mirror of
https://github.com/sd-webui/stable-diffusion-webui.git
synced 2024-12-14 06:35:14 +03:00
Fixed issue with new ldm folder requiring the personalization_config to be set even if empty.
Added shutup as a dependency to shutup python warnings for good.
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@ -67,6 +67,7 @@ retry==0.9.2 # used by sd_utils
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python-slugify==6.1.2 # used by sd_utils
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piexif==1.1.3 # used by sd_utils
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pywebview==3.6.3 # used by streamlit_webview.py
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shutup==0.2.0 # remove all the annoying warnings
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accelerate==0.12.0
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albumentations==0.4.3
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@ -72,6 +72,7 @@ from io import BytesIO
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from packaging import version
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from pathlib import Path
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from huggingface_hub import hf_hub_download
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import shutup
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#import librosa
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from logger import logger, set_logger_verbosity, quiesce_logger
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@ -91,6 +92,9 @@ except ImportError as e:
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# end of imports
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#---------------------------------------------------------------------------------------------------------------
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# remove all the annoying python warnings.
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shutup.please()
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try:
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# this silences the annoying "Some weights of the model checkpoint were not used when initializing..." message at start.
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from transformers import logging
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@ -261,10 +265,13 @@ def set_page_title(title):
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def make_grid(n_items=5, n_cols=5):
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# Compute number of rows
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n_rows = 1 + n_items // int(n_cols)
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# Create rows
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rows = [st.container() for _ in range(n_rows)]
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# Create columns in each row
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cols_per_row = [r.columns(n_cols) for r in rows]
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cols = [column for row in cols_per_row for column in row]
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@ -272,29 +279,29 @@ def make_grid(n_items=5, n_cols=5):
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def merge(file1, file2, out, weight):
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alpha = (weight)/100
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if not(file1.endswith(".ckpt")):
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file1 += ".ckpt"
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if not(file2.endswith(".ckpt")):
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file2 += ".ckpt"
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if not(out.endswith(".ckpt")):
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out += ".ckpt"
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try:
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#Load Models
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model_0 = torch.load(file1)
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model_1 = torch.load(file2)
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theta_0 = model_0['state_dict']
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theta_1 = model_1['state_dict']
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alpha = (weight)/100
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for key in theta_0.keys():
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if 'model' in key and key in theta_1:
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theta_0[key] = (alpha) * theta_0[key] + (1-alpha) * theta_1[key]
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logger.info("RUNNING...\n(STAGE 2)")
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for key in theta_1.keys():
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if 'model' in key and key not in theta_0:
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theta_0[key] = theta_1[key]
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torch.save(model_0, out)
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except:
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logger.error("Error in merging")
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def human_readable_size(size, decimal_places=3):
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@ -483,7 +490,7 @@ def load_model_from_config(config, ckpt, verbose=False):
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if "global_step" in pl_sd:
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logger.info(f"Global Step: {pl_sd['global_step']}")
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sd = pl_sd["state_dict"]
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model = instantiate_from_config(config.model)
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model = instantiate_from_config(config.model, personalization_config='')
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m, u = model.load_state_dict(sd, strict=False)
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if len(m) > 0 and verbose:
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logger.info("missing keys:")
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