add prod dtype #7932

simonJJJ · 2022-03-30T08:56:22Z

No description provided.

python/oneflow/nn/modules/reduce_ops.py

oneflow/core/functional/impl/math_functor.cpp

github-actions · 2022-04-15T22:21:47Z

View latest API docs preview at: https://staging.oneflow.info/docs/Oneflow-Inc/oneflow/pr/7932/

github-actions · 2022-04-15T22:25:34Z

Speed stats:

GPU Name: GeForce GTX 1080 

✔️ OneFlow resnet50 time: 128.8ms (= 12880.2ms / 100, input_shape=[16, 3, 224, 224])
PyTorch resnet50 time: 141.1ms (= 14114.8ms / 100, input_shape=[16, 3, 224, 224])
✔️ Relative speed: 1.10 (= 141.1ms / 128.8ms)

OneFlow resnet50 time: 80.4ms (= 8043.7ms / 100, input_shape=[8, 3, 224, 224])
PyTorch resnet50 time: 85.6ms (= 8555.2ms / 100, input_shape=[8, 3, 224, 224])
✔️ Relative speed: 1.06 (= 85.6ms / 80.4ms)

OneFlow resnet50 time: 55.2ms (= 11045.1ms / 200, input_shape=[4, 3, 224, 224])
PyTorch resnet50 time: 61.9ms (= 12383.6ms / 200, input_shape=[4, 3, 224, 224])
✔️ Relative speed: 1.12 (= 61.9ms / 55.2ms)

OneFlow resnet50 time: 45.0ms (= 8992.6ms / 200, input_shape=[2, 3, 224, 224])
PyTorch resnet50 time: 50.5ms (= 10108.4ms / 200, input_shape=[2, 3, 224, 224])
✔️ Relative speed: 1.12 (= 50.5ms / 45.0ms)

OneFlow resnet50 time: 39.3ms (= 7868.6ms / 200, input_shape=[1, 3, 224, 224])
PyTorch resnet50 time: 44.2ms (= 8833.1ms / 200, input_shape=[1, 3, 224, 224])
✔️ Relative speed: 1.12 (= 44.2ms / 39.3ms)

OneFlow swin dataloader time: 0.262s (= 52.351s / 200, num_workers=1)
PyTorch swin dataloader time: 0.256s (= 51.219s / 200, num_workers=1)
✔️ Relative speed: 0.978 (= 0.256s / 0.262s)

OneFlow swin dataloader time: 0.066s (= 13.129s / 200, num_workers=4)
PyTorch swin dataloader time: 0.067s (= 13.344s / 200, num_workers=4)
✔️ Relative speed: 1.016 (= 0.067s / 0.066s)

OneFlow swin dataloader time: 0.037s (= 7.491s / 200, num_workers=8)
PyTorch swin dataloader time: 0.036s (= 7.261s / 200, num_workers=8)
✔️ Relative speed: 0.969 (= 0.036s / 0.037s)

✔️ OneFlow resnet50 time: 135.6ms (= 13556.1ms / 100, input_shape=[16, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 160.0ms (= 16004.1ms / 100, input_shape=[16, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.18 (= 160.0ms / 135.6ms)

OneFlow resnet50 time: 88.6ms (= 8860.4ms / 100, input_shape=[8, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 102.4ms (= 10239.3ms / 100, input_shape=[8, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.16 (= 102.4ms / 88.6ms)

OneFlow resnet50 time: 61.3ms (= 12250.3ms / 200, input_shape=[4, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 77.3ms (= 15458.5ms / 200, input_shape=[4, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.26 (= 77.3ms / 61.3ms)

OneFlow resnet50 time: 51.1ms (= 10213.6ms / 200, input_shape=[2, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 76.3ms (= 15257.4ms / 200, input_shape=[2, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.49 (= 76.3ms / 51.1ms)

OneFlow resnet50 time: 49.7ms (= 9948.5ms / 200, input_shape=[1, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 69.8ms (= 13952.5ms / 200, input_shape=[1, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.40 (= 69.8ms / 49.7ms)

github-actions · 2022-04-16T00:01:48Z

View latest API docs preview at: https://staging.oneflow.info/docs/Oneflow-Inc/oneflow/pr/7932/

github-actions · 2022-04-16T00:11:16Z

Speed stats:

GPU Name: GeForce GTX 1080 

✔️ OneFlow resnet50 time: 128.5ms (= 12851.9ms / 100, input_shape=[16, 3, 224, 224])
PyTorch resnet50 time: 140.3ms (= 14027.8ms / 100, input_shape=[16, 3, 224, 224])
✔️ Relative speed: 1.09 (= 140.3ms / 128.5ms)

