Use docker img built with pytorch 1.10

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

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

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

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

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Speed stats:

GPU Name: GeForce GTX 1080 

✔️ OneFlow resnet50 time: 128.4ms (= 12843.7ms / 100, input_shape=[16, 3, 224, 224])
PyTorch resnet50 time: 143.2ms (= 14321.9ms / 100, input_shape=[16, 3, 224, 224])
✔️ Relative speed: 1.12 (= 143.2ms / 128.4ms)

OneFlow resnet50 time: 79.0ms (= 7901.4ms / 100, input_shape=[8, 3, 224, 224])
PyTorch resnet50 time: 83.9ms (= 8393.6ms / 100, input_shape=[8, 3, 224, 224])
✔️ Relative speed: 1.06 (= 83.9ms / 79.0ms)

OneFlow resnet50 time: 52.9ms (= 10586.3ms / 200, input_shape=[4, 3, 224, 224])
PyTorch resnet50 time: 58.7ms (= 11732.2ms / 200, input_shape=[4, 3, 224, 224])
✔️ Relative speed: 1.11 (= 58.7ms / 52.9ms)

OneFlow resnet50 time: 43.8ms (= 8763.4ms / 200, input_shape=[2, 3, 224, 224])
PyTorch resnet50 time: 41.0ms (= 8201.9ms / 200, input_shape=[2, 3, 224, 224])
❌ Relative speed: 0.94 (= 41.0ms / 43.8ms)

OneFlow resnet50 time: 39.3ms (= 7851.0ms / 200, input_shape=[1, 3, 224, 224])
PyTorch resnet50 time: 39.0ms (= 7793.6ms / 200, input_shape=[1, 3, 224, 224])
✔️ Relative speed: 0.99 (= 39.0ms / 39.3ms)

OneFlow swin dataloader time: 0.257s (= 51.460s / 200, num_workers=1)
PyTorch swin dataloader time: 0.260s (= 52.009s / 200, num_workers=1)
✔️ Relative speed: 1.011 (= 0.260s / 0.257s)

OneFlow swin dataloader time: 0.067s (= 13.482s / 200, num_workers=4)
PyTorch swin dataloader time: 0.070s (= 14.048s / 200, num_workers=4)
✔️ Relative speed: 1.042 (= 0.070s / 0.067s)

OneFlow swin dataloader time: 0.038s (= 7.608s / 200, num_workers=8)
PyTorch swin dataloader time: 0.038s (= 7.583s / 200, num_workers=8)
✔️ Relative speed: 0.997 (= 0.038s / 0.038s)

✔️ OneFlow resnet50 time: 135.7ms (= 13567.1ms / 100, input_shape=[16, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 162.3ms (= 16232.0ms / 100, input_shape=[16, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.20 (= 162.3ms / 135.7ms)

OneFlow resnet50 time: 89.2ms (= 8916.8ms / 100, input_shape=[8, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 107.9ms (= 10788.7ms / 100, input_shape=[8, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.21 (= 107.9ms / 89.2ms)

OneFlow resnet50 time: 61.2ms (= 12241.3ms / 200, input_shape=[4, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 77.0ms (= 15407.3ms / 200, input_shape=[4, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.26 (= 77.0ms / 61.2ms)

OneFlow resnet50 time: 53.7ms (= 10747.4ms / 200, input_shape=[2, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 71.1ms (= 14214.5ms / 200, input_shape=[2, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.32 (= 71.1ms / 53.7ms)

OneFlow resnet50 time: 48.9ms (= 9787.5ms / 200, input_shape=[1, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 67.5ms (= 13499.7ms / 200, input_shape=[1, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.38 (= 67.5ms / 48.9ms)

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View latest API docs preview at: https://staging.oneflow.info/docs/Oneflow-Inc/oneflow/pr/7019/