Loss function
While training our neural network, we will need to calculate the loss depending on the prediction of the network, and target labels. We can simply use a function to implement the loss function equation of categorical cross-entropy.
PYTHON
1def categorical_crossentropy(target, output):
2 output /= output.sum(axis=-1, keepdims=True)
3 output = np.clip(output, 1e-7, 1 - 1e-7) # So that weights dont become 0
4 return np.sum(target * -np.log(output), axis=-1, keepdims=False)