OneFlow resnet50 time: 80.3ms (= 8031.5ms / 100, input_shape=[8, 3, 224, 224])
PyTorch resnet50 time: 83.6ms (= 8363.2ms / 100, input_shape=[8, 3, 224, 224])
✔️ Relative speed: 1.04 (= 83.6ms / 80.3ms)

OneFlow resnet50 time: 51.7ms (= 10335.7ms / 200, input_shape=[4, 3, 224, 224])
PyTorch resnet50 time: 58.3ms (= 11656.2ms / 200, input_shape=[4, 3, 224, 224])
✔️ Relative speed: 1.13 (= 58.3ms / 51.7ms)

OneFlow resnet50 time: 45.2ms (= 9049.1ms / 200, input_shape=[2, 3, 224, 224])
PyTorch resnet50 time: 44.1ms (= 8810.0ms / 200, input_shape=[2, 3, 224, 224])
❌ Relative speed: 0.97 (= 44.1ms / 45.2ms)

OneFlow resnet50 time: 39.8ms (= 7965.8ms / 200, input_shape=[1, 3, 224, 224])
PyTorch resnet50 time: 37.8ms (= 7565.9ms / 200, input_shape=[1, 3, 224, 224])
✔️ Relative speed: 0.95 (= 37.8ms / 39.8ms)

OneFlow swin dataloader time: 0.252s (= 50.382s / 200, num_workers=1)
PyTorch swin dataloader time: 0.250s (= 50.078s / 200, num_workers=1)
✔️ Relative speed: 0.994 (= 0.250s / 0.252s)

OneFlow swin dataloader time: 0.065s (= 12.976s / 200, num_workers=4)
PyTorch swin dataloader time: 0.068s (= 13.647s / 200, num_workers=4)
✔️ Relative speed: 1.052 (= 0.068s / 0.065s)

OneFlow swin dataloader time: 0.036s (= 7.190s / 200, num_workers=8)
PyTorch swin dataloader time: 0.036s (= 7.227s / 200, num_workers=8)
✔️ Relative speed: 1.005 (= 0.036s / 0.036s)

✔️ OneFlow resnet50 time: 135.3ms (= 13532.6ms / 100, input_shape=[16, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 157.5ms (= 15754.2ms / 100, input_shape=[16, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.16 (= 157.5ms / 135.3ms)

OneFlow resnet50 time: 85.6ms (= 8555.2ms / 100, input_shape=[8, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 101.0ms (= 10103.9ms / 100, input_shape=[8, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.18 (= 101.0ms / 85.6ms)

OneFlow resnet50 time: 62.6ms (= 12512.3ms / 200, input_shape=[4, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 86.7ms (= 17348.4ms / 200, input_shape=[4, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.39 (= 86.7ms / 62.6ms)

OneFlow resnet50 time: 53.8ms (= 10758.3ms / 200, input_shape=[2, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 76.5ms (= 15306.0ms / 200, input_shape=[2, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.42 (= 76.5ms / 53.8ms)

OneFlow resnet50 time: 47.7ms (= 9532.3ms / 200, input_shape=[1, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 61.3ms (= 12264.5ms / 200, input_shape=[1, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.29 (= 61.3ms / 47.7ms)

github-actions · 2022-04-16T00:45:43Z

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

github-actions · 2022-04-16T18:24:42Z

Speed stats:

GPU Name: GeForce GTX 1080 

✔️ OneFlow resnet50 time: 128.5ms (= 12848.0ms / 100, input_shape=[16, 3, 224, 224])
PyTorch resnet50 time: 139.1ms (= 13908.8ms / 100, input_shape=[16, 3, 224, 224])
✔️ Relative speed: 1.08 (= 139.1ms / 128.5ms)

OneFlow resnet50 time: 82.4ms (= 8237.0ms / 100, input_shape=[8, 3, 224, 224])
PyTorch resnet50 time: 83.3ms (= 8327.9ms / 100, input_shape=[8, 3, 224, 224])
❌ Relative speed: 1.01 (= 83.3ms / 82.4ms)

OneFlow resnet50 time: 51.5ms (= 10297.7ms / 200, input_shape=[4, 3, 224, 224])
PyTorch resnet50 time: 59.4ms (= 11871.0ms / 200, input_shape=[4, 3, 224, 224])
✔️ Relative speed: 1.15 (= 59.4ms / 51.5ms)

OneFlow resnet50 time: 43.3ms (= 8657.5ms / 200, input_shape=[2, 3, 224, 224])
PyTorch resnet50 time: 49.3ms (= 9853.3ms / 200, input_shape=[2, 3, 224, 224])
✔️ Relative speed: 1.14 (= 49.3ms / 43.3ms)

