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How do you create a custom activation function with Keras?

Credits to this Github issue comment by Ritchie Ng. # Creating a model from keras.models import Sequential from keras.layers import Dense # Custom activation function from keras.layers import Activation from keras import backend as K from keras.utils.generic_utils import get_custom_objects def custom_activation(x): return (K.sigmoid(x) * 5) – 1 get_custom_objects().update({‘custom_activation’: Activation(custom_activation)}) # Usage model = Sequential() model.add(Dense(32, … Read more

Keras input explanation: input_shape, units, batch_size, dim, etc

Units: The amount of “neurons”, or “cells”, or whatever the layer has inside it. It’s a property of each layer, and yes, it’s related to the output shape (as we will see later). In your picture, except for the input layer, which is conceptually different from other layers, you have: Hidden layer 1: 4 units … Read more

Keras Dense layer’s input is not flattened

Currently, contrary to what has been stated in documentation, the Dense layer is applied on the last axis of input tensor: Contrary to the documentation, we don’t actually flatten it. It’s applied on the last axis independently. In other words, if a Dense layer with m units is applied on an input tensor of shape … Read more