From 2f4c91894d4c0a055c1069b2fda0e4da8fcda188 Mon Sep 17 00:00:00 2001 From: guaneec Date: Wed, 26 Oct 2022 12:10:30 +0800 Subject: Remove activation from final layer of HNs --- modules/hypernetworks/hypernetwork.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) (limited to 'modules') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index d647ea55..54346b64 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -41,8 +41,8 @@ class HypernetworkModule(torch.nn.Module): # Add a fully-connected layer linears.append(torch.nn.Linear(int(dim * layer_structure[i]), int(dim * layer_structure[i+1]))) - # Add an activation func - if activation_func == "linear" or activation_func is None: + # Add an activation func except last layer + if activation_func == "linear" or activation_func is None or i >= len(layer_structure) - 3: pass elif activation_func in self.activation_dict: linears.append(self.activation_dict[activation_func]()) @@ -53,7 +53,7 @@ class HypernetworkModule(torch.nn.Module): if add_layer_norm: linears.append(torch.nn.LayerNorm(int(dim * layer_structure[i+1]))) - # Add dropout expect last layer + # Add dropout except last layer if use_dropout and i < len(layer_structure) - 3: linears.append(torch.nn.Dropout(p=0.3)) -- cgit v1.2.1 From c702d4d0df21790199d199818f25c449213ffe0f Mon Sep 17 00:00:00 2001 From: guaneec Date: Wed, 26 Oct 2022 13:43:04 +0800 Subject: Fix off-by-one --- modules/hypernetworks/hypernetwork.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) (limited to 'modules') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 54346b64..3ce85bb5 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -42,7 +42,7 @@ class HypernetworkModule(torch.nn.Module): linears.append(torch.nn.Linear(int(dim * layer_structure[i]), int(dim * layer_structure[i+1]))) # Add an activation func except last layer - if activation_func == "linear" or activation_func is None or i >= len(layer_structure) - 3: + if activation_func == "linear" or activation_func is None or i >= len(layer_structure) - 2: pass elif activation_func in self.activation_dict: linears.append(self.activation_dict[activation_func]()) @@ -54,7 +54,7 @@ class HypernetworkModule(torch.nn.Module): linears.append(torch.nn.LayerNorm(int(dim * layer_structure[i+1]))) # Add dropout except last layer - if use_dropout and i < len(layer_structure) - 3: + if use_dropout and i < len(layer_structure) - 2: linears.append(torch.nn.Dropout(p=0.3)) self.linear = torch.nn.Sequential(*linears) -- cgit v1.2.1 From 877d94f97ca5491d8779440769b191e0dcd32c8e Mon Sep 17 00:00:00 2001 From: guaneec Date: Wed, 26 Oct 2022 14:50:58 +0800 Subject: Back compatibility --- modules/hypernetworks/hypernetwork.py | 17 ++++++++++------- 1 file changed, 10 insertions(+), 7 deletions(-) (limited to 'modules') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 3ce85bb5..dd317085 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -28,7 +28,7 @@ class HypernetworkModule(torch.nn.Module): "swish": torch.nn.Hardswish, } - def __init__(self, dim, state_dict=None, layer_structure=None, activation_func=None, add_layer_norm=False, use_dropout=False): + def __init__(self, dim, state_dict=None, layer_structure=None, activation_func=None, add_layer_norm=False, use_dropout=False, activate_output=False): super().__init__() assert layer_structure is not None, "layer_structure must not be None" @@ -42,7 +42,7 @@ class HypernetworkModule(torch.nn.Module): linears.append(torch.nn.Linear(int(dim * layer_structure[i]), int(dim * layer_structure[i+1]))) # Add an activation func except last layer - if activation_func == "linear" or activation_func is None or i >= len(layer_structure) - 2: + if activation_func == "linear" or activation_func is None or (i >= len(layer_structure) - 2 and not activate_output): pass elif activation_func in self.activation_dict: linears.append(self.activation_dict[activation_func]()) @@ -105,7 +105,7 @@ class Hypernetwork: filename = None name = None - def __init__(self, name=None, enable_sizes=None, layer_structure=None, activation_func=None, add_layer_norm=False, use_dropout=False): + def __init__(self, name=None, enable_sizes=None, layer_structure=None, activation_func=None, add_layer_norm=False, use_dropout=False, activate_output=False): self.filename = None self.name = name self.layers = {} @@ -116,11 +116,12 @@ class Hypernetwork: self.activation_func = activation_func self.add_layer_norm = add_layer_norm self.use_dropout = use_dropout + self.activate_output = activate_output for size in enable_sizes or []: self.layers[size] = ( - HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.add_layer_norm, self.use_dropout), - HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.add_layer_norm, self.use_dropout), + HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.add_layer_norm, self.use_dropout, self.activate_output), + HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.add_layer_norm, self.use_dropout, self.activate_output), ) def weights(self): @@ -147,6 +148,7 @@ class Hypernetwork: state_dict['use_dropout'] = self.use_dropout state_dict['sd_checkpoint'] = self.sd_checkpoint state_dict['sd_checkpoint_name'] = self.sd_checkpoint_name + state_dict['activate_output'] = self.activate_output torch.save(state_dict, filename) @@ -161,12 +163,13 @@ class Hypernetwork: self.activation_func = state_dict.get('activation_func', None) self.add_layer_norm = state_dict.get('is_layer_norm', False) self.use_dropout = state_dict.get('use_dropout', False) + self.activate_output = state_dict.get('activate_output', True) for size, sd in state_dict.items(): if type(size) == int: self.layers[size] = ( - HypernetworkModule(size, sd[0], self.layer_structure, self.activation_func, self.add_layer_norm, self.use_dropout), - HypernetworkModule(size, sd[1], self.layer_structure, self.activation_func, self.add_layer_norm, self.use_dropout), + HypernetworkModule(size, sd[0], self.layer_structure, self.activation_func, self.add_layer_norm, self.use_dropout, self.activate_output), + HypernetworkModule(size, sd[1], self.layer_structure, self.activation_func, self.add_layer_norm, self.use_dropout, self.activate_output), ) self.name = state_dict.get('name', self.name) -- cgit v1.2.1 From 91bb35b1e6842b30ce7553009c8ecea3643de8d2 Mon Sep 17 00:00:00 2001 From: guaneec Date: Wed, 26 Oct 2022 15:00:03 +0800 Subject: Merge fix --- modules/hypernetworks/hypernetwork.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index eab8b32f..bd171793 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -190,7 +190,7 @@ class Hypernetwork: print(f"Weight initialization is {self.weight_init}") self.add_layer_norm = state_dict.get('is_layer_norm', False) print(f"Layer norm is set to {self.add_layer_norm}") - self.use_dropout = state_dict.get('use_dropout', False + self.use_dropout = state_dict.get('use_dropout', False) print(f"Dropout usage is set to {self.use_dropout}" ) self.activate_output = state_dict.get('activate_output', True) -- cgit v1.2.1 From b6a8bb123bd519736306417399f6441e504f1e8b Mon Sep 17 00:00:00 2001 From: guaneec Date: Wed, 26 Oct 2022 15:15:19 +0800 Subject: Fix merge --- modules/hypernetworks/hypernetwork.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) (limited to 'modules') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index bd171793..2997cead 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -60,7 +60,7 @@ class HypernetworkModule(torch.nn.Module): linears.append(torch.nn.LayerNorm(int(dim * layer_structure[i+1]))) # Add dropout except last layer - if use_dropout and i < len(layer_structure) - 2: + if use_dropout and i < len(layer_structure) - 3: linears.append(torch.nn.Dropout(p=0.3)) self.linear = torch.nn.Sequential(*linears) @@ -126,7 +126,7 @@ class Hypernetwork: filename = None name = None - def __init__(self, name=None, enable_sizes=None, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False, activate_output=False) + def __init__(self, name=None, enable_sizes=None, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False, activate_output=False): self.filename = None self.name = name self.layers = {} -- cgit v1.2.1 From 85fcccc105aa50f1d78de559233eaa9f384608b5 Mon Sep 17 00:00:00 2001 From: AngelBottomless <35677394+aria1th@users.noreply.github.com> Date: