turn on nhwc for more PW ops (#1570)
Turning permutatoin support on for a few pointwise ops:
aten::softplus; aten::threshold; aten::where; aten::lerp
Initial request coming from an example with poor perf for channels last input tensor.
```
def smelu(x: torch.Tensor, beta: float):
zero=torch.empty((), dtype=x.dtype, device=x.device).fill_(0.) # to avoid synchronizing h2d transfer
return torch.where(x >= beta, x, torch.where(x <= - beta, zero, (x+beta)*(x+beta)/(4*beta)))
memory_format=torch.channels_last
x = torch.randn(10240000, device="cuda").view(128, 80, 10, 100).to(memory_format=memory_format).detach().requires_grad_(False)
scripted = torch.jit.script(smelu)
smelu(x, 2.)
gO = torch.rand_like(x)
with torch.jit.fuser("fuser2"):
for _ in range(10):
x.grad = None
out = scripted(x, 2.)
```
