Unknown activation function: leaky_relu

Leaky ReLU is an activation function commonly used in neural networks. It is similar to the ReLU activation function, but instead of setting all negative values to zero, it sets them to a small constant value (usually 0.01 times the input) to prevent the "dying ReLU" problem.

Here is an implementation of Leaky ReLU in Python using the NumPy library:

import numpy as np

def leaky_relu(x):
    return np.maximum(0.01*x, x)

You can use this function as an activation function in a neural network by passing it to the appropriate layer, such as a Dense layer in Keras:

from keras.layers import Dense
from keras.models import Sequential

model = Sequential()
model.add(Dense(32, activation=leaky_relu, input_shape=(input_dim,)))