Привет, я пробую модели GRU и CuDNNGRU на Keras.Модель GRU может отлично работать.Но когда я переключился на CuDNNGRU, ошибка указывает.Вот мои коды
def get_model():
input_words = Input((maxlen, ))
x_words = Embedding(max_features, 300,
weights=[embedding_matrix],
trainable=False)(input_words)
#x_words = SpatialDropout1D(0.5)(x_words)
x_words =Bidirectional(GRU(50, return_sequences=True))(x_words)
#x_words = Convolution1D(100, 3, activation="relu")(x_words)
x_words = GlobalMaxPool1D()(x_words)
x = Dense(50, activation="relu")(x_words)
x = Dropout(0.25)(x_words)
predictions = Dense(6, activation="sigmoid")(x_words)
model = Model(inputs=input_words, outputs=predictions)
model.compile(optimizer=optimizers.Adam(0.0005, decay=1e-6),
loss='binary_crossentropy',
metrics=['accuracy'])
return model
Когда я запускаю GRU, он работает отлично.Но я изменил его на CuDNNGRU, он покажет ошибку.Я не уверен, потому что Keras нужно больше параметров, или я не могу использовать CuDNNGRU здесь.Должен ли я пойти глубже в Tensorflow?Любой совет приветствуется.Спасибо
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
/opt/conda/lib/python3.6/site-packages/tensorflow/python/client/session.py
in _do_call(self, fn, *args)
1326 try:
-> 1327 return fn(*args)
1328 except errors.OpError as e:
/opt/conda/lib/python3.6/site-packages/tensorflow/python/client/session.py
in _run_fn(feed_dict, fetch_list, target_list, options, run_metadata)
1309 # Ensure any changes to the graph are reflected in the
runtime.
-> 1310 self._extend_graph()
1311 return self._call_tf_sessionrun(
/opt/conda/lib/python3.6/site-packages/tensorflow/python/client/session.py in _
- List item
extend_graph(self)
1357 tf_session.TF_ExtendGraph(self._session,
-> 1358 graph_def.SerializeToString(), status)
1359 self._opened = True
/opt/conda/lib/python3.6/site-packages/tensorflow/python/framework/errors_impl.py in __exit__(self, type_arg, value_arg, traceback_arg)
515 compat.as_text(c_api.TF_Message(self.status.status)),
--> 516 c_api.TF_GetCode(self.status.status))
517 # Delete the underlying status object from memory otherwise it stays alive
InvalidArgumentError: Node 'embedding_8/IsVariableInitialized': Unknown input node 'bidirectional_3/forward_cu_dnngru_1/kernel'
During handling of the above exception, another exception occurred:
InvalidArgumentError Traceback (most recent call last)
<ipython-input-39-98e1902305d7> in <module>()
----> 1 model = get_model()
<ipython-input-38-8788d950b75d> in get_model()
7 x_words = Embedding(max_features, 300,
8 weights=[embedding_matrix],
----> 9 trainable=False)(input_words)
10 #x_words = SpatialDropout1D(0.5)(x_words)
11 x_words =Bidirectional(GRU(50, return_sequences=True))(x_words)
/opt/conda/lib/python3.6/site-packages/Keras-2.1.5-py3.6.egg/keras/engine/topology.py in __call__(self, inputs, **kwargs)
597 # Load weights that were specified at layer instantiation.
598 if self._initial_weights is not None:
--> 599 self.set_weights(self._initial_weights)
600
601 # Raise exceptions in case the input is not compatible
/opt/conda/lib/python3.6/site-packages/Keras-2.1.5-py3.6.egg/keras/engine/topology.py in set_weights(self, weights)
1211 return
1212 weight_value_tuples = []
-> 1213 param_values = K.batch_get_value(params)
1214 for pv, p, w in zip(param_values, params, weights):
1215 if pv.shape != w.shape:
/opt/conda/lib/python3.6/site-packages/Keras-2.1.5-py3.6.egg/keras/backend/tensorflow_backend.py in batch_get_value(ops)
2325 """
2326 if ops:
-> 2327 return get_session().run(ops)
2328 else:
2329 return []
/opt/conda/lib/python3.6/site-packages/Keras-2.1.5-py3.6.egg/keras/backend/tensorflow_backend.py in get_session()
191 # not already marked as initialized.
192 is_initialized = session.run(
--> 193 [tf.is_variable_initialized(v) for v in candidate_vars])
194 uninitialized_vars = []
195 for flag, v in zip(is_initialized, candidate_vars):
/opt/conda/lib/python3.6/site-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
903 try:
904 result = self._run(None, fetches, feed_dict, options_ptr,
--> 905 run_metadata_ptr)
906 if run_metadata:
907 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
/opt/conda/lib/python3.6/site-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
1138 if final_fetches or final_targets or (handle and feed_dict_tensor):
1139 results = self._do_run(handle, final_targets, final_fetches,
-> 1140 feed_dict_tensor, options, run_metadata)
1141 else:
1142 results = []
/opt/conda/lib/python3.6/site-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
1319 if handle is None:
1320 return self._do_call(_run_fn, feeds, fetches, targets, options,
-> 1321 run_metadata)
1322 else:
1323 return self._do_call(_prun_fn, handle, feeds, fetches)
/opt/conda/lib/python3.6/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1338 except KeyError:
1339 pass
-> 1340 raise type(e)(node_def, op, message)
1341
1342 def _extend_graph(self):
InvalidArgumentError: Node 'embedding_8/IsVariableInitialized': Unknown input node 'bidirectional_3/forward_cu_dnngru_1/kernel'
history = model.fit( X_train_words, X_train_target, valida
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