Add support for aten.miopen_batch_norm

@rkayaith is already working on this.

Since Feb 23, 2026.

On ROCm 7.1+ (MIOpen 3.5+), PyTorch decomposes `BatchNorm2d` with channels-last inputs to `aten.miopen_batch_norm` instead of `aten._native_batch_norm_legit_functional`. torch-mlir doesn't have a lowering for this op, so it gets imported as a generic `torch.operator` and fails legalization.

## Reproducer

```mlir
// repro.mlir
module @module {
func.func @main(%arg0: !torch.vtensor<[8,64,56,56],bf16>) -> !torch.vtensor<[8,64,56,56],bf16> {
%weight = torch.vtensor.literal(dense<1.0> : tensor<64xf32>) : !torch.vtensor<[64],f32>
%bias = torch.vtensor.literal(dense<0.0> : tensor<64xf32>) : !torch.vtensor<[64],f32>
%running_mean = torch.vtensor.literal(dense<0.0> : tensor<64xf32>) : !torch.vtensor<[64],f32>
%running_var = torch.vtensor.literal(dense<1.0> : tensor<64xf32>) : !torch.vtensor<[64],f32>
%false = torch.constant.bool false
%momentum = torch.constant.float 1.000000e-01
%eps = torch.constant.float 1.000000e-05
%0:3 = torch.operator "torch.aten.miopen_batch_norm"(
%arg0, %weight, %bias, %running_mean, %running_var,
%false, %momentum, %eps
) : (!torch.vtensor<[8,64,56,56],bf16>,
!torch.vtensor<[64],f32>, !torch.vtensor<[64],f32>,
!torch.vtensor<[64],f32>, !torch.vtensor<[64],f32>,
!torch.bool, !torch.float, !torch.float)
-> (!torch.vtensor<[8,64,56,56],bf16>, !torch.vtensor<[0],bf16>, !torch.vtensor<[0],bf16>)
return %0#0 : !torch.vtensor<[8,64,56,56],bf16>
}
}
```

```
$ torch-mlir-opt repro.mlir --torch-function-to-torch-backend-pipeline
repro.mlir:12:12: error: failed to legalize operation 'torch.operator' that was explicitly marked illegal
%0:3 = torch.operator "torch.aten.miopen_batch_norm"(
^
```

### IREE Turbine reproducer

```python
import torch
import iree.turbine.aot as aot

model = torch.nn.BatchNorm2d(64).to(device="cuda", memory_format=torch.channels_last)
model.eval()
x = torch.randn(8, 64, 56, 56, device="cuda", dtype=torch.bfloat16).to(
memory_format=torch.channels_last
)

exported = aot.export(model, x)
exported.print_readable()
exported.compile(save_to=None)
```

## Suggested fix

Add a decomposition mapping `aten.miopen_batch_norm → aten.native_batch_norm`. The ops have the same signature and compatible output semantics. PyTorch Inductor has an equivalent decomposition: [torch/_inductor/decomposition.py#L867-L896](https://github.com/pytorch/pytorch/blob/449b1768410104d3ed79d3bcfe4ba1d65c7f22c0/torch/_inductor/decomposition.py#L867-L896)

## Environment

- PyTorch `2.10.0+rocm7.1`
- https://github.com/iree-org/iree-turbine/commit/391729bf9a123e9dcaf5faf449f480179eeb6107