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fixes to env parsing, textual inversion & help text

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- Make environment variable settings case InSenSiTive:
  INVOKEAI_MAX_LOADED_MODELS and InvokeAI_Max_Loaded_Models
  environment variables will both set `max_loaded_models`

- Updated realesrgan to use new config system.

- Updated textual_inversion_training to use new config system.

- Discovered a race condition when InvokeAIAppConfig is created
  at module load time, which makes it impossible to customize
  or replace the help message produced with --help on the command
  line. To fix this, moved all instances of get_invokeai_config()
  from module load time to object initialization time. Makes code
  cleaner, too.

- Added `--from_file` argument to `invokeai-node-cli` and changed
  github action to match. CI tests will hopefully work now.
This commit is contained in:
Lincoln Stein
2023-05-18 10:48:23 -04:00
parent f9710dd6ed
commit 7ea995149e
22 changed files with 118 additions and 116 deletions
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4
tests/preflight_prompts.txt
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@ -1,4 +0,0 @@
banana sushi -Ak_lms -W640 -H480 -S42 -s20
banana sushi -Ak_lms -S42 -G1 -U 2 0.5 -s20
banana sushi -Ak_lms -S42 -v0.2 -n3 -s20
banana sushi -Ak_lms -S42 -V1349749425:0.1,4145759947:0.1 -s20

5
tests/test_config.py
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@ -58,6 +58,11 @@ def test_env_override():
conf = InvokeAIAppConfig(conf=init1,argv=['--max_loaded=10'])
assert conf.nsfw_checker==True
# environment variables should be case insensitive
os.environ['InvokeAI_Max_Loaded_Models'] = '15'
conf = InvokeAIAppConfig(conf=init1)
assert conf.max_loaded_models == 15
conf = InvokeAIAppConfig(conf=init1,argv=['--no-nsfw_checker','--max_loaded=10'])
assert conf.nsfw_checker==False
assert conf.max_loaded_models==10

3
tests/validate_pr_prompt.txt
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@ -1,4 +1,3 @@
t2i --positive_prompt 'banana sushi' --seed 42
compel --prompt 'strawberry sushi' | compel | noise | t2l --scheduler heun --steps 3 --scheduler ddim --link -3 conditioning positive_conditioning --link -2 conditioning negative_conditioning | l2i
compel --prompt 'banana sushi' | compel | noise | t2i --scheduler heun --steps 3 --scheduler euler_a --link -3 conditioning positive_conditioning --link -2 conditioning negative_conditioning
compel --prompt 'banana sushi' | compel | noise | t2l --scheduler heun --steps 3 --scheduler euler_a --link -3 conditioning positive_conditioning --link -2 conditioning negative_conditioning