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Fix rand/randn bug #7914

Merged
merged 46 commits into from
Apr 3, 2022
Merged

Fix rand/randn bug #7914

merged 46 commits into from
Apr 3, 2022

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BBuf
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@BBuf BBuf commented Mar 28, 2022 •
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fix rand and randn tuple input bug.

BBuf
BBuf commented Mar 28, 2022
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python/oneflow/nn/modules/random_ops.py
@@ -146,50 +146,6 @@ def rand_op(
)


class RandN(Module):
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这个类过时了，已经迁移到Functor了，这里去掉。

@BBuf BBuf requested a review from oneflow-ci-bot March 28, 2022 09:00
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Code got formatted by CI. Please request CI again if you still want to have this PR merged. If the PR is from a forked repo, please download the patch files from the GitHub Actions web page and apply them locally.

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Code got formatted by CI. Please request CI again if you still want to have this PR merged. If the PR is from a forked repo, please download the patch files from the GitHub Actions web page and apply them locally.

@oneflow-ci-bot oneflow-ci-bot requested review from oneflow-ci-bot and removed request for oneflow-ci-bot March 28, 2022 11:32
@BBuf BBuf added the automerge label Apr 1, 2022
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github-actions bot commented Apr 1, 2022

View latest API docs preview at: https://staging.oneflow.info/docs/Oneflow-Inc/oneflow/pr/7914/

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github-actions bot commented Apr 1, 2022

Speed stats: 
GPU Name: GeForce GTX 1080 

✔️ OneFlow resnet50 time: 128.5ms (= 12851.2ms / 100, input_shape=[16, 3, 224, 224])
PyTorch resnet50 time: 139.7ms (= 13968.4ms / 100, input_shape=[16, 3, 224, 224])
✔️ Relative speed: 1.09 (= 139.7ms / 128.5ms)

✔️ OneFlow resnet50 time: 79.0ms (= 7903.1ms / 100, input_shape=[8, 3, 224, 224])
PyTorch resnet50 time: 85.5ms (= 8547.8ms / 100, input_shape=[8, 3, 224, 224])
✔️ Relative speed: 1.08 (= 85.5ms / 79.0ms)

OneFlow resnet50 time: 52.8ms (= 10555.0ms / 200, input_shape=[4, 3, 224, 224])
PyTorch resnet50 time: 61.0ms (= 12194.6ms / 200, input_shape=[4, 3, 224, 224])
✔️ Relative speed: 1.16 (= 61.0ms / 52.8ms)

OneFlow resnet50 time: 41.1ms (= 8216.9ms / 200, input_shape=[2, 3, 224, 224])
PyTorch resnet50 time: 49.1ms (= 9815.9ms / 200, input_shape=[2, 3, 224, 224])
✔️ Relative speed: 1.19 (= 49.1ms / 41.1ms)

OneFlow resnet50 time: 40.0ms (= 8004.2ms / 200, input_shape=[1, 3, 224, 224])
PyTorch resnet50 time: 38.7ms (= 7744.8ms / 200, input_shape=[1, 3, 224, 224])
✔️ Relative speed: 0.97 (= 38.7ms / 40.0ms)

OneFlow swin dataloader time: 0.248s (= 49.691s / 200, num_workers=1)
PyTorch swin dataloader time: 0.251s (= 50.194s / 200, num_workers=1)
✔️ Relative speed: 1.010 (= 0.251s / 0.248s)

OneFlow swin dataloader time: 0.064s (= 12.788s / 200, num_workers=4)
PyTorch swin dataloader time: 0.067s (= 13.384s / 200, num_workers=4)
✔️ Relative speed: 1.047 (= 0.067s / 0.064s)

OneFlow swin dataloader time: 0.037s (= 7.438s / 200, num_workers=8)
PyTorch swin dataloader time: 0.038s (= 7.532s / 200, num_workers=8)
✔️ Relative speed: 1.013 (= 0.038s / 0.037s)

✔️ OneFlow resnet50 time: 135.6ms (= 13557.0ms / 100, input_shape=[16, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 156.7ms (= 15669.5ms / 100, input_shape=[16, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.16 (= 156.7ms / 135.6ms)

OneFlow resnet50 time: 89.2ms (= 8921.0ms / 100, input_shape=[8, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 101.4ms (= 10138.9ms / 100, input_shape=[8, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.14 (= 101.4ms / 89.2ms)

OneFlow resnet50 time: 62.7ms (= 12533.4ms / 200, input_shape=[4, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 77.7ms (= 15536.9ms / 200, input_shape=[4, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.24 (= 77.7ms / 62.7ms)

