train 파일에서
아래와 같은 오류가 계속 발생해야 하는데 어떻게 수정 할 수 있을 까요?

19962 19962
/home/ubuntu/SuperResolution/super_resolution-master/processed/x_test/182638.npy
Traceback (most recent call last):
File "train.py", line 99, in
y_pred = model.predict(x1_test.reshape((1, 44, 44, 3)))
ValueError: cannot reshape array of size 1936 into shape (1,44,44,3)

y_train 용량이 얼마나 만들어지나요? 88G 까지 만들다가 용량 없어서 에러 나네요 ㅜㅜ

history = model.fit_generator(train_gen, validation_data=val_gen, epochs=10, verbose=1, callbacks=[
ModelCheckpoint(r'models\model.h5', monitor='val_loss', verbose=1, save_best_only=True)
])

위 셀 실행시 아래와 같은 오류가 납니다.
왜 그런건가요 그대로 했는데...
알려주세요
이건 있던 모델인데
모델을 직접 만들어야 하나요?

IndexError Traceback (most recent call last)
in
----> 1 history = model.fit_generator(train_gen, validation_data=val_gen, epochs=10, verbose=1, callbacks=[
2 ModelCheckpoint(r'models\model.h5', monitor='val_loss', verbose=1, save_best_only=True)
3 ])

~\anaconda3\lib\site-packages\tensorflow\python\util\deprecation.py in new_func(*args, **kwargs)
322 'in a future version' if date is None else ('after %s' % date),
323 instructions)
--> 324 return func(*args, **kwargs)
325 return tf_decorator.make_decorator(
326 func, new_func, 'deprecated',

~\anaconda3\lib\site-packages\tensorflow\python\keras\engine\training.py in fit_generator(self, generator, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, validation_freq, class_weight, max_queue_size, workers, use_multiprocessing, shuffle, initial_epoch)
1813 """
1814 _keras_api_gauge.get_cell('fit_generator').set(True)
-> 1815 return self.fit(
1816 generator,
1817 steps_per_epoch=steps_per_epoch,

~\anaconda3\lib\site-packages\tensorflow\python\keras\engine\training.py in _method_wrapper(self, *args, **kwargs)
106 def _method_wrapper(self, *args, **kwargs):
107 if not self._in_multi_worker_mode(): # pylint: disable=protected-access
--> 108 return method(self, *args, **kwargs)
109
110 # Running inside run_distribute_coordinator already.

~\anaconda3\lib\site-packages\tensorflow\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_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing)
1047 training_utils.RespectCompiledTrainableState(self):
1048 # Creates a tf.data.Dataset and handles batch and epoch iteration.
-> 1049 data_handler = data_adapter.DataHandler(
1050 x=x,
1051 y=y,

~\anaconda3\lib\site-packages\tensorflow\python\keras\engine\data_adapter.py in init(self, x, y, sample_weight, batch_size, steps_per_epoch, initial_epoch, epochs, shuffle, class_weight, max_queue_size, workers, use_multiprocessing, model, steps_per_execution)
1103
1104 adapter_cls = select_data_adapter(x, y)
-> 1105 self._adapter = adapter_cls(
1106 x,
1107 y,

~\anaconda3\lib\site-packages\tensorflow\python\keras\engine\data_adapter.py in init(self, x, y, sample_weights, shuffle, workers, use_multiprocessing, max_queue_size, model, **kwargs)
907 self._keras_sequence = x
908 self._enqueuer = None
--> 909 super(KerasSequenceAdapter, self).init(
910 x,
911 shuffle=False, # Shuffle is handed in the _make_callable override.

~\anaconda3\lib\site-packages\tensorflow\python\keras\engine\data_adapter.py in init(self, x, y, sample_weights, workers, use_multiprocessing, max_queue_size, model, **kwargs)
784 # Since we have to know the dtype of the python generator when we build the
785 # dataset, we have to look at a batch to infer the structure.
--> 786 peek, x = self._peek_and_restore(x)
787 peek = self._standardize_batch(peek)
788 peek = _process_tensorlike(peek)

~\anaconda3\lib\site-packages\tensorflow\python\keras\engine\data_adapter.py in _peek_and_restore(x)
918 @staticmethod
919 def _peek_and_restore(x):
--> 920 return x[0], x
921
922 def _handle_multiprocessing(self, x, workers, use_multiprocessing,

~\Desktop...\DataGenerator.py in getitem(self, index)
30
31 # Generate data
---> 32 X, y = self.__data_generation(list_IDs_temp)
33
34 return X, y

~\Desktop,..SuperResolution\DataGenerator.py in __data_generation(self, list_IDs_temp)
52
53 splited = ID.split('/')
---> 54 splited[-2] = 'y' + splited[-2][1:] # x_train -> y_train
55 y_path = os.path.join(os.sep, *splited)
56

IndexError: list index out of range

그리고 그래픽 카드 메모리를 확 차지하네요 90% 이상 fit_generator 실행하면 에러나면서

이 학습 잘 돌아가는 케라스 , 텐서 플로 버전이 어떻게 되나요?
fit_generator 에서 아래와 같은 오류 나고 Epoch 1/10 에서 오류 납니다.
WARNING:tensorflow:From :1: Model.fit_generator (from tensorflow.python.keras.engine.training) is deprecated and will be removed in a future version.
Instructions for updating:
Please use Model.fit, which supports generators
Epoch 1/10

UnknownError Traceback (most recent call last)
...