Styjun

I am trying to override the keras.util.Sequence with my class SequenceGenerator(Sequence) and pass it to the fit_generator, but the fit_generator raised an error ValueError

Here is my custom class

import os
import numpy as np
from keras.utils import Sequence
from batchGenerator import BatchGenerator

from settings import batch_size, train_folder, test_folder

class SequenceGenerator(Sequence):
 def __init__(self, batches_folder):
 self.batch_generator = BatchGenerator(folder_name=batches_folder) 
 self.names = [f for f in os.listdir(batches_folder) if f.lower().endswith('.jpg')]

 def __len__(self):
 return int(np.ceil(len(self.names) / float(batch_size)))

 def __getitem__(self, idx):
 print('Getting a bacth0'.format(idx))
 [X_batch, Y_batch] = self.batch_generator.load_batch_from_disk(idx)
 return X_batch, Y_batch


def train_seq_genenrator():
 return SequenceGenerator(train_folder)


def test_seq_generator():
 return SequenceGenerator(test_folder)

and in jupyter notebook, I imported the following

from sequenceGenerator import train_seq_genenrator, test_seq_generator

finally here you are the fit_generator call

history = new_model.fit_generator(train_seq_genenrator()
 , steps_per_epoch=num_train_samples // batch_size 
 , validation_data=test_seq_generator()
 , validation_steps=num_test_samples // batch_size
 , epochs=epochs
 , shuffle=True)

I got the following error:

---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-63-347bef86c8c0> in <module>()
 4 , validation_steps=num_test_samples // batch_size
 5 , epochs=epochs
----> 6 , shuffle=True)

~Anaconda3envstensorflowlibsite-packagestensorflowpythonkerasenginetraining.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)
 1759 use_multiprocessing=use_multiprocessing,
 1760 shuffle=shuffle,
-> 1761 initial_epoch=initial_epoch)
 1762 
 1763 def evaluate_generator(self,

~Anaconda3envstensorflowlibsite-packagestensorflowpythonkerasenginetraining_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)
 121 '`validation_data` should be a tuple '
 122 '`(val_x, val_y, val_sample_weight)` '
--> 123 'or `(val_x, val_y)`. Found: ' + str(validation_data))
 124 val_x, val_y, val_sample_weights = model._standardize_user_data(
 125 val_x, val_y, val_sample_weight)

ValueError: `validation_data` should be a tuple `(val_x, val_y, val_sample_weight)` or `(val_x, val_y)`. Found: <sequenceGenerator.SequenceGenerator object at 0x000001DCB58259B0>

I don't know why this happens, however this found in https://keras.io/models/sequential/

validation_data: This can be either

• a generator or a Sequence object for the validation data


• tuple (x_val, y_val)


• tuple (x_val, y_val, val_sample_weights)