tf.keras.ops.binary_crossentropy | TensorFlow v2.16.1 (original) (raw)
tf.keras.ops.binary_crossentropy
Computes binary cross-entropy loss between target and output tensor.
View aliases
Main aliases
tf.keras.ops.nn.binary_crossentropy
tf.keras.ops.binary_crossentropy(
target, output, from_logits=False
)
The binary cross-entropy loss is commonly used in binary classification tasks where each input sample belongs to one of the two classes. It measures the dissimilarity between the target and output probabilities or logits.
| Args | |
|---|---|
| target | The target tensor representing the true binary labels. Its shape should match the shape of the output tensor. |
| output | The output tensor representing the predicted probabilities or logits. Its shape should match the shape of thetarget tensor. |
| from_logits | (optional) Whether output is a tensor of logits or probabilities. Set it to True if output represents logits; otherwise, set it to False if output represents probabilities. Defaults toFalse. |
| Returns |
|---|
| Integer tensor: The computed binary cross-entropy loss betweentarget and output. |
Example:
target = keras.ops.convert_to_tensor([0, 1, 1, 0])
output = keras.ops.convert_to_tensor([0.1, 0.9, 0.8, 0.2])
binary_crossentropy(target, output)
array([0.10536054 0.10536054 0.22314355 0.22314355],
shape=(4,), dtype=float32)
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Last updated 2024-06-07 UTC.