Update final docs/environment.md

docs/environment.md

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+# Environment
+
+## Validated Jittor setup
+
+| Component | Version |
+|---|---|
+| Python | 3.10 |
+| Jittor | 1.3.8.5 |
+| NumPy | 1.26.4 |
+| CUDA toolchain | Jittor CUDA 11.2 + cuDNN 8 |
+| C++ compiler | g++-10 |
+
+Install the Python dependencies and expose the repository package:
+
+```bash
+pip install -r requirements.txt
+export cc_path=/usr/bin/g++-10
+export PYTHONPATH="$PWD:$PWD/python"
+```
+
+Jittor compiles operators on first use, so the first model construction can
+take several minutes.
+
+## Compatibility notes
+
+### NumPy
+
+Keep NumPy at 1.26.4. Jittor 1.3.8.5 combined with NumPy 2.x can produce
+incorrect values for operations consuming NumPy-backed arrays without raising
+an exception. Verify the installation with:
+
+```bash
+python - <<'PY'
+import jittor as jt
+x = jt.float32([1, 2, 3])
+assert (x + x).numpy().tolist() == [2.0, 4.0, 6.0]
+print('Jittor array check passed')
+PY
+```
+
+### Compiler
+
+Jittor's CUDA 11.2 frontend is incompatible with newer system compiler headers
+on some Linux distributions. The validated toolchain uses g++-10 selected by
+the lowercase `cc_path` environment variable.
+
+### Reference environment
+
+Regenerating PyTorch goldens or using the reference DOTA merge metric requires
+the original Point2RBox-v3 environment: PyTorch 2.2, torchvision 0.17,
+mmengine 0.10.7, mmcv 2.2.0, mmdet 3.3.0 and the reference mmrotate package.
+Regular Jittor training and inference do not require this second environment.