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add hash and fix undo hijack bug

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Signed-off-by: zhaohu xing <920232796@qq.com>
This commit is contained in:
zhaohu xing 2022-12-06 16:04:50 +08:00
parent a25dfebeed
commit 5dcc22606d
4 changed files with 11 additions and 6 deletions
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.DS_Store vendored Normal file
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10
launch.py
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@ -234,11 +234,11 @@ def prepare_enviroment():
os.makedirs(dir_repos, exist_ok=True) os.makedirs(dir_repos, exist_ok=True)
git_clone(stable_diffusion_repo, repo_dir('stable-diffusion-stability-ai'), "Stable Diffusion", ) git_clone(stable_diffusion_repo, repo_dir('stable-diffusion-stability-ai'), "Stable Diffusion", stable_diffusion_commit_hash)
git_clone(taming_transformers_repo, repo_dir('taming-transformers'), "Taming Transformers", ) git_clone(taming_transformers_repo, repo_dir('taming-transformers'), "Taming Transformers", taming_transformers_commit_hash)
git_clone(k_diffusion_repo, repo_dir('k-diffusion'), "K-diffusion", ) git_clone(k_diffusion_repo, repo_dir('k-diffusion'), "K-diffusion", k_diffusion_commit_hash)
git_clone(codeformer_repo, repo_dir('CodeFormer'), "CodeFormer", ) git_clone(codeformer_repo, repo_dir('CodeFormer'), "CodeFormer", codeformer_commit_hash)
git_clone(blip_repo, repo_dir('BLIP'), "BLIP", ) git_clone(blip_repo, repo_dir('BLIP'), "BLIP", blip_commit_hash)
if not is_installed("lpips"): if not is_installed("lpips"):
run_pip(f"install -r {os.path.join(repo_dir('CodeFormer'), 'requirements.txt')}", "requirements for CodeFormer") run_pip(f"install -r {os.path.join(repo_dir('CodeFormer'), 'requirements.txt')}", "requirements for CodeFormer")

6
modules/sd_hijack.py
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@ -112,7 +112,11 @@ class StableDiffusionModelHijack:
self.layers = flatten(m) self.layers = flatten(m)
def undo_hijack(self, m): def undo_hijack(self, m):
if type(m.cond_stage_model) == sd_hijack_clip.FrozenCLIPEmbedderWithCustomWords:
if shared.text_model_name == "XLMR-Large":
m.cond_stage_model = m.cond_stage_model.wrapped
elif type(m.cond_stage_model) == sd_hijack_clip.FrozenCLIPEmbedderWithCustomWords:
m.cond_stage_model = m.cond_stage_model.wrapped m.cond_stage_model = m.cond_stage_model.wrapped
model_embeddings = m.cond_stage_model.transformer.text_model.embeddings model_embeddings = m.cond_stage_model.transformer.text_model.embeddings

1
v2-inference.yaml → v2-inference-v.yaml
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@ -2,6 +2,7 @@ model:
base_learning_rate: 1.0e-4 base_learning_rate: 1.0e-4
target: ldm.models.diffusion.ddpm.LatentDiffusion target: ldm.models.diffusion.ddpm.LatentDiffusion
params: params:
parameterization: "v"
linear_start: 0.00085 linear_start: 0.00085
linear_end: 0.0120 linear_end: 0.0120
num_timesteps_cond: 1 num_timesteps_cond: 1