Hi! I met an error in solubility_test_new_message.ipynb.
---Error section -----
with warnings.catch_warnings():
warnings.simplefilter("ignore")
hist = model.fit_generator(train_generator,validation_data=test_generator,epochs=50, verbose=2)
----Error output----
Epoch 1/50
ValueError Traceback (most recent call last)
in
2 warnings.simplefilter("ignore")
3
----> 4 hist = model.fit_generator(train_generator,validation_data=test_generator,epochs=50, verbose=1)
/anaconda3/lib/python3.6/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/python3.6/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/python3.6/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)
215 outs = model.train_on_batch(x, y,
216 sample_weight=sample_weight,
--> 217 class_weight=class_weight)
218
219 outs = to_list(outs)
/anaconda3/lib/python3.6/site-packages/keras/engine/training.py in train_on_batch(self, x, y, sample_weight, class_weight)
1209 x, y,
1210 sample_weight=sample_weight,
-> 1211 class_weight=class_weight)
1212 if self._uses_dynamic_learning_phase():
1213 ins = x + y + sample_weights + [1.]
/anaconda3/lib/python3.6/site-packages/nfp/models/models.py in _standardize_user_data(self, *args, **kwargs)
10 def _standardize_user_data(self, *args, **kwargs):
11 kwargs['check_array_lengths'] = False
---> 12 return super(GraphModel, self)._standardize_user_data(*args, **kwargs)
/anaconda3/lib/python3.6/site-packages/keras/engine/training.py in _standardize_user_data(self, x, y, sample_weight, class_weight, check_array_lengths, batch_size)
802 ]
803 # Check that all arrays have the same length.
--> 804 check_array_length_consistency(x, y, sample_weights)
805 if self._is_graph_network:
806 # Additional checks to avoid users mistakenly
/anaconda3/lib/python3.6/site-packages/keras/engine/training_utils.py in check_array_length_consistency(inputs, targets, weights)
226 raise ValueError('All input arrays (x) should have '
227 'the same number of samples. Got array shapes: ' +
--> 228 str([x.shape for x in inputs]))
229 if len(set_y) > 1:
230 raise ValueError('All target arrays (y) should have '
ValueError: All input arrays (x) should have the same number of samples. Got array shapes: [(657, 1), (657, 1), (1350, 1), (1350, 2)]