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[GAUDI] Disable Gaudi CI. (#23)
The GAUD CI pipeline has been temporarily disabled because the required Gaudi 3 cards are not available on Intel Cloud. This change will be reverted once the necessary hardware becomes accessible.
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.github/workflows/gaudi_hpu_test.yml

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@@ -69,6 +69,11 @@ on:
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- 8
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default: '0'
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description: 'The device selected to run on'
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skip_run:
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required: true
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type: boolean
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default: true
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description: 'Skip the run of the workflow'
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concurrency:
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group: ${{ github.workflow }}-${{ github.event_name }}-${{ github.ref }}
@@ -77,6 +82,7 @@ concurrency:
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jobs:
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prepare:
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name: Prepare
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if: ${{ github.event.inputs.skip_run == 'false' }}
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runs-on: ubuntu-latest
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env:
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REL_VERSION: "1.21.0"
@@ -113,6 +119,7 @@ jobs:
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name: Build torch
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needs:
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- prepare
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if: ${{ github.event.inputs.skip_run == 'false' }}
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# if: ${{ needs.prepare.outputs.ref }}
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uses: ./.github/workflows/_build_torch.yml
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with:
@@ -126,7 +133,7 @@ jobs:
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needs:
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- prepare
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- build-torch
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if: ${{ !cancelled() && (success() || needs.build-torch.result == 'skipped') }}
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if: ${{ !cancelled() && (success() || needs.build-torch.result == 'skipped') && github.event.inputs.skip_run == 'false' }}
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uses: ./.github/workflows/_gaudi_hpu_build_torch_hpu.yml
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with:
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runner: ${{ needs.prepare.outputs.runner }}
@@ -143,7 +150,8 @@ jobs:
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- build
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if: |
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!cancelled() && github.event_name != 'repository_dispatch' &&
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(success() || (needs.build-torch.result == 'skipped' && needs.build.result == 'success'))
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(success() || (needs.build-torch.result == 'skipped' && needs.build.result == 'success')) &&
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github.event.inputs.skip_run == 'false'
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uses: ./.github/workflows/_gaudi_hpu_ut.yml
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with:
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ref: ${{ needs.prepare.outputs.ref }}
@@ -164,7 +172,8 @@ jobs:
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- test
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if: |
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!cancelled() && github.event_name != 'repository_dispatch' &&
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(success() || (needs.build-torch.result == 'skipped' && needs.build.result == 'success'))
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(success() || (needs.build-torch.result == 'skipped' && needs.build.result == 'success')) &&
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github.event.inputs.skip_run == 'false'
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uses: ./.github/workflows/_gaudi_hpu_benchmark.yml
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with:
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ref: ${{ needs.prepare.outputs.ref }}

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