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fix several issues with Windows installs

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1. resize installer window to give more room for configure and download forms
2. replace '\' with '/' in directory names to allow user to drag-and-drop
   folders into the dialogue boxes that accept directories.
3. similar change in CLI for the !import_model and !convert_model commands
4. better error reporting when a model download fails due to network errors
5. put the launcher scripts into a loop so that menu reappears after
   invokeai, merge script, etc exits. User can quit with "Q".
6. do not try to download fp16 of sd-ft-mse-vae, since it doesn't exist.
7. cleaned up status reporting when installing models
This commit is contained in:
Lincoln Stein
2023-02-23 00:43:25 -05:00
parent 3083356cf0
commit 9b157b6532
10 changed files with 66 additions and 68 deletions
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35
ldm/invoke/config/invokeai_configure.py
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@ -66,7 +66,7 @@ SD_Configs = Path(global_config_dir()) / "stable-diffusion"
Datasets = OmegaConf.load(Dataset_path)
# minimum size for the UI
MIN_COLS = 120
MIN_COLS = 135
MIN_LINES = 45
INIT_FILE_PREAMBLE = """# InvokeAI initialization file
@ -165,7 +165,6 @@ def download_with_progress_bar(model_url: str, model_dest: str, label: str = "th
print(f"Installing {label} model file {model_url}...", end="", file=sys.stderr)
if not os.path.exists(model_dest):
os.makedirs(os.path.dirname(model_dest), exist_ok=True)
print("", file=sys.stderr)
request.urlretrieve(
model_url, model_dest, ProgressBar(os.path.basename(model_dest))
)
@ -183,26 +182,22 @@ def download_with_progress_bar(model_url: str, model_dest: str, label: str = "th
def download_bert():
print(
"Installing bert tokenizer...",
end="",
file=sys.stderr,
file=sys.stderr
)
with warnings.catch_warnings():
warnings.filterwarnings("ignore", category=DeprecationWarning)
from transformers import BertTokenizerFast
download_from_hf(BertTokenizerFast, "bert-base-uncased")
print("...success", file=sys.stderr)
# ---------------------------------------------
def download_clip():
print("Installing CLIP model...", file=sys.stderr)
version = "openai/clip-vit-large-patch14"
print("Tokenizer...", file=sys.stderr, end="")
print("Tokenizer...", file=sys.stderr)
download_from_hf(CLIPTokenizer, version)
print("Text model...", file=sys.stderr, end="")
print("Text model...", file=sys.stderr)
download_from_hf(CLIPTextModel, version)
print("...success", file=sys.stderr)
# ---------------------------------------------
@ -255,7 +250,7 @@ def download_codeformer():
# ---------------------------------------------
def download_clipseg():
print("Installing clipseg model for text-based masking...", end="", file=sys.stderr)
print("Installing clipseg model for text-based masking...", file=sys.stderr)
CLIPSEG_MODEL = "CIDAS/clipseg-rd64-refined"
try:
download_from_hf(AutoProcessor, CLIPSEG_MODEL)
@ -263,7 +258,6 @@ def download_clipseg():
except Exception:
print("Error installing clipseg model:")
print(traceback.format_exc())
print("...success", file=sys.stderr)
# -------------------------------------
@ -279,15 +273,14 @@ def download_safety_checker():
print(traceback.format_exc())
return
safety_model_id = "CompVis/stable-diffusion-safety-checker"
print("AutoFeatureExtractor...", end="", file=sys.stderr)
print("AutoFeatureExtractor...", file=sys.stderr)
download_from_hf(AutoFeatureExtractor, safety_model_id)
print("StableDiffusionSafetyChecker...", end="", file=sys.stderr)
print("StableDiffusionSafetyChecker...", file=sys.stderr)
download_from_hf(StableDiffusionSafetyChecker, safety_model_id)
print("...success", file=sys.stderr)
# -------------------------------------
def download_vaes(precision: str):
def download_vaes():
print("Installing stabilityai VAE...", file=sys.stderr)
try:
# first the diffusers version
@ -295,8 +288,6 @@ def download_vaes(precision: str):
args = dict(
cache_dir=global_cache_dir("diffusers"),
)
if precision == "float16":
args.update(torch_dtype=torch.float16, revision="fp16")
if not AutoencoderKL.from_pretrained(repo_id, **args):
raise Exception(f"download of {repo_id} failed")
@ -309,7 +300,6 @@ def download_vaes(precision: str):
model_dir=str(Globals.root / Model_dir / Weights_dir),
):
raise Exception(f"download of {model_name} failed")
print("...downloaded successfully", file=sys.stderr)
except Exception as e:
print(f"Error downloading StabilityAI standard VAE: {str(e)}", file=sys.stderr)
print(traceback.format_exc(), file=sys.stderr)
@ -706,6 +696,9 @@ def write_opts(opts: Namespace, init_file: Path):
args_to_skip = re.compile(
"^--?(o|out|no-xformer|xformer|no-ckpt|ckpt|free|no-nsfw|nsfw|prec|max_load|embed|always|ckpt|free_gpu)"
)
# fix windows paths
opts.outdir = opts.outdir.replace('\\','/')
opts.embedding_path = opts.embedding_path.replace('\\','/')
new_file = f"{init_file}.new"
try:
lines = [x.strip() for x in open(init_file, "r").readlines()]
@ -845,7 +838,7 @@ def main():
download_codeformer()
download_clipseg()
download_safety_checker()
download_vaes(init_options.precision)
download_vaes()
if opt.skip_sd_weights:
print("\n** SKIPPING DIFFUSION WEIGHTS DOWNLOAD PER USER REQUEST **")
@ -856,10 +849,6 @@ def main():
postscript(errors=errors)
except KeyboardInterrupt:
print("\nGoodbye! Come back soon.")
except Exception as e:
print(f'\nA problem occurred during initialization.\nThe error was: "{str(e)}"')
print(traceback.format_exc())
# -------------------------------------
if __name__ == "__main__":