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‎src/diffusers/modular_pipelines/hunyuan_video1_5/modular_blocks_hunyuan_video1_5.py‎

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@@ -31,6 +31,57 @@
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# auto_docstring
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class HunyuanVideo15CoreDenoiseStep(SequentialPipelineBlocks):
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"""
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Denoise block that takes encoded conditions and runs the denoising process.
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Components:
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transformer (`HunyuanVideo15Transformer3DModel`)
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scheduler (`FlowMatchEulerDiscreteScheduler`)
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guider (`ClassifierFreeGuidance`)
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Inputs:
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num_videos_per_prompt (`None`, *optional*, defaults to 1):
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TODO: Add description.
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prompt_embeds (`Tensor`):
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TODO: Add description.
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batch_size (`int`, *optional*):
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TODO: Add description.
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num_inference_steps (`None`, *optional*, defaults to 50):
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TODO: Add description.
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sigmas (`None`, *optional*):
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TODO: Add description.
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height (`int`, *optional*):
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TODO: Add description.
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width (`int`, *optional*):
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TODO: Add description.
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num_frames (`int`, *optional*, defaults to 121):
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TODO: Add description.
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latents (`Tensor | NoneType`, *optional*):
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TODO: Add description.
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generator (`None`, *optional*):
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TODO: Add description.
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attention_kwargs (`None`, *optional*):
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TODO: Add description.
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negative_prompt_embeds (`Tensor`, *optional*):
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TODO: Add description.
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prompt_embeds_mask (`Tensor`):
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TODO: Add description.
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negative_prompt_embeds_mask (`Tensor`, *optional*):
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TODO: Add description.
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prompt_embeds_2 (`Tensor`):
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TODO: Add description.
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negative_prompt_embeds_2 (`Tensor`, *optional*):
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TODO: Add description.
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prompt_embeds_mask_2 (`Tensor`):
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TODO: Add description.
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negative_prompt_embeds_mask_2 (`Tensor`, *optional*):
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TODO: Add description.
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Outputs:
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latents (`Tensor`):
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Denoised latents.
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"""
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model_name = "hunyuan-video-1.5"
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block_classes = [
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HunyuanVideo15TextInputStep,
@@ -51,6 +102,69 @@ def outputs(self):
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# auto_docstring
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class HunyuanVideo15Blocks(SequentialPipelineBlocks):
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"""
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Modular pipeline blocks for HunyuanVideo 1.5 text-to-video.
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Components:
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text_encoder (`Qwen2_5_VLTextModel`)
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tokenizer (`Qwen2TokenizerFast`)
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text_encoder_2 (`T5EncoderModel`)
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tokenizer_2 (`ByT5Tokenizer`)
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guider (`ClassifierFreeGuidance`)
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transformer (`HunyuanVideo15Transformer3DModel`)
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scheduler (`FlowMatchEulerDiscreteScheduler`)
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vae (`AutoencoderKLHunyuanVideo15`)
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video_processor (`HunyuanVideo15ImageProcessor`)
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Inputs:
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prompt (`None`, *optional*):
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TODO: Add description.
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negative_prompt (`None`, *optional*):
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TODO: Add description.
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prompt_embeds (`Tensor`, *optional*):
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TODO: Add description.
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prompt_embeds_mask (`Tensor`, *optional*):
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TODO: Add description.
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negative_prompt_embeds (`Tensor`, *optional*):
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TODO: Add description.
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negative_prompt_embeds_mask (`Tensor`, *optional*):
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TODO: Add description.
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prompt_embeds_2 (`Tensor`, *optional*):
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TODO: Add description.
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prompt_embeds_mask_2 (`Tensor`, *optional*):
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TODO: Add description.
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negative_prompt_embeds_2 (`Tensor`, *optional*):
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TODO: Add description.
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negative_prompt_embeds_mask_2 (`Tensor`, *optional*):
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TODO: Add description.
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num_videos_per_prompt (`int`, *optional*, defaults to 1):
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TODO: Add description.
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batch_size (`int`, *optional*):
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TODO: Add description.
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num_inference_steps (`None`, *optional*, defaults to 50):
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TODO: Add description.
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sigmas (`None`, *optional*):
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TODO: Add description.
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height (`int`, *optional*):
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TODO: Add description.
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width (`int`, *optional*):
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TODO: Add description.
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num_frames (`int`, *optional*, defaults to 121):
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TODO: Add description.
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latents (`Tensor | NoneType`, *optional*):
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TODO: Add description.
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generator (`None`, *optional*):
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TODO: Add description.
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attention_kwargs (`None`, *optional*):
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TODO: Add description.
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output_type (`str`, *optional*, defaults to np):
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TODO: Add description.
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Outputs:
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videos (`list`):
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The generated videos.
