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93a4b76114
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/12178 Fisher GAN calls processor_util.add_mlp, which inject the layer norm through the normalizer. We allow to use alternative impl for LayerNorn in the normalizer. Reviewed By: Wakeupbuddy Differential Revision: D9235528 fbshipit-source-id: 88c126c658102926613242ef84a481f6de1676ed
43 lines
1.2 KiB
Python
43 lines
1.2 KiB
Python
# @package optimizer
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# Module caffe2.python.normalizer
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from __future__ import absolute_import, division, print_function, unicode_literals
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class Normalizer(object):
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def __init__(self):
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pass
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"""
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Adds normalization to train_net for given parameter. Its factor ahead of
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regularization is given when initialization.
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The param should be a BlobReference.
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"""
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def __call__(self, net, param):
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return self._run(net, param)
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def _run(self, net, param):
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raise Exception("Not Impelemented")
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class BatchNormalizer(Normalizer):
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def __init__(self, momentum):
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super(BatchNormalizer, self).__init__()
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self._momentum = float(momentum)
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def _run(self, layer_model, param):
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return layer_model.BatchNormalization(
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param, momentum=self._momentum
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)
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class LayerNormalizer(Normalizer):
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def __init__(self, epsilon, use_layer_norm_op=True):
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super(LayerNormalizer, self).__init__()
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self._epsilon = float(epsilon)
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self._use_layer_norm_op = use_layer_norm_op
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def _run(self, layer_model, param):
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return layer_model.LayerNormalization(
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param, epsilon=self._epsilon, use_layer_norm_op=self._use_layer_norm_op
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)
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