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Support returning dictionaries in DataParallel #6113

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Merged
apaszke merged 3 commits into from
Apr 2, 2018
Merged

Support returning dictionaries in DataParallel #6113

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a43eec9
Support returning dictionaries in DataParallel
Mar 29, 2018
463102c
Ensure consistent key-value ordering
Mar 30, 2018
57b966f
Raise error on dicts with different lengths
Apr 1, 2018
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24 changes: 23 additions & 1 deletion test/test_nn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2054,6 +2054,18 @@ def test_gather_cpu(self):
def test_gather_gpu(self):
self._test_gather(0)

@unittest.skipIf(not TEST_MULTIGPU, "multi-GPU not supported")
def test_gather_different_len_dicts(self):
inputs = (
{'a': Variable(torch.randn(1, 2).cuda(0), requires_grad=True)},
{
'b': Variable(torch.randn(1, 2).cuda(1), requires_grad=True),
'a': Variable(torch.randn(1, 2).cuda(1), requires_grad=True)
}
)
with self.assertRaises(ValueError):
_ = dp.gather(inputs, target_device=0)

def _test_broadcast_double_backwards(self, *tensors):
variables = tuple(Variable(t, requires_grad=True) for t in tensors)
_assertGradAndGradgradChecks(self, lambda *i: Broadcast.apply((0, 1), *i), variables)
Expand Down Expand Up @@ -2297,7 +2309,10 @@ def test_data_parallel_sparse(self):
@unittest.skipIf(not TEST_MULTIGPU, "multi-GPU not supported")
def test_data_parallel_nested_output(self):
def fn(input):
return [input, (input.sin(), input.cos(), [input.add(1)]), input]
return [
input, (input.sin(), input.cos(), [input.add(1)]), input,
{'a': input, 'b': [input.sin()]}
]

class Net(nn.Module):
def forward(self, input):
Expand All @@ -2314,6 +2329,13 @@ def forward(self, input):
self.assertIsInstance(output[1][2], list)
self.assertIsInstance(output[1][2][0], Variable)
self.assertIsInstance(output[2], Variable)
self.assertIsInstance(output[3], dict)
self.assertEqual(len(output[3]), 2)
self.assertIn('a', output[3])
self.assertIn('b', output[3])
self.assertIsInstance(output[3]['a'], Variable)
self.assertIsInstance(output[3]['b'], list)
self.assertIsInstance(output[3]['b'][0], Variable)

@unittest.skipIf(not TEST_MULTIGPU, "multi-GPU not supported")
def test_data_parallel_nested_input(self):
Expand Down
5 changes: 5 additions & 0 deletions torch/nn/parallel/scatter_gather.py
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Original file line number Diff line number Diff line change
Expand Up @@ -57,6 +57,11 @@ def gather_map(outputs):
return Gather.apply(target_device, dim, *outputs)
if out is None:
return None
if isinstance(out, dict):
if not all((len(out) == len(d) for d in outputs)):
raise ValueError('All dicts must have the same number of keys')
return type(out)(((k, gather_map([d[k] for d in outputs]))
for k in out))
return type(out)(map(gather_map, zip(*outputs)))

# Recursive function calls like this create reference cycles.
Expand Down