min-dalle-test/replicate_predictor.py

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from contextlib import suppress
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from min_dalle import MinDalle
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import tempfile
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from typing import Iterator
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from math import log2
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from cog import BasePredictor, Path, Input
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class ReplicatePredictor(BasePredictor):
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def setup(self):
self.model = MinDalle(is_mega=True)
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def predict(
self,
text: str = Input(
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description='Text',
default='Dali painting of WALL·E'
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),
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grid_size: int = Input(
description='Size of the image grid',
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ge=1,
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le=4,
default=4
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),
seed: int = Input(
description='Set the seed to a positive number for reproducible results',
default=-1
),
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log2_intermediate_image_count: int = Input(
description='Set the total number of images to show while running. Each image adds a slight delay.',
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ge=0,
le=4,
default=2
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),
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log2_supercondition_factor: int = Input(
description='Higher values result in better agreement with the text but a narrower variety of generated images',
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ge=1,
le=6,
default=4
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),
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) -> Iterator[Path]:
image_stream = self.model.generate_image_stream(
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text,
seed,
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grid_size=grid_size,
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log2_mid_count=log2_intermediate_image_count,
log2_supercondition_factor=log2_supercondition_factor,
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is_verbose=True
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)
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iter = 0
path = Path(tempfile.mkdtemp())
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for image in image_stream:
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iter += 1
image_path = path / 'min-dalle-iter-{}.jpg'.format(iter)
image.save(str(image_path))
yield image_path