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Upload h3_split_blocks.py with huggingface_hub

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  1. h3_split_blocks.py +147 -0
h3_split_blocks.py ADDED
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+ """Composable conditioner and generator halves of MiniMax-H3, for both checkpoint partitions.
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+
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+ The blocks cut `MiniMaxH3Blocks` at its `text_encoder` step. They can run in separate Spaces with `prompt_embeds` and
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+ `text_token_tags` as a wire format, or sequentially in one GPU worker when a compact local conditioner fits beside
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+ the generator.
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+
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+ `resize` / `setup` run on **both** sides: they own no pretrained component, and each half needs the canvas and the
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+ prepared keyframes or normalized references. Both conditioner halves also return the resolved `height` / `width` /
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+ `num_frames`, which the generating half pins rather than re-deriving.
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+
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+ Two things the blocks leave to the caller: a keyframe reaches them EXIF-transposed and in RGB, and the `t2va` / `fl2va`
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+ frame count is aligned to `17 * n + 5` before the call, since that arithmetic lives on the denoising side of the cut.
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+ """
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+
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+ from diffusers.modular_pipelines.minimax_h3.before_encoder import MiniMaxH3Ref2VASetupStep
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+ from diffusers.modular_pipelines.minimax_h3.decoders import MiniMaxH3AfterDenoiseStep
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+ from diffusers.modular_pipelines.minimax_h3.encoders import (
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+ MiniMaxH3Ref2VAReferenceEncoderStep,
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+ MiniMaxH3Ref2VATextEncoderStep,
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+ MiniMaxH3TextEncoderStep,
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+ )
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+ from diffusers.modular_pipelines.minimax_h3.modular_blocks_minimax_h3 import (
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+ MiniMaxH3AutoKeyframeVaeEncoderStep,
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+ MiniMaxH3AutoResizeStep,
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+ MiniMaxH3CoreDenoiseStep,
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+ MiniMaxH3DecodeStep,
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+ MiniMaxH3Ref2VACoreDenoiseStep,
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+ _generation_outputs,
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+ )
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+ from diffusers.modular_pipelines.modular_pipeline import SequentialPipelineBlocks
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+ from diffusers.modular_pipelines.modular_pipeline_utils import OutputParam
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+
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+
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+ def _wire_outputs(num_frames: bool = True) -> list[OutputParam]:
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+ """The wire format of the split. `num_frames` is declared by the `ref2va` half alone, whose setup resolves one."""
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+ return [
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+ OutputParam.template("prompt_embeds"),
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+ OutputParam("text_token_tags", description="The per-row modality tag of every row of `prompt_embeds`."),
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+ OutputParam("height", type_hint=int, description="Resolved height of the generated video in pixels."),
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+ OutputParam("width", type_hint=int, description="Resolved width of the generated video in pixels."),
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+ *(
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+ [OutputParam("num_frames", type_hint=int, description="Resolved number of frames, of the form 17 * n + 5.")]
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+ if num_frames
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+ else []
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+ ),
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+ ]
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+
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+
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+ class MiniMaxH3ConditionerBlocks(SequentialPipelineBlocks):
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+ """The conditioner half of a split MiniMax-H3: the keyframes on the canvas plus the Qwen3-VL read at layer 50."""
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+
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+ model_name = "minimax-h3"
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+ block_classes = [MiniMaxH3AutoResizeStep, MiniMaxH3TextEncoderStep]
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+ block_names = ["resize", "text_encoder"]
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+
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+ @property
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+ def description(self):
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+ return (
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+ "The conditioner half of a split MiniMax-H3 deployment: puts the keyframes onto the target canvas and "
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+ "encodes MiniMax-H3's presentation of the request into the `prompt_embeds` / `text_token_tags` pair the "
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+ "denoising half consumes. The frame count is the caller's to align."
