69 lines
1.4 KiB
Python
69 lines
1.4 KiB
Python
"""
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Data model for the riffusion API.
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"""
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from dataclasses import dataclass
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import typing as T
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@dataclass(frozen=True)
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class PromptInput:
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"""
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Parameters for one end of interpolation.
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"""
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# Text prompt fed into a CLIP model
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prompt: str
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# Random seed for denoising
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seed: int
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# Denoising strength
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denoising: float = 0.75
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# Classifier-free guidance strength
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guidance: float = 7.0
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@dataclass(frozen=True)
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class InferenceInput:
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"""
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Parameters for a single run of the riffusion model, interpolating between
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a start and end set of PromptInputs. This is the API required for a request
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to the model server.
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"""
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# Start point of interpolation
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start: PromptInput
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# End point of interpolation
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end: PromptInput
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# Interpolation alpha [0, 1]. A value of 0 uses start fully, a value of 1
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# uses end fully.
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alpha: float
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# Number of inner loops of the diffusion model
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num_inference_steps: int = 50
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# Which seed image to use
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seed_image_id: str = "og_beat"
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# ID of mask image to use
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mask_image_id: T.Optional[str] = None
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@dataclass(frozen=True)
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class InferenceOutput:
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"""
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Response from the model inference server.
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"""
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# base64 encoded spectrogram image as a JPEG
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image: str
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# base64 encoded audio clip as an MP3
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audio: str
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# The duration of the audio clip
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duration_s: float
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