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@XiaobingSuper XiaobingSuper commented May 16, 2019

mkldnn backward ops list:

@pytorchbot pytorchbot added module: mkldnn Related to Intel IDEEP or oneDNN (a.k.a. mkldnn) integration module: operators labels May 16, 2019
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This PR depend on #20569, which adds a new ideep mul API. Thanks!

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Please first solve the issue #20895 problem, thanks!

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bddppq commented Jun 11, 2019

#20569 has been merged to master, please rebase

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@bddppq, rebased, please help review it, thanks!

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

@XiaobingSuper XiaobingSuper deleted the mkldnn_mul branch June 13, 2019 05:50
zdevito pushed a commit to zdevito/ATen that referenced this pull request Jun 13, 2019
Summary:
### mkldnn backward ops list:
 - [ ] \(pytorch/pytorch#20567) Add aten mkldnn conv2d backward operator 💛
 - [ ] \(pytorch/pytorch#20570) Add aten mkldnn backward ops: relu, linear and reshape 💛
 - [ ] \(pytorch/pytorch#20571) Add aten mkldnn backward ops: max_pool2d, avg_pool2d and adaptive_avg_poo2d 💛
 - [ ] \(pytorch/pytorch#20572) Add aten mkldnn batchnorm backward operator 💛
 - [ ] \(pytorch/pytorch#20573) Add aten mkldnn zero_ operator:yellow_heart:
 - [ ] \(pytorch/pytorch#20575) Add mkldnn mul operator 💛
Pull Request resolved: pytorch/pytorch#20575

Differential Revision: D15799529

Pulled By: bddppq

fbshipit-source-id: 4887d8ef1a0e316ad9db199b657d9481fc13e486
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@bddppq merged this pull request in b599bb3.

facebook-github-bot pushed a commit that referenced this pull request Jun 14, 2019
Summary:
### mkldnn backward ops list:
 - [ ] \(#20567) Add aten mkldnn conv2d backward operator 💛
 - [ ] \(#20570) Add aten mkldnn backward ops: relu, linear and reshape 💛
 - [ ] \(#20571) Add aten mkldnn backward ops: max_pool2d, avg_pool2d and adaptive_avg_poo2d 💛
 - [ ] \(#20572) Add aten mkldnn batchnorm backward operator 💛
 - [ ] \(#20573) Add aten mkldnn zero_ operator:yellow_heart:
 - [ ] \(#20575) Add mkldnn mul operator 💚
Pull Request resolved: #20573

Differential Revision: D15820477

Pulled By: bddppq

fbshipit-source-id: 35d95f5b4e013c8db1911f52148550a2e40a2e68
zdevito pushed a commit to zdevito/ATen that referenced this pull request Jun 14, 2019
Summary:
### mkldnn backward ops list:
 - [ ] \(pytorch/pytorch#20567) Add aten mkldnn conv2d backward operator 💛
 - [ ] \(pytorch/pytorch#20570) Add aten mkldnn backward ops: relu, linear and reshape 💛
 - [ ] \(pytorch/pytorch#20571) Add aten mkldnn backward ops: max_pool2d, avg_pool2d and adaptive_avg_poo2d 💛
 - [ ] \(pytorch/pytorch#20572) Add aten mkldnn batchnorm backward operator 💛
 - [ ] \(pytorch/pytorch#20573) Add aten mkldnn zero_ operator:yellow_heart:
 - [ ] \(pytorch/pytorch#20575) Add mkldnn mul operator 💚
Pull Request resolved: pytorch/pytorch#20573

Differential Revision: D15820477

Pulled By: bddppq

fbshipit-source-id: 35d95f5b4e013c8db1911f52148550a2e40a2e68
@VitalyFedyunin VitalyFedyunin self-requested a review October 25, 2019 14:55
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Overall looks good, but need some tests improvement.

self.assertEqual(out, mkldnn_out.to_dense())

def test_mul(self):
N = torch.randint(3, 10, (1,)).item()
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Please do not relay on random numbers. You are not freezing random seed, that means every test execution will generate new shape. It might create false sense of security, but many modern test frameworks will attempt to rerun failed test hiding problem prom developers.

Much better if you explicitly specify shapes you are interested to test.

def test_mul(self):
N = torch.randint(3, 10, (1,)).item()
C = torch.randint(3, 100, (1,)).item()
value = torch.randn(1, dtype=torch.float32).item()
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value = 1.

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