl.NotFoundError: Op type not registered 'BatchMatMulV2' in binary running on ID-00368-NB01. Make sure the Op and Kernel are registered in the binary running in this process. Note that if you are loading a saved graph which used ops from tf.contrib, accessing (e.g.) tf.contrib.resampler should be done before importing the graph, as contrib ops are lazily registered when the module is first accessed. I:SINK:send config client b'e4d5dbdc-97ff-4ec5-8bd3-96e0c11d5c60'

Serving Flask app "bert_base.server.http" (lazy loading)
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