OneFlow resnet50 time: 39.4ms (= 7888.9ms / 200, input_shape=[1, 3, 224, 224])
PyTorch resnet50 time: 38.1ms (= 7622.2ms / 200, input_shape=[1, 3, 224, 224])
✔️ Relative speed: 0.97 (= 38.1ms / 39.4ms)

OneFlow swin dataloader time: 0.252s (= 50.418s / 200, num_workers=1)
PyTorch swin dataloader time: 0.252s (= 50.413s / 200, num_workers=1)
✔️ Relative speed: 1.000 (= 0.252s / 0.252s)

OneFlow swin dataloader time: 0.067s (= 13.389s / 200, num_workers=4)
PyTorch swin dataloader time: 0.069s (= 13.712s / 200, num_workers=4)
✔️ Relative speed: 1.024 (= 0.069s / 0.067s)

OneFlow swin dataloader time: 0.036s (= 7.179s / 200, num_workers=8)
PyTorch swin dataloader time: 0.037s (= 7.384s / 200, num_workers=8)
✔️ Relative speed: 1.029 (= 0.037s / 0.036s)

✔️ OneFlow resnet50 time: 135.5ms (= 13550.9ms / 100, input_shape=[16, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 155.4ms (= 15537.9ms / 100, input_shape=[16, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.15 (= 155.4ms / 135.5ms)

OneFlow resnet50 time: 87.5ms (= 8746.2ms / 100, input_shape=[8, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 99.2ms (= 9924.8ms / 100, input_shape=[8, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.13 (= 99.2ms / 87.5ms)

OneFlow resnet50 time: 60.5ms (= 12092.0ms / 200, input_shape=[4, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 86.2ms (= 17237.8ms / 200, input_shape=[4, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.43 (= 86.2ms / 60.5ms)

OneFlow resnet50 time: 53.8ms (= 10761.5ms / 200, input_shape=[2, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 66.5ms (= 13306.0ms / 200, input_shape=[2, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.24 (= 66.5ms / 53.8ms)

OneFlow resnet50 time: 47.9ms (= 9571.6ms / 200, input_shape=[1, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 62.5ms (= 12500.2ms / 200, input_shape=[1, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.31 (= 62.5ms / 47.9ms)

github-actions · 2022-04-16T18:41:45Z

View latest API docs preview at: https://staging.oneflow.info/docs/Oneflow-Inc/oneflow/pr/7932/

github-actions · 2022-04-16T19:22:11Z

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

github-actions · 2022-04-17T07:14:34Z

Speed stats:

GPU Name: GeForce GTX 1080 

✔️ OneFlow resnet50 time: 128.5ms (= 12851.1ms / 100, input_shape=[16, 3, 224, 224])
PyTorch resnet50 time: 137.5ms (= 13754.9ms / 100, input_shape=[16, 3, 224, 224])
✔️ Relative speed: 1.07 (= 137.5ms / 128.5ms)

OneFlow resnet50 time: 78.6ms (= 7855.6ms / 100, input_shape=[8, 3, 224, 224])
PyTorch resnet50 time: 84.1ms (= 8414.9ms / 100, input_shape=[8, 3, 224, 224])
✔️ Relative speed: 1.07 (= 84.1ms / 78.6ms)

OneFlow resnet50 time: 53.3ms (= 10665.2ms / 200, input_shape=[4, 3, 224, 224])
PyTorch resnet50 time: 53.7ms (= 10747.4ms / 200, input_shape=[4, 3, 224, 224])
✔️ Relative speed: 1.01 (= 53.7ms / 53.3ms)

OneFlow resnet50 time: 43.3ms (= 8669.8ms / 200, input_shape=[2, 3, 224, 224])
PyTorch resnet50 time: 48.8ms (= 9762.1ms / 200, input_shape=[2, 3, 224, 224])
✔️ Relative speed: 1.13 (= 48.8ms / 43.3ms)

OneFlow resnet50 time: 36.4ms (= 7285.5ms / 200, input_shape=[1, 3, 224, 224])
PyTorch resnet50 time: 37.4ms (= 7487.7ms / 200, input_shape=[1, 3, 224, 224])
✔️ Relative speed: 1.03 (= 37.4ms / 36.4ms)

OneFlow swin dataloader time: 0.253s (= 50.654s / 200, num_workers=1)
PyTorch swin dataloader time: 0.264s (= 52.730s / 200, num_workers=1)
✔️ Relative speed: 1.041 (= 0.264s / 0.253s)

