How to calculate the number of Parameters

 Suppose we have a CNN layer,

input is - 1*1*28*28 (batch_size * channels * height * width )

nn.Conv2d(1, 64, kernel_size=3)

means here input channel is 1 and the ouput channel is 64. the kernel is of size 3 X 3 


How to find a number of parameters?

(kernel width * kernel height * number of channel in the previous layer + 1)  * Number of filters of the CNN

(3 * 3 * 1 + 1) * 64 = 640 parameters


How to find CNN output size?

[(W-K+2P) / S] + 1

if you have an image of size 1*28*28 where 1 is a channel, 28 is height, and 28 width.

so Input shape = 1*28*28

W- width of an image

K - Kernel size

P - padding

S - Stride

in our case output size is

[(28-3+2*0)/1]+1 = 25

Output shape: 1* 25*25



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