Unkown OSERROR -2 for keras CNN

Question

I have been using keras to train a CNN. Earlier today I was able to train a model fine tuning VGG16 and decided to compare this to a fine tuned VGG19 model.

Initially I was getting the "Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.""

and with a stackoverflow search I found that my CUDA was not compatible with my tensorflow version. So I found what versions were compatible and worked together and installed them.

I went to rerun my VGG16 model to make sure everything was okay and working...but now I get...

---------------------------------------------------------------------------
OSError                                   Traceback (most recent call last)
<ipython-input-13-4d283cf7c5f9> in <module>
      4     validation_data = validation_generator,
      5     validation_steps = 700,
----> 6     epochs = 5)

~\Anaconda3\lib\site-packages\keras\legacy\interfaces.py in wrapper(*args, **kwargs)
     89                 warnings.warn('Update your `' + object_name + '` call to the ' +
     90                               'Keras 2 API: ' + signature, stacklevel=2)
---> 91             return func(*args, **kwargs)
     92         wrapper._original_function = func
     93         return wrapper

~\Anaconda3\lib\site-packages\keras\engine\training.py in fit_generator(self, generator, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, class_weight, max_queue_size, workers, use_multiprocessing, shuffle, initial_epoch)
   1416             use_multiprocessing=use_multiprocessing,
   1417             shuffle=shuffle,
-> 1418             initial_epoch=initial_epoch)
   1419 
   1420     @interfaces.legacy_generator_methods_support

~\Anaconda3\lib\site-packages\keras\engine\training_generator.py in fit_generator(model, generator, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, class_weight, max_queue_size, workers, use_multiprocessing, shuffle, initial_epoch)
    179             batch_index = 0
    180             while steps_done < steps_per_epoch:
--> 181                 generator_output = next(output_generator)
    182 
    183                 if not hasattr(generator_output, '__len__'):

~\Anaconda3\lib\site-packages\keras\utils\data_utils.py in get(self)
    707                     "`use_multiprocessing=False, workers > 1`."
    708                     "For more information see issue #1638.")
--> 709             six.reraise(*sys.exc_info())

~\Anaconda3\lib\site-packages\six.py in reraise(tp, value, tb)
    694             if value.__traceback__ is not tb:
    695                 raise value.with_traceback(tb)
--> 696             raise value
    697         finally:
    698             value = None

~\Anaconda3\lib\site-packages\keras\utils\data_utils.py in get(self)
    683         try:
    684             while self.is_running():
--> 685                 inputs = self.queue.get(block=True).get()
    686                 self.queue.task_done()
    687                 if inputs is not None:

~\Anaconda3\lib\multiprocessing\pool.py in get(self, timeout)
    681             return self._value
    682         else:
--> 683             raise self._value
    684 
    685     def _set(self, i, obj):

~\Anaconda3\lib\multiprocessing\pool.py in worker(inqueue, outqueue, initializer, initargs, maxtasks, wrap_exception)
    119         job, i, func, args, kwds = task
    120         try:
--> 121             result = (True, func(*args, **kwds))
    122         except Exception as e:
    123             if wrap_exception and func is not _helper_reraises_exception:

~\Anaconda3\lib\site-packages\keras\utils\data_utils.py in next_sample(uid)
    624         The next value of generator `uid`.
    625     """
--> 626     return six.next(_SHARED_SEQUENCES[uid])
    627 
    628 

~\Anaconda3\lib\site-packages\keras_preprocessing\image\iterator.py in __next__(self, *args, **kwargs)
    102 
    103     def __next__(self, *args, **kwargs):
--> 104         return self.next(*args, **kwargs)
    105 
    106     def next(self):

~\Anaconda3\lib\site-packages\keras_preprocessing\image\iterator.py in next(self)
    114         # The transformation of images is not under thread lock
    115         # so it can be done in parallel
--> 116         return self._get_batches_of_transformed_samples(index_array)
    117 
    118     def _get_batches_of_transformed_samples(self, index_array):

~\Anaconda3\lib\site-packages\keras_preprocessing\image\iterator.py in _get_batches_of_transformed_samples(self, index_array)
    228                            color_mode=self.color_mode,
    229                            target_size=self.target_size,
--> 230                            interpolation=self.interpolation)
    231             x = img_to_array(img, data_format=self.data_format)
    232             # Pillow images should be closed after `load_img`,

~\Anaconda3\lib\site-packages\keras_preprocessing\image\utils.py in load_img(path, grayscale, color_mode, target_size, interpolation)
    130                         ", ".join(_PIL_INTERPOLATION_METHODS.keys())))
    131             resample = _PIL_INTERPOLATION_METHODS[interpolation]
--> 132             img = img.resize(width_height_tuple, resample)
    133     return img
    134 

~\Anaconda3\lib\site-packages\PIL\Image.py in resize(self, size, resample, box)
   1780             return self.convert('RGBa').resize(size, resample, box).convert('RGBA')
   1781 
-> 1782         self.load()
   1783 
   1784         return self._new(self.im.resize(size, resample, box))

~\Anaconda3\lib\site-packages\PIL\TiffImagePlugin.py in load(self)
   1065     def load(self):
   1066         if self.use_load_libtiff:
-> 1067             return self._load_libtiff()
   1068         return super(TiffImageFile, self).load()
   1069 

~\Anaconda3\lib\site-packages\PIL\TiffImagePlugin.py in _load_libtiff(self)
   1157 
   1158         if err < 0:
-> 1159             raise IOError(err)
   1160 
   1161         return Image.Image.load(self)

OSError: -2```


Any idea?