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Keras Sample Weight Generator

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Keras Sample Weight Generator


Keras Sample Weight Generator. Returns a generator — as well as the number of step per epoch — which is given to fit. Create a balanced batch generator to train keras model.

Ensemble Neural Network Model Weights In Keras Polyak Averaging
Ensemble Neural Network Model Weights In Keras Polyak Averaging from machinelearningmastery.com
You may have noticed that our first basic example didn't make any mention of sample weighting. From keras.models import model from keras.layers import input, dense a = input(shape=(32,)) b = dense(32)(a). Our goal will be to implement a keras generator capable of training a.

Our goal will be to implement a keras generator capable of training a.

Import numpy as np import keras import librosa from time. Numpy array of weights for the training samples, used for scaling the loss function (during training only). You may have noticed that our first basic example didn't make any mention of sample weighting. Typically you will use metrics='accuracy'.