ValueError: `validation_steps=None` is only valid for a generator based on the `keras.utils.Sequence` class. Please specify `validation_steps` or use the `keras.utils.Sequence` class.

ValueError Traceback (most recent call last) <ipython-input-22-9e051c003cc7> in <module>() 10 validation_data=val_generator, 11 validation_steps=ceil(val_dataset_size/batch_size), —> 12 initial_epoch=initial_epoch)

~/anaconda2/envs/py3/lib/python3.5/site-packages/keras/legacy/interfaces.py in wrapper(*args, **kwargs) 89 warnings.warn('Update your ' + object_name + 90 ' call to the Keras 2 API: ’ + signature, stacklevel=2) —> 91 return func(*args, **kwargs) 92 wrapper._original_function = func 93 return wrapper

~/anaconda2/envs/py3/lib/python3.5/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) 2105 if (val_gen and not isinstance(validation_data, Sequence) and 2106 not validation_steps): -> 2107 raise ValueError(‘validation_steps=None is only valid for a’ 2108 ’ generator based on the keras.utils.Sequence’ 2109 ’ class. Please specify validation_steps or use’

ValueError: validation_steps=None is only valid for a generator based on the keras.utils.Sequence class. Please specify validation_steps or use the keras.utils.Sequence class. I found an error using ssd-training，thanks

[asetkn]

Hi,

I had the same error. My validation_steps were set to: validation_steps=nb_validation_samples // batch_size Turns out my nb_validation_samples were less than batch_size

[emanuelevivoli]

I had the same error, and I came out of this after modified the validation_steps. Maybe it cannot be too low.