python-kerasHow do I use the pad_sequences function in Python Keras?
The pad_sequences function in Python Keras is used to ensure that all sequences in a list have the same length. This is important for neural networks, as inputs must be consistently sized in order to be processed.
For example, to pad a sequence of length 4 to a maximum length of 6, the code would be:
from keras.preprocessing.sequence import pad_sequences
input_sequence = [1, 2, 3, 4]
padded_sequence = pad_sequences([input_sequence], maxlen=6, padding='post')
print(padded_sequence)
The output of this code would be [[1 2 3 4 0 0]]
.
The code is composed of the following parts:
from keras.preprocessing.sequence import pad_sequences
: imports the pad_sequences function from the Keras library.input_sequence = [1, 2, 3, 4]
: defines the input sequence.pad_sequences([input_sequence], maxlen=6, padding='post')
: uses the pad_sequences function to pad the input sequence to a maximum length of 6, with padding added to the end of the sequence (post).print(padded_sequence)
: prints the padded sequence.
Helpful links
More of Python Keras
- How do I use zero padding in Python Keras?
- How can I use Python Keras to create a neural network with zero hidden layers?
- How do I use Python Keras to create a Zoom application?
- How do I use Python Keras to zip a file?
- How can I use word2vec and Keras to develop a machine learning model in Python?
- How can I use YOLO with Python and Keras?
- How can I use XGBoost, Python and Keras together to build a machine learning model?
- How can I install the python module tensorflow.keras in R?
- How do I save weights in a Python Keras model?
- How do I use a webcam with Python and Keras?
See more codes...