CoCalc -- pipeline

GitHub Repository: shivamshrirao/diffusers
Path: blob/main/tests/pipeline_params.py
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# These are canonical sets of parameters for different types of pipelines.
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# They are set on subclasses of `PipelineTesterMixin` as `params` and
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# `batch_params`.
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#
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# If a pipeline's set of arguments has minor changes from one of the common sets
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# of arguments, do not make modifications to the existing common sets of arguments.
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# I.e. a text to image pipeline with non-configurable height and width arguments
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# should set its attribute as `params = TEXT_TO_IMAGE_PARAMS - {'height', 'width'}`.
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TEXT_TO_IMAGE_PARAMS = frozenset(
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    [
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        "prompt",
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        "height",
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        "width",
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        "guidance_scale",
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        "negative_prompt",
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        "prompt_embeds",
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        "negative_prompt_embeds",
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        "cross_attention_kwargs",
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    ]
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)
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TEXT_TO_IMAGE_BATCH_PARAMS = frozenset(["prompt", "negative_prompt"])
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IMAGE_VARIATION_PARAMS = frozenset(
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    [
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        "image",
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        "height",
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        "width",
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        "guidance_scale",
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    ]
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)
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IMAGE_VARIATION_BATCH_PARAMS = frozenset(["image"])
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TEXT_GUIDED_IMAGE_VARIATION_PARAMS = frozenset(
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    [
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        "prompt",
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        "image",
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        "height",
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        "width",
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        "guidance_scale",
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        "negative_prompt",
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        "prompt_embeds",
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        "negative_prompt_embeds",
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    ]
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)
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TEXT_GUIDED_IMAGE_VARIATION_BATCH_PARAMS = frozenset(["prompt", "image", "negative_prompt"])
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TEXT_GUIDED_IMAGE_INPAINTING_PARAMS = frozenset(
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    [
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        # Text guided image variation with an image mask
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        "prompt",
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        "image",
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        "mask_image",
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        "height",
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        "width",
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        "guidance_scale",
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        "negative_prompt",
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        "prompt_embeds",
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        "negative_prompt_embeds",
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    ]
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)
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TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS = frozenset(["prompt", "image", "mask_image", "negative_prompt"])
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IMAGE_INPAINTING_PARAMS = frozenset(
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    [
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        # image variation with an image mask
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        "image",
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        "mask_image",
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        "height",
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        "width",
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        "guidance_scale",
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    ]
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)
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IMAGE_INPAINTING_BATCH_PARAMS = frozenset(["image", "mask_image"])
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IMAGE_GUIDED_IMAGE_INPAINTING_PARAMS = frozenset(
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    [
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        "example_image",
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        "image",
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        "mask_image",
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        "height",
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        "width",
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        "guidance_scale",
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    ]
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)
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IMAGE_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS = frozenset(["example_image", "image", "mask_image"])
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CLASS_CONDITIONED_IMAGE_GENERATION_PARAMS = frozenset(["class_labels"])
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CLASS_CONDITIONED_IMAGE_GENERATION_BATCH_PARAMS = frozenset(["class_labels"])
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UNCONDITIONAL_IMAGE_GENERATION_PARAMS = frozenset(["batch_size"])
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UNCONDITIONAL_IMAGE_GENERATION_BATCH_PARAMS = frozenset([])
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UNCONDITIONAL_AUDIO_GENERATION_PARAMS = frozenset(["batch_size"])
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UNCONDITIONAL_AUDIO_GENERATION_BATCH_PARAMS = frozenset([])
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TEXT_TO_AUDIO_PARAMS = frozenset(
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    [
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        "prompt",
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        "audio_length_in_s",
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        "guidance_scale",
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        "negative_prompt",
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        "prompt_embeds",
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        "negative_prompt_embeds",
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        "cross_attention_kwargs",
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    ]
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)
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TEXT_TO_AUDIO_BATCH_PARAMS = frozenset(["prompt", "negative_prompt"])
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TOKENS_TO_AUDIO_GENERATION_PARAMS = frozenset(["input_tokens"])
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TOKENS_TO_AUDIO_GENERATION_BATCH_PARAMS = frozenset(["input_tokens"])
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