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| from caffe2.python import schema |
| from caffe2.python.layers.layers import ModelLayer |
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|
| class Dropout(ModelLayer): |
|
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| def __init__( |
| self, |
| model, |
| input_record, |
| name='dropout', |
| ratio=0.5, |
| dropout_for_eval=False, |
| **kwargs): |
|
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| super(Dropout, self).__init__(model, name, input_record, **kwargs) |
| assert isinstance(input_record, schema.Scalar), "Incorrect input type" |
| assert (ratio >= 0 and ratio < 1.0), \ |
| "Expected 0 <= ratio < 1, but got ratio of %s" % ratio |
|
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| self.output_schema = input_record.clone_schema() |
| self.output_schema.set_value(self.get_next_blob_reference('output')) |
| self.dropout_for_eval = dropout_for_eval |
|
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| self.ratio = ratio |
|
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| def _add_ops(self, net, is_test): |
| input_blob = self.input_record.field_blobs() |
| output_blobs = self.output_schema.field_blobs() \ |
| + [net.NextScopedBlob('d_mask')] |
|
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| net.Dropout(input_blob, |
| output_blobs, |
| ratio=self.ratio, |
| is_test=is_test) |
|
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| def add_train_ops(self, net): |
| self._add_ops(net, is_test=False) |
|
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| def add_eval_ops(self, net): |
| self._add_ops(net, is_test=(not self.dropout_for_eval)) |
|
|
| def add_ops(self, net): |
| self.add_eval_ops(net) |
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|
