Comments (1)
hma02
commented on August 15, 2024
Hi @ksarker1205 , when the computing graph is compiled into a theano function, the forward and backward propagation happens each time the function is called at this line:
https://github.com/uoguelph-mlrg/theano_alexnet/blob/master/train_funcs.py#L165
The function is responsible for taking the input and forward propagating through the graph, and the update argument of the function specifies how the gradient is used in backward propagation.
See how the theano function is constructed here:
https://github.com/uoguelph-mlrg/theano_alexnet/blob/master/alex_net.py#L216
from theano_alexnet.
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from theano_alexnet.