🐛 Describe the bug

GroupNorm does not return channels_last tensor.

norm = nn.GroupNorm(8, 32).to(device, memory_format=torch.channels_last)
x = torch.randn([4, 32, 24, 24], device=device).to(memory_format=torch.channels_last)

print(x.stride())
assert x.is_contiguous(memory_format=torch.channels_last) # Pass

y = norm(x)

print(y.stride())
assert y.is_contiguous(memory_format=torch.channels_last) # Fail

I had to implement groupnorm manually. Somehow this works great and fast.

class GroupNorm(nn.GroupNorm):
    def forward(self, x):
        dtype = x.dtype
        x = x.float()
        x = rearrange(x, "b (g c) h w -> b g c h w", g=self.num_groups)

        mean = x.mean(dim=[2,3,4], keepdim=True)
        var = x.var(dim=[2,3,4], keepdim=True)

        x = (x - mean) * (var + self.eps).rsqrt()
        x = rearrange(x, "b g c h w -> b (g c) h w")

        if self.affine:
            weight = rearrange(self.weight, "c -> 1 c 1 1")
            bias = rearrange(self.bias, "c -> 1 c 1 1")
            x = x * weight + bias

        x = x.type(dtype)
        return x

Versions

Collecting environment information...
PyTorch version: 2.1.0+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A

OS: Debian GNU/Linux 11 (bullseye) (x86_64)
GCC version: (Debian 10.2.1-6) 10.2.1 20210110
Clang version: Could not collect
CMake version: version 3.18.4
Libc version: glibc-2.31

Python version: 3.9.2 (default, Feb 28 2021, 17:03:44) [GCC 10.2.1 20210110] (64-bit runtime)
Python platform: Linux-5.4.56.bsk.11-amd64-x86_64-with-glibc2.31
Is CUDA available: True
CUDA runtime version: 12.2.140
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA A100-SXM4-80GB
Nvidia driver version: 470.129.06
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.9.4
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.9.4
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.9.4
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.9.4
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.9.4
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.9.4
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.9.4
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Byte Order: Little Endian
Address sizes: 46 bits physical, 48 bits virtual
CPU(s): 96
On-line CPU(s) list: 0-95
Thread(s) per core: 2
Core(s) per socket: 24
Socket(s): 2
NUMA node(s): 2
Vendor ID: GenuineIntel
CPU family: 6
Model: 85
Model name: Intel(R) Xeon(R) Platinum 8275CL CPU @ 3.00GHz
Stepping: 7
CPU MHz: 3599.940
BogoMIPS: 5999.99
Hypervisor vendor: KVM
Virtualization type: full
L1d cache: 1.5 MiB
L1i cache: 1.5 MiB
L2 cache: 48 MiB
L3 cache: 71.5 MiB
NUMA node0 CPU(s): 0-23,48-71
NUMA node1 CPU(s): 24-47,72-95
Vulnerability Itlb multihit: KVM: Vulnerable
Vulnerability L1tf: Mitigation; PTE Inversion
Vulnerability Mds: Vulnerable: Clear CPU buffers attempted, no microcode; SMT Host state unknown
Vulnerability Meltdown: Vulnerable
Vulnerability Spec store bypass: Vulnerable
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Vulnerable, STIBP: disabled
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid mpx avx512f avx512dq rdseed adx smap clflushopt clwb avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves ida arat pku ospke

Versions of relevant libraries:
[pip3] byted-torch==2.1.0.post0
[pip3] byted-torch-monitor==0.0.1
[pip3] numpy==1.26.1
[pip3] torch==2.1.0
[pip3] torchaudio==2.1.0+cu121
[pip3] torchvision==0.16.0
[pip3] triton==2.1.0
[conda] Could not collect

cc @albanD @mruberry @jbschlosser @walterddr @mikaylagawarecki @ptrblck @jamesr66a @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10