Keras ValueError:对已关闭文件的I/O操作 [英] Keras ValueError: I/O operation on closed file
问题描述
我正在尝试编写一个单层网络.当它开始通过model.fit进行训练时，在某个随机的时期，它将引发以下错误:
I am trying to write a single layer network. When it starts to train through model.fit, at some random epoch it will throw the following error:
ValueError: I/O operation on closed file
这是我使用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相同的问题，请告诉我.
Please let me know if you have any thoughts or is encountering the same problem.
谢谢
以下是错误的完整输出:
Here is the full output of the error:
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
推荐答案
我遇到了同样的问题，并已将其修复.通过在model.fit中设置verbose = 2可以帮助解决此问题.在model.fit的Keras文档中，您可以找到:详细:0表示不记录到stdout，1表示进度条记录，2表示每个纪元一个日志行.".设置verbose = 2将在每个时期后更新进度，并有助于减少输出到屏幕的日志信息的数量，我猜这是造成IO关闭问题的原因.有人建议将verbose设置为0以禁用输出，但是在那种情况下，我们无法跟踪进度.我希望这也可以解决您的问题.
I got the same problem and had it fixed now. By setting verbose = 2 in model.fit can help to solve this problem. In Keras document for model.fit, you can find this: "verbose: 0 for no logging to stdout, 1 for progress bar logging, 2 for one log line per epoch.". Setting verbose = 2 will update the progress after each epoch, and help to reduce the amount of logging information output to the screen, which i guess caused the IO closed problem. Some people suggest to set verbose = 0 to disable the output but in that case we can't track the progress. I hope this can help to solve your problem as well.
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