helpful error message when trying to load 2.0 without config (02d7abf5) · Commits · github_fork / Stable Diffusion Webui

modules/errors.py

+23 −2

Original line number	Diff line number	Diff line
		@@ -2,9 +2,30 @@ import sys
		import traceback


		def print_error_explanation(message):
		lines = message.strip().split("\n")
		max_len = max([len(x) for x in lines])

		print('=' * max_len, file=sys.stderr)
		for line in lines:
		print(line, file=sys.stderr)
		print('=' * max_len, file=sys.stderr)


		def display(e: Exception, task):
		print(f"{task or 'error'}: {type(e).__name__}", file=sys.stderr)
		print(traceback.format_exc(), file=sys.stderr)

		message = str(e)
		if "copying a param with shape torch.Size([640, 1024]) from checkpoint, the shape in current model is torch.Size([640, 768])" in message:
		print_error_explanation("""
		The most likely cause of this is you are trying to load Stable Diffusion 2.0 model without specifying its connfig file.
		See https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#stable-diffusion-20 for how to solve this.
		""")


		def run(code, task):
		try:
		code()
		except Exception as e:
		print(f"{task}: {type(e).__name__}", file=sys.stderr)
		print(traceback.format_exc(), file=sys.stderr)
		display(task, e)

+18 −8

Original line number	Diff line number	Diff line
		@@ -278,6 +278,7 @@ def enable_midas_autodownload():

		midas.api.load_model = load_model_wrapper


		def load_model(checkpoint_info=None):
		from modules import lowvram, sd_hijack
		checkpoint_info = checkpoint_info or select_checkpoint()
		@@ -312,6 +313,7 @@ def load_model(checkpoint_info=None):
		sd_config.model.params.unet_config.params.use_fp16 = False

		sd_model = instantiate_from_config(sd_config.model)

		load_model_weights(sd_model, checkpoint_info)

		if shared.cmd_opts.lowvram or shared.cmd_opts.medvram:
		@@ -340,6 +342,8 @@ def reload_model_weights(sd_model=None, info=None):
		if not sd_model:
		sd_model = shared.sd_model

		current_checkpoint_info = sd_model.sd_checkpoint_info

		if sd_model.sd_model_checkpoint == checkpoint_info.filename:
		return

		@@ -356,8 +360,13 @@ def reload_model_weights(sd_model=None, info=None):

		sd_hijack.model_hijack.undo_hijack(sd_model)

		try:
		load_model_weights(sd_model, checkpoint_info)

		except Exception as e:
		print("Failed to load checkpoint, restoring previous")
		load_model_weights(sd_model, current_checkpoint_info)
		raise
		finally:
		sd_hijack.model_hijack.hijack(sd_model)
		script_callbacks.model_loaded_callback(sd_model)

		@@ -365,4 +374,5 @@ def reload_model_weights(sd_model=None, info=None):
		sd_model.to(devices.device)

		print("Weights loaded.")

		return sd_model

+7 −2

Original line number	Diff line number	Diff line
		@@ -14,7 +14,7 @@ import modules.interrogate
		import modules.memmon
		import modules.styles
		import modules.devices as devices
		from modules import localization, sd_vae, extensions, script_loading
		from modules import localization, sd_vae, extensions, script_loading, errors
		from modules.paths import models_path, script_path, sd_path


		@@ -494,7 +494,12 @@ class Options:
		return False

		if self.data_labels[key].onchange is not None:
		try:
		self.data_labels[key].onchange()
		except Exception as e:
		errors.display(e, f"changing setting {key} to {value}")
		setattr(self, key, oldval)
		return False

		return True

+10 −2

Original line number	Diff line number	Diff line
		@@ -9,7 +9,7 @@ from fastapi import FastAPI
		from fastapi.middleware.cors import CORSMiddleware
		from fastapi.middleware.gzip import GZipMiddleware

		from modules import import_hook
		from modules import import_hook, errors
		from modules.call_queue import wrap_queued_call, queue_lock, wrap_gradio_gpu_call
		from modules.paths import script_path

		@@ -61,7 +61,15 @@ def initialize():
		modelloader.load_upscalers()

		modules.sd_vae.refresh_vae_list()

		try:
		modules.sd_models.load_model()
		except Exception as e:
		errors.display(e, "loading stable diffusion model")
		print("", file=sys.stderr)
		print("Stable diffusion model failed to load, exiting", file=sys.stderr)
		exit(1)

		shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights()))
		shared.opts.onchange("sd_vae", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False)
		shared.opts.onchange("sd_vae_as_default", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False)