我正在尝试编写单层网络。当它开始训练model.fit
时,在某个随机时期它会抛出以下错误:
ValueError: I/O operation on closed file
以下是我使用model.fit
my_model = model.fit(train_x, train_y, batch_size=100, nb_epoch=20, show_accuracy=True, verbose=1)
如果您有任何想法或遇到同样的问题,请告诉我。
由于
以下是错误的完整输出:
Epoch 1/20
47900/60816 [======================>.......] - ETA: 3s - loss: 0.1688 - acc: 0.9594
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-4-273f2082a322> in <module>()
14 model.compile(loss='binary_crossentropy', optimizer='adadelta')
15
---> 16 model.fit(train_x, train_y, batch_size=100, nb_epoch=20, show_accuracy=True, verbose=1)
17 score = model.evaluate(test_x, test_y, show_accuracy=True, verbose=0)
18 print('Test loss:', score[0])
/usr/local/lib/python2.7/dist-packages/keras/models.pyc in fit(self, X, y, batch_size, nb_epoch, verbose, callbacks, validation_split, validation_data, shuffle, show_accuracy, class_weight, sample_weight)
699 verbose=verbose, callbacks=callbacks,
700 val_f=val_f, val_ins=val_ins,
--> 701 shuffle=shuffle, metrics=metrics)
702
703 def predict(self, X, batch_size=128, verbose=0):
/usr/local/lib/python2.7/dist-packages/keras/models.pyc in _fit(self, f, ins, out_labels, batch_size, nb_epoch, verbose, callbacks, val_f, val_ins, shuffle, metrics)
321 batch_logs[l] = o
322
--> 323 callbacks.on_batch_end(batch_index, batch_logs)
324
325 epoch_logs = {}
/usr/local/lib/python2.7/dist-packages/keras/callbacks.pyc in on_batch_end(self, batch, logs)
58 t_before_callbacks = time.time()
59 for callback in self.callbacks:
---> 60 callback.on_batch_end(batch, logs)
61 self._delta_ts_batch_end.append(time.time() - t_before_callbacks)
62 delta_t_median = np.median(self._delta_ts_batch_end)
/usr/local/lib/python2.7/dist-packages/keras/callbacks.pyc in on_batch_end(self, batch, logs)
187 # will be handled by on_epoch_end
188 if self.verbose and self.seen < self.params['nb_sample']:
--> 189 self.progbar.update(self.seen, self.log_values)
190
191 def on_epoch_end(self, epoch, logs={}):
/usr/local/lib/python2.7/dist-packages/keras/utils/generic_utils.pyc in update(self, current, values)
59 prev_total_width = self.total_width
60 sys.stdout.write("\b" * prev_total_width)
---> 61 sys.stdout.write("\r")
62
63 numdigits = int(np.floor(np.log10(self.target))) + 1
/usr/local/lib/python2.7/dist-packages/ipykernel/iostream.pyc in write(self, string)
315
316 is_child = (not self._is_master_process())
--> 317 self._buffer.write(string)
318 if is_child:
319 # newlines imply flush in subprocesses
ValueError: I/O operation on closed file
答案 0 :(得分:7)
正如问题评论中提到的那样(直到现在才看到),这实际上是由于IPython / Jupyter IO中的一个错误以及它如何处理来自Keras的详细输出。您可以通过在模型上调用的verbose=False
和train
或predict
方法上设置predict_proba
作为同时解决方法来停用报告,或者只是在笔记本。
有issue on the Keras Github总结了问题。
答案 1 :(得分:7)
我遇到了同样的问题并立即修复了。通过在model.fit中设置verbose = 2可以帮助解决这个问题。在Model.fit的Keras文档中,您可以找到:&#34;详细:0表示没有记录到stdout,1表示进度条记录,2表示每个纪元的一个日志行。&#34;。设置verbose = 2将更新每个纪元后的进度,并有助于减少输出到屏幕的日志信息量,我猜这会导致IO关闭问题。有些人建议设置verbose = 0来禁用输出,但在这种情况下我们无法跟踪进度。我希望这也有助于解决您的问题。