tf.raw_ops.SoftmaxCrossEntropyWithLogits

Computes softmax cross entropy cost and gradients to backpropagate.

Compat aliases for migration

tf.compat.v1.raw_ops.SoftmaxCrossEntropyWithLogits

tf.raw_ops.SoftmaxCrossEntropyWithLogits(
    features, labels, name=None
)

Inputs are the logits, not probabilities.

Args
`features`	A `Tensor`. Must be one of the following types: `half`, `bfloat16`, `float32`, `float64`. batch_size x num_classes matrix
`labels`	A `Tensor`. Must have the same type as `features`. batch_size x num_classes matrix The caller must ensure that each batch of labels represents a valid probability distribution.
`name`	A name for the operation (optional).

Returns
A tuple of `Tensor` objects (loss, backprop).
`loss`	A `Tensor`. Has the same type as `features`.
`backprop`	A `Tensor`. Has the same type as `features`.

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Last updated 2024-04-26 UTC.

Args