PyCUDA 2025.1 fails to build from source with NumPy >= 2.3.0 (removed NPY_FARRAY / NPY_CARRAY macros)

## Describe the bug

PyCUDA 2025.1 cannot be built from source when the build environment resolves to NumPy >= 2.3.0. The C++ compilation fails because `src/wrapper/mempool.cpp` uses `NPY_FARRAY` and `NPY_CARRAY`, legacy macros that were deprecated since NumPy 1.7 and fully removed in NumPy 2.3.0 (Jun 7, 2025).

Since `pyproject.toml` declares `numpy>=1.24` with no upper bound, pip's PEP 517 build isolation pulls the latest NumPy (currently 2.4.2) into the isolated build environment, making `pip install pycuda==2025.1` fail for any new source installation on Python >= 3.11.

PyCUDA 2026.1 is unaffected — it builds cleanly against all NumPy versions from 2.2.0 through 2.4.2, confirming the source code was updated to use the modern equivalents.

## To Reproduce

1. Use a Python 3.11+ environment
2. Run `pip install pycuda==2025.1 --no-cache`
3. Build fails with C++ compilation errors in `src/wrapper/mempool.cpp`

Minimal reproduction:

```bash
# Fails — isolated build env pulls latest NumPy (2.4.2)
pip install pycuda==2025.1 --no-cache

# Succeeds — constraining build env to NumPy < 2.3
echo "numpy<2.3" > /tmp/constraints.txt
PIP_CONSTRAINT=/tmp/constraints.txt pip install pycuda==2025.1 --no-cache

# Succeeds — 2026.1 uses modern NumPy API
pip install pycuda==2026.1 --no-cache
```

Bisect across 15 NumPy versions using `PIP_CONSTRAINT` to control the isolated build environment:

| NumPy | PyCUDA 2025.1 | PyCUDA 2026.1 |
|---|---|---|
| 2.2.0 - 2.2.6 | ✅ Builds | ✅ Builds |
| 2.3.0 (breaking point) | ❌ Fails | ✅ Builds |
| 2.3.1 - 2.4.2 | ❌ Fails | ✅ Builds |

## Expected behavior

`pip install pycuda==2025.1` should either build successfully or fail with a clear dependency resolution error, not with cryptic C++ compilation errors. The `pyproject.toml` should have an upper bound on NumPy that matches what the source code can actually compile against.

## Environment

- OS: Linux x86_64 (Docker, base image `pytorch/pytorch:2.5.1-cuda12.1-cudnn9-devel`)
- CUDA version: 12.1
- PyCUDA version: 2025.1
- Python version: 3.11.10
- Compiler: g++ (conda compiler_compat)

## Additional context

Compilation errors:

```
src/wrapper/mempool.cpp:205:16: error: 'NPY_FARRAY' was not declared in this scope; did you mean 'NPY_FR_Y'?
src/wrapper/mempool.cpp:207:16: error: 'NPY_CARRAY' was not declared in this scope; did you mean 'NPY_WRAP'?
error: command '/usr/bin/g++' failed with exit code 1
```

This does not surface on Python 3.10 because NumPy 2.3+ requires Python >= 3.11, so the build env is naturally capped at NumPy 2.2.6 which still has the deprecated macros.

Suggested fix for the 2025.1 release — add an upper bound in `pyproject.toml`:

```toml
requires = ["setuptools", "wheel", "numpy>=1.24,<2.3"]
```