mirror of https://github.com/JDAI-CV/fast-reid.git
37 lines
1.0 KiB
Python
37 lines
1.0 KiB
Python
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# encoding: utf-8
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"""
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@author: xingyu liao
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@contact: sherlockliao01@gmail.com
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"""
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import torch.nn.functional as F
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from fastreid.modeling.heads import REID_HEADS_REGISTRY, EmbeddingHead
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@REID_HEADS_REGISTRY.register()
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class ClasHead(EmbeddingHead):
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def forward(self, features, targets=None):
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"""
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See :class:`ClsHeads.forward`.
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"""
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pool_feat = self.pool_layer(features)
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neck_feat = self.bottleneck(pool_feat)
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neck_feat = neck_feat.view(neck_feat.size(0), -1)
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if self.cls_layer.__class__.__name__ == 'Linear':
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logits = F.linear(neck_feat, self.weight)
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else:
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logits = F.linear(F.normalize(neck_feat), F.normalize(self.weight))
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# Evaluation
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if not self.training: return logits * self.cls_layer.s
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cls_outputs = self.cls_layer(logits, targets)
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return {
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"cls_outputs": cls_outputs,
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"pred_class_logits": logits * self.cls_layer.s,
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"features": neck_feat,
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}
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