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fixed save quantization

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This commit is contained in:
DeepBeepMeep
2025-06-13 18:41:35 +02:00
parent 5a63326bb9
commit 73cf4e43c3
12 changed files with 116 additions and 64 deletions
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6
hyvideo/diffusion/pipelines/pipeline_hunyuan_video.py
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@@ -949,11 +949,11 @@ class HunyuanVideoPipeline(DiffusionPipeline):
# width = width or self.transformer.config.sample_size * self.vae_scale_factor
# to deal with lora scaling and other possible forward hooks
trans = self.transformer
if trans.enable_teacache:
if trans.enable_cache:
teacache_multiplier = trans.teacache_multiplier
trans.accumulated_rel_l1_distance = 0
trans.rel_l1_thresh = 0.1 if teacache_multiplier < 2 else 0.15
# trans.teacache_start_step = int(tea_cache_start_step_perc*num_inference_steps/100)
# trans.cache_start_step = int(tea_cache_start_step_perc*num_inference_steps/100)
# 1. Check inputs. Raise error if not correct
self.check_inputs(
prompt,
@@ -1208,7 +1208,7 @@ class HunyuanVideoPipeline(DiffusionPipeline):
if ip_cfg_scale>0:
latent_items += 1
if self.transformer.enable_teacache:
if self.transformer.enable_cache:
self.transformer.previous_residual = [None] * latent_items
# if is_progress_bar:

8
hyvideo/diffusion/pipelines/pipeline_hunyuan_video_audio.py
View File

@@ -934,7 +934,7 @@ class HunyuanVideoAudioPipeline(DiffusionPipeline):
transformer = self.transformer
if transformer.enable_teacache:
if transformer.enable_cache:
teacache_multiplier = transformer.teacache_multiplier
transformer.accumulated_rel_l1_distance = 0
transformer.rel_l1_thresh = 0.1 if teacache_multiplier < 2 else 0.15
@@ -1136,7 +1136,7 @@ class HunyuanVideoAudioPipeline(DiffusionPipeline):
if self._interrupt:
return [None]
if transformer.enable_teacache:
if transformer.enable_cache:
cache_size = round( infer_length / frames_per_batch )
transformer.previous_residual = [None] * latent_items
cache_all_previous_residual = [None] * latent_items
@@ -1180,7 +1180,7 @@ class HunyuanVideoAudioPipeline(DiffusionPipeline):
img_ref_len = (latent_model_input.shape[-1] // 2) * (latent_model_input.shape[-2] // 2) * ( 1)
img_all_len = (latents_all.shape[-1] // 2) * (latents_all.shape[-2] // 2) * latents_all.shape[-3]
if transformer.enable_teacache and cache_size > 1:
if transformer.enable_cache and cache_size > 1:
for l in range(latent_items):
if cache_all_previous_residual[l] != None:
bsz = cache_all_previous_residual[l].shape[0]
@@ -1297,7 +1297,7 @@ class HunyuanVideoAudioPipeline(DiffusionPipeline):
pred_latents[:, :, p] += latents[:, :, iii]
counter[:, :, p] += 1
if transformer.enable_teacache and cache_size > 1:
if transformer.enable_cache and cache_size > 1:
for l in range(latent_items):
if transformer.previous_residual[l] != None:
bsz = transformer.previous_residual[l].shape[0]