Update model.py

model.py

@@ -59,8 +59,8 @@ class PointerNetworks(nn.Module):
         self.nnEm = nn.Embedding(self.voca_size,self.word_dim,padding_idx=2000001)
         #self.nnEm = nn.Embedding.from_pretrained(self.voc_embeddings,freeze=self.finedtuning,padding_idx=-1)
         self.initEmbeddings(self.voc_embeddings)
-        if self.use_cuda:
-            self.nnEm = self.nnEm.cuda()
+        #if self.use_cuda:
+        #    self.nnEm = self.nnEm.cuda()
 
 
 
@@ -102,17 +102,17 @@ class PointerNetworks(nn.Module):
             h_0 = Variable(torch.zeros(self.num_encoder_bi*self.num_rnn_layers, batchsize, hsize))
             c_0 = Variable(torch.zeros(self.num_encoder_bi*self.num_rnn_layers, batchsize, hsize))
 
-            if self.use_cuda:
-                h_0 = h_0.cuda()
-                c_0 = c_0.cuda()
+            #if self.use_cuda:
+            #    h_0 = h_0.cuda()
+            #    c_0 = c_0.cuda()
 
             return (h_0, c_0)
         else:
 
             h_0 = Variable(torch.zeros(self.num_encoder_bi*self.num_rnn_layers, batchsize, hsize))
 
-            if self.use_cuda:
-                h_0 = h_0.cuda()
+            #if self.use_cuda:
+            #    h_0 = h_0.cuda()
 
 
             return h_0
@@ -229,8 +229,8 @@ class PointerNetworks(nn.Module):
             #print(curX)
 
             x_index_var = Variable(torch.from_numpy(curX_index.astype(np.int64)))
-            if self.use_cuda:
-                x_index_var = x_index_var.cuda()
+            #if self.use_cuda:
+            #    x_index_var = x_index_var.cuda()
             cur_lookup = curX[x_index_var]
             #print(cur_lookup)
 
@@ -277,8 +277,8 @@ class PointerNetworks(nn.Module):
                 # TODO: make it point backward, only consider predict_range in current time step
                 # align groundtruth
                 cur_groundy_var = Variable(torch.LongTensor([int(cur_groundy) - int(cur_start_index)]))
-                if self.use_cuda:
-                    cur_groundy_var = cur_groundy_var.cuda()
+                #if self.use_cuda:
+                #    cur_groundy_var = cur_groundy_var.cuda()
 
                 curencoder_hn_back = curencoder_hn[predict_range,:]
 
@@ -395,8 +395,8 @@ class PointerNetworks(nn.Module):
 
 
                 cur_groundy_var = Variable(torch.LongTensor([max(0,int(cur_groundy) - loopstart)]))
-                if self.use_cuda:
-                    cur_groundy_var = cur_groundy_var.cuda()
+                #if self.use_cuda:
+                #    cur_groundy_var = cur_groundy_var.cuda()
 
                 batch_loss = batch_loss + loss_function(cur_logists, cur_groundy_var)