cuDNN errors using GRU

# on random data, using pytorch nightly

---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-7-8e0bb34a545a> in <module>
     17 
     18 
---> 19         score, y_pred1,y_pred2 = model(x1,x2) #train
     20         optimizer.zero_grad()
     21 

~\AppData\Local\Continuum\anaconda3\envs\pytorch\lib\site-packages\torch\nn\modules\module.py in __call__(self, *input, **kwargs)
    556             result = self._slow_forward(*input, **kwargs)
    557         else:
--> 558             result = self.forward(*input, **kwargs)
    559         for hook in self._forward_hooks.values():
    560             hook_result = hook(self, input, result)

<ipython-input-3-e9430b51afae> in forward(self, seq1, seq2)
     40         h1 = X1.new_zeros(self.num_layers*2,N,self.embedding_dim)
     41         h1.normal_()
---> 42         y1, _ = self.decoder(encoded1,h1)
     43         y1 =  y1[:seqLen1]
     44 

~\AppData\Local\Continuum\anaconda3\envs\pytorch\lib\site-packages\torch\nn\modules\module.py in __call__(self, *input, **kwargs)
    556             result = self._slow_forward(*input, **kwargs)
    557         else:
--> 558             result = self.forward(*input, **kwargs)
    559         for hook in self._forward_hooks.values():
    560             hook_result = hook(self, input, result)

~\AppData\Local\Continuum\anaconda3\envs\pytorch\lib\site-packages\torch\nn\modules\rnn.py in forward(self, input, hx)
    725         if batch_sizes is None:
    726             result = _VF.gru(input, hx, self._flat_weights, self.bias, self.num_layers,
--> 727                              self.dropout, self.training, self.bidirectional, self.batch_first)
    728         else:
    729             result = _VF.gru(input, batch_sizes, hx, self._flat_weights, self.bias,

RuntimeError: cuDNN error: CUDNN_STATUS_EXECUTION_FAILED

### after a few epoch

EPOCH 0, TRAINING_LOSS (2.2211820125579833, 0.09678182060993716), VALIDATION_LOSS (1.9168838739395142, 0.1996632924416813), DURATION 3.023939847946167s
EPOCH 1, TRAINING_LOSS (2.034844923019409, 0.15472564236398484), VALIDATION_LOSS (2.109210205078125, 0.28845978025577057), DURATION 3.3116555213928223s
EPOCH 2, TRAINING_LOSS (2.189433765411377, 0.3070423362611613), VALIDATION_LOSS (2.024661064147949, 0.3095052250150218), DURATION 3.024496078491211s

---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-6-8e0bb34a545a> in <module>
     17 
     18 
---> 19         score, y_pred1,y_pred2 = model(x1,x2) #train
     20         optimizer.zero_grad()
     21 

~\AppData\Local\Continuum\anaconda3\envs\pytorch\lib\site-packages\torch\nn\modules\module.py in __call__(self, *input, **kwargs)
    556             result = self._slow_forward(*input, **kwargs)
    557         else:
--> 558             result = self.forward(*input, **kwargs)
    559         for hook in self._forward_hooks.values():
    560             hook_result = hook(self, input, result)

<ipython-input-2-e9430b51afae> in forward(self, seq1, seq2)
     31         h0.normal_()
     32 
---> 33         _, last_hidden2 = self.encoder(X2,h0)
     34         encoded2 = last_hidden2[-1].repeat((len(X2),1,1))
     35 

~\AppData\Local\Continuum\anaconda3\envs\pytorch\lib\site-packages\torch\nn\modules\module.py in __call__(self, *input, **kwargs)
    556             result = self._slow_forward(*input, **kwargs)
    557         else:
--> 558             result = self.forward(*input, **kwargs)
    559         for hook in self._forward_hooks.values():
    560             hook_result = hook(self, input, result)

~\AppData\Local\Continuum\anaconda3\envs\pytorch\lib\site-packages\torch\nn\modules\rnn.py in forward(self, input, hx)
    725         if batch_sizes is None:
    726             result = _VF.gru(input, hx, self._flat_weights, self.bias, self.num_layers,
--> 727                              self.dropout, self.training, self.bidirectional, self.batch_first)
    728         else:
    729             result = _VF.gru(input, batch_sizes, hx, self._flat_weights, self.bias,

RuntimeError: cuDNN error: CUDNN_STATUS_EXECUTION_FAILED

### and this also occurs
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-6-8e0bb34a545a> in <module>
     17 
     18 
---> 19         score, y_pred1,y_pred2 = model(x1,x2) #train
     20         optimizer.zero_grad()
     21 

~\AppData\Local\Continuum\anaconda3\envs\pytorch\lib\site-packages\torch\nn\modules\module.py in __call__(self, *input, **kwargs)
    556             result = self._slow_forward(*input, **kwargs)
    557         else:
--> 558             result = self.forward(*input, **kwargs)
    559         for hook in self._forward_hooks.values():
    560             hook_result = hook(self, input, result)

<ipython-input-2-e9430b51afae> in forward(self, seq1, seq2)
     25         h0.normal_()
     26 
---> 27         _, last_hidden1 = self.encoder(X1,h0)
     28         encoded1 = last_hidden1[-1].repeat((len(X1),1,1))
     29 

~\AppData\Local\Continuum\anaconda3\envs\pytorch\lib\site-packages\torch\nn\modules\module.py in __call__(self, *input, **kwargs)
    556             result = self._slow_forward(*input, **kwargs)
    557         else:
--> 558             result = self.forward(*input, **kwargs)
    559         for hook in self._forward_hooks.values():
    560             hook_result = hook(self, input, result)

~\AppData\Local\Continuum\anaconda3\envs\pytorch\lib\site-packages\torch\nn\modules\rnn.py in forward(self, input, hx)
    725         if batch_sizes is None:
    726             result = _VF.gru(input, hx, self._flat_weights, self.bias, self.num_layers,
--> 727                              self.dropout, self.training, self.bidirectional, self.batch_first)
    728         else:
    729             result = _VF.gru(input, batch_sizes, hx, self._flat_weights, self.bias,

RuntimeError: cuDNN error: CUDNN_STATUS_INTERNAL_ERROR