Spaces:
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Migrate from yapf to black
Browse files- .pre-commit-config.yaml +19 -15
- .style.yapf +0 -5
- .vscode/settings.json +11 -8
- app.py +127 -113
- notebook.ipynb +3 -41
.pre-commit-config.yaml
CHANGED
@@ -1,6 +1,6 @@
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repos:
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- repo: https://github.com/pre-commit/pre-commit-hooks
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-
rev: v4.
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hooks:
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- id: check-executables-have-shebangs
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- id: check-json
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@@ -8,39 +8,43 @@ repos:
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- id: check-shebang-scripts-are-executable
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- id: check-toml
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- id: check-yaml
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-
- id: double-quote-string-fixer
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- id: end-of-file-fixer
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- id: mixed-line-ending
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-
args: [
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- id: requirements-txt-fixer
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- id: trailing-whitespace
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- repo: https://github.com/myint/docformatter
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-
rev: v1.
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hooks:
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- id: docformatter
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-
args: [
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- repo: https://github.com/pycqa/isort
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rev: 5.12.0
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hooks:
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- id: isort
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- repo: https://github.com/pre-commit/mirrors-mypy
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-
rev:
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hooks:
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- id: mypy
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-
args: [
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-
additional_dependencies: [
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-
- repo: https://github.com/
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-
rev:
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hooks:
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-
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-
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- repo: https://github.com/kynan/nbstripout
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-
rev: 0.6.
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hooks:
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- id: nbstripout
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-
args: [
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- repo: https://github.com/nbQA-dev/nbQA
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rev: 1.7.0
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hooks:
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- id: nbqa-isort
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-
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repos:
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- repo: https://github.com/pre-commit/pre-commit-hooks
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+
rev: v4.4.0
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hooks:
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- id: check-executables-have-shebangs
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- id: check-json
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- id: check-shebang-scripts-are-executable
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- id: check-toml
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- id: check-yaml
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- id: end-of-file-fixer
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- id: mixed-line-ending
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+
args: ["--fix=lf"]
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- id: requirements-txt-fixer
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- id: trailing-whitespace
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- repo: https://github.com/myint/docformatter
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+
rev: v1.7.5
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hooks:
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- id: docformatter
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+
args: ["--in-place"]
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- repo: https://github.com/pycqa/isort
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rev: 5.12.0
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hooks:
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- id: isort
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+
args: ["--profile", "black"]