Wed, 26 Oct 2022 22:24:33 +0900 Subject: Squashed commit of fixing dropout silently fix dropouts for future hypernetworks add kwargs for Hypernetwork class hypernet UI for gradio input add recommended options remove as options revert adding options in ui --- modules/hypernetworks/hypernetwork.py | 25 +++++++++++++++++-------- modules/ui.py | 4 ++-- 2 files changed, 19 insertions(+), 10 deletions(-) (limited to 'modules') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 2997cead..dd921153 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -34,7 +34,8 @@ class HypernetworkModule(torch.nn.Module): } activation_dict.update({cls_name.lower(): cls_obj for cls_name, cls_obj in inspect.getmembers(torch.nn.modules.activation) if inspect.isclass(cls_obj) and cls_obj.__module__ == 'torch.nn.modules.activation'}) - def __init__(self, dim, state_dict=None, layer_structure=None, activation_func=None, weight_init='Normal', add_layer_norm=False, use_dropout=False, activate_output=False): + def __init__(self, dim, state_dict=None, layer_structure=None, activation_func=None, weight_init='Normal', + add_layer_norm=False, use_dropout=False, activate_output=False, **kwargs): super().__init__() assert layer_structure is not None, "layer_structure must not be None" @@ -60,7 +61,7 @@ class HypernetworkModule(torch.nn.Module): linears.append(torch.nn.LayerNorm(int(dim * layer_structure[i+1]))) # Add dropout except last layer - if use_dropout and i < len(layer_structure) - 3: + if 'last_layer_dropout' in kwargs and kwargs['last_layer_dropout'] and use_dropout and i < len(layer_structure) - 2: linears.append(torch.nn.Dropout(p=0.3)) self.linear = torch.nn.Sequential(*linears) @@ -126,7 +127,7 @@ class Hypernetwork: filename = None name = None - def __init__(self, name=None, enable_sizes=None, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False, activate_output=False): + def __init__(self, name=None, enable_sizes=None, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False, activate_output=False, **kwargs): self.filename = None self.name = name self.layers = {} @@ -139,11 +140,14 @@ class Hypernetwork: self.add_layer_norm = add_layer_norm self.use_dropout = use_dropout self.activate_output = activate_output + self.last_layer_dropout = kwargs['last_layer_dropout'] if 'last_layer_dropout' in kwargs else True for size in enable_sizes or []: self.layers[size] = ( - HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.weight_init, self.add_layer_norm, self.use_dropout, self.activate_output), - HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.weight_init, self.add_layer_norm, self.use_dropout, self.activate_output), + HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.weight_init, + self.add_layer_norm, self.use_dropout, self.activate_output, last_layer_dropout=self.last_layer_dropout), + HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.weight_init, + self.add_layer_norm, self.use_dropout, self.activate_output, last_layer_dropout=self.last_layer_dropout), ) def weights(self): @@ -172,7 +176,8 @@ class Hypernetwork: state_dict['sd_checkpoint'] = self.sd_checkpoint state_dict['sd_checkpoint_name'] = self.sd_checkpoint_name state_dict['activate_output'] = self.activate_output - + state_dict['last_layer_dropout'] = self.last_layer_dropout + torch.save(state_dict, filename) def load(self, filename): @@ -193,12 +198,16 @@ class Hypernetwork: self.use_dropout = state_dict.get('use_dropout', False) print(f"Dropout usage is set to {self.use_dropout}" ) self.activate_output = state_dict.get('activate_output', True) + print(f"Activate last layer is set to {self.activate_output}") + self.last_layer_dropout = state_dict.get('last_layer_dropout', False) for size, sd in state_dict.items(): if type(size) == int: