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failFast.js
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Brady James Garvin authoredBrady James Garvin authored
cnnff.py 998 B
from scipy.signal import correlate as conv
import numpy as np
from activations import relu, softmax
def cnnff(x, net):
''' cnnff
perform feed-forward pass for convolutional network
inputs:
x: batch of input images (N x H x W x Cin numpy array)
net: List structure describing the network architecture (see cnn.py for details)
outputs:
net: updated net data structure that stores outputs from each layer
'''
# set input layer
# loop over layers 1...L
for n in range(1,len(net)):
# current input
inp = net[n-1]['output']
# current layer
layer = net[n]
# if layer type is Conv
if layer['type'] is 'Conv':
# conv followed by activation function
''' *** put code here *** '''
# if layer type is Pool
elif layer['type'] is 'Pool':
''' *** put code here *** '''
return net