OneFlow swin dataloader time: 0.064s (= 12.703s / 200, num_workers=4)
PyTorch swin dataloader time: 0.069s (= 13.773s / 200, num_workers=4)
✔️ Relative speed: 1.084 (= 0.069s / 0.064s)

OneFlow swin dataloader time: 0.036s (= 7.299s / 200, num_workers=8)
PyTorch swin dataloader time: 0.038s (= 7.691s / 200, num_workers=8)
✔️ Relative speed: 1.054 (= 0.038s / 0.036s)

✔️ OneFlow resnet50 time: 135.3ms (= 13527.7ms / 100, input_shape=[16, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 156.2ms (= 15624.8ms / 100, input_shape=[16, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.16 (= 156.2ms / 135.3ms)

OneFlow resnet50 time: 86.8ms (= 8683.1ms / 100, input_shape=[8, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 106.7ms (= 10673.0ms / 100, input_shape=[8, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.23 (= 106.7ms / 86.8ms)

OneFlow resnet50 time: 61.3ms (= 12258.6ms / 200, input_shape=[4, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 75.3ms (= 15051.6ms / 200, input_shape=[4, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.23 (= 75.3ms / 61.3ms)

OneFlow resnet50 time: 54.7ms (= 10937.0ms / 200, input_shape=[2, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 66.7ms (= 13332.6ms / 200, input_shape=[2, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.22 (= 66.7ms / 54.7ms)

OneFlow resnet50 time: 47.5ms (= 9490.8ms / 200, input_shape=[1, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 60.8ms (= 12164.6ms / 200, input_shape=[1, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.28 (= 60.8ms / 47.5ms)

github-actions · 2022-04-17T08:12:14Z

View latest API docs preview at: https://staging.oneflow.info/docs/Oneflow-Inc/oneflow/pr/7932/

github-actions · 2022-04-17T09:29:09Z

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

github-actions · 2022-04-17T16:22:25Z

Speed stats:

GPU Name: GeForce GTX 1080 

✔️ OneFlow resnet50 time: 128.4ms (= 12837.0ms / 100, input_shape=[16, 3, 224, 224])
PyTorch resnet50 time: 140.5ms (= 14049.6ms / 100, input_shape=[16, 3, 224, 224])
✔️ Relative speed: 1.09 (= 140.5ms / 128.4ms)

OneFlow resnet50 time: 77.2ms (= 7718.9ms / 100, input_shape=[8, 3, 224, 224])
PyTorch resnet50 time: 85.7ms (= 8566.0ms / 100, input_shape=[8, 3, 224, 224])
✔️ Relative speed: 1.11 (= 85.7ms / 77.2ms)

OneFlow resnet50 time: 53.6ms (= 10722.4ms / 200, input_shape=[4, 3, 224, 224])
PyTorch resnet50 time: 54.6ms (= 10911.4ms / 200, input_shape=[4, 3, 224, 224])
✔️ Relative speed: 1.02 (= 54.6ms / 53.6ms)

OneFlow resnet50 time: 43.8ms (= 8762.2ms / 200, input_shape=[2, 3, 224, 224])
PyTorch resnet50 time: 42.8ms (= 8557.8ms / 200, input_shape=[2, 3, 224, 224])
❌ Relative speed: 0.98 (= 42.8ms / 43.8ms)

OneFlow resnet50 time: 38.7ms (= 7747.1ms / 200, input_shape=[1, 3, 224, 224])
PyTorch resnet50 time: 38.2ms (= 7634.7ms / 200, input_shape=[1, 3, 224, 224])
✔️ Relative speed: 0.99 (= 38.2ms / 38.7ms)

OneFlow swin dataloader time: 0.249s (= 49.739s / 200, num_workers=1)
PyTorch swin dataloader time: 0.253s (= 50.577s / 200, num_workers=1)
✔️ Relative speed: 1.017 (= 0.253s / 0.249s)

OneFlow swin dataloader time: 0.066s (= 13.182s / 200, num_workers=4)
PyTorch swin dataloader time: 0.065s (= 13.022s / 200, num_workers=4)
✔️ Relative speed: 0.988 (= 0.065s / 0.066s)

OneFlow swin dataloader time: 0.037s (= 7.320s / 200, num_workers=8)
PyTorch swin dataloader time: 0.038s (= 7.540s / 200, num_workers=8)
✔️ Relative speed: 1.030 (= 0.038s / 0.037s)

✔️ OneFlow resnet50 time: 135.0ms (= 13503.5ms / 100, input_shape=[16, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 157.5ms (= 15746.3ms / 100, input_shape=[16, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.17 (= 157.5ms / 135.0ms)

