56 lines
1.7 KiB
Python
56 lines
1.7 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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"""Request parameters shared by official LTX guidance pipelines."""
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LTX_EXTRA_BODY_PARAMS = frozenset(
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{
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"video_cfg_scale",
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"audio_cfg_scale",
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"video_cfg_guidance_scale",
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"audio_cfg_guidance_scale",
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"video_stg_scale",
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"audio_stg_scale",
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"video_stg_guidance_scale",
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"audio_stg_guidance_scale",
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"video_modality_scale",
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"audio_modality_scale",
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"a2v_guidance_scale",
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"v2a_guidance_scale",
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"video_rescale_scale",
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"audio_rescale_scale",
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"video_stg_blocks",
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"audio_stg_blocks",
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"sigmas",
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"stage_1_sigmas",
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"stage_2_sigmas",
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"image_crf",
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}
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)
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LTX_EXTRA_OUTPUT_PARAMS = frozenset()
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def ltx_preserves_reference_image_size(*, model: str | None, revision: str | None = None) -> bool:
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"""Keep source geometry until LTX-2.5 applies conditioning compression."""
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if model is None:
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return False
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from vllm_omni.diffusion.models.ltx2.ltx2_components import (
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preserves_reference_image_size as ltx_preserves_reference_image_size,
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)
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return ltx_preserves_reference_image_size(model=model, revision=revision)
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def ltx_transformer_config_subfolder(
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*,
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model: str | None,
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revision: str | None = None,
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) -> str:
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"""Select the transformer config used by the requested LTX checkpoint."""
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if model is None:
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return "transformer"
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from vllm_omni.diffusion.models.ltx2.ltx2_components import detect_ltx_model_version
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return "transformer_full" if detect_ltx_model_version(model, revision=revision) == "2.5" else "transformer"
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