tf.keras.losses.poisson

Computes the Poisson loss between y_true and y_pred.

View aliases

Main aliases

tf.keras.metrics.poisson

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

Formula:

loss = y_pred - y_true * log(y_pred)

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

Returns
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)