我正在创建一个用于检测脑肿瘤的python应用程序。
关于数据：该数据集包含2个文件夹：是和否，其中包含253个脑MRI图像。文件夹"是"包含155个肿瘤性脑MRI图像，文件夹"否"包含98个非肿瘤性脑核磁共振图像。
# tensorboard
log_file_name = f'brain_tumor_detection_cnn_{int(time.time())}'
tensorboard = TensorBoard(log_dir=f'logs/{log_file_name}')
# checkpoint
# unique file name that will include the epoch and the validation (development) accuracy
filepath="cnn-parameters-improvement-{epoch:02d}-{val_acc:.2f}"
# save the model with the best validation (development) accuracy till now
checkpoint = ModelCheckpoint("models/{}.model".format(filepath, monitor='val_acc', verbose=1, save_best_only=True, mode='max'))
# ## Train the model
model.fit(x=X_train, y=y_train, batch_size=32, epochs=10, validation_data=(X_val, y_val), callbacks=[tensorboard, checkpoint])
在训练模型时，我得到了以下错误：
Epoch 1/10
91/91 [==============================] - ETA: 0s - loss: 0.7457 - accuracy: 0.6735
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
c:python38libsite-packagestensorflowpythonkerascallbacks.py in _get_file_path(self, epoch, logs)
1243 # placeholders can cause formatting to fail.
-> 1244 return self.filepath.format(epoch=epoch + 1, **logs)
1245 except KeyError as e:
KeyError: 'val_acc'
During handling of the above exception, another exception occurred:
KeyError Traceback (most recent call last)
<ipython-input-20-b50661a1419b> in <module>
1 start_time = time.time()
2
----> 3 model.fit(x=X_train, y=y_train, batch_size=32, epochs=10, validation_data=(X_val, y_val), callbacks=[tensorboard, checkpoint])
4
5 end_time = time.time()
c:python38libsite-packagestensorflowpythonkerasenginetraining.py in _method_wrapper(self, *args, **kwargs)
64 def _method_wrapper(self, *args, **kwargs):
65 if not self._in_multi_worker_mode(): # pylint: disable=protected-access
---> 66 return method(self, *args, **kwargs)
67
68 # Running inside `run_distribute_coordinator` already.
c:python38libsite-packagestensorflowpythonkerasenginetraining.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_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing, **kwargs)
811 epoch_logs.update(val_logs)
812
--> 813 callbacks.on_epoch_end(epoch, epoch_logs)
814 if self.stop_training:
815 break
c:python38libsite-packagestensorflowpythonkerascallbacks.py in on_epoch_end(self, epoch, logs)
363 logs = self._process_logs(logs)
364 for callback in self.callbacks:
--> 365 callback.on_epoch_end(epoch, logs)
366
367 def on_train_batch_begin(self, batch, logs=None):
c:python38libsite-packagestensorflowpythonkerascallbacks.py in on_epoch_end(self, epoch, logs)
1175 self._save_model(epoch=epoch, logs=logs)
1176 else:
-> 1177 self._save_model(epoch=epoch, logs=logs)
1178 if self.model._in_multi_worker_mode():
1179 # For multi-worker training, back up the weights and current training
c:python38libsite-packagestensorflowpythonkerascallbacks.py in _save_model(self, epoch, logs)
1194 int) or self.epochs_since_last_save >= self.period:
1195 self.epochs_since_last_save = 0
-> 1196 filepath = self._get_file_path(epoch, logs)
1197
1198 try:
c:python38libsite-packagestensorflowpythonkerascallbacks.py in _get_file_path(self, epoch, logs)
1244 return self.filepath.format(epoch=epoch + 1, **logs)
1245 except KeyError as e:
-> 1246 raise KeyError('Failed to format this callback filepath: "{}". '
1247 'Reason: {}'.format(self.filepath, e))
1248 else:
KeyError: 'Failed to format this callback filepath: "models/cnn-parameters-improvement-{epoch:02d}-{val_acc:.2f}.model". Reason: 'val_acc''
如果将tensorflow与keras一起使用，请尝试使用val_accuracy而不是val_acc