GitLab

Instead of replacing all #ifdef USE_CUDA, just add USE_CUDA define to ROCm build.

Previously #6086 added ROCm support but after numerous rebases it lost
critical changes. This PR restores the ROCm build.

There are many source file changes but most were automated using the
following:

```bash
for f in `grep -rl '#ifdef USE_CUDA'`
do
    sed -i 's@#ifdef USE_CUDA@#if defined(USE_CUDA) || defined(USE_ROCM)@g' $f
done

for f in `grep -rl '#endif  // USE_CUDA'`
do
    sed -i 's@#endif  // USE_CUDA@#endif  // USE_CUDA || USE_ROCM@g' $f
done
```

* add l1 metric for cuda_exp

* add huber/fair metric for cuda_exp

* add poisson/mape/gamma/gamma_deviance/tweedie  metrics for cuda_exp

* fix cpplint error

* fix return  error

Co-authored-by: James Lamb <jaylamb20@gmail.com>

* [ci] speed up if-else, swig, and lint conda setup

* add 'source activate'

* python constraint

* start removing cuda v1

* comment out CI

* remove more references

* revert some unnecessaary changes

* revert a few more mistakes

* revert another change that ignored params

* sigh

* remove CUDATreeLearner

* fix tests, docs

* fix quoting in setup.py

* restore all CI

* Apply suggestions from code review
Co-authored-by: shiyu1994 <shiyu_k1994@qq.com>

* Apply suggestions from code review

* completely remove cuda_exp, update docs

---------
Co-authored-by: shiyu1994 <shiyu_k1994@qq.com>

* add rmse metric for new cuda version

* add Init for CUDAMetricInterface

* fix lint errors

* fix rmse and add l2 metric for new cuda version

* use CUDAL2Metric

* explicit template instantiation

* write result only with the first thread

* pre allocate buffer for output converting

* fix l2 regression with cuda metric evaluation

* weighting loss in cuda metric evaluation

* mark CUDATree::AsConstantTree as override

* add rmse metric for new cuda version

* add Init for CUDAMetricInterface

* fix lint errors