[ty] Fix subtyping of type[Any] / type[T] and protocols (#21678)

## Summary

This is a bugfix for subtyping of `type[Any]` / `type[T]` and protocols.

## Test Plan

Regression test that will only be really meaningful once
https://github.com/astral-sh/ruff/pull/21553 lands.

crates/ty_python_semantic/resources/mdtest/libraries/numpy.md

@@ -0,0 +1,67 @@
+# numpy
+
+```toml
+[environment]
+python-version = "3.14"
+```
+
+## numpy's `dtype`
+
+numpy functions often accept a `dtype` parameter. For example, one of `np.array`'s overloads accepts
+a `dtype` parameter of type `DTypeLike | None`. Here, we build up something that resembles numpy's
+internals in order to model the type `DTypeLike`. Many details have been left out.
+
+`mini_numpy.py`:
+
+```py
+from typing import TypeVar, Generic, Any, Protocol, TypeAlias, runtime_checkable, final
+import builtins
+
+_ItemT_co = TypeVar("_ItemT_co", default=Any, covariant=True)
+
+class generic(Generic[_ItemT_co]):
+    @property
+    def dtype(self) -> _DTypeT_co:
+        raise NotImplementedError
+
+_BoolItemT_co = TypeVar("_BoolItemT_co", bound=builtins.bool, default=builtins.bool, covariant=True)
+
+class bool(generic[_BoolItemT_co], Generic[_BoolItemT_co]): ...
+
+@final
+class object_(generic): ...
+
+_ScalarT = TypeVar("_ScalarT", bound=generic)
+_ScalarT_co = TypeVar("_ScalarT_co", bound=generic, default=Any, covariant=True)
+
+@final
+class dtype(Generic[_ScalarT_co]): ...
+
+_DTypeT_co = TypeVar("_DTypeT_co", bound=dtype, default=dtype, covariant=True)
+
+@runtime_checkable
+class _SupportsDType(Protocol[_DTypeT_co]):
+    @property
+    def dtype(self) -> _DTypeT_co: ...
+
+# TODO: no errors here
+# error: [invalid-type-arguments] "Type `typing.TypeVar` is not assignable to upper bound `generic[Any]` of type variable `_ScalarT_co@dtype`"
+# error: [invalid-type-arguments] "Type `typing.TypeVar` is not assignable to upper bound `generic[Any]` of type variable `_ScalarT_co@dtype`"
+_DTypeLike: TypeAlias = type[_ScalarT] | dtype[_ScalarT] | _SupportsDType[dtype[_ScalarT]]
+
+DTypeLike: TypeAlias = _DTypeLike[Any] | str | None
+```
+
+Now we can make sure that a function which accepts `DTypeLike | None` works as expected:
+
+```py
+import mini_numpy as np
+
+def accepts_dtype(dtype: np.DTypeLike | None) -> None: ...
+
+accepts_dtype(dtype=np.bool)
+accepts_dtype(dtype=np.dtype[np.bool])
+accepts_dtype(dtype=object)
+accepts_dtype(dtype=np.object_)
+accepts_dtype(dtype="U")
+```