Give op override wrappers descriptive names for stack traces

[Ashutosh0x]

Summary

When debugging tensor subclass issues, stack traces show in _ for every op override because the @implements decorator pattern uses _ as the function name. This makes it impossible to identify which op handler is failing without cross-referencing line numbers with source files.

Before:

File '.../float8_tensor.py', line 432, in _
    block_size = self.block_size.copy()

After:

File '.../float8_tensor.py', line 432, in impl_aten_narrow_default
    block_size = self.block_size.copy()

Approach

Added _op_display_name() helper that derives readable names from the op/function being registered, then overrides __name__ and __qualname__ on the wrapper after functools.wraps in both _implements() and _implements_torch_function() decorators.

This is done centrally in the decorator, so all 89+ existing call sites automatically get descriptive names without any changes to other files.

I chose this approach over renaming every def _ across the codebase because:

1. It's a single-file change (minimal review surface)
2. Future op overrides written as def _ will automatically get descriptive names
3. It matches vkuzo's ask: 'we should have descriptive names for these to reduce the level of indirection when debugging'

Examples of generated names:

• torch.ops.aten.narrow.default -> impl_aten_narrow_default
• torch.nn.functional.linear -> impl_linear
• torch.ops.aten.detach.default -> impl_aten_detach_default

Fixes #3045

Test Plan

Verified by inspection that _op_display_name produces correct names for both aten ops and torch functions. The change only affects __name__/__qualname__ attributes on wrapper functions, with no runtime behavior change.

This change was authored with the assistance of an AI coding assistant.

[pytorch-bot]

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