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- repo: https://github.com/pre-commit/mirrors-mypy
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+
rev: v1.5.1
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hooks:
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- id: mypy
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+
args: ["--ignore-missing-imports"]
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+
additional_dependencies: ["types-python-slugify", "types-requests", "types-PyYAML"]
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+
- repo: https://github.com/psf/black
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+
rev: 23.7.0
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hooks:
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- id: black
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+
language_version: python3.10
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+
args: ["--line-length", "119"]
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- repo: https://github.com/kynan/nbstripout
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+
rev: 0.6.1
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hooks:
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- id: nbstripout
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+
args: ["--extra-keys", "metadata.interpreter metadata.kernelspec cell.metadata.pycharm"]
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- repo: https://github.com/nbQA-dev/nbQA
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rev: 1.7.0
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hooks:
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+
- id: nbqa-black
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+
- id: nbqa-pyupgrade
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+
args: ["--py37-plus"]
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- id: nbqa-isort
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+
args: ["--float-to-top"]
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.style.yapf
DELETED
@@ -1,5 +0,0 @@
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-
[style]
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-
based_on_style = pep8
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-
blank_line_before_nested_class_or_def = false
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-
spaces_before_comment = 2
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-
split_before_logical_operator = true
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.vscode/settings.json
CHANGED
@@ -1,18 +1,21 @@
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{
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-
"python.linting.enabled": true,
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-
"python.linting.flake8Enabled": true,
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-
"python.linting.pylintEnabled": false,
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-
"python.linting.lintOnSave": true,
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-
"python.formatting.provider": "yapf",
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-
"python.formatting.yapfArgs": [
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-
"--style={based_on_style: pep8, indent_width: 4, blank_line_before_nested_class_or_def: false, spaces_before_comment: 2, split_before_logical_operator: true}"
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-
],
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"[python]": {
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"editor.formatOnType": true,
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"editor.codeActionsOnSave": {
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"source.organizeImports": true
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}
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},
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"editor.formatOnSave": true,
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"files.insertFinalNewline": true
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}
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{
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"[python]": {
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+
"editor.defaultFormatter": "ms-python.black-formatter",
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"editor.formatOnType": true,
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"editor.codeActionsOnSave": {
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"source.organizeImports": true
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}
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},
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+
"black-formatter.args": [
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+
"--line-length=119"
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+
],
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+
"isort.args": ["--profile", "black"],
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+
"flake8.args": [
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+
"--max-line-length=119"
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],
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+
"ruff.args": [
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"--line-length=119"
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],
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"editor.formatOnSave": true,
