Convolutions for Images

http://d2l.ai/chapter_convolutional-neural-networks/conv-layer.html

Help me please, I tried using our defined Conv2D class in place of tf.keras.layers.Conv2D. Whenever I specify kernel_size (1, 2) by calling build method on instance of our defined Conv2D class, it works. But then when I call conv2d(X) with X.shape is (1, 6, 8, 1), the weight kernel_size is re initialized to have the shape as X. Is build method called again inside call method? Help me please, thank you. @mli

Y_hat computation on section 6.2.4 Learning a Kernel has been repeated. Y_hat computation just above for loop can be omitted.

In the Learning a Kernel section, what’s the purpose to multiply a factor 3e-2 to the gradient in the update step.

@qyqstc
I think, 3e-2 is the “learning rate”, which controls the velocity to update.

1 Like

Hi @qyqstc, great catch! Just fixed in https://github.com/d2l-ai/d2l-en/pull/1706.

Thanks for the timely reply!!!

the velocity to optim…