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Computes binary cross-entropy loss between target and output tensor.
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.
Returns | |
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Integer tensor: The computed binary cross-entropy loss between
target 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)