fixed save quantization
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@@ -949,11 +949,11 @@ class HunyuanVideoPipeline(DiffusionPipeline):
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# width = width or self.transformer.config.sample_size * self.vae_scale_factor
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# to deal with lora scaling and other possible forward hooks
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trans = self.transformer
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if trans.enable_teacache:
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if trans.enable_cache:
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teacache_multiplier = trans.teacache_multiplier
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trans.accumulated_rel_l1_distance = 0
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trans.rel_l1_thresh = 0.1 if teacache_multiplier < 2 else 0.15
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# trans.teacache_start_step = int(tea_cache_start_step_perc*num_inference_steps/100)
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# trans.cache_start_step = int(tea_cache_start_step_perc*num_inference_steps/100)
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# 1. Check inputs. Raise error if not correct
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self.check_inputs(
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prompt,
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@@ -1208,7 +1208,7 @@ class HunyuanVideoPipeline(DiffusionPipeline):
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if ip_cfg_scale>0:
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latent_items += 1
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if self.transformer.enable_teacache:
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if self.transformer.enable_cache:
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self.transformer.previous_residual = [None] * latent_items
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# if is_progress_bar:
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