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cheerss update the calculation of num_batches_per_epoch
the number of batches per epoch also depends on the number of gpus. it should be `num_batches_per_epoch = (cifar10.NUM_EXAMPLES_PER_EPOCH_FOR_TRAIN / FLAGS.batch_size / FLAGS.num_gpus)`
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README.md Update README.md Dec 21, 2017
__init__.py Remove all references to 'tensorflow.models' which is no longer correct Dec 22, 2016
cifar10.py
cifar10_eval.py Revert "Flags" Jan 5, 2018
cifar10_input.py
cifar10_input_test.py
cifar10_multi_gpu_train.py
cifar10_train.py Fix too much value of default max_steps of 2560 epoch to 256 epoch Jun 19, 2018

README.md

NOTE: For users interested in multi-GPU, we recommend looking at the newer cifar10_estimator example instead.


CIFAR-10 is a common benchmark in machine learning for image recognition.

http://www.cs.toronto.edu/~kriz/cifar.html

Code in this directory demonstrates how to use TensorFlow to train and evaluate a convolutional neural network (CNN) on both CPU and GPU. We also demonstrate how to train a CNN over multiple GPUs.

Detailed instructions on how to get started available at:

http://tensorflow.org/tutorials/deep_cnn/

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