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"files.insertFinalNewline": true
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}
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app.py
CHANGED
@@ -11,31 +11,32 @@ import PIL.Image
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import torch
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from diffusers import DiffusionPipeline
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-
DESCRIPTION =
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if not torch.cuda.is_available():
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DESCRIPTION +=
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MAX_SEED = np.iinfo(np.int32).max
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-
CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv(
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-
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-
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-
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-
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ENABLE_REFINER = os.getenv('ENABLE_REFINER', '1') == '1'
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-
device = torch.device(
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if torch.cuda.is_available():
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pipe = DiffusionPipeline.from_pretrained(
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-
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torch_dtype=torch.float16,
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use_safetensors=True,
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variant=
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if ENABLE_REFINER:
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refiner = DiffusionPipeline.from_pretrained(
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-
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torch_dtype=torch.float16,
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use_safetensors=True,
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variant=
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if ENABLE_CPU_OFFLOAD:
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pipe.enable_model_cpu_offload()
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@@ -47,13 +48,9 @@ if torch.cuda.is_available():
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refiner.to(device)
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if USE_TORCH_COMPILE:
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-
pipe.unet = torch.compile(pipe.unet,
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-
mode='reduce-overhead',
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-
fullgraph=True)
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if ENABLE_REFINER:
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-
refiner.unet = torch.compile(refiner.unet,
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-
mode='reduce-overhead',
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-
fullgraph=True)
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else:
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pipe = None
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refiner = None
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@@ -65,21 +62,23 @@ def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
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return seed
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-
def generate(
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-
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-
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-
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-
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-
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-
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-
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-
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-
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-
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-
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-
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-
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-
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generator = torch.Generator().manual_seed(seed)
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if not use_negative_prompt:
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@@ -90,140 +89,153 @@ def generate(prompt: str,
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negative_prompt_2 = None # type: ignore
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if not apply_refiner:
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-
return pipe(
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-
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-
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-
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-
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-
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-
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-
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-
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-
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else:
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-