OneFlow resnet50 time: 52.1ms (= 10421.9ms / 200, input_shape=[2, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 67.3ms (= 13457.8ms / 200, input_shape=[2, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.29 (= 67.3ms / 52.1ms)

OneFlow resnet50 time: 51.6ms (= 10318.0ms / 200, input_shape=[1, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 64.0ms (= 12795.3ms / 200, input_shape=[1, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.24 (= 64.0ms / 51.6ms)

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github-actions bot commented Apr 1, 2022

CI failed when running job: cpu-module. PR label automerge has been removed

@github-actions github-actions bot removed the automerge label Apr 1, 2022
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github-actions bot commented Apr 2, 2022

Code got formatted by CI. Please request CI again if you still want to have this PR merged. If the PR is from a forked repo, please download the patch files from the GitHub Actions web page and apply them locally.

@BBuf BBuf requested review from oneflow-ci-bot and removed request for oneflow-ci-bot April 2, 2022 01:22
@BBuf BBuf added the automerge label Apr 2, 2022
@BBuf BBuf changed the title Fix randn bug Fix rand/randn bug Apr 2, 2022
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github-actions bot commented Apr 2, 2022

Speed stats: 
GPU Name: GeForce GTX 1080 

✔️ OneFlow resnet50 time: 128.5ms (= 12850.9ms / 100, input_shape=[16, 3, 224, 224])
PyTorch resnet50 time: 140.7ms (= 14074.7ms / 100, input_shape=[16, 3, 224, 224])
✔️ Relative speed: 1.10 (= 140.7ms / 128.5ms)

❌ OneFlow resnet50 time: 82.0ms (= 8199.6ms / 100, input_shape=[8, 3, 224, 224])
PyTorch resnet50 time: 87.4ms (= 8743.0ms / 100, input_shape=[8, 3, 224, 224])
✔️ Relative speed: 1.07 (= 87.4ms / 82.0ms)

OneFlow resnet50 time: 54.4ms (= 10881.3ms / 200, input_shape=[4, 3, 224, 224])
PyTorch resnet50 time: 63.8ms (= 12769.5ms / 200, input_shape=[4, 3, 224, 224])
✔️ Relative speed: 1.17 (= 63.8ms / 54.4ms)

OneFlow resnet50 time: 42.0ms (= 8403.8ms / 200, input_shape=[2, 3, 224, 224])
PyTorch resnet50 time: 52.2ms (= 10447.3ms / 200, input_shape=[2, 3, 224, 224])
✔️ Relative speed: 1.24 (= 52.2ms / 42.0ms)

OneFlow resnet50 time: 38.9ms (= 7773.8ms / 200, input_shape=[1, 3, 224, 224])
PyTorch resnet50 time: 44.0ms (= 8795.5ms / 200, input_shape=[1, 3, 224, 224])
✔️ Relative speed: 1.13 (= 44.0ms / 38.9ms)

OneFlow swin dataloader time: 0.268s (= 53.589s / 200, num_workers=1)
PyTorch swin dataloader time: 0.255s (= 51.013s / 200, num_workers=1)
✔️ Relative speed: 0.952 (= 0.255s / 0.268s)

OneFlow swin dataloader time: 0.067s (= 13.365s / 200, num_workers=4)
PyTorch swin dataloader time: 0.070s (= 13.992s / 200, num_workers=4)
✔️ Relative speed: 1.047 (= 0.070s / 0.067s)

OneFlow swin dataloader time: 0.037s (= 7.302s / 200, num_workers=8)
PyTorch swin dataloader time: 0.040s (= 8.023s / 200, num_workers=8)
✔️ Relative speed: 1.099 (= 0.040s / 0.037s)

✔️ OneFlow resnet50 time: 135.9ms (= 13590.0ms / 100, input_shape=[16, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 159.1ms (= 15912.3ms / 100, input_shape=[16, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.17 (= 159.1ms / 135.9ms)

OneFlow resnet50 time: 89.2ms (= 8918.3ms / 100, input_shape=[8, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 103.3ms (= 10333.8ms / 100, input_shape=[8, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.16 (= 103.3ms / 89.2ms)

OneFlow resnet50 time: 62.4ms (= 12479.9ms / 200, input_shape=[4, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 87.1ms (= 17412.4ms / 200, input_shape=[4, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.40 (= 87.1ms / 62.4ms)

OneFlow resnet50 time: 55.6ms (= 11128.1ms / 200, input_shape=[2, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 67.4ms (= 13470.7ms / 200, input_shape=[2, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.21 (= 67.4ms / 55.6ms)

