tf.contrib.losses.sparse_softmax_cross_entropy(
logits,
labels,
weights=1.0,
scope=None
)
Defined in tensorflow/contrib/losses/python/losses/loss_ops.py
.
Cross-entropy loss using tf.nn.sparse_softmax_cross_entropy_with_logits
. (deprecated)
weights
acts as a coefficient for the loss. If a scalar is provided,
then the loss is simply scaled by the given value. If weights
is a
tensor of size [batch_size
], then the loss weights apply to each
corresponding sample.
Args:
logits
: [batch_size, num_classes] logits outputs of the network .labels
: [batch_size, 1] or [batch_size] labels of dtypeint32
orint64
in the range[0, num_classes)
.weights
: Coefficients for the loss. The tensor must be a scalar or a tensor of shape [batch_size] or [batch_size, 1].scope
: the scope for the operations performed in computing the loss.
Returns:
A scalar Tensor
representing the mean loss value.
Raises:
ValueError
: If the shapes oflogits
,labels
, andweights
are incompatible, or ifweights
is None.