Sequence
Defined in tensorflow/python/keras/_impl/keras/utils/data_utils.py.
Base object for fitting to a sequence of data, such as a dataset.
Every Sequence must implements the __getitem__ and the __len__ methods.
Examples:
from skimage.io import imread
from skimage.transform import resize
import numpy as np
# Here, `x_set` is list of path to the images
# and `y_set` are the associated classes.
class CIFAR10Sequence(Sequence):
def __init__(self, x_set, y_set, batch_size):
self.X,self.y = x_set,y_set
self.batch_size = batch_size
def __len__(self):
return len(self.X) // self.batch_size
def __getitem__(self,idx):
batch_x = self.X[idx*self.batch_size:(idx+1)*self.batch_size]
batch_y = self.y[idx*self.batch_size:(idx+1)*self.batch_size]
return np.array([
resize(imread(file_name), (200,200))
for file_name in batch_x]), np.array(batch_y)
__getitem____getitem__(index)
Gets batch at position index.
index: position of the batch in the Sequence.A batch
__len____len__()
Number of batch in the Sequence.
The number of batches in the Sequence.
on_epoch_endon_epoch_end()
Method called at the end of every epoch.
© 2017 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/keras/utils/Sequence