update param name

models/HACNN.py

@@ -152,7 +152,7 @@ class HACNN(nn.Module):
     Reference:
     Li et al. Harmonious Attention Network for Person Re-identification. CVPR 2018.
     """
-    def __init__(self, num_classes, loss={'xent'}, nchannels=[32, 64, 96], embed_dim=512, **kwargs):
+    def __init__(self, num_classes, loss={'xent'}, nchannels=[32, 64, 96], feat_dim=512, **kwargs):
         super(HACNN, self).__init__()
         self.loss = loss
         self.conv = ConvBlock(3, 32, 3, s=2, p=1)
@@ -178,10 +178,10 @@ class HACNN(nn.Module):
         )
         self.ha3 = HarmAttn(nchannels[2]*6)
 
-        self.fc_global = nn.Sequential(nn.Linear(nchannels[2]*6, embed_dim), nn.BatchNorm1d(embed_dim), nn.ReLU())
+        self.fc_global = nn.Sequential(nn.Linear(nchannels[2]*6, feat_dim), nn.BatchNorm1d(feat_dim), nn.ReLU())
 
-        self.classifier = nn.Linear(embed_dim, num_classes)
-        self.feat_dim = embed_dim
+        self.classifier = nn.Linear(feat_dim, num_classes)
+        self.feat_dim = feat_dim
 
     def forward(self, x):
         # input size (3, 160, 64)