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+ )
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+
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+ @property
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+ def outputs(self):
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+ return _wire_outputs(num_frames=False)
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+
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+
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+ class MiniMaxH3GeneratorBlocks(SequentialPipelineBlocks):
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+ """The denoising half of a split MiniMax-H3: `MiniMaxH3Blocks` with its `text_encoder` step removed."""
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+
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+ model_name = "minimax-h3"
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+ block_classes = [
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+ MiniMaxH3AutoResizeStep,
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+ MiniMaxH3AutoKeyframeVaeEncoderStep,
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+ MiniMaxH3CoreDenoiseStep,
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+ MiniMaxH3AfterDenoiseStep,
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+ MiniMaxH3DecodeStep,
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+ ]
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+ block_names = ["resize", "vae_encoder", "denoise", "after_denoise", "decode"]
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+
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+ @property
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+ def description(self):
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+ return (
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+ "The denoising half of a split MiniMax-H3 deployment: the `t2va` / `fl2va` branch of `MiniMaxH3Blocks` "
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+ "without its text-encoder step, so `prompt_embeds` and `text_token_tags` come in as inputs and the "
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+ "conditioner is supplied by the caller or by the preceding local conditioner half."
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+ )
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+
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+ @property
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+ def outputs(self):
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+ return _generation_outputs()
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+
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+
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+ class MiniMaxH3Ref2VAConditionerBlocks(SequentialPipelineBlocks):
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+ """The conditioner half of a split `ref2va`: the resolved plan plus the Qwen3-VL read at its 50th layer.
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+
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+ Component for component this is `MiniMaxH3ConditionerBlocks`, so one conditioner Space serves both partitions.
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+ What differs is the presentation: `ref2va` prepends a label per reference and a vision block per image and per
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+ merged video frame pair, so the references themselves have to reach this half.
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+ """
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+
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+ model_name = "minimax-h3"
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+ block_classes = [MiniMaxH3Ref2VASetupStep, MiniMaxH3Ref2VATextEncoderStep]
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+ block_names = ["setup", "text_encoder"]
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+
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+ @property
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+ def description(self):
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+ return (
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+ "The conditioner half of a split MiniMax-H3 `ref2va` deployment: resolves the request plan (canvas, frame "
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+ "count, references normalized onto MiniMax-H3's own rates and resolutions) and encodes MiniMax-H3's "
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+ "presentation of it into the `prompt_embeds` / `text_token_tags` pair the denoising half consumes."
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+ )
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+
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+ @property
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+ def outputs(self):
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+ return _wire_outputs()
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+
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+
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+ class MiniMaxH3Ref2VAGeneratorBlocks(SequentialPipelineBlocks):
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+ """The denoising half of a split `ref2va`: the `ref2va` branch with its `text_encoder` step removed.
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+
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+ `reference_encoder` stays here, next to the two autoencoders it runs: its output shapes are where every reference
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+ block's geometry in the packed layout comes from.
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+ """
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+
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+ model_name = "minimax-h3"
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+ block_classes = [
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+ MiniMaxH3Ref2VASetupStep,
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+ MiniMaxH3Ref2VAReferenceEncoderStep,
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+ MiniMaxH3Ref2VACoreDenoiseStep,
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+ MiniMaxH3AfterDenoiseStep,
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+ MiniMaxH3DecodeStep,
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+ ]
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+ block_names = ["setup", "reference_encoder", "denoise", "after_denoise", "decode"]
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+
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+ @property
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+ def description(self):
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+ return (
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+ "The denoising half of a split MiniMax-H3 `ref2va` deployment: the `ref2va` branch of `MiniMaxH3Blocks` "
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+ "without its text-encoder step, so `prompt_embeds` and `text_token_tags` come in as inputs and the "
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+ "conditioner is supplied by the caller or preceding local half. The transformer is the `transformer_ref` partition."
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+ )
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+
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+ @property
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+ def outputs(self):
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+ return _generation_outputs()