tf.contrib.losses.sparse_softmax_cross_entropy
Cross-entropy loss using tf.nn.sparse_softmax_cross_entropy_with_logits
. (deprecated)
tf.contrib.losses.sparse_softmax_cross_entropy( logits, labels, weights=1.0, scope=None )
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 dtype int32 or int64 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 of logits , labels , and weights are incompatible, or if weights is None. |
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/contrib/losses/sparse_softmax_cross_entropy