latents = pipe(
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-
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-
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-
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-
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-
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-
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-
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-
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-
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-
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-
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-
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-
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-
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-
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-
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-
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return image
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examples = [
|
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-
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127 |
-
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]
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-
with gr.Blocks(css=
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gr.Markdown(DESCRIPTION)
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-
gr.DuplicateButton(
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-
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-
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with gr.Group():
|
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with gr.Row():
|
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prompt = gr.Text(
|
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-
label=
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show_label=False,
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140 |
max_lines=1,
|
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-
placeholder=
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container=False,
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)
|
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-
run_button = gr.Button(
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-
result = gr.Image(label=
|
146 |
-
with gr.Accordion(
|
147 |
with gr.Row():
|
148 |
-
use_negative_prompt = gr.Checkbox(label=
|
149 |
-
|
150 |
-
|
151 |
-
use_negative_prompt_2 = gr.Checkbox(label='Use negative prompt 2',
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152 |
-
value=False)
|
153 |
negative_prompt = gr.Text(
|
154 |
-
label=
|
155 |
max_lines=1,
|
156 |
-
placeholder=
|
157 |
visible=False,
|
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)
|
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prompt_2 = gr.Text(
|
160 |
-
label=
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161 |
max_lines=1,
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162 |
-
placeholder=
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visible=False,
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)
|
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negative_prompt_2 = gr.Text(
|
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-
label=
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max_lines=1,
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-
placeholder=
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visible=False,
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)
|
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-
seed = gr.Slider(
|
173 |
-
|
174 |
-
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175 |
-
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176 |
-
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-
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with gr.Row():
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width = gr.Slider(
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-
label=
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minimum=256,
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182 |
maximum=MAX_IMAGE_SIZE,
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step=32,
|
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value=1024,
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)
|
186 |
height = gr.Slider(
|
187 |
-
label=
|
188 |
minimum=256,
|
189 |
maximum=MAX_IMAGE_SIZE,
|
190 |
step=32,
|
191 |
value=1024,
|
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)
|
193 |
-
apply_refiner = gr.Checkbox(label=
|
194 |
-
value=False,
|
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-
visible=ENABLE_REFINER)
|
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with gr.Row():
|
197 |
-
guidance_scale_base = gr.Slider(
|
198 |
-
|
199 |
-
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-
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-
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num_inference_steps_base = gr.Slider(
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-
label=
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minimum=10,
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maximum=100,
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step=1,
|
207 |
-
value=50
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with gr.Row(visible=False) as refiner_params:
|
