fix several issues with Windows installs

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

ldm/invoke/CLI.py

@@ -496,6 +496,7 @@ def main_loop(gen, opt):
 def do_command(command: str, gen, opt: Args, completer) -> tuple:
     global infile
     operation = "generate"  # default operation, alternative is 'postprocess'
+    command = command.replace('\\','/') # windows
 
     if command.startswith(
         "!dream"
@@ -630,7 +631,6 @@ def import_model(model_path: str, gen, opt, completer, convert=False) -> str:
     (3) a huggingface repository id; or (4) a local directory containing a
     diffusers model.
     """
-    model_path = model_path.replace("\\", "/")  # windows
     default_name = Path(model_path).stem
     model_name = None
     model_desc = None

ldm/invoke/_version.py

@@ -1 +1 @@
-__version__='2.3.1+rc1'
+__version__='2.3.1+rc2'

ldm/invoke/config/invokeai_configure.py

@@ -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__":

ldm/invoke/config/model_install.py

@@ -12,7 +12,6 @@ The work is actually done in backend code in model_install_backend.py.
 import argparse
 import os
 import sys
-import traceback
 from argparse import Namespace
 from pathlib import Path
 from typing import List
@@ -482,7 +481,7 @@ def main():
         sys.exit(-1)
     except KeyboardInterrupt:
         print("\nGoodbye! Come back soon.")
-    except (widget.NotEnoughSpaceForWidget, Exception) as e:
+    except widget.NotEnoughSpaceForWidget as e:
         if str(e).startswith("Height of 1 allocated"):
             print(
                 "** Insufficient vertical space for the interface. Please make your window taller and try again"
@@ -491,11 +490,6 @@ def main():
             print(
                 "** Insufficient horizontal space for the interface. Please make your window wider and try again."
             )
-        else:
-            print(f"** An error has occurred: {str(e)}")
-            traceback.print_exc()
-        sys.exit(-1)
-
 
 # -------------------------------------
 if __name__ == "__main__":

ldm/invoke/config/model_install_backend.py

@@ -120,12 +120,13 @@ def install_requested_models(
         argument = '--autoconvert' if convert_to_diffusers else '--autoimport'
         initfile = Path(Globals.root, Globals.initfile)
         replacement = Path(Globals.root, f'{Globals.initfile}.new')
+        directory = str(scan_directory).replace('\\','/')
         with open(initfile,'r') as input:
             with open(replacement,'w') as output:
                 while line := input.readline():
                     if not line.startswith(argument):
                         output.writelines([line])
-                output.writelines([f'{argument} {str(scan_directory)}'])
+                output.writelines([f'{argument} {directory}'])
         os.replace(replacement,initfile)
 
 # -------------------------------------
@@ -234,7 +235,6 @@ def _download_ckpt_weights(mconfig: DictConfig, access_token: str) -> Path:
 def download_from_hf(
     model_class: object, model_name: str, cache_subdir: Path = Path("hub"), **kwargs
 ):
-    print("", file=sys.stderr)  # to prevent tqdm from overwriting
     path = global_cache_dir(cache_subdir)
     model = model_class.from_pretrained(
         model_name,

ldm/invoke/config/widgets.py

@@ -4,25 +4,25 @@ Widget class definitions used by model_select.py, merge_diffusers.py and textual
 import math
 import platform
 import npyscreen
+import os
 import sys
 import curses
-import termios
 import struct
-import fcntl
 
 from shutil import get_terminal_size
 
 # -------------------------------------
 def set_terminal_size(columns: int, lines: int):
-    os = platform.uname().system
-    if os=="Windows":
+    OS = platform.uname().system
+    if OS=="Windows":
         os.system(f'mode con: cols={columns} lines={lines}')
-    elif os in ['Darwin', 'Linux']:
+    elif OS in ['Darwin', 'Linux']:
+        import termios
+        import fcntl
         winsize = struct.pack("HHHH", lines, columns, 0, 0)
-        fcntl.ioctl(0, termios.TIOCSWINSZ, winsize)
+        fcntl.ioctl(sys.stdout.fileno(), termios.TIOCSWINSZ, winsize)
         sys.stdout.write("\x1b[8;{rows};{cols}t".format(rows=lines, cols=columns))
         sys.stdout.flush()
-    
 
 def set_min_terminal_size(min_cols: int, min_lines: int):
     # make sure there's enough room for the ui

ldm/invoke/model_manager.py

@@ -428,8 +428,6 @@ class ModelManager(object):
             torch.cuda.reset_peak_memory_stats()
             torch.cuda.empty_cache()
 
-        tic = time.time()
-
         # this does the work
         if not os.path.isabs(config):
             config = os.path.join(Globals.root, config)
@@ -642,21 +640,18 @@ class ModelManager(object):
         models.yaml file.
         """
         model_name = model_name or Path(repo_or_path).stem
-        description = model_description or f"imported diffusers model {model_name}"
+        model_description = model_description or f"imported diffusers model {model_name}"
         new_config = dict(
             description=model_description,
             vae=vae,
             format="diffusers",
         )
-        print(f"DEBUG: here i am 1")
         if isinstance(repo_or_path, Path) and repo_or_path.exists():
             new_config.update(path=str(repo_or_path))
         else:
             new_config.update(repo_id=repo_or_path)
-        print(f"DEBUG: here i am 2")
 
         self.add_model(model_name, new_config, True)
-        print(f"DEBUG: config = {self.config}")
         if commit_to_conf:
             self.commit(commit_to_conf)
         return model_name