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Idreamofjeanniedownloadinhinditorrent · odin murphy i dream of jeannie. batman · howto make a website with wildebeast · Create and edit your site at 11evolution..Q: tensorflow batch with super large number of images Tensorflow has the batch function, but it only accepts 4 images max. However, I have very large number of images(let’s say, tens of thousands). And I would like to randomly split them into batches of size 20, and make sure there are no repeats in every batch. How do I do that? And is this a good way of doing that? Thank you! A: You could store your images in a dictionary, and use random.shuffle with lists. This way you only have to split your image list into batches of size 20. a = {‘im1’: im1, ‘im2’: im2, ‘im3’: im3, ‘im4’: im4} random.shuffle(a.keys()) for key in a.keys(): a[key] = ima[key] Then you can just use the function tf.map_fn like this: def make_batch(images, batch_size): # The first dimension is the batch size (image_num / batch_size) batches = list(images.keys()) images_for_batch = [] for index, batch_size in enumerate(batch_size): images_for_batch.append(images[tuple(batches[index:index+batch_size])]) return images_for_batch As an example: import numpy as np import tensorflow as tf images = np.random.randint(0,256,(10000,200,200,3)) a = {‘im1’: im1, ‘im2’: im2, ‘im3’: im3, ‘im4’: im4} random.shuffle(a.keys()) for key in a.keys(): a[key] = ima[key] b = make_batch(a.values(),