[hop][BE] add util diff_meta with prettier error message. (#142162)

The error message changes from:
```python
-torch._dynamo.exc.Unsupported: Expected branches to return tensors with same metadata. [(tensor_pair, difference)...]:[('pair0:', TensorMetadata(shape=torch.Size([4, 3]), dtype=torch.float32, requires_grad=False, stride=(3, 1), memory_format=None, is_quantized=False, qparams={}), TensorMetadata(shape=torch.Size([2, 3]), dtype=torch.float32, requires_grad=False, stride=(3, 1), memory_format=None, is_quantized=False, qparams={}))]
```
to
```python
+torch._dynamo.exc.Unsupported: Expect branches to return tensors with same metadata but find pair[0] differ in 'shape', where lhs is TensorMetadata(shape=torch.Size([4, 3]), dtype=torch.float32, requires_grad=False, stride=(3, 1), memory_format=None, is_quantized=False, qparams={}) and rhs is TensorMetadata(shape=torch.Size([2, 3]), dtype=torch.float32, requires_grad=False, stride=(3, 1), memory_format=None, is_quantized=False, qparams={})
```

Pull Request resolved: https://github.com/pytorch/pytorch/pull/142162
Approved by: https://github.com/zou3519

torch/_higher_order_ops/utils.py

@@ -9,6 +9,7 @@ import torch.fx.traceback as fx_traceback
 import torch.utils._pytree as pytree
 from torch._ops import OperatorBase
 from torch.fx.experimental.proxy_tensor import make_fx
+from torch.fx.passes.shape_prop import TensorMetadata
 from torch.multiprocessing.reductions import StorageWeakRef
 
 
@@ -481,6 +482,27 @@ def first_slice_copy(t: torch.Tensor, dim: int = 0) -> torch.Tensor:
     return torch.select_copy(t, dim, 0)
 
 
+# Reports the difference between meta of two tensors in a string
+def diff_tensor_meta(
+    meta1: TensorMetadata, meta2: TensorMetadata, check_grad=True
+) -> List[str]:
+    from torch.fx.experimental.symbolic_shapes import GuardOnDataDependentSymNode
+
+    pair_diffs = []
+    for meta_name in TensorMetadata._fields:
+        if not check_grad and meta_name == "requires_grad":
+            continue
+        val1 = getattr(meta1, meta_name)
+        val2 = getattr(meta2, meta_name)
+        try:
+            if val1 != val2:
+                pair_diffs.append(f"'{meta_name}'")
+        except GuardOnDataDependentSymNode as _:
+            pair_diffs.append(f"'{meta_name}'")
+            continue
+    return pair_diffs
+
+
 # Note [lifted arg types in hop]
 # For dynamoed hops, we automatically lift the free symbols in tensors as arguments.
 # This has implications for the types of lifted args for different dispatch keys: