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author | xucj98 <975114697@qq.com> | 2022-11-25 09:07:00 +0000 |
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committer | GitHub <noreply@github.com> | 2022-11-25 09:07:00 +0000 |
commit | 263b323de12eb2444b0818105575a2bc69ab0344 (patch) | |
tree | 7bc4a7802bdaba21550ad281cc08c3fc1037b074 /modules/sd_vae.py | |
parent | d20dbe47e06de7f6c0e65242a04c9bb1410ef7cb (diff) | |
parent | 828438b4a190759807f9054932cae3a8b880ddf1 (diff) | |
download | stable-diffusion-webui-gfx803-263b323de12eb2444b0818105575a2bc69ab0344.tar.gz stable-diffusion-webui-gfx803-263b323de12eb2444b0818105575a2bc69ab0344.tar.bz2 stable-diffusion-webui-gfx803-263b323de12eb2444b0818105575a2bc69ab0344.zip |
Merge branch 'AUTOMATIC1111:master' into draft
Diffstat (limited to 'modules/sd_vae.py')
-rw-r--r-- | modules/sd_vae.py | 36 |
1 files changed, 22 insertions, 14 deletions
diff --git a/modules/sd_vae.py b/modules/sd_vae.py index 71e7a6e6..9c120975 100644 --- a/modules/sd_vae.py +++ b/modules/sd_vae.py @@ -83,47 +83,54 @@ def refresh_vae_list(vae_path=vae_path, model_path=model_path): return vae_list -def resolve_vae(checkpoint_file, vae_file="auto"): +def get_vae_from_settings(vae_file="auto"): + # else, we load from settings, if not set to be default + if vae_file == "auto" and shared.opts.sd_vae is not None: + # if saved VAE settings isn't recognized, fallback to auto + vae_file = vae_dict.get(shared.opts.sd_vae, "auto") + # if VAE selected but not found, fallback to auto + if vae_file not in default_vae_values and not os.path.isfile(vae_file): + vae_file = "auto" + print(f"Selected VAE doesn't exist: {vae_file}") + return vae_file + + +def resolve_vae(checkpoint_file=None, vae_file="auto"): global first_load, vae_dict, vae_list # if vae_file argument is provided, it takes priority, but not saved if vae_file and vae_file not in default_vae_list: if not os.path.isfile(vae_file): + print(f"VAE provided as function argument doesn't exist: {vae_file}") vae_file = "auto" - print("VAE provided as function argument doesn't exist") # for the first load, if vae-path is provided, it takes priority, saved, and failure is reported if first_load and shared.cmd_opts.vae_path is not None: if os.path.isfile(shared.cmd_opts.vae_path): vae_file = shared.cmd_opts.vae_path shared.opts.data['sd_vae'] = get_filename(vae_file) else: - print("VAE provided as command line argument doesn't exist") - # else, we load from settings - if vae_file == "auto" and shared.opts.sd_vae is not None: - # if saved VAE settings isn't recognized, fallback to auto - vae_file = vae_dict.get(shared.opts.sd_vae, "auto") - # if VAE selected but not found, fallback to auto - if vae_file not in default_vae_values and not os.path.isfile(vae_file): - vae_file = "auto" - print("Selected VAE doesn't exist") + print(f"VAE provided as command line argument doesn't exist: {vae_file}") + # fallback to selector in settings, if vae selector not set to act as default fallback + if not shared.opts.sd_vae_as_default: + vae_file = get_vae_from_settings(vae_file) # vae-path cmd arg takes priority for auto if vae_file == "auto" and shared.cmd_opts.vae_path is not None: if os.path.isfile(shared.cmd_opts.vae_path): vae_file = shared.cmd_opts.vae_path - print("Using VAE provided as command line argument") + print(f"Using VAE provided as command line argument: {vae_file}") # if still not found, try look for ".vae.pt" beside model model_path = os.path.splitext(checkpoint_file)[0] if vae_file == "auto": vae_file_try = model_path + ".vae.pt" if os.path.isfile(vae_file_try): vae_file = vae_file_try - print("Using VAE found beside selected model") + print(f"Using VAE found similar to selected model: {vae_file}") # if still not found, try look for ".vae.ckpt" beside model if vae_file == "auto": vae_file_try = model_path + ".vae.ckpt" if os.path.isfile(vae_file_try): vae_file = vae_file_try - print("Using VAE found beside selected model") + print(f"Using VAE found similar to selected model: {vae_file}") # No more fallbacks for auto if vae_file == "auto": vae_file = None @@ -139,6 +146,7 @@ def load_vae(model, vae_file=None): # save_settings = False if vae_file: + assert os.path.isfile(vae_file), f"VAE file doesn't exist: {vae_file}" print(f"Loading VAE weights from: {vae_file}") vae_ckpt = torch.load(vae_file, map_location=shared.weight_load_location) vae_dict_1 = {k: v for k, v in vae_ckpt["state_dict"].items() if k[0:4] != "loss" and k not in vae_ignore_keys} |