Merge pull request #10232 from akx/eff (d6a9b22c) · Commits · github_fork / Stable Diffusion Webui

modules/api/api.py

+11 −11

Original line number	Diff line number	Diff line
		@@ -570,20 +570,20 @@ class Api:
		filename = create_embedding(**args) # create empty embedding
		sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings() # reload embeddings so new one can be immediately used
		shared.state.end()
		return CreateResponse(info = "create embedding filename: {filename}".format(filename = filename))
		return CreateResponse(info=f"create embedding filename: {filename}")
		except AssertionError as e:
		shared.state.end()
		return TrainResponse(info = "create embedding error: {error}".format(error = e))
		return TrainResponse(info=f"create embedding error: {e}")

		def create_hypernetwork(self, args: dict):
		try:
		shared.state.begin()
		filename = create_hypernetwork(**args) # create empty embedding
		shared.state.end()
		return CreateResponse(info = "create hypernetwork filename: {filename}".format(filename = filename))
		return CreateResponse(info=f"create hypernetwork filename: {filename}")
		except AssertionError as e:
		shared.state.end()
		return TrainResponse(info = "create hypernetwork error: {error}".format(error = e))
		return TrainResponse(info=f"create hypernetwork error: {e}")

		def preprocess(self, args: dict):
		try:
		@@ -593,13 +593,13 @@ class Api:
		return PreprocessResponse(info = 'preprocess complete')
		except KeyError as e:
		shared.state.end()
		return PreprocessResponse(info = "preprocess error: invalid token: {error}".format(error = e))
		return PreprocessResponse(info=f"preprocess error: invalid token: {e}")
		except AssertionError as e:
		shared.state.end()
		return PreprocessResponse(info = "preprocess error: {error}".format(error = e))
		return PreprocessResponse(info=f"preprocess error: {e}")
		except FileNotFoundError as e:
		shared.state.end()
		return PreprocessResponse(info = 'preprocess error: {error}'.format(error = e))
		return PreprocessResponse(info=f'preprocess error: {e}')

		def train_embedding(self, args: dict):
		try:
		@@ -617,10 +617,10 @@ class Api:
		if not apply_optimizations:
		sd_hijack.apply_optimizations()
		shared.state.end()
		return TrainResponse(info = "train embedding complete: filename: {filename} error: {error}".format(filename = filename, error = error))
		return TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}")
		except AssertionError as msg:
		shared.state.end()
		return TrainResponse(info = "train embedding error: {msg}".format(msg = msg))
		return TrainResponse(info=f"train embedding error: {msg}")

		def train_hypernetwork(self, args: dict):
		try:
		@@ -641,10 +641,10 @@ class Api:
		if not apply_optimizations:
		sd_hijack.apply_optimizations()
		shared.state.end()
		return TrainResponse(info="train embedding complete: filename: {filename} error: {error}".format(filename=filename, error=error))
		return TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}")
		except AssertionError as msg:
		shared.state.end()
		return TrainResponse(info="train embedding error: {error}".format(error=error))
		return TrainResponse(info=f"train embedding error: {error}")

		def get_memory(self):
		try:

modules/call_queue.py

+3 −2

Original line number	Diff line number	Diff line
		@@ -60,7 +60,7 @@ def wrap_gradio_call(func, extra_outputs=None, add_stats=False):
		max_debug_str_len = 131072 # (1024*1024)/8

		print("Error completing request", file=sys.stderr)
		argStr = f"Arguments: {str(args)} {str(kwargs)}"
		argStr = f"Arguments: {args} {kwargs}"
		print(argStr[:max_debug_str_len], file=sys.stderr)
		if len(argStr) > max_debug_str_len:
		print(f"(Argument list truncated at {max_debug_str_len}/{len(argStr)} characters)", file=sys.stderr)
		@@ -73,7 +73,8 @@ def wrap_gradio_call(func, extra_outputs=None, add_stats=False):
		if extra_outputs_array is None:
		extra_outputs_array = [None, '']

		res = extra_outputs_array + [f"<div class='error'>{html.escape(type(e).__name__+': '+str(e))}</div>"]
		error_message = f'{type(e).__name__}: {e}'
		res = extra_outputs_array + [f"<div class='error'>{html.escape(error_message)}</div>"]

		shared.state.skipped = False
		shared.state.interrupted = False

modules/esrgan_model.py

+7 −4

Original line number	Diff line number	Diff line
		@@ -156,13 +156,16 @@ class UpscalerESRGAN(Upscaler):

