make eager test cases

[wyushun]

including:

test_consistent_cumsum.py
test_consistent_deconv2d.py
test_consistent_diagonal.py
test_consistent_dropout.py
test_consistent_fold.py

Task list: https://github.com/Oneflow-Inc/OneTeam/issues/933

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Speed stats:

GPU Name: GeForce GTX 1080 

✔️ OneFlow resnet50 time: 128.2ms (= 12823.7ms / 100, input_shape=[16, 3, 224, 224])
PyTorch resnet50 time: 136.9ms (= 13691.6ms / 100, input_shape=[16, 3, 224, 224])
✔️ Relative speed: 1.07 (= 136.9ms / 128.2ms)

✔️ OneFlow resnet50 time: 76.6ms (= 7655.3ms / 100, input_shape=[8, 3, 224, 224])
PyTorch resnet50 time: 82.8ms (= 8282.3ms / 100, input_shape=[8, 3, 224, 224])
✔️ Relative speed: 1.08 (= 82.8ms / 76.6ms)

OneFlow resnet50 time: 50.8ms (= 10160.2ms / 200, input_shape=[4, 3, 224, 224])
PyTorch resnet50 time: 56.5ms (= 11309.8ms / 200, input_shape=[4, 3, 224, 224])
✔️ Relative speed: 1.11 (= 56.5ms / 50.8ms)

OneFlow resnet50 time: 43.0ms (= 8597.1ms / 200, input_shape=[2, 3, 224, 224])
PyTorch resnet50 time: 48.5ms (= 9692.1ms / 200, input_shape=[2, 3, 224, 224])
✔️ Relative speed: 1.13 (= 48.5ms / 43.0ms)

OneFlow resnet50 time: 38.3ms (= 7663.5ms / 200, input_shape=[1, 3, 224, 224])
PyTorch resnet50 time: 40.8ms (= 8156.5ms / 200, input_shape=[1, 3, 224, 224])
✔️ Relative speed: 1.06 (= 40.8ms / 38.3ms)

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: 1.00 (= 50.8s / 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: 0.98 (= 13.6s / 13.3s)

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: 0.97 (= 7.6s / 7.3s)

✔️ OneFlow resnet50 time: 135.4ms (= 13535.6ms / 100, input_shape=[16, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 156.3ms (= 15630.5ms / 100, input_shape=[16, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.15 (= 156.3ms / 135.4ms)

OneFlow resnet50 time: 87.5ms (= 8746.6ms / 100, input_shape=[8, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 100.2ms (= 10021.8ms / 100, input_shape=[8, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.15 (= 100.2ms / 87.5ms)

OneFlow resnet50 time: 60.4ms (= 12083.0ms / 200, input_shape=[4, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 86.3ms (= 17256.3ms / 200, input_shape=[4, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.43 (= 86.3ms / 60.4ms)

OneFlow resnet50 time: 51.7ms (= 10330.9ms / 200, input_shape=[2, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 65.7ms (= 13133.2ms / 200, input_shape=[2, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.27 (= 65.7ms / 51.7ms)

OneFlow resnet50 time: 46.3ms (= 9258.6ms / 200, input_shape=[1, 3, 224, 224], ddp, world size=2)
PyTorch resnet50 time: 63.7ms (= 12738.8ms / 200, input_shape=[1, 3, 224, 224], ddp, world size=2)
✔️ Relative speed: 1.38 (= 63.7ms / 46.3ms)