softmax_cross_entropy_with_logits¶

dragon.vm.tensorflow.nn.softmax_cross_entropy_with_logits(
  labels,
  logits,
  name=None
)[source]¶

Compute the loss of softmax cross entropy.

Examples:

labels = tf.constant([[0., 1., ], [1., 0.]], dtype=tf.float32)
logits = tf.constant([[0.5, 0.5], [0.3, 0.7]], dtype=tf.float32)
print(tf.nn.softmax_cross_entropy_with_logits(labels, logits))  # [0.6931472, 0.9130153]

Parameters:

• labels (dragon.Tensor) – The label tensor.
• logits (dragon.Tensor) – The logit tensor.
• name (str, optional) – The operation name.

Returns:

dragon.Tensor – The output tensor.