Fix DecomposeLayerNormPass to handle 6-arg layer_norm (#16516)

Summary:

## Problem

When using `nn.LayerNorm` in models that go through the ARM backend's quantization flow, the `DecomposeLayerNormPass` fails with:

```
ValueError: DecomposeLayerNormPass: too many values to unpack (expected 2)
```

This happens because `torch.ops.aten.layer_norm.default` has **6 arguments**:
```
layer_norm(input, normalized_shape, weight, bias, eps, cudnn_enable)
```

But `DecomposeLayerNormPass` only handled up to 5 arguments (for `native_layer_norm`).

The error occurs during `transform_for_annotation_pipeline` in the ARM quantizer, which runs before edge transformation when the op is still `aten.layer_norm.default`.

## Solution

Add `case 6:` to the `match len(args)` block in `DecomposeLayerNormPass.call()` to handle the 6th argument (`cudnn_enable`). This argument is simply ignored during decomposition since it's only relevant for cuDNN GPU optimization.
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Reviewed By: JacobSzwejbka

Differential Revision: D90395786

Author: Andrew Pullin

backends/arm/_passes/decompose_layernorm_pass.py

@@ -90,6 +90,11 @@ def call(self, graph_module: torch.fx.GraphModule):
             args = node.args
             meta = node.meta
             match len(args):
+                case 6:
+                    # torch.ops.aten.layer_norm.default has 6 args:
+                    # (input, normalized_shape, weight, bias, eps, cudnn_enable)
+                    # cudnn_enable is not used in the decomposition
+                    x, normalized_shape, weights, bias, epsilon, _cudnn_enable = args
                 case 5:
                     x, normalized_shape, weights, bias, epsilon = args
                 case 4:

backends/arm/test/targets.bzl

@@ -19,7 +19,7 @@ def define_arm_tests():
         "ops/test_avg_pool2d.py",
         "ops/test_cat.py",
         "ops/test_conv2d.py",
-        "ops/test_linear.py", 
+        "ops/test_linear.py",
         "ops/test_mul.py",
         "ops/test_permute.py",
         "ops/test_rsqrt.py",