tf.keras.losses.Dice
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Computes the Dice loss value between y_true
and y_pred
.
Inherits From: Loss
tf.keras.losses.Dice(
reduction='sum_over_batch_size', name='dice'
)
loss = 1 - (2 * sum(y_true * y_pred)) / (sum(y_true) + sum(y_pred))
Args |
y_true
|
tensor of true targets.
|
y_pred
|
tensor of predicted targets.
|
Methods
call
View source
call(
y_true, y_pred
)
from_config
View source
@classmethod
from_config(
config
)
get_config
View source
get_config()
__call__
View source
__call__(
y_true, y_pred, sample_weight=None
)
Call self as a function.
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Last updated 2024-06-07 UTC.
[null,null,["Last updated 2024-06-07 UTC."],[],[],null,["# tf.keras.losses.Dice\n\n\u003cbr /\u003e\n\n|-----------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/keras-team/keras/tree/v3.3.3/keras/src/losses/losses.py#L1947-L1979) |\n\nComputes the Dice loss value between `y_true` and `y_pred`.\n\nInherits From: [`Loss`](../../../tf/keras/Loss) \n\n tf.keras.losses.Dice(\n reduction='sum_over_batch_size', name='dice'\n )\n\n#### Formula:\n\n loss = 1 - (2 * sum(y_true * y_pred)) / (sum(y_true) + sum(y_pred))\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|----------|------------------------------|\n| `y_true` | tensor of true targets. |\n| `y_pred` | tensor of predicted targets. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| Dice loss value. ||\n\n\u003cbr /\u003e\n\nMethods\n-------\n\n### `call`\n\n[View source](https://github.com/keras-team/keras/tree/v3.3.3/keras/src/losses/losses.py#L20-L22) \n\n call(\n y_true, y_pred\n )\n\n### `from_config`\n\n[View source](https://github.com/keras-team/keras/tree/v3.3.3/keras/src/losses/losses.py#L30-L34) \n\n @classmethod\n from_config(\n config\n )\n\n### `get_config`\n\n[View source](https://github.com/keras-team/keras/tree/v3.3.3/keras/src/losses/losses.py#L1975-L1979) \n\n get_config()\n\n### `__call__`\n\n[View source](https://github.com/keras-team/keras/tree/v3.3.3/keras/src/losses/loss.py#L32-L61) \n\n __call__(\n y_true, y_pred, sample_weight=None\n )\n\nCall self as a function."]]