Explain with an example how He_normal initializer work?

Explain with an example how He_normal initializer work?

Explain with an example how He_normal initializer work?

This recipe explains with an example how He_normal initializer work


Recipe Objective

He_Normal initializer

He_Normal initializer takes samples from a truncated normal distribution centered on 0 with stddev = sqrt(2 / fan_in) where fan_in is the number of input units in the weight tensor.

Step 1- Importing Libraries

import numpy as np import keras from keras.models import Sequential from keras.layers import Activation, Dense import tensorflow as tf

Step-2 Initializing the He_normal initializers.

We show you two ways to initialize the He_normal initializers.

initializer = tf.keras.initializers.HeNormal() values = initializer(shape=(2, 2)) layer = tf.keras.layers.Dense(3, kernel_initializer=initializer)

Step 3- We will create the model

We will be reshaping and creating the model

# define input data X = np.array([17, 35, 400, 230]) # show input data for context print(X) # reshape input data into one sample a sample with a channel X = X.reshape((1, 2, 2, 1)) # define model model = Sequential() model.add(Dense(13, input_dim=13, kernel_initializer=initializer, activation='relu')) model.summary()

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