I have a Keras model that has an input shape = (frames, height, width, channels) and has two scalar outputs (see next code par). My model does use an LSTM, that is why I have to add an additional dimension.
height = 32 width = 64 channels = 3 frames = 2 img_shape = (height, width, channels) input_shape = (frames, height, width, channels) If have defined a batch generator as follows
def generator(df, batch_size, frames_per_scene=frames_per_scene): ### read data frame columns # inputs img_list = df['filename'] # outputs happiness= df['happiness'] anger = df['anger'] # create empty arrays for input and output batch_img = np.zeros((batch_size, frames_per_scene) + img_shape) batch_label = np.zeros((batch_size, 2)) index = 0 while True: for i in range(batch_size): for j in range(frames_per_scene): label = [happiness.iloc[index], anger.iloc[index]] img_name = img_list[index] pil_img = image.load_img(img_name) batch_img[i, j, :] = image.img_to_array(pil_img) batch_label[i] = label index += 1 if index == len(img_list): img_list = df['filename'] happiness = df['happiness'] anger = df['anger'] index = 0 yield batch_img, batch_label When I try to use the following method of my model.
model.fit_generator( train_batch, train_steps, epochs=epochs, verbose=verbose, callbacks=callbacks_list, validation_data=validation_batch, validation_steps=val_steps) I get the following error
--------------------------------------------------------------------------- KeyError Traceback (most recent call last) <ipython-input-7-289c48f3bbf8> in <module> ----> 1 train_model(_episode=0) <ipython-input-6-b4f2c2235a41> in train_model(_episode) 56 TensorBoard(log_dir=path_tensorboard, histogram_freq=0, write_graph=False, write_images=False)] 57 ---> 58 model.fit_generator(train_batch, train_steps, epochs=epochs, verbose=verbose, callbacks=callbacks_list, validation_data=validation_batch, validation_steps=val_steps) c:\envs\lstm\lib\site-packages\keras\legacy\interfaces.py in wrapper(*args, **kwargs) 85 warnings.warn('Update your `' + object_name + 86 '` call to the Keras 2 API: ' + signature, stacklevel=2) ---> 87 return func(*args, **kwargs) 88 wrapper._original_function = func 89 return wrapper c:\envs\lstm\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) 2167 max_queue_size=max_queue_size, 2168 workers=workers, -> 2169 use_multiprocessing=use_multiprocessing) 2170 else: 2171 # No need for try/except because c:\envs\lstm\lib\site-packages\keras\legacy\interfaces.py in wrapper(*args, **kwargs) 85 warnings.warn('Update your `' + object_name + 86 '` call to the Keras 2 API: ' + signature, stacklevel=2) ---> 87 return func(*args, **kwargs) 88 wrapper._original_function = func 89 return wrapper c:\envs\lstm\lib\site-packages\keras\engine\training.py in evaluate_generator(self, generator, steps, max_queue_size, workers, use_multiprocessing) 2278 2279 while steps_done < steps: -> 2280 generator_output = next(output_generator) 2281 if not hasattr(generator_output, '__len__'): 2282 raise ValueError('Output of generator should be a tuple ' c:\envs\lstm\lib\site-packages\keras\utils\data_utils.py in get(self) 733 success, value = self.queue.get() 734 if not success: --> 735 six.reraise(value.__class__, value, value.__traceback__) c:\envs\lstm\lib\site-packages\six.py in reraise(tp, value, tb) 691 if value.__traceback__ is not tb: 692 raise value.with_traceback(tb) --> 693 raise value 694 finally: 695 value = None c:\envs\lstm\lib\site-packages\keras\utils\data_utils.py in data_generator_task() 633 try: 634 if self._use_multiprocessing or self.queue.qsize() < max_queue_size: --> 635 generator_output = next(self._generator) 636 self.queue.put((True, generator_output)) 637 else: <ipython-input-5-b23230fc675a> in generator(df, batch_size, frames_per_scene) 18 for j in range(frames_per_scene): 19 label = [steer.iloc[index], throttle.iloc[index]] ---> 20 img_name = img_list[index] 21 22 pil_img = image.load_img(img_name) c:\pyenvs\ca\lib\site-packages\pandas\core\series.py in __getitem__(self, key) 765 key = com._apply_if_callable(key, self) 766 try: --> 767 result = self.index.get_value(self, key) 768 769 if not is_scalar(result): c:\envs\lstm\lib\site-packages\pandas\core\indexes\base.py in get_value(self, series, key) 3116 try: 3117 return self._engine.get_value(s, k, -> 3118 tz=getattr(series.dtype, 'tz', None)) 3119 except KeyError as e1: 3120 if len(self) > 0 and self.inferred_type in ['integer', 'boolean']: pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_value() pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_value() pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc() pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.Int64HashTable.get_item() pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.Int64HashTable.get_item() KeyError: 0 Question: Has anyone encountered a similar error?
