Когда я читаю учебные пособия по Google tenorflow2.0, я сталкиваюсь с удивленной ошибкой, когда пытаюсь протестировать мой jupyter. Это так странно! Это бегло бегать в Google colab! Учебники: this Мой компьютер GPU - gtx1060 6G, а память - 16G, я думаю, что мой компьютер в порядке, чтобы запустить эти учебники.
Я пытаюсь запустить его на Jupyter, и он запускает ошибку. Но бегло бегите в Google colab!
Вы можете увидеть следующий код ошибки или перейти в Интернет :
from __future__ import absolute_import, division, print_function, unicode_literals
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers
import tensorflow_datasets as tfds
# tfds.disable_progress_bar()
(train_data, test_data), info = tfds.load(
'imdb_reviews/subwords8k',
split = (tfds.Split.TRAIN, tfds.Split.TEST),
with_info=True, as_supervised=True)
encoder = info.features['text'].encoder
padded_shapes = ([None],())
train_batches = train_data.shuffle(1000).padded_batch(10, padded_shapes = padded_shapes)
test_batches = test_data.shuffle(1000).padded_batch(10, padded_shapes = padded_shapes)
embedding_dim=16
model = keras.Sequential([
layers.Embedding(encoder.vocab_size, embedding_dim,mask_zero=True),
layers.Bidirectional(tf.keras.layers.LSTM(32)),
layers.Dense(1, activation='sigmoid')
])
model.compile(optimizer='adam',
loss='binary_crossentropy',
metrics=['accuracy'])
history = model.fit(
train_batches,
epochs=10,
validation_data=test_batches, validation_steps=20,verbose=2)
Я впервые встречаюсь с этой ошибкой, и я не знаю, как это исправить, но он бегло работает на Google colab, я не знаю почему? Ошибка следующая:
Epoch 1/10
---------------------------------------------------------------------------
CancelledError Traceback (most recent call last)
<ipython-input-2-8f27353fef79> in <module>
31 train_batches,
32 epochs=10,
---> 33 validation_data=test_batches, validation_steps=20,verbose=2)
c:\users\sha\anaconda3\envs\tensorflow2\lib\site-packages\tensorflow_core\python\keras\engine\training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_freq, max_queue_size, workers, use_multiprocessing, **kwargs)
726 max_queue_size=max_queue_size,
727 workers=workers,
--> 728 use_multiprocessing=use_multiprocessing)
729
730 def evaluate(self,
c:\users\sha\anaconda3\envs\tensorflow2\lib\site-packages\tensorflow_core\python\keras\engine\training_v2.py in fit(self, model, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_freq, **kwargs)
322 mode=ModeKeys.TRAIN,
323 training_context=training_context,
--> 324 total_epochs=epochs)
325 cbks.make_logs(model, epoch_logs, training_result, ModeKeys.TRAIN)
326
c:\users\sha\anaconda3\envs\tensorflow2\lib\site-packages\tensorflow_core\python\keras\engine\training_v2.py in run_one_epoch(model, iterator, execution_function, dataset_size, batch_size, strategy, steps_per_epoch, num_samples, mode, training_context, total_epochs)
121 step=step, mode=mode, size=current_batch_size) as batch_logs:
122 try:
--> 123 batch_outs = execution_function(iterator)
124 except (StopIteration, errors.OutOfRangeError):
125 # TODO(kaftan): File bug about tf function and errors.OutOfRangeError?
c:\users\sha\anaconda3\envs\tensorflow2\lib\site-packages\tensorflow_core\python\keras\engine\training_v2_utils.py in execution_function(input_fn)
84 # `numpy` translates Tensors to values in Eager mode.
85 return nest.map_structure(_non_none_constant_value,
---> 86 distributed_function(input_fn))
87
88 return execution_function
c:\users\sha\anaconda3\envs\tensorflow2\lib\site-packages\tensorflow_core\python\eager\def_function.py in __call__(self, *args, **kwds)
455
456 tracing_count = self._get_tracing_count()
--> 457 result = self._call(*args, **kwds)
458 if tracing_count == self._get_tracing_count():
459 self._call_counter.called_without_tracing()
c:\users\sha\anaconda3\envs\tensorflow2\lib\site-packages\tensorflow_core\python\eager\def_function.py in _call(self, *args, **kwds)
485 # In this case we have created variables on the first call, so we run the
486 # defunned version which is guaranteed to never create variables.
--> 487 return self._stateless_fn(*args, **kwds) # pylint: disable=not-callable
488 elif self._stateful_fn is not None:
489 # Release the lock early so that multiple threads can perform the call
c:\users\sha\anaconda3\envs\tensorflow2\lib\site-packages\tensorflow_core\python\eager\function.py in __call__(self, *args, **kwargs)
1821 """Calls a graph function specialized to the inputs."""
1822 graph_function, args, kwargs = self._maybe_define_function(args, kwargs)
-> 1823 return graph_function._filtered_call(args, kwargs) # pylint: disable=protected-access
1824
1825 @property
c:\users\sha\anaconda3\envs\tensorflow2\lib\site-packages\tensorflow_core\python\eager\function.py in _filtered_call(self, args, kwargs)
1139 if isinstance(t, (ops.Tensor,
1140 resource_variable_ops.BaseResourceVariable))),
-> 1141 self.captured_inputs)
1142
1143 def _call_flat(self, args, captured_inputs, cancellation_manager=None):
c:\users\sha\anaconda3\envs\tensorflow2\lib\site-packages\tensorflow_core\python\eager\function.py in _call_flat(self, args, captured_inputs, cancellation_manager)
1222 if executing_eagerly:
1223 flat_outputs = forward_function.call(
-> 1224 ctx, args, cancellation_manager=cancellation_manager)
1225 else:
1226 gradient_name = self._delayed_rewrite_functions.register()
c:\users\sha\anaconda3\envs\tensorflow2\lib\site-packages\tensorflow_core\python\eager\function.py in call(self, ctx, args, cancellation_manager)
509 inputs=args,
510 attrs=("executor_type", executor_type, "config_proto", config),
--> 511 ctx=ctx)
512 else:
513 outputs = execute.execute_with_cancellation(
c:\users\sha\anaconda3\envs\tensorflow2\lib\site-packages\tensorflow_core\python\eager\execute.py in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name)
65 else:
66 message = e.message
---> 67 six.raise_from(core._status_to_exception(e.code, message), None)
68 except TypeError as e:
69 keras_symbolic_tensors = [
c:\users\sha\anaconda3\envs\tensorflow2\lib\site-packages\six.py in raise_from(value, from_value)
CancelledError: [_Derived_]RecvAsync is cancelled.
[[{{node Reshape_11/_38}}]] [Op:__inference_distributed_function_16087]
Function call stack:
distributed_function
Спасибо за помощь, помогите мне！