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[feature]:Add adaptation of all models to zero3

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feng0w0
2026-02-03 15:44:53 +08:00
parent 2070bbd925
commit ca9b5e64ea
4 changed files with 9 additions and 14 deletions
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13
diffsynth/pipelines/flux2_image.py
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@@ -348,13 +348,12 @@ class Flux2Unit_Qwen3PromptEmbedder(PipelineUnit):
attention_mask = torch.cat(all_attention_masks, dim=0).to(device)
# Forward pass through the model
with torch.no_grad():
output = text_encoder(
input_ids=input_ids,
attention_mask=attention_mask,
output_hidden_states=True,
use_cache=False,
)
output = text_encoder(
input_ids=input_ids,
attention_mask=attention_mask,
output_hidden_states=True,
use_cache=False,
)
# Only use outputs from intermediate layers and stack them
out = torch.stack([output.hidden_states[k] for k in self.hidden_states_layers], dim=1)

6
diffsynth/pipelines/wan_video.py
View File

@@ -1334,15 +1334,13 @@ def model_fn_wan_video(
x, x_vap = torch.utils.checkpoint.checkpoint(
create_custom_forward_vap(block, vap),
x, context, t_mod, freqs, x_vap, context_vap, t_mod_vap, freqs_vap, block_id,
use_reentrant=False,
determinism_check="none"
use_reentrant=False
)
elif use_gradient_checkpointing:
x, x_vap = torch.utils.checkpoint.checkpoint(
create_custom_forward_vap(block, vap),
x, context, t_mod, freqs, x_vap, context_vap, t_mod_vap, freqs_vap, block_id,
use_reentrant=False,
determinism_check="none"
use_reentrant=False
)
else:
x, x_vap = vap(block, x, context, t_mod, freqs, x_vap, context_vap, t_mod_vap, freqs_vap, block_id)