Tensorflow CIFAR10 code analysis
<p>I'm trying to figure out, a Tensorflow CIFAR10 tutorial and currently I can't understand <a href="https://github.com/tensorflow/tensorflow/blob/r0.10/tensorflow/models/image/cifar10/cifar10.py#L245" rel="nofollow">line #245</a>, namely why is the shape for weight [dim, 384]? Is 384 a hyperparameter or is it somehow calculated?</p>

<p>Basically it was an arbitrary choice that worked out with their batch size and knowledge about the dataset.</p>

<p>So cifar images are 32 * 32 * 3 and by the convolution now they have 32 * 32 * 64 features and just before that they had 64 filters but they just max pooled it so now it's half the size so now its 16 * 16 * 64.  They resized the images to the batch size = 128 so now its 128 * 128.  Then they use weights to bring it up to 384.  </p>

<p>Feel free to use another number but make sure you change the next layers as well.  It's just an example CNN.</p>

python image-processing tensorflow conv-neural-network