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# Licensed under the Apache License, Version 2.0 (the "License");
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#
# http://www.apache.org/licenses/LICENSE-2.0
#
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from sparseml.tensorflow_v1.utils.helpers import tf_compat
__all__ = ["batch_cross_entropy_loss", "accuracy"]
[docs]def batch_cross_entropy_loss(
logits: tf_compat.Tensor, labels: tf_compat.Tensor
) -> tf_compat.Tensor:
"""
Standard cross entropy loss that reduces across the batch dimension.
:param logits: the logits from the model to use
:param labels: the labels to compare the logits to
:return: the cross entropy loss
"""
with tf_compat.name_scope("loss/batch_cross_entropy/"):
return tf_compat.reduce_mean(
tf_compat.nn.softmax_cross_entropy_with_logits_v2(
logits=logits, labels=labels
)
)
[docs]def accuracy(
logits: tf_compat.Tensor, labels: tf_compat.Tensor, index: int = 1
) -> tf_compat.Tensor:
"""
Standard evaluation for accuracy.
:param logits: the logits from the model to use
:param labels: the labels to compare the logits to
:param index: the index in the tensors to compare against
:return: the accuracy
"""
with tf_compat.name_scope("loss/accuracy/"):
return tf_compat.reduce_mean(
tf_compat.cast(
tf_compat.equal(
tf_compat.argmax(logits, index), tf_compat.argmax(labels, index)
),
tf_compat.float32,
)
)