OneFlow resnet50 time: 88.6ms (= 8860.8ms / 100, input_shape=[8, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 99.4ms (= 9939.2ms / 100, input_shape=[8, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.12 (= 99.4ms / 88.6ms)

OneFlow resnet50 time: 59.2ms (= 11836.3ms / 200, input_shape=[4, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 75.3ms (= 15052.3ms / 200, input_shape=[4, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.27 (= 75.3ms / 59.2ms)

OneFlow resnet50 time: 53.1ms (= 10620.7ms / 200, input_shape=[2, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 67.5ms (= 13501.7ms / 200, input_shape=[2, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.27 (= 67.5ms / 53.1ms)

OneFlow resnet50 time: 48.5ms (= 9690.7ms / 200, input_shape=[1, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 61.6ms (= 12326.8ms / 200, input_shape=[1, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.27 (= 61.6ms / 48.5ms)

github-actions · 2022-04-17T16:44:30Z

View latest API docs preview at: https://staging.oneflow.info/docs/Oneflow-Inc/oneflow/pr/7932/

add prod dtype

38b7955

simonJJJ added enhancement automerge eager api labels Mar 30, 2022

simonJJJ requested a review from MARD1NO March 30, 2022 08:56

simonJJJ requested review from hjchen2, BBuf, daquexian and jackalcooper as code owners March 30, 2022 08:56

BBuf reviewed Mar 30, 2022

View reviewed changes

python/oneflow/nn/modules/reduce_ops.py Show resolved Hide resolved

BBuf approved these changes Mar 30, 2022

View reviewed changes

MARD1NO reviewed Mar 30, 2022

View reviewed changes

oneflow/core/functional/impl/math_functor.cpp Outdated Show resolved Hide resolved

refine

1cd9dc1

MARD1NO approved these changes Mar 30, 2022

View reviewed changes

simonJJJ requested a review from oneflow-ci-bot March 30, 2022 09:56

oneflow-ci-bot requested review from oneflow-ci-bot and removed request for oneflow-ci-bot March 30, 2022 10:07

Merge branch 'master' into add_prod_dtype

8fae502

Merge branch 'master' into add_prod_dtype

5faa4bd

github-actions bot removed the automerge label Apr 16, 2022

simonJJJ added the automerge label Apr 16, 2022

Merge branch 'master' into add_prod_dtype

3e33d4b

github-actions bot removed the automerge label Apr 16, 2022

simonJJJ added the automerge label Apr 17, 2022

mergify bot added 2 commits April 17, 2022 02:57

Merge branch 'master' into add_prod_dtype

11135bd

Merge branch 'master' into add_prod_dtype

604f3fa

github-actions bot removed the automerge label Apr 17, 2022

simonJJJ added automerge ci labels Apr 17, 2022

mergify bot added 2 commits April 17, 2022 13:29

Merge branch 'master' into add_prod_dtype

2913d6f

Merge branch 'master' into add_prod_dtype

187842e

mergify bot merged commit 1aa979c into master Apr 17, 2022

mergify bot deleted the add_prod_dtype branch April 17, 2022 17:24

BBuf mentioned this pull request Apr 22, 2022

OneFlow 算子对齐 PyTorch 完备计划推进表 #4936

Closed

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

add prod dtype #7932

add prod dtype #7932

simonJJJ commented Mar 30, 2022

github-actions bot commented Apr 15, 2022

github-actions bot commented Apr 15, 2022

github-actions bot commented Apr 16, 2022

github-actions bot commented Apr 16, 2022

github-actions bot commented Apr 16, 2022

github-actions bot commented Apr 16, 2022

github-actions bot commented Apr 16, 2022

github-actions bot commented Apr 16, 2022

github-actions bot commented Apr 17, 2022

github-actions bot commented Apr 17, 2022

github-actions bot commented Apr 17, 2022

github-actions bot commented Apr 17, 2022

github-actions bot commented Apr 17, 2022

add prod dtype #7932

add prod dtype #7932

Conversation

simonJJJ commented Mar 30, 2022

github-actions bot commented Apr 15, 2022

github-actions bot commented Apr 15, 2022

github-actions bot commented Apr 16, 2022

github-actions bot commented Apr 16, 2022

github-actions bot commented Apr 16, 2022

github-actions bot commented Apr 16, 2022

github-actions bot commented Apr 16, 2022

github-actions bot commented Apr 16, 2022

github-actions bot commented Apr 17, 2022

github-actions bot commented Apr 17, 2022

github-actions bot commented Apr 17, 2022

github-actions bot commented Apr 17, 2022

github-actions bot commented Apr 17, 2022