How do GRUs work with Keras Explain with an example?

How do GRUs work with Keras Explain with an example?

How do GRUs work with Keras Explain with an example?

This recipe explains how GRUs work with Keras Explain with an example


Recipe Objective

How do GRU's work with Keras? Explain with an example

GRU stands for Gated Recurrent Units. It was created as the solution to short-term Memory. It is very similar to LSTM its internal mechanism is controlled by gates and they regulate the flow of information. GRU uses a hidden state instead of a cell state to transfer information, it only has two gates update gate and the reset gate.

Step 1- Importing Libraries

import keras from keras.models import Sequential from keras.layers import GRU import numpy as np

Step 2- Define the model.

We will define the model and Add a GRU layer to it.

model = Sequential() model.add(GRU(1, input_shape=(20,1))) model.compile(optimizer='adam', loss='mse')

Step 3- We will define a sample array to run in the model.

We will define the arrays and run them in the model.

# input time steps y = np.array([[1, 2, 3, 4, 5, 6, 7, 8, 9, 10],[9, 8, 7, 6, 5, 4, 3, 2, 1, 0]]).reshape((1,20,1)) # make and show prediction print(model.predict(y))

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