cleanup

kim/nn.py

@@ -425,7 +425,7 @@ def forward(self, X, h0=None):
             hiddens = [init.zeros(bs, self.hidden_size, device=self.device) for _ in range(self.num_layers)]
         else:
             assert list(h0.shape) == [self.num_layers, bs, self.hidden_size]
-            hiddens = list(ops.split(h0, 0).detach())
+            hiddens = list(ops.split(h0, 0))
 
         # Init outputs from X
         outputs = [ Tensor(X.realize_cached_data()[i,:,:].reshape((bs, input_size)).compact(), device=self.device)
@@ -443,7 +443,6 @@ def forward(self, X, h0=None):
         assert outputs[-1] == hiddens[-1]
 
         return ops.stack(outputs, 0), ops.stack(hiddens, 0)
-        # Tham khảo https://pytorch.org/docs/stable/generated/torch.nn.RNN.html
 
 
 class LSTMCell(Module):

run.sh

@@ -26,13 +26,13 @@
 
 BACKEND_DEVICE=cuda python3 -m mugrade submit _r1VOvEAgPZvLXFJ18agr -k "resnet9"
 python3 -m mugrade submit _r1VOvEAgPZvLXFJ18agr -k "rnn"
-python3 -m pytest -k "test_rnn and relu and cuda"
+python3 -m pytest -k "test_rnn[cuda-relu-False-False-12-11-1-1-13]"
 
 python3 -m mugrade submit _r1VOvEAgPZvLXFJ18agr -k "lstm"
-python3 -m pytest -k "lstm_cell and cpu-False-False-12-1-15"
-python3 -m pytest -k "test_lstm[cuda-False-False-12-11-15-2-13]"
+python3 -m pytest -k "lstm_cell and cuda-False-False-12-1-15"
 python3 -m pytest -k "test_lstm"
-python3 -m pytest -k "test_lstm[cuda-True-True-1-1-1-1-13]" # bị hang
+python3 -m pytest -k "test_lstm[cuda-False-False-12-11-15-2-13]"
+python3 -m pytest -k "test_lstm[cuda-True-True-1-1-1-1-13]"
 
 python3 -m mugrade submit _r1VOvEAgPZvLXFJ18agr -k "ptb"
 python3 -m pytest -l -v -k "ptb_dataset"