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author | Jordan Gong <jordan.gong@protonmail.com> | 2021-04-10 22:38:23 +0800 |
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committer | Jordan Gong <jordan.gong@protonmail.com> | 2021-04-10 22:38:23 +0800 |
commit | f7df51490f9c3cc932672493e6c91595686df9ce (patch) | |
tree | 04975117a0f4a6b0d559a38091aba1db51a7a048 /models/part_net.py | |
parent | 5e00cd7de1729db12329e793a4e84b6c7900a948 (diff) | |
parent | 20110729ab450c84d90965f5b8930236035f093a (diff) |
Merge branch 'python3.8' into python3.7python3.7
Diffstat (limited to 'models/part_net.py')
-rw-r--r-- | models/part_net.py | 20 |
1 files changed, 12 insertions, 8 deletions
diff --git a/models/part_net.py b/models/part_net.py index de19c8c..06884e9 100644 --- a/models/part_net.py +++ b/models/part_net.py @@ -128,23 +128,27 @@ class PartNet(nn.Module): torch.empty(num_parts, in_channels, embedding_dims) ) - def forward(self, x): + def _horizontal_pool(self, x): n, t, c, h, w = x.size() x = x.view(n * t, c, h, w) - # n * t x c x h x w - - # Horizontal Pooling - _, c, h, w = x.size() split_size = h // self.num_part x = x.split(split_size, dim=2) x = [self.avg_pool(x_) + self.max_pool(x_) for x_ in x] x = [x_.view(n, t, c) for x_ in x] x = torch.stack(x) + return x + def forward(self, f_c1_t2, f_c2_t2=None): + # n, t, c, h, w + f_c1_t2_ = self._horizontal_pool(f_c1_t2) # p, n, t, c - x = self.tfa(x) - + x = self.tfa(f_c1_t2_) # p, n, c x = x @ self.fc_mat # p, n, d - return x + + if self.training: + f_c2_t2_ = self._horizontal_pool(f_c2_t2) + return x, (f_c1_t2_, f_c2_t2_) + else: + return x |