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hunyuan 1.5 flf: remove spaces from empty lines

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kabachuha 2025-12-11 20:49:45 +03:00
parent 1e4f506f03
commit a7e8008fdc
1 changed files with 14 additions and 14 deletions
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comfy_extras/nodes_hunyuan.py
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@ -154,35 +154,35 @@ class HunyuanVideo15FirstLastFrameToVideo(io.ComfyNode):
@classmethod @classmethod
def execute(cls, positive, negative, vae, width, height, length, batch_size, start_image=None, end_image=None, clip_vision_start_image=None, clip_vision_end_image=None) -> io.NodeOutput: def execute(cls, positive, negative, vae, width, height, length, batch_size, start_image=None, end_image=None, clip_vision_start_image=None, clip_vision_end_image=None) -> io.NodeOutput:
latent = torch.zeros([batch_size, 32, ((length - 1) // 4) + 1, height // 16, width // 16], latent = torch.zeros([batch_size, 32, ((length - 1) // 4) + 1, height // 16, width // 16],
device=comfy.model_management.intermediate_device()) device=comfy.model_management.intermediate_device())
concat_latent_image = torch.zeros((batch_size, 32, latent.shape[2], latent.shape[3], latent.shape[4]), concat_latent_image = torch.zeros((batch_size, 32, latent.shape[2], latent.shape[3], latent.shape[4]),
device=comfy.model_management.intermediate_device()) device=comfy.model_management.intermediate_device())
mask = torch.ones((1, 1, latent.shape[2], latent.shape[3], latent.shape[4]), mask = torch.ones((1, 1, latent.shape[2], latent.shape[3], latent.shape[4]),
device=comfy.model_management.intermediate_device()) device=comfy.model_management.intermediate_device())
if start_image is not None: if start_image is not None:
start_image = comfy.utils.common_upscale(start_image[:length].movedim(-1, 1), width, height, "bilinear", "center").movedim(1, -1) start_image = comfy.utils.common_upscale(start_image[:length].movedim(-1, 1), width, height, "bilinear", "center").movedim(1, -1)
encoded_start = vae.encode(start_image[:, :, :, :3]) encoded_start = vae.encode(start_image[:, :, :, :3])
concat_latent_image[:, :, :encoded_start.shape[2], :, :] = encoded_start concat_latent_image[:, :, :encoded_start.shape[2], :, :] = encoded_start
start_frames_in_latent = ((start_image.shape[0] - 1) // 4) + 1 start_frames_in_latent = ((start_image.shape[0] - 1) // 4) + 1
mask[:, :, :start_frames_in_latent] = 0.0 mask[:, :, :start_frames_in_latent] = 0.0
if end_image is not None: if end_image is not None:
end_image = comfy.utils.common_upscale(end_image[-length:].movedim(-1, 1), width, height, "bilinear", "center").movedim(1, -1) end_image = comfy.utils.common_upscale(end_image[-length:].movedim(-1, 1), width, height, "bilinear", "center").movedim(1, -1)
encoded_end = vae.encode(end_image[:, :, :, :3]) encoded_end = vae.encode(end_image[:, :, :, :3])
end_frames_in_latent = ((end_image.shape[0] - 1) // 4) + 1 end_frames_in_latent = ((end_image.shape[0] - 1) // 4) + 1
concat_latent_image[:, :, -end_frames_in_latent:, :, :] = encoded_end[:, :, -end_frames_in_latent:, :, :] concat_latent_image[:, :, -end_frames_in_latent:, :, :] = encoded_end[:, :, -end_frames_in_latent:, :, :]
mask[:, :, -end_frames_in_latent:] = 0.0 mask[:, :, -end_frames_in_latent:] = 0.0
positive = node_helpers.conditioning_set_values(positive, {"concat_latent_image": concat_latent_image, "concat_mask": mask}) positive = node_helpers.conditioning_set_values(positive, {"concat_latent_image": concat_latent_image, "concat_mask": mask})
negative = node_helpers.conditioning_set_values(negative, {"concat_latent_image": concat_latent_image, "concat_mask": mask}) negative = node_helpers.conditioning_set_values(negative, {"concat_latent_image": concat_latent_image, "concat_mask": mask})