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fixed standin with boost off

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deepbeepmeep 2025-08-30 16:10:19 +02:00
parent 336e941183
commit 6490af145a
2 changed files with 7 additions and 7 deletions
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4
models/wan/modules/model.py
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@ -1306,7 +1306,7 @@ class WanModel(ModelMixin, ConfigMixin):
if standin_ref is not None: if standin_ref is not None:
standin_cache_enabled = False standin_cache_enabled = False
kwargs["standin_phase"] = 2 kwargs["standin_phase"] = 2
if (current_step == 0 or not standin_cache_enabled) and x_id == 0: if current_step == 0 or not standin_cache_enabled :
standin_x = self.patch_embedding(standin_ref).to(modulation_dtype).flatten(2).transpose(1, 2) standin_x = self.patch_embedding(standin_ref).to(modulation_dtype).flatten(2).transpose(1, 2)
standin_e = self.time_embedding( sinusoidal_embedding_1d(self.freq_dim, torch.zeros_like(t)).to(modulation_dtype) ) standin_e = self.time_embedding( sinusoidal_embedding_1d(self.freq_dim, torch.zeros_like(t)).to(modulation_dtype) )
standin_e0 = self.time_projection(standin_e).unflatten(1, (6, self.dim)).to(e.dtype) standin_e0 = self.time_projection(standin_e).unflatten(1, (6, self.dim)).to(e.dtype)
@ -1453,7 +1453,7 @@ class WanModel(ModelMixin, ConfigMixin):
return [None] * len(x_list) return [None] * len(x_list)
if standin_x is not None: if standin_x is not None:
if not standin_cache_enabled and x_id ==0 : get_cache("standin").clear() if not standin_cache_enabled: get_cache("standin").clear()
standin_x = block(standin_x, context = None, grid_sizes = None, e= standin_e0, freqs = standin_freqs, standin_phase = 1) standin_x = block(standin_x, context = None, grid_sizes = None, e= standin_e0, freqs = standin_freqs, standin_phase = 1)
if slg_layers is not None and block_idx in slg_layers: if slg_layers is not None and block_idx in slg_layers:

10
wgp.py
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@ -1,4 +1,8 @@
import os import os
# # os.environ.pop("TORCH_LOGS", None) # make sure no env var is suppressing/overriding
# os.environ["TORCH_LOGS"]= "recompiles"
import torch._logging as tlog
# tlog.set_logs(recompiles=True, guards=True, graph_breaks=True)
import time import time
import sys import sys
import threading import threading
@ -55,7 +59,7 @@ AUTOSAVE_FILENAME = "queue.zip"
PROMPT_VARS_MAX = 10 PROMPT_VARS_MAX = 10
target_mmgp_version = "3.5.10" target_mmgp_version = "3.5.10"
WanGP_version = "8.2" WanGP_version = "8.21"
settings_version = 2.27 settings_version = 2.27
max_source_video_frames = 3000 max_source_video_frames = 3000
prompt_enhancer_image_caption_model, prompt_enhancer_image_caption_processor, prompt_enhancer_llm_model, prompt_enhancer_llm_tokenizer = None, None, None, None prompt_enhancer_image_caption_model, prompt_enhancer_image_caption_processor, prompt_enhancer_llm_model, prompt_enhancer_llm_tokenizer = None, None, None, None
@ -4308,10 +4312,6 @@ def generate_video(
model_filename, model_filename,
mode, mode,
): ):
# import os
# os.environ.pop("TORCH_LOGS", None) # make sure no env var is suppressing/overriding
# import torch._logging as tlog
# tlog.set_logs(recompiles=True, guards=True, graph_breaks=True)