Describe the issue:

I'm looking to parametrize a numpy array with a type variable. Not sure if this is meant to be implemented, and thus a bug, or not-yet-implemented, and thus a feature request. The following code is flagged by Pylance:

Reproduce the code example:

from numpy.typing import NDArray
from typing import TypeVar

T = TypeVar("T")
GridsearchResult = Annotated[NDArray[T], "(n_metrics, n_plot_axis)"]

Error message:

Could not specialize type "NDArray[_ScalarType_co@NDArray]"
  Type "T@GridsearchResult" cannot be assigned to type "generic"
    "object" is incompatible with "generic"

Runtime information:

[{'numpy_version': '1.26.2',
'python': '3.10.12 (main, Jun 11 2023, 05:26:28) [GCC 11.4.0]',
'uname': uname_result(system='Linux', node='pontus', release='6.2.0-36-generic', version='#37~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Mon Oct 9 15:34:04 UTC 2', machine='x86_64')},
{'simd_extensions': {'baseline': ['SSE', 'SSE2', 'SSE3'],
'found': ['SSSE3',
'SSE41',
'POPCNT',
'SSE42',
'AVX',
'F16C',
'FMA3',
'AVX2'],
'not_found': ['AVX512F',
'AVX512CD',
'AVX512_KNL',
'AVX512_KNM',
'AVX512_SKX',
'AVX512_CLX',
'AVX512_CNL',
'AVX512_ICL']}},
{'architecture': 'Haswell',
'filepath': '/home/xenophon/github/gen-experiments/env/lib/python3.10/site-packages/numpy.libs/libopenblas64_p-r0-0cf96a72.3.23.dev.so',
'internal_api': 'openblas',
'num_threads': 4,
'prefix': 'libopenblas',
'threading_layer': 'pthreads',
'user_api': 'blas',
'version': '0.3.23.dev'}]

Context for the issue:

My gridsearch code returns a tuple of arrays, both 2D of the same size. One return array carries the maxes of a larger array along several axes, the other return array carries the argmax along those indices. So the two types are:

Annotated[NDArray[np.float64], "(n_metrics, plot_axis_length)"]
Annotated[NDArray[np.dtype("i,i,i,i")], "(n_metrics, plot_axis_length)"]

Here, the length of the indexing tuple is variable/determined later, but I would like a function signature akin to (ignoring the size annotation for now):

def maxes_and_argmaxes[T, U](arr: NDArray[T], axes: tuple[int, ...]): -> tuple[NDArray[T], NDArray[U]]

Here, U would be the variadic tuple of ints dtype.

I admit I'm a bit new to type variables, so this may not be the right approach. But I imagine the correct final form, if I want to Annotate the NDArrays is

T = TypeVar("T")
GridsearchResult = Annotated[NDArray[T], "(n_metrics, n_plot_axis)"]

def maxes_and_argmaxes[T, U](
     arr: NDArray[T], axes: tuple[int, ...]
): -> tuple[GridsearchResult[T], GridsearchResult[U]]