Get weights and biases of a particular layer of NN in MXNet

In this recipe, we will see how to get weights and biases of a particular layer of NN in MXNet

Recipe Objective: How to get weights and biases of a particular layer of NN in MXNet?

This recipe explains how to get weights and biases of a particular layer of NN in MXNet.

Learn to Build a Multi Class Image Classification Model in Python from Scratch

Step 1: Importing library

Let us first import the necessary libraries. We'll import the neural network (nn alias) package from mxnet.gluon

from mxnet.gluon import nn

Step 2: Chain Layer

We can chain layers into the neural network with the help of sequential. We execute the layers sequentially, one after another. The layers are piled in the same manner they are defined. Its index can access any layer.

layer = nn.Sequential()
layer.add(nn.Dense(720,in_units=3,activation='relu'),
    nn.Dense(316, activation='relu'), nn.Dense(10))
layer[1]

Step 3: Weights and Biases

We can access weights and bias with the .data() method. We can access the weight or bias of a specific layer by using its index.

layer[0].weight.data()
layer[2].bias.data()

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