
- Keras Tutorial
- Keras - Home
- Keras - Introduction
- Keras - Installation
- Keras - Backend Configuration
- Keras - Overview of Deep learning
- Keras - Deep learning
- Keras - Modules
- Keras - Layers
- Keras - Customized Layer
- Keras - Models
- Keras - Model Compilation
- Keras - Model Evaluation and Prediction
- Keras - Convolution Neural Network
- Keras - Regression Prediction using MPL
- Keras - Time Series Prediction using LSTM RNN
- Keras - Applications
- Keras - Real Time Prediction using ResNet Model
- Keras - Pre-Trained Models
- Keras Useful Resources
- Keras - Quick Guide
- Keras - Useful Resources
- Keras - Discussion
Keras - Lambda Layers
Lambda is used to transform the input data using an expression or function. For example, if Lambda with expression lambda x: x ** 2 is applied to a layer, then its input data will be squared before processing.
RepeatVector has four arguments and it is as follows −
keras.layers.Lambda(function, output_shape = None, mask = None, arguments = None)
function represent the lambda function.
output_shape represent the shape of the transformed input.
mask represent the mask to be applied, if any.
arguments represent the optional argument for the lamda function as dictionary.
Advertisements