wikiabhi / image-caption-generator Goto Github PK

for i in range(epochs):
generator = data_generator(train_descriptions, train_features, tokenizer, max_length)
model.fit_generator(generator, epochs=1, steps_per_epoch=steps, verbose=1)
model.save('model_' + str(i) + '.h5')
getting error while training model :
Dataset: 6000
Descriptions: train= 6000
Photos: train= 6000
Vocabulary Size: 7579
Description Length: 34
Model: "model_1"

---

ValueError Traceback (most recent call last)
in
17 for i in range(epochs):
18 generator = data_generator(train_descriptions, train_features, tokenizer, max_length)
---> 19 model.fit_generator(generator, epochs=1, steps_per_epoch=steps, verbose=1)
20 model.save('model_' + str(i) + '.h5')

~\Anaconda3\lib\site-packages\tensorflow_core\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)
1295 shuffle=shuffle,
1296 initial_epoch=initial_epoch,
-> 1297 steps_name='steps_per_epoch')
1298
1299 def evaluate_generator(self,

~\Anaconda3\lib\site-packages\tensorflow_core\python\keras\engine\training_generator.py in model_iteration(model, data, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, validation_freq, class_weight, max_queue_size, workers, use_multiprocessing, shuffle, initial_epoch, mode, batch_size, steps_name, **kwargs)
263
264 is_deferred = not model._is_compiled
--> 265 batch_outs = batch_function(*batch_data)
266 if not isinstance(batch_outs, list):
267 batch_outs = [batch_outs]

~\Anaconda3\lib\site-packages\tensorflow_core\python\keras\engine\training.py in train_on_batch(self, x, y, sample_weight, class_weight, reset_metrics)
971 outputs = training_v2_utils.train_on_batch(
972 self, x, y=y, sample_weight=sample_weight,
--> 973 class_weight=class_weight, reset_metrics=reset_metrics)
974 outputs = (outputs['total_loss'] + outputs['output_losses'] +
975 outputs['metrics'])

~\Anaconda3\lib\site-packages\tensorflow_core\python\keras\engine\training_v2_utils.py in train_on_batch(model, x, y, sample_weight, class_weight, reset_metrics)
251 x, y, sample_weights = model._standardize_user_data(
252 x, y, sample_weight=sample_weight, class_weight=class_weight,
--> 253 extract_tensors_from_dataset=True)
254 batch_size = array_ops.shape(nest.flatten(x, expand_composites=True)[0])[0]
255 # If model._distribution_strategy is True, then we are in a replica context

~\Anaconda3\lib\site-packages\tensorflow_core\python\keras\engine\training.py in _standardize_user_data(self, x, y, sample_weight, class_weight, batch_size, check_steps, steps_name, steps, validation_split, shuffle, extract_tensors_from_dataset)
2470 feed_input_shapes,
2471 check_batch_axis=False, # Don't enforce the batch size.
-> 2472 exception_prefix='input')
2473
2474 # Get typespecs for the input data and sanitize it if necessary.

~\Anaconda3\lib\site-packages\tensorflow_core\python\keras\engine\training_utils.py in standardize_input_data(data, names, shapes, check_batch_axis, exception_prefix)
504 elif isinstance(data, (list, tuple)):
505 if isinstance(data[0], (list, tuple)):
--> 506 data = [np.asarray(d) for d in data]
507 elif len(names) == 1 and isinstance(data[0], (float, int)):
508 data = [np.asarray(data)]

~\Anaconda3\lib\site-packages\tensorflow_core\python\keras\engine\training_utils.py in (.0)
504 elif isinstance(data, (list, tuple)):
505 if isinstance(data[0], (list, tuple)):
--> 506 data = [np.asarray(d) for d in data]
507 elif len(names) == 1 and isinstance(data[0], (float, int)):
508 data = [np.asarray(data)]

~\Anaconda3\lib\site-packages\numpy\core\numeric.py in asarray(a, dtype, order)
536
537 """
--> 538 return array(a, dtype, copy=False, order=order)
539
540

ValueError: could not broadcast input array from shape (47,1000) into shape (47)