Computes softmax cross entropy cost and gradients to backpropagate.
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 .
|