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|
| | from caffe2.python import schema |
| | from caffe2.python.layers.layers import ModelLayer |
| |
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| |
|
| | class Dropout(ModelLayer): |
| |
|
| | def __init__( |
| | self, |
| | model, |
| | input_record, |
| | name='dropout', |
| | ratio=0.5, |
| | dropout_for_eval=False, |
| | **kwargs): |
| |
|
| | 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 |
| |
|
| | 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 |
| |
|
| | self.ratio = ratio |
| |
|
| | 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')] |
| |
|
| | net.Dropout(input_blob, |
| | output_blobs, |
| | ratio=self.ratio, |
| | is_test=is_test) |
| |
|
| | def add_train_ops(self, net): |
| | self._add_ops(net, is_test=False) |
| |
|
| | 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) |
| |
|