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"""
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model_name = "hunyuan-video-1.5"
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block_classes = [
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HunyuanVideo15TextEncoderStep,
@@ -70,6 +184,59 @@ def outputs(self):
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# auto_docstring
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class HunyuanVideo15Image2VideoCoreDenoiseStep(SequentialPipelineBlocks):
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"""
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Denoise block for image-to-video that takes encoded conditions and runs the denoising process.
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Components:
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transformer (`HunyuanVideo15Transformer3DModel`)
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scheduler (`FlowMatchEulerDiscreteScheduler`)
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vae (`AutoencoderKLHunyuanVideo15`)
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video_processor (`HunyuanVideo15ImageProcessor`)
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image_encoder (`SiglipVisionModel`)
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feature_extractor (`SiglipImageProcessor`)
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guider (`ClassifierFreeGuidance`)
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Inputs:
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num_videos_per_prompt (`None`, *optional*, defaults to 1):
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TODO: Add description.
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prompt_embeds (`Tensor`):
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TODO: Add description.
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batch_size (`int`, *optional*):
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TODO: Add description.
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num_inference_steps (`None`, *optional*, defaults to 50):
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TODO: Add description.
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sigmas (`None`, *optional*):
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TODO: Add description.
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image (`None`):
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TODO: Add description.
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num_frames (`int`, *optional*, defaults to 121):
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TODO: Add description.
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latents (`Tensor | NoneType`, *optional*):
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TODO: Add description.
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generator (`None`, *optional*):
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TODO: Add description.
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attention_kwargs (`None`, *optional*):
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TODO: Add description.
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negative_prompt_embeds (`Tensor`, *optional*):
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TODO: Add description.
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prompt_embeds_mask (`Tensor`):
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TODO: Add description.
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negative_prompt_embeds_mask (`Tensor`, *optional*):
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TODO: Add description.
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prompt_embeds_2 (`Tensor`):
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TODO: Add description.
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negative_prompt_embeds_2 (`Tensor`, *optional*):
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TODO: Add description.
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prompt_embeds_mask_2 (`Tensor`):
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TODO: Add description.
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negative_prompt_embeds_mask_2 (`Tensor`, *optional*):
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TODO: Add description.
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Outputs:
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latents (`Tensor`):
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Denoised latents.
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"""
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model_name = "hunyuan-video-1.5"
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block_classes = [
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HunyuanVideo15TextInputStep,
@@ -90,6 +257,69 @@ def outputs(self):
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# auto_docstring
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class HunyuanVideo15Image2VideoBlocks(SequentialPipelineBlocks):
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"""
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Modular pipeline blocks for HunyuanVideo 1.5 image-to-video.
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Components:
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text_encoder (`Qwen2_5_VLTextModel`)
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tokenizer (`Qwen2TokenizerFast`)
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text_encoder_2 (`T5EncoderModel`)
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tokenizer_2 (`ByT5Tokenizer`)
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guider (`ClassifierFreeGuidance`)
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transformer (`HunyuanVideo15Transformer3DModel`)
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scheduler (`FlowMatchEulerDiscreteScheduler`)
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vae (`AutoencoderKLHunyuanVideo15`)
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video_processor (`HunyuanVideo15ImageProcessor`)
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image_encoder (`SiglipVisionModel`)
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feature_extractor (`SiglipImageProcessor`)
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Inputs:
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prompt (`None`, *optional*):
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TODO: Add description.
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negative_prompt (`None`, *optional*):
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TODO: Add description.
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prompt_embeds (`Tensor`, *optional*):
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TODO: Add description.
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prompt_embeds_mask (`Tensor`, *optional*):
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TODO: Add description.
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negative_prompt_embeds (`Tensor`, *optional*):
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TODO: Add description.
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negative_prompt_embeds_mask (`Tensor`, *optional*):
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TODO: Add description.
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prompt_embeds_2 (`Tensor`, *optional*):
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TODO: Add description.
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prompt_embeds_mask_2 (`Tensor`, *optional*):
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TODO: Add description.
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negative_prompt_embeds_2 (`Tensor`, *optional*):
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TODO: Add description.
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negative_prompt_embeds_mask_2 (`Tensor`, *optional*):
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TODO: Add description.
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num_videos_per_prompt (`int`, *optional*, defaults to 1):
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TODO: Add description.
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batch_size (`int`, *optional*):
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TODO: Add description.
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num_inference_steps (`None`, *optional*, defaults to 50):
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TODO: Add description.
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sigmas (`None`, *optional*):
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TODO: Add description.
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image (`None`):
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TODO: Add description.
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num_frames (`int`, *optional*, defaults to 121):
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TODO: Add description.
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latents (`Tensor | NoneType`, *optional*):
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TODO: Add description.
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generator (`None`, *optional*):
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TODO: Add description.
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attention_kwargs (`None`, *optional*):
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TODO: Add description.
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output_type (`str`, *optional*, defaults to np):
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TODO: Add description.
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Outputs:
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videos (`list`):
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The generated videos.
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"""
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model_name = "hunyuan-video-1.5"
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block_classes = [
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HunyuanVideo15TextEncoderStep,

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