Multi-GPU Support

[calperk]

Hi,

Do you think to support Multi-GPU in the future?

Thanks.

[ZhuoranLyu]

I tried to use torch.nn.DataParallel(seq2seq_model).cuda() but it failed. It gives me this error:

`TypeError Traceback (most recent call last)
in ()
17 batch_label = batch_label.cuda()
18
---> 19 decoder_outputs, decoder_hidden, other = seq2seq_model(batch_data, input_lengths = None, target_variable = batch_label,teacher_forcing_ratio=0.8)
20
21 learning_rate = 1e-4

~/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py in call(self, *input, **kwargs)
489 result = self._slow_forward(*input, **kwargs)
490 else:
--> 491 result = self.forward(*input, **kwargs)
492 for hook in self._forward_hooks.values():
493 hook_result = hook(self, input, result)

~/anaconda3/lib/python3.6/site-packages/torch/nn/parallel/data_parallel.py in forward(self, *inputs, **kwargs)
113 replicas = self.replicate(self.module, self.device_ids[:len(inputs)])
114 outputs = self.parallel_apply(replicas, inputs, kwargs)
--> 115 return self.gather(outputs, self.output_device)
116
117 def replicate(self, module, device_ids):

~/anaconda3/lib/python3.6/site-packages/torch/nn/parallel/data_parallel.py in gather(self, outputs, output_device)
125
126 def gather(self, outputs, output_device):
--> 127 return gather(outputs, output_device, dim=self.dim)
128
129

~/anaconda3/lib/python3.6/site-packages/torch/nn/parallel/scatter_gather.py in gather(outputs, target_device, dim)
66 # Setting the function to None clears the refcycle.
67 try:
---> 68 return gather_map(outputs)
69 finally:
70 gather_map = None

~/anaconda3/lib/python3.6/site-packages/torch/nn/parallel/scatter_gather.py in gather_map(outputs)
61 return type(out)(((k, gather_map([d[k] for d in outputs]))
62 for k in out))
---> 63 return type(out)(map(gather_map, zip(*outputs)))
64
65 # Recursive function calls like this create reference cycles.

~/anaconda3/lib/python3.6/site-packages/torch/nn/parallel/scatter_gather.py in gather_map(outputs)
60 raise ValueError('All dicts must have the same number of keys')
61 return type(out)(((k, gather_map([d[k] for d in outputs]))
---> 62 for k in out))
63 return type(out)(map(gather_map, zip(*outputs)))
64

~/anaconda3/lib/python3.6/site-packages/torch/nn/parallel/scatter_gather.py in (.0)
60 raise ValueError('All dicts must have the same number of keys')
61 return type(out)(((k, gather_map([d[k] for d in outputs]))
---> 62 for k in out))
63 return type(out)(map(gather_map, zip(*outputs)))
64

~/anaconda3/lib/python3.6/site-packages/torch/nn/parallel/scatter_gather.py in gather_map(outputs)
61 return type(out)(((k, gather_map([d[k] for d in outputs]))
62 for k in out))
---> 63 return type(out)(map(gather_map, zip(*outputs)))
64
65 # Recursive function calls like this create reference cycles.

~/anaconda3/lib/python3.6/site-packages/torch/nn/parallel/scatter_gather.py in gather_map(outputs)
61 return type(out)(((k, gather_map([d[k] for d in outputs]))
62 for k in out))
---> 63 return type(out)(map(gather_map, zip(*outputs)))
64
65 # Recursive function calls like this create reference cycles.

TypeError: zip argument #1 must support iteration`

Any suggestions?

Thanks