Need help with this code completion below in python:class LinearLayer: def __init__(self,M,N): self.W = np.random.randn(N, M) * 0.1 self.b =np.zeros(shape =(N, 1)) self.Wgrad = None self.bgrad = None self.X = None def forward(self,X): self.X = X # YOUR CODE HERE return def backward(self,dY): # YOUR CODE HERE return diff Linear LayerThe linear layerY = L(X)takes X of size M × P and translates it to Y of dimension N x P. It performsY = WX + b.Here W is of dimension N × M and b is of dimension N x 1The backward step need to computeVxC, VwC = VyC×XT, and V,C =VyCx1The intermediate variable X need to be saved during the forward pass

Given python code: class LinearLayer: def __init__(self,M,N): self.W =…

Answered: Need help with this code completion…

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

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Need help with this code completion below in python:

class LinearLayer:
def __init__(self,M,N):
self.W = np.random.randn(N, M) * 0.1
self.b =np.zeros(shape =(N, 1))
self.Wgrad = None
self.bgrad = None
self.X = None


def forward(self,X):
self.X = X

# YOUR CODE HERE
return


def backward(self,dY):

# YOUR CODE HERE

return diff

Linear Layer
The linear layer
Y = L(X)
takes X of size M × P and translates it to Y of dimension N x P. It performs
Y = WX + b.
Here W is of dimension N × M and b is of dimension N x 1
The backward step need to compute
VxC, VwC = VyC×XT, and V,C =VyCx1
The intermediate variable X need to be saved during the forward pass

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