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inductor-perf-test-nightly-a10g.yml
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name: inductor-perf-nightly-A10g
on:
schedule:
# - cron: 0 7 * * 1-6
# - cron: 0 7 * * 0
# Do not perform weekly max-autotune run for now.
- cron: 0 7 * * *
# NB: GitHub has an upper limit of 10 inputs here, so before we can sort it
# out, let try to run torchao cudagraphs_low_precision as part of cudagraphs
workflow_dispatch:
inputs:
training:
description: Run training (on by default)?
required: false
type: boolean
default: true
inference:
description: Run inference (off by default)?
required: false
type: boolean
default: false
default:
description: Run inductor_default?
required: false
type: boolean
default: false
dynamic:
description: Run inductor_dynamic_shapes?
required: false
type: boolean
default: false
cudagraphs:
description: Run inductor_cudagraphs?
required: false
type: boolean
default: true
freezing_cudagraphs:
description: Run inductor_cudagraphs with freezing for inference?
required: false
type: boolean
default: false
freeze_autotune_cudagraphs:
description: Run inductor_cudagraphs with freezing and max autotune for inference?
required: false
type: boolean
default: false
aotinductor:
description: Run aot_inductor for inference?
required: false
type: boolean
default: false
maxautotune:
description: Run inductor_max_autotune?
required: false
type: boolean
default: false
benchmark_configs:
description: The list of configs used the benchmark
required: false
type: string
default: inductor_huggingface_perf_cuda_a10g,inductor_timm_perf_cuda_a10g,inductor_torchbench_perf_cuda_a10g
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref_name }}-${{ github.ref_type == 'branch' && github.sha }}-${{ github.event_name == 'workflow_dispatch' }}-${{ github.event_name == 'schedule' }}
cancel-in-progress: true
permissions: read-all
jobs:
linux-focal-cuda12_1-py3_10-gcc9-inductor-build:
name: cuda12.1-py3.10-gcc9-sm80
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-focal-cuda12.1-py3.10-gcc9-sm80
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9-inductor-benchmarks
cuda-arch-list: '8.0'
test-matrix: |
{ include: [
{ config: "inductor_huggingface_perf_cuda_a10g", shard: 1, num_shards: 3, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor_huggingface_perf_cuda_a10g", shard: 2, num_shards: 3, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor_huggingface_perf_cuda_a10g", shard: 3, num_shards: 3, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor_timm_perf_cuda_a10g", shard: 1, num_shards: 5, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor_timm_perf_cuda_a10g", shard: 2, num_shards: 5, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor_timm_perf_cuda_a10g", shard: 3, num_shards: 5, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor_timm_perf_cuda_a10g", shard: 4, num_shards: 5, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor_timm_perf_cuda_a10g", shard: 5, num_shards: 5, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor_torchbench_perf_cuda_a10g", shard: 1, num_shards: 4, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor_torchbench_perf_cuda_a10g", shard: 2, num_shards: 4, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor_torchbench_perf_cuda_a10g", shard: 3, num_shards: 4, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor_torchbench_perf_cuda_a10g", shard: 4, num_shards: 4, runner: "linux.g5.4xlarge.nvidia.gpu" },
]}
selected-test-configs: ${{ inputs.benchmark_configs }}
secrets:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
linux-focal-cuda12_1-py3_10-gcc9-inductor-test-nightly:
name: cuda12.1-py3.10-gcc9-sm80
uses: ./.github/workflows/_linux-test.yml
needs: linux-focal-cuda12_1-py3_10-gcc9-inductor-build
if: github.event.schedule == '0 7 * * *'
with:
build-environment: linux-focal-cuda12.1-py3.10-gcc9-sm80
dashboard-tag: training-true-inference-true-default-true-dynamic-true-cudagraphs-true-aotinductor-true-freezing_cudagraphs-true-cudagraphs_low_precision-true
docker-image: ${{ needs.linux-focal-cuda12_1-py3_10-gcc9-inductor-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-focal-cuda12_1-py3_10-gcc9-inductor-build.outputs.test-matrix }}
use-gha: anything-non-empty-to-use-gha
timeout-minutes: 720
secrets:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
linux-focal-cuda12_1-py3_10-gcc9-inductor-test:
name: cuda12.1-py3.10-gcc9-sm80
uses: ./.github/workflows/_linux-test.yml
needs: linux-focal-cuda12_1-py3_10-gcc9-inductor-build
if: github.event_name == 'workflow_dispatch'
with:
build-environment: linux-focal-cuda12.1-py3.10-gcc9-sm80
dashboard-tag: training-${{ inputs.training }}-inference-${{ inputs.inference }}-default-${{ inputs.default }}-dynamic-${{ inputs.dynamic }}-cudagraphs-${{ inputs.cudagraphs }}-aotinductor-${{ inputs.aotinductor }}-maxautotune-${{ inputs.maxautotune }}-freezing_cudagraphs-${{ inputs.freezing_cudagraphs }}-cudagraphs_low_precision-${{ inputs.cudagraphs }}
docker-image: ${{ needs.linux-focal-cuda12_1-py3_10-gcc9-inductor-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-focal-cuda12_1-py3_10-gcc9-inductor-build.outputs.test-matrix }}
use-gha: anything-non-empty-to-use-gha
timeout-minutes: 720
secrets:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}