eager global maxpool

[liufengwei0103]

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Speed stats:

GPU Name: GeForce GTX 1080 

✔️ OneFlow resnet50 time: 128.2ms (= 12819.7ms / 100, input_shape=[16, 3, 224, 224])
PyTorch resnet50 time: 139.5ms (= 13953.9ms / 100, input_shape=[16, 3, 224, 224])
✔️ Relative speed: 1.09 (= 139.5ms / 128.2ms)

✔️ OneFlow resnet50 time: 76.5ms (= 7650.8ms / 100, input_shape=[8, 3, 224, 224])
PyTorch resnet50 time: 84.4ms (= 8438.0ms / 100, input_shape=[8, 3, 224, 224])
✔️ Relative speed: 1.10 (= 84.4ms / 76.5ms)

OneFlow resnet50 time: 51.8ms (= 10355.9ms / 200, input_shape=[4, 3, 224, 224])
PyTorch resnet50 time: 53.7ms (= 10739.6ms / 200, input_shape=[4, 3, 224, 224])
✔️ Relative speed: 1.04 (= 53.7ms / 51.8ms)

OneFlow resnet50 time: 40.0ms (= 8004.5ms / 200, input_shape=[2, 3, 224, 224])
PyTorch resnet50 time: 43.7ms (= 8743.2ms / 200, input_shape=[2, 3, 224, 224])
✔️ Relative speed: 1.09 (= 43.7ms / 40.0ms)

OneFlow resnet50 time: 36.5ms (= 7308.3ms / 200, input_shape=[1, 3, 224, 224])
PyTorch resnet50 time: 44.1ms (= 8825.3ms / 200, input_shape=[1, 3, 224, 224])
✔️ Relative speed: 1.21 (= 44.1ms / 36.5ms)

md5 /home/ci-user/ci-cache/test_cache/onerec_test/nanodataset.zip 7f5cde8b5a6c411107517ac9b00f29db
md5 /home/ci-user/ci-cache/test_cache/onerec_test/nanodataset.zip 7f5cde8b5a6c411107517ac9b00f29db
build_dataset >>>>>> ImageFolder
build_dataset >>>>>> ImageFolder
✔️ Relative speed: 1.02 (= 50.0s / 50.9s)

md5 /home/ci-user/ci-cache/test_cache/onerec_test/nanodataset.zip 7f5cde8b5a6c411107517ac9b00f29db
md5 /home/ci-user/ci-cache/test_cache/onerec_test/nanodataset.zip 7f5cde8b5a6c411107517ac9b00f29db
build_dataset >>>>>> ImageFolder
build_dataset >>>>>> ImageFolder
✔️ Relative speed: 1.09 (= 13.5s / 14.7s)

md5 /home/ci-user/ci-cache/test_cache/onerec_test/nanodataset.zip 7f5cde8b5a6c411107517ac9b00f29db
md5 /home/ci-user/ci-cache/test_cache/onerec_test/nanodataset.zip 7f5cde8b5a6c411107517ac9b00f29db
build_dataset >>>>>> ImageFolder
build_dataset >>>>>> ImageFolder
✔️ Relative speed: 0.95 (= 7.6s / 7.2s)

✔️ OneFlow resnet50 time: 135.4ms (= 13544.0ms / 100, input_shape=[16, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 155.0ms (= 15502.0ms / 100, input_shape=[16, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.14 (= 155.0ms / 135.4ms)

OneFlow resnet50 time: 88.7ms (= 8866.3ms / 100, input_shape=[8, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 100.1ms (= 10013.1ms / 100, input_shape=[8, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.13 (= 100.1ms / 88.7ms)

OneFlow resnet50 time: 61.1ms (= 12218.6ms / 200, input_shape=[4, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 76.6ms (= 15327.1ms / 200, input_shape=[4, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.25 (= 76.6ms / 61.1ms)

OneFlow resnet50 time: 53.8ms (= 10755.2ms / 200, input_shape=[2, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 66.8ms (= 13352.7ms / 200, input_shape=[2, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.24 (= 66.8ms / 53.8ms)

OneFlow resnet50 time: 52.6ms (= 10527.4ms / 200, input_shape=[1, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 63.3ms (= 12665.7ms / 200, input_shape=[1, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.20 (= 63.3ms / 52.6ms)