feat: CI Stream for NVIDIA platform#21
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CI system for NVIDIA platformNVIDIA platform
NVIDIA platformCI Stream for NVIDIA platform
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- Pass host UID/GID into container and `chown` results after tests, so mounted `ci-results/` is accessible by the host user. - Limit `pytest-xdist` workers from `-n auto` to `-n 8` to prevent OOM worker crashes on high-core-count machines. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
…orm detection and job resolution
Add Dockerfile, config, and mx-smi GPU detection for MetaX (MACA) platform. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add GPU detection via mthreads-gmi, Dockerfile, config, and update docs with Moore and MetaX platform deployment instructions. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Capture last 50 lines of Docker output via ring buffer so failed jobs return diagnostic info to the CLI client. - Store raw bytes during execution; decode only on the failure path. - Align job name columns in `<==` result lines for readability. - Show summary only when jobs fail, removing redundant all-pass output. Co-Authored-By: Claude <noreply@anthropic.com>
- Add .ci/images/cambricon/Dockerfile for AnolisOS-based Cambricon image - Add cambricon platform to config.yaml with MLU-style GPU passthrough - Add GPU_STYLE_MLU constant and MLU_VISIBLE_DEVICES support in run.py - Add cnmon-based GPU detection (_detect_gpus_cambricon) in ci_resource.py - Add --test CLI flag to override pytest test path at runtime - Skip empty stage run commands instead of erroring (compilation-only mode) - Fix _torch_gemm fallback for CPU float16/bfloat16 (upcast to float32) - Skip bfloat16 on MLU (cnnlBatchMatMulEx does not support it) - Hoist _PYTEST_VALUE_FLAGS to module level; add ValueError guard in cambricon parser - Remove redundant yaml import guard in agent.py (utils.py already handles it) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
…DIA scheduler - Rewrite README.md entirely in English; add Cambricon to platform table and directory tree. - Translate all inline comments in config.yaml to English. - Replace `gpu_ids: "0"` with `ngpus: 1` for NVIDIA platform so the scheduler auto-picks a free GPU rather than pinning to device 0. - Add `ngpus` support to `parse_gpu_requirement` in ci_resource.py so scheduler correctly counts NVIDIA GPU demand. - Replace deprecated `gpu_count` fallback with `ngpus` in run.py `build_docker_args`. Co-Authored-By: Claude <noreply@anthropic.com>
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