[PERF] Specialize pow(x,2) as x*x. llama-7B (#434)

Right now `pow` with const exp argument is implemented simply. We
convert const to const tensor and run elementwise `pow` of 2 tensors. It
is simply but not always efficient.

llama2 (RMSNorm part) has `x*x` that implemented as `tensor.pow(2)`. 

Convert `pow(x,2)` to `x*x`.

Improvement on llama2-7B is around **0.237%**

python/hidet/graph/frontend/torch/register_functions.py

@@ -962,6 +962,8 @@ def tensor_where(self: Tensor, condition: Tensor, y: Union[Tensor, Number]):
 @register_method(torch.Tensor.pow_)
 def torch_pow(base: Union[Number, Tensor], exponent: Union[Number, Tensor]):
     if isinstance(exponent, (int, float, bool)):
+        if exponent in (2, 2.0):
+            return ops.square(base)
         exponent = full_like(base, exponent)
     elif isinstance(base, (int, float, bool)):
         base = full_like(exponent, base)