tf.raw_ops.SoftmaxCrossEntropyWithLogits

Computes softmax cross entropy cost and gradients to backpropagate.

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Compat aliases for migration

See Migration guide for more details.

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.