mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
Update test-invoke-pip.yml
(#2524)
test-invoke-pip.yml: - enable caching of pip dependencies in `actions/setup-python@v4` - add workflow_dispatch trigger - fix indentation in concurrency - set env `PIP_USE_PEP517: '1'` - cache python dependencies - remove models cache (since we currently use 190.96 GB of 10 GB while I am writing this) - add step to set `INVOKEAI_OUTDIR` - add outdir arg to invokeai - fix path in archive results model_manager.py: - read files in chunks when calculating sha (windows runner is crashing otherwise)
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commit
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57
.github/workflows/test-invoke-pip.yml
vendored
57
.github/workflows/test-invoke-pip.yml
vendored
@ -8,10 +8,11 @@ on:
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- 'ready_for_review'
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- 'opened'
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- 'synchronize'
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workflow_dispatch:
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concurrency:
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group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
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cancel-in-progress: true
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group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
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cancel-in-progress: true
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jobs:
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matrix:
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@ -62,28 +63,13 @@ jobs:
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# github-env: $env:GITHUB_ENV
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name: ${{ matrix.pytorch }} on ${{ matrix.python-version }}
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runs-on: ${{ matrix.os }}
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env:
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PIP_USE_PEP517: '1'
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steps:
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- name: Checkout sources
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id: checkout-sources
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uses: actions/checkout@v3
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- name: setup python
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uses: actions/setup-python@v4
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with:
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python-version: ${{ matrix.python-version }}
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- name: Set Cache-Directory Windows
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if: runner.os == 'Windows'
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id: set-cache-dir-windows
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run: |
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echo "CACHE_DIR=$HOME\invokeai\models" >> ${{ matrix.github-env }}
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echo "PIP_NO_CACHE_DIR=1" >> ${{ matrix.github-env }}
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- name: Set Cache-Directory others
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if: runner.os != 'Windows'
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id: set-cache-dir-others
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run: echo "CACHE_DIR=$HOME/invokeai/models" >> ${{ matrix.github-env }}
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- name: set test prompt to main branch validation
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if: ${{ github.ref == 'refs/heads/main' }}
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run: echo "TEST_PROMPTS=tests/preflight_prompts.txt" >> ${{ matrix.github-env }}
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@ -92,26 +78,29 @@ jobs:
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if: ${{ github.ref != 'refs/heads/main' }}
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run: echo "TEST_PROMPTS=tests/validate_pr_prompt.txt" >> ${{ matrix.github-env }}
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- name: setup python
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uses: actions/setup-python@v4
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with:
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python-version: ${{ matrix.python-version }}
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cache: pip
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cache-dependency-path: pyproject.toml
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- name: install invokeai
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env:
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PIP_EXTRA_INDEX_URL: ${{ matrix.extra-index-url }}
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run: >
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pip3 install
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--use-pep517
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--editable=".[test]"
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- name: run pytest
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id: run-pytest
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run: pytest
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- name: Use Cached models
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id: cache-sd-model
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uses: actions/cache@v3
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env:
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cache-name: huggingface-models
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with:
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path: ${{ env.CACHE_DIR }}
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key: ${{ env.cache-name }}
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enableCrossOsArchive: true
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- name: set INVOKEAI_OUTDIR
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run: >
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python -c
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"import os;from ldm.invoke.globals import Globals;OUTDIR=os.path.join(Globals.root,str('outputs'));print(f'INVOKEAI_OUTDIR={OUTDIR}')"
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>> ${{ matrix.github-env }}
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- name: run invokeai-configure
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id: run-preload-models
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@ -124,9 +113,8 @@ jobs:
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--full-precision
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# can't use fp16 weights without a GPU
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- name: Run the tests
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if: runner.os != 'Windows'
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id: run-tests
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- name: run invokeai
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id: run-invokeai
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env:
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# Set offline mode to make sure configure preloaded successfully.
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HF_HUB_OFFLINE: 1
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@ -137,10 +125,11 @@ jobs:
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--no-patchmatch
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--no-nsfw_checker
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--from_file ${{ env.TEST_PROMPTS }}
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--outdir ${{ env.INVOKEAI_OUTDIR }}/${{ matrix.python-version }}/${{ matrix.pytorch }}
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- name: Archive results
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id: archive-results
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uses: actions/upload-artifact@v3
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with:
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name: results_${{ matrix.pytorch }}_${{ matrix.python-version }}
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path: ${{ env.INVOKEAI_ROOT }}/outputs
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name: results
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path: ${{ env.INVOKEAI_OUTDIR }}
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@ -753,7 +753,7 @@ class ModelManager(object):
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return search_folder, found_models
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def _choose_diffusers_vae(self, model_name:str, vae:str=None)->Union[dict,str]:
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# In the event that the original entry is using a custom ckpt VAE, we try to
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# map that VAE onto a diffuser VAE using a hard-coded dictionary.
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# I would prefer to do this differently: We load the ckpt model into memory, swap the
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@ -954,7 +954,7 @@ class ModelManager(object):
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def _has_cuda(self) -> bool:
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return self.device.type == 'cuda'
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def _diffuser_sha256(self,name_or_path:Union[str, Path])->Union[str,bytes]:
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def _diffuser_sha256(self,name_or_path:Union[str, Path],chunksize=4096)->Union[str,bytes]:
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path = None
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if isinstance(name_or_path,Path):
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path = name_or_path
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@ -976,7 +976,8 @@ class ModelManager(object):
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for name in files:
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count += 1
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with open(os.path.join(root,name),'rb') as f:
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sha.update(f.read())
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while chunk := f.read(chunksize):
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sha.update(chunk)
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hash = sha.hexdigest()
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toc = time.time()
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print(f' | sha256 = {hash} ({count} files hashed in','%4.2fs)' % (toc - tic))
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