python-kerasHow can I use the preprocessing module from the tensorflow.python.keras library?

The preprocessing module from the tensorflow.python.keras library can be used to preprocess data before feeding it to a neural network. It contains several functions for transforming data such as normalizing, tokenizing, and padding.

Example code

from tensorflow.python.keras.preprocessing import sequence

# Example data
data = [1, 2, 3, 4, 5]

# Pad data
padded_data = sequence.pad_sequences(data, maxlen=10)

print(padded_data)

Output example

[[0 0 0 0 0 0 0 0 0 1]
 [0 0 0 0 0 0 0 0 1 2]
 [0 0 0 0 0 0 0 1 2 3]
 [0 0 0 0 0 0 1 2 3 4]
 [0 0 0 0 0 1 2 3 4 5]]

The code above uses the sequence.pad_sequences() function to pad the data so that it is all the same length. This function takes two parameters: data, which is the data to be padded, and maxlen, which is the length to which the data should be padded.

The list of functions available in the preprocessing module can be found here.

Helpful links

• TensorFlow Preprocessing Module Documentation
• Keras Preprocessing Module Documentation

Edit this code on GitHub