tf.keras.losses.poisson | TensorFlow v2.16.1 (original) (raw)
tf.keras.losses.poisson
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Computes the Poisson loss between y_true and y_pred.
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Main aliases
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)
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Last updated 2024-06-07 UTC.