Files
pytorch/torch
Nicolas Macchioni cf81180007 allow SubConfigProxy of arbitrary depth (#133418)
Before, having arbitrary depth nested configs like

```
class Foo:
    foo: List[int] = [1, 2, 3]
    class Bar:
        bar: str = "1"
        class Baz:
            baz: int = 1
```

would cause problems beyond the first layer. For example, if we tried

```
from torch._inductor import config as inductor_config

print(inductor_config.Foo)
print(repr(inductor_config.Foo.foo))
print(inductor_config.Foo.Bar)
print(repr(inductor_config.Foo.Bar.bar))
print(inductor_config.Foo.Bar.Baz)
print(repr(inductor_config.Foo.Bar.Baz.baz))
```

we would get some output like

```
<torch.utils._config_module.SubConfigProxy object at 0x7fac65de00a0>
[1, 2, 3]
...
AttributeError: torch._inductor.config.Foo.Bar does not exist
```

Obviously, this is not what we want. With these changes, we get the right values

```
<torch.utils._config_module.SubConfigProxy object at 0x7f840d05bf40>
[1, 2, 3]
<torch.utils._config_module.SubConfigProxy object at 0x7f840cedc940>
'1'
<torch.utils._config_module.SubConfigProxy object at 0x7f840cedc100>
1
```

Fixes #ISSUE_NUMBER

Pull Request resolved: https://github.com/pytorch/pytorch/pull/133418
Approved by: https://github.com/oulgen
2024-08-14 18:43:00 +00:00
..
2024-07-30 18:42:54 +00:00

Note [TH abstraction violation]
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

TH/THC provide some hpp headers, which are proper C++ headers rather than
C headers.  These headers serve double duty as *internal implementation
detail* headers, whose contents should largely not be used by external
clients.

Ideally, we would not install these headers at all; instead, you should
use public functions (in headers like `THTensor.h`, NOT `THTensor.hpp`)
to manipulate these structs.  However, there are a few places
in torch/csrc where we violate this abstraction.  They are marked with
a pointer to this note.  Each of those sites will have to be refactored
when we refactor the guts of THTensor and related structures.