OneFlow resnet50 time: 46.2ms (= 9239.1ms / 200, input_shape=[1, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 62.8ms (= 12568.5ms / 200, input_shape=[1, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.36 (= 62.8ms / 46.2ms)

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github-actions bot commented Apr 2, 2022

CI failed when running job: cuda-speed-test. PR label automerge has been removed

@github-actions github-actions bot removed the automerge label Apr 2, 2022
@BBuf BBuf added the automerge label Apr 2, 2022
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github-actions bot commented Apr 3, 2022

Speed stats: 
GPU Name: GeForce GTX 1080 

✔️ OneFlow resnet50 time: 128.4ms (= 12843.6ms / 100, input_shape=[16, 3, 224, 224])
PyTorch resnet50 time: 141.1ms (= 14105.7ms / 100, input_shape=[16, 3, 224, 224])
✔️ Relative speed: 1.10 (= 141.1ms / 128.4ms)

✔️ OneFlow resnet50 time: 79.9ms (= 7990.0ms / 100, input_shape=[8, 3, 224, 224])
PyTorch resnet50 time: 85.6ms (= 8563.4ms / 100, input_shape=[8, 3, 224, 224])
✔️ Relative speed: 1.07 (= 85.6ms / 79.9ms)

OneFlow resnet50 time: 53.6ms (= 10714.6ms / 200, input_shape=[4, 3, 224, 224])
PyTorch resnet50 time: 55.0ms (= 11007.6ms / 200, input_shape=[4, 3, 224, 224])
✔️ Relative speed: 1.03 (= 55.0ms / 53.6ms)

OneFlow resnet50 time: 43.2ms (= 8642.1ms / 200, input_shape=[2, 3, 224, 224])
PyTorch resnet50 time: 48.4ms (= 9672.1ms / 200, input_shape=[2, 3, 224, 224])
✔️ Relative speed: 1.12 (= 48.4ms / 43.2ms)

OneFlow resnet50 time: 40.3ms (= 8055.7ms / 200, input_shape=[1, 3, 224, 224])
PyTorch resnet50 time: 41.2ms (= 8232.8ms / 200, input_shape=[1, 3, 224, 224])
✔️ Relative speed: 1.02 (= 41.2ms / 40.3ms)

OneFlow swin dataloader time: 0.251s (= 50.241s / 200, num_workers=1)
PyTorch swin dataloader time: 0.249s (= 49.877s / 200, num_workers=1)
✔️ Relative speed: 0.993 (= 0.249s / 0.251s)

OneFlow swin dataloader time: 0.072s (= 14.493s / 200, num_workers=4)
PyTorch swin dataloader time: 0.071s (= 14.166s / 200, num_workers=4)
✔️ Relative speed: 0.977 (= 0.071s / 0.072s)

OneFlow swin dataloader time: 0.037s (= 7.311s / 200, num_workers=8)
PyTorch swin dataloader time: 0.037s (= 7.303s / 200, num_workers=8)
✔️ Relative speed: 0.999 (= 0.037s / 0.037s)

✔️ OneFlow resnet50 time: 135.4ms (= 13540.6ms / 100, input_shape=[16, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 156.2ms (= 15618.5ms / 100, input_shape=[16, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.15 (= 156.2ms / 135.4ms)

OneFlow resnet50 time: 89.8ms (= 8980.6ms / 100, input_shape=[8, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 104.7ms (= 10470.0ms / 100, input_shape=[8, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.17 (= 104.7ms / 89.8ms)

OneFlow resnet50 time: 61.8ms (= 12358.6ms / 200, input_shape=[4, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 77.1ms (= 15414.7ms / 200, input_shape=[4, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.25 (= 77.1ms / 61.8ms)

OneFlow resnet50 time: 51.7ms (= 10341.2ms / 200, input_shape=[2, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 66.2ms (= 13249.6ms / 200, input_shape=[2, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.28 (= 66.2ms / 51.7ms)

OneFlow resnet50 time: 50.6ms (= 10110.5ms / 200, input_shape=[1, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 69.4ms (= 13882.6ms / 200, input_shape=[1, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.37 (= 69.4ms / 50.6ms)

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github-actions bot commented Apr 3, 2022

View latest API docs preview at: https://staging.oneflow.info/docs/Oneflow-Inc/oneflow/pr/7914/

@daquexian daquexian merged commit b8547c6 into master Apr 3, 2022
@daquexian daquexian deleted the fix_randn_bug branch April 3, 2022 02:11
@BBuf BBuf mentioned this pull request Apr 22, 2022
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@Flowingsun007 Flowingsun007 Flowingsun007 approved these changes

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@daquexian daquexian Awaiting requested review from daquexian

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