		def load_model(self, path: str):
		if "http" in path:
		filename = load_file_from_url(url=self.model_url, model_dir=self.model_path,
		file_name="%s.pth" % self.model_name,
		progress=True)
		filename = load_file_from_url(
		url=self.model_url,
		model_dir=self.model_path,
		file_name=f"{self.model_name}.pth",
		progress=True,
		)
		else:
		filename = path
		if not os.path.exists(filename) or filename is None:
		print("Unable to load %s from %s" % (self.model_path, filename))
		print(f"Unable to load {self.model_path} from {filename}")
		return None

		state_dict = torch.load(filename, map_location='cpu' if devices.device_esrgan.type == 'mps' else None)

modules/esrgan_model_arch.py

+8 −8

Original line number	Diff line number	Diff line
		@@ -38,7 +38,7 @@ class RRDBNet(nn.Module):
		elif upsample_mode == 'pixelshuffle':
		upsample_block = pixelshuffle_block
		else:
		raise NotImplementedError('upsample mode [{:s}] is not found'.format(upsample_mode))
		raise NotImplementedError(f'upsample mode [{upsample_mode}] is not found')
		if upscale == 3:
		upsampler = upsample_block(nf, nf, 3, act_type=act_type, convtype=convtype)
		else:
		@@ -261,10 +261,10 @@ class Upsample(nn.Module):

		def extra_repr(self):
		if self.scale_factor is not None:
		info = 'scale_factor=' + str(self.scale_factor)
		info = f'scale_factor={self.scale_factor}'
		else:
		info = 'size=' + str(self.size)
		info += ', mode=' + self.mode
		info = f'size={self.size}'
		info += f', mode={self.mode}'
		return info


		@@ -350,7 +350,7 @@ def act(act_type, inplace=True, neg_slope=0.2, n_prelu=1, beta=1.0):
		elif act_type == 'sigmoid': # [0, 1] range output
		layer = nn.Sigmoid()
		else:
		raise NotImplementedError('activation layer [{:s}] is not found'.format(act_type))
		raise NotImplementedError(f'activation layer [{act_type}] is not found')
		return layer


		@@ -372,7 +372,7 @@ def norm(norm_type, nc):
		elif norm_type == 'none':
		def norm_layer(x): return Identity()
		else:
		raise NotImplementedError('normalization layer [{:s}] is not found'.format(norm_type))
		raise NotImplementedError(f'normalization layer [{norm_type}] is not found')
		return layer


		@@ -388,7 +388,7 @@ def pad(pad_type, padding):
		elif pad_type == 'zero':
		layer = nn.ZeroPad2d(padding)
		else:
		raise NotImplementedError('padding layer [{:s}] is not implemented'.format(pad_type))
		raise NotImplementedError(f'padding layer [{pad_type}] is not implemented')
		return layer


		@@ -432,7 +432,7 @@ def conv_block(in_nc, out_nc, kernel_size, stride=1, dilation=1, groups=1, bias=
		pad_type='zero', norm_type=None, act_type='relu', mode='CNA', convtype='Conv2D',
		spectral_norm=False):
		""" Conv layer with padding, normalization, activation """
		assert mode in ['CNA', 'NAC', 'CNAC'], 'Wrong conv mode [{:s}]'.format(mode)
		assert mode in ['CNA', 'NAC', 'CNAC'], f'Wrong conv mode [{mode}]'
		padding = get_valid_padding(kernel_size, dilation)
		p = pad(pad_type, padding) if pad_type and pad_type != 'zero' else None
		padding = padding if pad_type == 'zero' else 0

modules/extra_networks_hypernet.py

+2 −1

Original line number	Diff line number	Diff line
		@@ -10,7 +10,8 @@ class ExtraNetworkHypernet(extra_networks.ExtraNetwork):
		additional = shared.opts.sd_hypernetwork

		if additional != "None" and additional in shared.hypernetworks and len([x for x in params_list if x.items[0] == additional]) == 0:
		p.all_prompts = [x + f"<hypernet:{additional}:{shared.opts.extra_networks_default_multiplier}>" for x in p.all_prompts]
		hypernet_prompt_text = f"<hypernet:{additional}:{shared.opts.extra_networks_default_multiplier}>"
		p.all_prompts = [f"{prompt}{hypernet_prompt_text}" for prompt in p.all_prompts]
		params_list.append(extra_networks.ExtraNetworkParams(items=[additional, shared.opts.extra_networks_default_multiplier]))

		names = []

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