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# CUDA Hardware Configuration for TransformerEngine-FL
# Refactored for A100 Nodes
# This file defines environment variables, volumes, and test filters for TE tests.
hardware_name: cuda
display_name: 'NVIDIA CUDA (A100)'
checkout_submodules: recursive
# CI image for online env
ci_image: harbor.baai.ac.cn/flagscale/cuda12.8.1-torch2.7.1-python3.10-te2.9:20260209
# Runner labels for self-hosted A100 node
runner_labels:
- self-hosted
- Linux
- X64
- nvidia
- gpu-8
# Runner labels for online env
runner_labels:
- nv-8g-cicd-te
# Container volumes
container_volumes:
- /home/flagscale_cicd/flask/static:/workspace/report
# Container options
container_options: >-
--privileged
--gpus all
--shm-size=500g
--ipc=host
--ulimit memlock=-1
--ulimit stack=67108864
--user root
# Platform-specific environment setup script
setup_script: .github/scripts/setup_cuda.sh
# Device types to run tests on
device_types:
- a100
coverage:
enabled: true
required: false
python: /opt/miniconda3/envs/flagscale-train/bin/python3
sources:
- transformer_engine
include:
- transformer_engine/pytorch/*
- transformer_engine/debug/*
- transformer_engine/plugin/*
omit:
- '*/setup.py'
- '*/transformer_engine/plugin/core/_build_config.py'
unit_test_matrix:
- name: pytorch_debug
runner: script
path: qa/L0_pytorch_debug_unittest/test.sh
- name: pytorch_unittest
runner: script
path: qa/L0_pytorch_unittest/test.sh
- name: pytorch_distributed_unittest
runner: script
path: qa/L1_pytorch_distributed_unittest/test.sh
- name: pytorch_onnx_unittest
runner: script
path: qa/L1_pytorch_onnx_unittest/test.sh
integration_test_matrix:
- name: pytorch_mcore_integration
path: qa/L1_pytorch_mcore_integration/test.sh
# Test matrix configuration
test_matrix:
l0_pytorch:
path: 'qa/L0_pytorch_unittest/test.sh'
ignored_tests:
- test_sanity_layernorm_mlp
- test_sanity_gpt
- test_sanity_bert
- test_sanity_T5
- test_sanity_amp_and_nvfuser
- test_sanity_drop_path
- test_layernorm_mlp_accuracy
- test_grouped_linear_accuracy
- test_gpt_accuracy
- test_basic_linear
- test_layer_norm