tf.keras.losses.poisson

Computes the Poisson loss between y_true and y_pred.

tf.keras.losses.poisson( y_true, y_pred )

Formula:

loss = y_pred - y_true * log(y_pred)

y_true Ground truth values. shape = [batch_size, d0, .. dN].
y_pred The predicted values. shape = [batch_size, d0, .. dN].

Poisson loss values with shape = [batch_size, d0, .. dN-1].

Example:

y_true = np.random.randint(0, 2, size=(2, 3)) y_pred = np.random.random(size=(2, 3)) loss = keras.losses.poisson(y_true, y_pred) assert loss.shape == (2,) y_pred = y_pred + 1e-7 assert np.allclose(  loss, np.mean(y_pred - y_true * np.log(y_pred), axis=-1),  atol=1e-5)