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args

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This commit is contained in:
Haoming 2026-06-08 00:03:09 +08:00
parent 8cb0be72f3
commit ebece7016c
3 changed files with 10 additions and 2 deletions
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4
backend/args.py
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@ -162,10 +162,14 @@ class dynamic_args(metaclass=_DynamicArgsMeta):
"""Flux.2 Klein"""
wan: bool = False
"""Wan 2.2"""
pid: bool = False
"""PiD"""
ref_latents: list["torch.Tensor"] = []
"""Reference Latent(s) for Flux Kontext / Qwen-Image-Edit / Flux.2 Klein"""
concat_latent: "torch.Tensor" = None
"""Input Latent for Wan 2.2 I2V"""
lq_latent: tuple["torch.Tensor", "torch.Tensor"] = None
"""lq_latent & degrade_sigma for PiD"""
is_referencing: bool = False
"""Appending Reference Latent(s) (by. ImageStitch)"""
ops: str = None

3
backend/loader.py
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@ -867,13 +867,14 @@ def forge_loader(sd: os.PathLike, additional_state_dicts: list[os.PathLike] = No
except AttributeError:
raise ValueError("Failed to recognize model...") from None
repo_name = estimated_config.huggingface_repo
repo_name: str = estimated_config.huggingface_repo
backend.args.dynamic_args.kontext = "kontext" in str(sd).lower()
backend.args.dynamic_args.edit = "qwen" in str(sd).lower() and "edit" in str(sd).lower()
backend.args.dynamic_args.nunchaku = getattr(estimated_config, "nunchaku", False)
backend.args.dynamic_args.klein = "klein" in repo_name
backend.args.dynamic_args.wan = "Wan" in repo_name
backend.args.dynamic_args.pid = "PiD" in repo_name
if "xl" in repo_name and "rectified" in str(sd).lower():
estimated_config.sampling_settings["RF"] = True

5
backend/nn/pixeldit/pid.py
View File

@ -4,6 +4,8 @@ import torch
import torch.nn as nn
import torch.nn.functional as F
from backend.args import dynamic_args
from .model import PixDiT_T2I
from .modules import precompute_freqs_cis_2d
@ -178,7 +180,8 @@ class PidNet(PixDiT_T2I):
return s
return self.lq_proj.gate(s, pid_lq_features[out_idx], pid_degrade_sigma, out_idx)
def forward(self, x, timesteps, context=None, attention_mask=None, transformer_options={}, lq_latent=None, degrade_sigma=None, **kwargs):
def forward(self, x, timesteps, context=None, attention_mask=None, transformer_options={}, **kwargs):
lq_latent, degrade_sigma = dynamic_args.lq_latent
assert lq_latent is not None
expected_c = self.lq_proj.latent_channels