- Keras Tutorial
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- Keras - Introduction
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- Keras - Convolution Neural Network
- Keras - Regression Prediction using MPL
- Keras - Time Series Prediction using LSTM RNN
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- Keras - Pre-Trained Models
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Keras - Reshape Layers
Reshape is used to change the shape of the input. For example, if reshape with argument (2,3) is applied to layer having input shape as (batch_size, 3, 2), then the output shape of the layer will be (batch_size, 2, 3)
Reshape has one argument as follows −
keras.layers.v(target_shape)
A simple example to use Reshape layers is as follows −
>>> from keras.models import Sequential >>> from keras.layers import Activation, Dense, Reshape >>> >>> >>> model = Sequential() >>> layer_1 = Dense(16, input_shape = (8,8)) >>> model.add(layer_1) >>> layer_2 = Reshape((16, 8)) >>> model.add(layer_2) >>> layer_2.input_shape (None, 8, 16) >>> layer_2.output_shape (None, 16, 8) >>>
where, (16, 8) is set as target shape.
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