Remove debug comments

examples/ncf/neumf.py

@@ -75,8 +75,6 @@ class NeuMF(nn.Module):
             lecunn_uniform(self.final_mlp)
             lecunn_uniform(self.final_mf)
 
-        # self.post_embed_device = torch.device('cpu')
-
     def load_state_dict(self, state_dict, strict=True):
         if 'final.weight' in state_dict and self.split_final:
             # Loading no-split checkpoint into split model
@@ -99,53 +97,24 @@ class NeuMF(nn.Module):
         super(NeuMF, self).load_state_dict(state_dict, strict)
 
     def forward(self, user, item, sigmoid):
-        xmfu = self.mf_user_embed(user)  # .to(self.post_embed_device)
-        xmfi = self.mf_item_embed(item)  # .to(self.post_embed_device)
+        xmfu = self.mf_user_embed(user)
+        xmfi = self.mf_item_embed(item)
         xmf = self.mf_mult(xmfu, xmfi)
-        # @DEBUG
-        # np.save(os.path.join(msglogger.logdir, 'mf_mult'), xmf.cpu().detach().numpy())
 
-        xmlpu = self.mlp_user_embed(user)  # .to(self.post_embed_device)
-        xmlpi = self.mlp_item_embed(item)  # .to(self.post_embed_device)
+        xmlpu = self.mlp_user_embed(user)
+        xmlpi = self.mlp_item_embed(item)
         xmlp = self.mlp_concat(xmlpu, xmlpi)
-        # @DEBUG
-        # np.save(os.path.join(msglogger.logdir, 'mlp_concat'), xmlp.cpu().detach().numpy())
         for i, (layer, act) in enumerate(zip(self.mlp, self.mlp_relu)):
             xmlp = layer(xmlp)
-            # @DEBUG
-            # np.save(os.path.join(msglogger.logdir, 'mlp.{}'.format(i)), xmlp.detach().cpu().numpy())
             xmlp = act(xmlp)
-            # @DEBUG
-            # np.save(os.path.join(msglogger.logdir, 'mlp_relu.{}'.format(i)), xmlp.detach().cpu().numpy())
 
         if not self.split_final:
             x = self.final_concat(xmf, xmlp)
             x = self.final(x)
         else:
             xmf = self.final_mf(xmf)
-            # @DEBUG
-            # np.save(os.path.join(msglogger.logdir, 'final_mf'), xmf.detach().cpu().numpy())
             xmlp = self.final_mlp(xmlp)
-            # @DEBUG
-            # np.save(os.path.join(msglogger.logdir, 'final_mlp'), xmlp.detach().cpu().numpy())
             x = self.final_add(xmf, xmlp)
-            # @DEBUG
-            # np.save(os.path.join(msglogger.logdir, 'final_add'), x.detach().cpu().numpy())
         if sigmoid:
             x = self.sigmoid(x)
         return x
-
-    # def to_cuda(self, device=None, embeds_on_gpu=True):
-    #     self.post_embed_device = device if device is not None else torch.device('cuda')
-    #
-    #     if embeds_on_gpu:
-    #         return self.cuda(device=device)
-    #
-    #     for m in self.modules():
-    #         if isinstance(m, nn.Embedding):
-    #             m.cpu()
-    #         else:
-    #             m.cuda(device=device)
-    #
-    #     return self
-