fix GroupNorm init

[fpzh2011]

Creating GroupNorm with device and dtype throws Exceptions.

import oneflow as flow
m = flow.nn.GroupNorm(2, 3, device=flow.device("cpu"), dtype=flow.float32)

Exception messages:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/zhengjianhua/oneflow/python/oneflow/nn/modules/normalization.py", line 140, in __init__
    self.weight = flow.nn.Parameter(flow.Tensor(num_channels, **factory_kwargs))
TypeError: Error: _legacy_tensor_ctor(): received an invalid combination of arguments. The valid signatures are:
        *0: Tensor (*, Device device=None)
        *1: Tensor (*, Placement placement, SbpList sbp)
        *2: Tensor (Tensor other)
        *3: Tensor (PyObject* data, *, Device device=None)
        *4: Tensor (PyObject* data, *, Placement placement, SbpList sbp)
        *5: Tensor (Shape size, *, Device device=None)
        *6: Tensor (Shape size, *, Placement placement, SbpList sbp)

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View latest API docs preview at: https://oneflow-staging.oss-cn-beijing.aliyuncs.com/docs/Oneflow-Inc/oneflow/pr/10494/

[github-actions[bot]]

View latest API docs preview at: https://oneflow-staging.oss-cn-beijing.aliyuncs.com/docs/Oneflow-Inc/oneflow/pr/10494/

[github-actions[bot]]

Speed stats:

``` ```

[github-actions[bot]]

View latest API docs preview at: https://oneflow-staging.oss-cn-beijing.aliyuncs.com/docs/Oneflow-Inc/oneflow/pr/10494/

[github-actions[bot]]

Speed stats:

``` GPU Name: NVIDIA GeForce RTX 3080 Ti ❌ OneFlow resnet50 time: 43.6ms (= 4357.7ms / 100, input_shape=[16, 3, 224, 224]) PyTorch resnet50 time: 56.6ms (= 5658.9ms / 100, input_shape=[16, 3, 224, 224]) ✔️ Relative speed: 1.30 (= 56.6ms / 43.6ms) OneFlow resnet50 time: 26.6ms (= 2657.9ms / 100, input_shape=[8, 3, 224, 224]) PyTorch resnet50 time: 38.2ms (= 3815.3ms / 100, input_shape=[8, 3, 224, 224]) ✔️ Relative speed: 1.44 (= 38.2ms / 26.6ms) OneFlow resnet50 time: 17.7ms (= 3536.9ms / 200, input_shape=[4, 3, 224, 224]) PyTorch resnet50 time: 35.5ms (= 7108.8ms / 200, input_shape=[4, 3, 224, 224]) ✔️ Relative speed: 2.01 (= 35.5ms / 17.7ms) OneFlow resnet50 time: 17.6ms (= 3511.0ms / 200, input_shape=[2, 3, 224, 224]) PyTorch resnet50 time: 32.2ms (= 6432.5ms / 200, input_shape=[2, 3, 224, 224]) ✔️ Relative speed: 1.83 (= 32.2ms / 17.6ms) OneFlow resnet50 time: 17.1ms (= 3414.7ms / 200, input_shape=[1, 3, 224, 224]) PyTorch resnet50 time: 29.0ms (= 5802.7ms / 200, input_shape=[1, 3, 224, 224]) ✔️ Relative speed: 1.70 (= 29.0ms / 17.1ms) OneFlow swin dataloader time: 0.202s (= 40.335s / 200, num_workers=1) PyTorch swin dataloader time: 0.127s (= 25.378s / 200, num_workers=1) Relative speed: 0.629 (= 0.127s / 0.202s) OneFlow swin dataloader time: 0.058s (= 11.654s / 200, num_workers=4) PyTorch swin dataloader time: 0.033s (= 6.614s / 200, num_workers=4) Relative speed: 0.568 (= 0.033s / 0.058s) OneFlow swin dataloader time: 0.030s (= 6.026s / 200, num_workers=8) PyTorch swin dataloader time: 0.017s (= 3.385s / 200, num_workers=8) Relative speed: 0.562 (= 0.017s / 0.030s) ❌ OneFlow resnet50 time: 49.4ms (= 4938.4ms / 100, input_shape=[16, 3, 224, 224], ddp, world size=2) PyTorch resnet50 time: 66.4ms (= 6642.8ms / 100, input_shape=[16, 3, 224, 224], ddp, world size=2) ✔️ Relative speed: 1.35 (= 66.4ms / 49.4ms) OneFlow resnet50 time: 36.5ms (= 3654.0ms / 100, input_shape=[8, 3, 224, 224], ddp, world size=2) PyTorch resnet50 time: 47.0ms (= 4701.4ms / 100, input_shape=[8, 3, 224, 224], ddp, world size=2) ✔️ Relative speed: 1.29 (= 47.0ms / 36.5ms) OneFlow resnet50 time: 27.6ms (= 5516.4ms / 200, input_shape=[4, 3, 224, 224], ddp, world size=2) PyTorch resnet50 time: 38.6ms (= 7723.3ms / 200, input_shape=[4, 3, 224, 224], ddp, world size=2) ✔️ Relative speed: 1.40 (= 38.6ms / 27.6ms) OneFlow resnet50 time: 25.1ms (= 5016.6ms / 200, input_shape=[2, 3, 224, 224], ddp, world size=2) PyTorch resnet50 time: 40.0ms (= 7997.2ms / 200, input_shape=[2, 3, 224, 224], ddp, world size=2) ✔️ Relative speed: 1.59 (= 40.0ms / 25.1ms) OneFlow resnet50 time: 24.9ms (= 4986.2ms / 200, input_shape=[1, 3, 224, 224], ddp, world size=2) PyTorch resnet50 time: 36.1ms (= 7224.7ms / 200, input_shape=[1, 3, 224, 224], ddp, world size=2) ✔️ Relative speed: 1.45 (= 36.1ms / 24.9ms) ```