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guidance_scale_refiner = gr.Slider(
|
210 |
-
label=
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minimum=1,
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maximum=20,
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step=0.1,
|
214 |
-
value=5.0
|
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num_inference_steps_refiner = gr.Slider(
|
216 |
-
label=
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minimum=10,
|
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maximum=100,
|
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step=1,
|
220 |
-
value=50
|
|
|
221 |
|
222 |
-
gr.Examples(
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223 |
-
|
224 |
-
|
225 |
-
|
226 |
-
|
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|
227 |
|
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use_negative_prompt.change(
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229 |
fn=lambda x: gr.update(visible=x),
|
@@ -281,7 +293,7 @@ with gr.Blocks(css='style.css') as demo:
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fn=generate,
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inputs=inputs,
|
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outputs=result,
|
284 |
-
api_name=
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)
|
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negative_prompt.submit(
|
287 |
fn=randomize_seed_fn,
|
@@ -331,4 +343,6 @@ with gr.Blocks(css='style.css') as demo:
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outputs=result,
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api_name=False,
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)
|
334 |
-
|
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import torch
|
12 |
from diffusers import DiffusionPipeline
|
13 |
|
14 |
+
DESCRIPTION = "# SD-XL"
|
15 |
if not torch.cuda.is_available():
|
16 |
+
DESCRIPTION += "\n<p>Running on CPU 🥶 This demo does not work on CPU.</p>"
|
17 |
|
18 |
MAX_SEED = np.iinfo(np.int32).max
|
19 |
+
CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv("CACHE_EXAMPLES") == "1"
|
20 |
+
MAX_IMAGE_SIZE = int(os.getenv("MAX_IMAGE_SIZE", "1024"))
|
21 |
+
USE_TORCH_COMPILE = os.getenv("USE_TORCH_COMPILE") == "1"
|
22 |
+
ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD") == "1"
|
23 |
+
ENABLE_REFINER = os.getenv("ENABLE_REFINER", "1") == "1"
|
|
|
24 |
|
25 |
+
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
|
26 |
if torch.cuda.is_available():
|
27 |
pipe = DiffusionPipeline.from_pretrained(
|
28 |
+
"stabilityai/stable-diffusion-xl-base-1.0",
|
29 |
torch_dtype=torch.float16,
|
30 |
use_safetensors=True,
|
31 |
+
variant="fp16",
|
32 |
+
)
|
33 |
if ENABLE_REFINER:
|
34 |
refiner = DiffusionPipeline.from_pretrained(
|
35 |
+
"stabilityai/stable-diffusion-xl-refiner-1.0",
|
36 |
torch_dtype=torch.float16,
|
37 |
use_safetensors=True,
|
38 |
+
variant="fp16",
|
39 |
+
)
|
40 |
|
41 |
if ENABLE_CPU_OFFLOAD:
|
42 |
pipe.enable_model_cpu_offload()
|
|
|
48 |
refiner.to(device)
|
49 |
|
50 |
if USE_TORCH_COMPILE:
|
51 |
+
pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
|
|
|
|
|
52 |
if ENABLE_REFINER:
|
53 |
+
refiner.unet = torch.compile(refiner.unet, mode="reduce-overhead", fullgraph=True)
|
|
|
|
|
54 |
else:
|
55 |
pipe = None
|
56 |
refiner = None
|
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|
62 |
return seed
|
63 |
|
64 |
|
65 |
+
def generate(
|
66 |
+
prompt: str,
|
67 |
+
negative_prompt: str = "",
|
68 |
+
prompt_2: str = "",
|
69 |
+
negative_prompt_2: str = "",
|
70 |
+
use_negative_prompt: bool = False,
|
71 |
+
use_prompt_2: bool = False,
|
72 |
+
use_negative_prompt_2: bool = False,
|
73 |
+
seed: int = 0,
|
74 |
+
width: int = 1024,
|
75 |
+
height: int = 1024,
|
76 |
+
guidance_scale_base: float = 5.0,
|
77 |
+
guidance_scale_refiner: float = 5.0,
|
78 |
+
num_inference_steps_base: int = 50,
|
79 |
+
num_inference_steps_refiner: int = 50,
|
80 |
+
apply_refiner: bool = False,
|
81 |
+
) -> PIL.Image.Image:
|
82 |
generator = torch.Generator().manual_seed(seed)
|
83 |
|
84 |
if not use_negative_prompt:
|
|
|
89 |
negative_prompt_2 = None # type: ignore
|
90 |
|
91 |
if not apply_refiner:
|
92 |
+
return pipe(
|
93 |
+
prompt=prompt,
|
94 |
+
negative_prompt=negative_prompt,
|
95 |
+
prompt_2=prompt_2,
|
96 |
+
negative_prompt_2=negative_prompt_2,
|
97 |
+
width=width,
|
98 |
+
height=height,
|
99 |
+
guidance_scale=guidance_scale_base,
|
100 |
+
num_inference_steps=num_inference_steps_base,
|
101 |
+
generator=generator,
|
102 |
+
output_type="pil",
|
103 |
+
).images[0]
|
104 |
else:
|
105 |
+
latents = pipe(
|
106 |
+
prompt=prompt,
|
107 |
+
negative_prompt=negative_prompt,
|
108 |
+
prompt_2=prompt_2,
|
109 |
+
negative_prompt_2=negative_prompt_2,
|
110 |
+
width=width,
|
111 |
+
height=height,
|
112 |
+
guidance_scale=guidance_scale_base,
|
113 |
+
num_inference_steps=num_inference_steps_base,
|
114 |
+
generator=generator,
|
115 |
+
output_type="latent",
|
116 |
+
).images
|
117 |
+
image = refiner(
|
118 |
+
prompt=prompt,
|
119 |
+
negative_prompt=negative_prompt,
|
120 |
+
prompt_2=prompt_2,
|
121 |
+
negative_prompt_2=negative_prompt_2,
|
122 |
+
guidance_scale=guidance_scale_refiner,
|
123 |
+
num_inference_steps=num_inference_steps_refiner,
|
124 |
+
image=latents,
|
125 |
+
generator=generator,
|
126 |
+
).images[0]
|
127 |
return image
|
128 |
|
129 |
|
130 |
examples = [
