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@pytorchbot retest this please

@vishwakftw
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I believe there are some instances of the same case in nn/parallel/distributed.py and nn/parallel/distributed_c10d.py. Could those be changed too?

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@vishwakftw I see, I will change them as well

test/test_nn.py Outdated
# test output_device
l = nn.Linear(10, 5).float().cuda()
i = Variable(torch.randn(20, 10).float().cuda())
out = dp.data_parallel(l, i, (0, 1), torch.device('cuda'))

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@weiyangfb weiyangfb added the ready for review (this tag is deprecated) All PRs are ready for review unless they are draft, WIP, or have undismissed requested changes label Aug 14, 2018
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This looks good to me.

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li-roy commented Aug 16, 2018

actually, can we add a test for the other two code paths as well?

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The better fix is to make scatter, gather, parallel_apply, etc. to accept device objects (vs. converting to idx in DP). You can also make device_ids to support device objects this way.

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fmassa commented Aug 28, 2018

ping @weiyangfb on @ssnl suggestion.

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ssnl commented Aug 28, 2018

you can probably use/adapt torch.cuda._get_device_index now to do that after #10833 .

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weiyangfb has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator.

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is this good to go? @ssnl

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is this good to go? @ssnl @teng-li @ailzhang

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test/test_nn.py Outdated

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@ssnl would you like to take quick pass on this? The updates are separated test function and doc fixes. Thanks!

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lgtm, but there is one remaining nit to be addressed

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@ssnl I see, fixed more places with Device -> torch.device

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…d APIs

1. convert torch.device to device.index in APIs
2. docs fixes
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torch.device and torch.nn.parallel.data_parallel compatibility

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