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.
|