|
131 |
+
"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
|
132 |
+
"An astronaut riding a green horse",
|
133 |
]
|
134 |
|
135 |
+
with gr.Blocks(css="style.css") as demo:
|
136 |
gr.Markdown(DESCRIPTION)
|
137 |
+
gr.DuplicateButton(
|
138 |
+
value="Duplicate Space for private use",
|
139 |
+
elem_id="duplicate-button",
|
140 |
+
visible=os.getenv("SHOW_DUPLICATE_BUTTON") == "1",
|
141 |
+
)
|
142 |
with gr.Group():
|
143 |
with gr.Row():
|
144 |
prompt = gr.Text(
|
145 |
+
label="Prompt",
|
146 |
show_label=False,
|
147 |
max_lines=1,
|
148 |
+
placeholder="Enter your prompt",
|
149 |
container=False,
|
150 |
)
|
151 |
+
run_button = gr.Button("Run", scale=0)
|
152 |
+
result = gr.Image(label="Result", show_label=False)
|
153 |
+
with gr.Accordion("Advanced options", open=False):
|
154 |
with gr.Row():
|
155 |
+
use_negative_prompt = gr.Checkbox(label="Use negative prompt", value=False)
|
156 |
+
use_prompt_2 = gr.Checkbox(label="Use prompt 2", value=False)
|
157 |
+
use_negative_prompt_2 = gr.Checkbox(label="Use negative prompt 2", value=False)
|
|
|
|
|
158 |
negative_prompt = gr.Text(
|
159 |
+
label="Negative prompt",
|
160 |
max_lines=1,
|
161 |
+
placeholder="Enter a negative prompt",
|
162 |
visible=False,
|
163 |
)
|
164 |
prompt_2 = gr.Text(
|
165 |
+
label="Prompt 2",
|
166 |
max_lines=1,
|
167 |
+
placeholder="Enter your prompt",
|
168 |
visible=False,
|
169 |
)
|
170 |
negative_prompt_2 = gr.Text(
|
171 |
+
label="Negative prompt 2",
|
172 |
max_lines=1,
|
173 |
+
placeholder="Enter a negative prompt",
|
174 |
visible=False,
|
175 |
)
|
176 |
|
177 |
+
seed = gr.Slider(
|
178 |
+
label="Seed",
|
179 |
+
minimum=0,
|
180 |
+
maximum=MAX_SEED,
|
181 |
+
step=1,
|
182 |
+
value=0,
|
183 |
+
)
|
184 |
+
randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
|
185 |
with gr.Row():
|
186 |
width = gr.Slider(
|
187 |
+
label="Width",
|
188 |
minimum=256,
|
189 |
maximum=MAX_IMAGE_SIZE,
|
190 |
step=32,
|
191 |
value=1024,
|
192 |
)
|
193 |
height = gr.Slider(
|
194 |
+
label="Height",
|
195 |
minimum=256,
|
196 |
maximum=MAX_IMAGE_SIZE,
|
197 |
step=32,
|
198 |
value=1024,
|
199 |
)
|
200 |
+
apply_refiner = gr.Checkbox(label="Apply refiner", value=False, visible=ENABLE_REFINER)
|
|
|
|
|
201 |
with gr.Row():
|
202 |
+
guidance_scale_base = gr.Slider(
|
203 |
+
label="Guidance scale for base",
|
204 |
+
minimum=1,
|
205 |
+
maximum=20,
|
206 |
+
step=0.1,
|
207 |
+
value=5.0,
|
208 |
+
)
|
209 |
num_inference_steps_base = gr.Slider(
|
210 |
+
label="Number of inference steps for base",
|
211 |
minimum=10,
|
212 |
maximum=100,
|
213 |
step=1,
|
214 |
+
value=50,
|
215 |
+
)
|
216 |
with gr.Row(visible=False) as refiner_params:
|
217 |
guidance_scale_refiner = gr.Slider(
|
218 |
+
label="Guidance scale for refiner",
|
219 |
minimum=1,
|
220 |
maximum=20,
|
221 |
step=0.1,
|
222 |
+
value=5.0,
|
223 |
+
)
|
224 |
num_inference_steps_refiner = gr.Slider(
|
225 |
+
label="Number of inference steps for refiner",
|
226 |
minimum=10,
|
227 |
maximum=100,
|
228 |
step=1,
|
229 |
+
value=50,
|
230 |
+
)
|
231 |
|
232 |
+
gr.Examples(
|
233 |
+
examples=examples,
|
234 |
+
inputs=prompt,
|
235 |
+
outputs=result,
|
236 |
+
fn=generate,
|
237 |
+
cache_examples=CACHE_EXAMPLES,
|
238 |
+
)
|
239 |
|
240 |
use_negative_prompt.change(
|
241 |
fn=lambda x: gr.update(visible=x),
|
|
|
293 |
fn=generate,
|
294 |
inputs=inputs,
|
295 |
outputs=result,
|
296 |
+
api_name="run",
|
297 |
)
|
298 |
negative_prompt.submit(
|
299 |
fn=randomize_seed_fn,
|
|
|
343 |
outputs=result,
|
344 |
api_name=False,
|
345 |
)
|
346 |
+
|
347 |
+
if __name__ == "__main__":
|
348 |
+
demo.queue(max_size=20).launch()
|
notebook.ipynb
CHANGED
@@ -51,47 +51,9 @@
|
|
51 |
"source": [
|
52 |
"import os\n",
|
53 |
"\n",
|
54 |
-
"
|
55 |
-
|
56 |
-
|
57 |
-
{
|
58 |
-
"cell_type": "code",
|
59 |
-
"execution_count": null,
|
60 |
-
"metadata": {
|
61 |
-
"colab": {
|
62 |
-
"base_uri": "https://localhost:8080/",
|
63 |
-
"height": 710,
|
64 |
-
"referenced_widgets": [
|
65 |
-
"68c1e33d84b94f009db258e278fe7068",
|
66 |
-
"b1b1ca6d1cc44a738c3b4b6de17f3a5b",
|
67 |
-
"104833166be14046873bfea2c1a2a887",
|
68 |
-
"32f25821a48d4c9589f58c134e3b56d7",
|
69 |
-
"3ed7cc7759074df58a91fd7fb28a4933",
|
70 |
-
"c8885bd4a35d4cdcbb6acce5c52e15e2",
|
71 |
-
"5d1d83dfd090460d9f948b71f95aaed8",
|
72 |
-
"773e06ed1d734e53a7def5305cd35131",
|
73 |
-
"753b336dbeb147349e4520715035d8da",
|
74 |
-
"c5215236213242b89a971a1095afcea5",
|
75 |
-
"bd0a6a0e16944533b59eaa3f5188e99f",
|
76 |
-
"96b1de32a367400bba75babd39bc7308",
|
77 |
-
"65291f8203964f4499a1b422af91f75e",
|
78 |
-
"0c3fad2a850b4320b47586ff4d0ac73e",
|
79 |
-
"69a6be1033c5424988a702c5d69590ee",
|
80 |
-
"b22729413d9b449a94892b91d95cf1e4",
|
81 |
-
"6c8f51c69f394eeea67eb515831f60b2",
|
82 |
-
"bb779e8367e44a939d607ace70493d94",
|
83 |
-
"4d3862b22c3245d8b3d8b6442e149c8d",
|
84 |
-
"16ef5a40c9d441aea180d1732442df97",
|
85 |
-
"db54ca7070cf43adbda196d44967464c",
|
86 |
-
"cadddb2624804c308710a219bf8cf4f3"
|
87 |
-
]
|
88 |
-
},
|
89 |
-
"id": "4FTmJkt_J8j_",
|
90 |
-
"outputId": "850aba86-acb4-4452-bac2-28b5c815ec0f"
|
91 |
-
},
|
92 |
-
"outputs": [],
|
93 |
-
"source": [
|
94 |
-
"import app"
|
95 |
]
|
96 |
},
|
97 |
{
|
|
|
51 |
"source": [
|
52 |
"import os\n",
|
53 |
"\n",
|
54 |
+
"import app\n",
|
55 |
+
"\n",
|
56 |
+
"os.environ[\"ENABLE_REFINER\"] = \"0\""
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
57 |
]
|
58 |
},
|
59 |
{
|