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fixed pretrains list

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SayanoAI
2024-09-10 11:58:28 -04:00
parent 91e552f756
commit ec21a76e84
3 changed files with 26 additions and 16 deletions
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custom_nodes/rvc_nodes.py
+12 -3
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@@ -20,7 +20,7 @@ from ..lib.model_utils import load_hubert
from .utils import MultipleTypeProxy, increment_filename_no_overwrite, model_downloader
from .settings import PITCH_EXTRACTION_OPTIONS
from .settings.downloader import PRETRAINED_MODELS, RVC_DOWNLOAD_LINK, RVC_INDEX, RVC_MODELS, download_file, extract_zip_without_structure
from .settings.downloader import PRETRAINED_MODELS_D, PRETRAINED_MODELS_G, RVC_DOWNLOAD_LINK, RVC_INDEX, RVC_MODELS, download_file, extract_zip_without_structure
from ..lib.audio import SUPPORTED_AUDIO, audio_to_bytes, load_input_audio, save_input_audio, get_audio, SR_MAP
@@ -387,9 +387,18 @@ class RVCTrainModelNode:
@classmethod
def INPUT_TYPES(cls):
DEVICES = [str(i) for i in range(torch.cuda.device_count())]
PRETRAINED_G = [model for model in PRETRAINED_MODELS if "G" in model] + get_filenames(root=BASE_MODELS_DIR,folder="pretrained_v2",name_filters=["G"],format_func=lambda x: f"pretrained_v2/{os.path.basename(x)}")
PRETRAINED_G = PRETRAINED_MODELS_G + get_filenames(
root=BASE_MODELS_DIR,
folder="pretrained_v2",
name_filters=["G"],
filter_func=lambda x: os.stat(x).st_size/1024**2<600, #generators are 400+mb
format_func=lambda x: f"pretrained_v2/{os.path.basename(x)}")
PRETRAINED_G = list(set(PRETRAINED_G)) # dedupe
PRETRAINED_D = [model for model in PRETRAINED_MODELS if "D" in model] + get_filenames(root=BASE_MODELS_DIR,folder="pretrained_v2",name_filters=["D"],format_func=lambda x: f"pretrained_v2/{os.path.basename(x)}")
PRETRAINED_D = PRETRAINED_MODELS_D + get_filenames(
root=BASE_MODELS_DIR,folder="pretrained_v2",
name_filters=["D"],
filter_func=lambda x: os.stat(x).st_size/1024**2>600, #discriminators are 800+mb
format_func=lambda x: f"pretrained_v2/{os.path.basename(x)}")
PRETRAINED_D = list(set(PRETRAINED_D)) # dedupe
return {
custom_nodes/settings/downloader.py
+12 -11
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@@ -37,27 +37,28 @@ RVC_INDEX = [
]
BASE_MODELS = ["content-vec-best.safetensors", "rmvpe.pt"]
VITS_MODELS = ["VITS/pretrained_ljs.pth"]
PRETRAINED_MODELS = [
"pretrained_v2/D48k.pth",
PRETRAINED_MODELS_G = [
"pretrained_v2/G48k.pth",
"pretrained_v2/D32k.pth",
"pretrained_v2/G32k.pth",
"pretrained_v2/D40k.pth",
"pretrained_v2/G40k.pth",
"pretrained_v2/f0D48k.pth",
"pretrained_v2/f0G48k.pth",
"pretrained_v2/f0D40k.pth",
"pretrained_v2/f0G40k.pth",
"pretrained_v2/f0D32k.pth",
"pretrained_v2/f0G32k.pth",
"pretrained_v2/f0_RIN_E3_40k_D.pth",
"pretrained_v2/f0_RIN_E3_40k_G.pth",
"pretrained_v2/f0Ov2Super32kD.pth",
"pretrained_v2/f0Ov2Super32kG.pth",
"pretrained_v2/f0Ov2Super40kD.pth",
"pretrained_v2/f0Ov2Super40kG.pth",
]
PRETRAINED_MODELS_D = [
"pretrained_v2/D48k.pth",
"pretrained_v2/D32k.pth",
"pretrained_v2/D40k.pth",
"pretrained_v2/f0D48k.pth",
"pretrained_v2/f0D40k.pth",
"pretrained_v2/f0D32k.pth",
"pretrained_v2/f0_RIN_E3_40k_D.pth",
"pretrained_v2/f0Ov2Super32kD.pth",
"pretrained_v2/f0Ov2Super40kD.pth",
]
LLM_MODELS = [
"https://huggingface.co/TheBloke/Airoboros-L2-7B-2.1-GGUF/resolve/main/airoboros-l2-7b-2.1.Q4_K_M.gguf",
"https://huggingface.co/TheBloke/Pygmalion-2-7B-GGUF/resolve/main/pygmalion-2-7b.Q4_K_M.gguf",
lib/utils.py
+2 -2
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@@ -41,11 +41,11 @@ def get_subprocesses(pid = os.getpid()):
})
yield process
def get_filenames(root=CWD,folder="**",exts=["*"],name_filters=[""],filter_func=any,format_func=lambda x:x):
def get_filenames(root=CWD,folder="**",exts=["*"],name_filters=[""],filter_func=bool,format_func=lambda x:x):
fnames = []
for ext in exts:
fnames.extend(glob.glob(f"{root}/{folder}/*.{ext}",recursive=True))
return sorted([format_func(ele) for ele in fnames if filter_func([nf.lower() in ele.lower() for nf in name_filters])])
return sorted([format_func(ele) for ele in fnames if any([nf.lower() in ele.lower() for nf in name_filters]) and filter_func(ele)])
def get_index(arr,value):
if arr is not None: