tf.contrib.losses.sparse_softmax_cross_entropy()

tf.contrib.losses.sparse_softmax_cross_entropy(logits, labels, weight=1.0, scope=None)

Cross-entropy loss using tf.nn.sparse_softmax_cross_entropy_with_logits.

weight acts as a coefficient for the loss. If a scalar is provided, then the loss is simply scaled by the given value. If weight 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] target labels of dtype int32 or int64 in the range [0, num_classes).
• weight: 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 loss value.

Raises:

• ValueError: If the shapes of logits, labels, and weight are incompatible, or if weight is None.