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Backpropagation Solution Needed

Please list the forward pass and backwards pass calculations for the backpropagation problem attached.

example calcs:

Forward Pass: needed

sigy = 1.0 / (1 + exp(-y)) #(1)

num = x + sigy # numerator #(2)

sigx = 1.0 / (1 + exp(-x)) #(3)

xpy = x + y #(4)

xpysqr = xpy**2 #(5)

den = sigx + xpysqr # denominator #(6)

invden = 1.0 / den #(7)

f = num * invden #(8)

Backward Pass:

# gradient at the top

df = 1.0

# backprop f = num * invden

dnum = 1.0 * invden # gradient on numerator #(8)

dinvden = 1.0 * num #(8)

# backprop invden = 1.0 / den

dden = (-1.0 / (den**2)) * dinvden #(7)

# backprop den = sigx + xpysqr

dsigx = (1) * dden #(6)

dxpysqr = (1) * dden #(6)

# backprop xpysqr = xpy**2

dxpy = (2 * xpy) * dxpysqr #(5)

# backprop xpy = x + y

dx = (1) * dxpy #(4)

dy = (1) * dxpy #(4)

# backprop sigx = 1.0 / (1 + exp(-x))

dx += ((1 - sigx) * sigx) * dsigx # ATTENTION !!

# backprop num = x + sigy

dx += (1) * dnum #(2)

dsigy = (1) * dnum #(2)

# backprop sigy = 1.0 / (1 + exp(-y))

dy += ((1 - sigy) * sigy) * dsigy #(1)

reference:

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Навыки: Алгоритмы, Machine Learning (ML), Neural Networks

О работодателе:
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ID проекта: #32102242

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