self.layers[size] = ( - HypernetworkModule(size, sd[0], self.layer_structure, self.activation_func, self.weight_init, self.add_layer_norm, self.use_dropout, self.activate_output), - HypernetworkModule(size, sd[1], self.layer_structure, self.activation_func, self.weight_init, self.add_layer_norm, self.use_dropout, self.activate_output), + HypernetworkModule(size, sd[0], self.layer_structure, self.activation_func, self.weight_init, + self.add_layer_norm, self.use_dropout, self.activate_output, last_layer_dropout=self.last_layer_dropout), + HypernetworkModule(size, sd[1], self.layer_structure, self.activation_func, self.weight_init, + self.add_layer_norm, self.use_dropout, self.activate_output, last_layer_dropout=self.last_layer_dropout), ) self.name = state_dict.get('name', self.name) diff --git a/modules/ui.py b/modules/ui.py index 0a63e357..55cbe859 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1238,8 +1238,8 @@ def create_ui(wrap_gradio_gpu_call): new_hypernetwork_name = gr.Textbox(label="Name") new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "320", "640", "1280"]) new_hypernetwork_layer_structure = gr.Textbox("1, 2, 1", label="Enter hypernetwork layer structure", placeholder="1st and last digit must be 1. ex:'1, 2, 1'") - new_hypernetwork_activation_func = gr.Dropdown(value="relu", label="Select activation function of hypernetwork", choices=modules.hypernetworks.ui.keys) - new_hypernetwork_initialization_option = gr.Dropdown(value = "Normal", label="Select Layer weights initialization. relu-like - Kaiming, sigmoid-like - Xavier is recommended", choices=["Normal", "KaimingUniform", "KaimingNormal", "XavierUniform", "XavierNormal"]) + new_hypernetwork_activation_func = gr.Dropdown(value="relu", label="Select activation function of hypernetwork. Recommended : Swish / Linear(none)", choices=modules.hypernetworks.ui.keys) + new_hypernetwork_initialization_option = gr.Dropdown(value = "Normal", label="Select Layer weights initialization. Normal is default, for experiments, relu-like - Kaiming, sigmoid-like - Xavier is recommended", choices=["Normal", "KaimingUniform", "KaimingNormal", "XavierUniform", "XavierNormal"]) new_hypernetwork_add_layer_norm = gr.Checkbox(label="Add layer normalization") new_hypernetwork_use_dropout = gr.Checkbox(label="Use dropout") overwrite_old_hypernetwork = gr.Checkbox(value=False, label="Overwrite Old Hypernetwork") -- cgit v1.2.1 From cc56df996e95c2c82295ab7b9928da2544791220 Mon Sep 17 00:00:00 2001 From: guaneec Date: Wed, 26 Oct 2022 23:51:51 +0800 Subject: Fix dropout logic --- modules/hypernetworks/hypernetwork.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) (limited to 'modules') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index dd921153..b17598fe 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -35,7 +35,7 @@ class HypernetworkModule(torch.nn.Module): activation_dict.update({cls_name.lower(): cls_obj for cls_name, cls_obj in inspect.getmembers(torch.nn.modules.activation) if inspect.isclass(cls_obj) and cls_obj.__module__ == 'torch.nn.modules.activation'}) def __init__(self, dim, state_dict=None, layer_structure=None, activation_func=None, weight_init='Normal', - add_layer_norm=False, use_dropout=False, activate_output=False, **kwargs): + add_layer_norm=False, use_dropout=False, activate_output=False, last_layer_dropout=True): super().__init__() assert layer_structure is not None, "layer_structure must not be None" @@ -61,7 +61,7 @@ class HypernetworkModule(torch.nn.Module): linears.append(torch.nn.LayerNorm(int(dim * layer_structure[i+1]))) # Add dropout except last layer - if 'last_layer_dropout' in kwargs and kwargs['last_layer_dropout'] and use_dropout and i < len(layer_structure) - 2: + if use_dropout and (i < len(layer_structure) - 3 or last_layer_dropout and i < len(layer_structure) - 2): linears.append(torch.nn.Dropout(p=0.3)) self.linear = torch.nn.Sequential(*linears) -- cgit v1.2.1 From 029d7c75436558f1e884bb127caed73caaecb83a Mon Sep 17 00:00:00 2001 From: AngelBottomless <35677394+aria1th@users.noreply.github.com> Date: Thu, 27 Oct 2022 14:44:53 +0900 Subject: Revert unresolved changes in Bias initialization it should be zeros_ or parameterized in future properly. --- modules/hypernetworks/hypernetwork.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index b17598fe..25427a37 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -75,7 +75,7 @@ class HypernetworkModule(torch.nn.Module): w, b = layer.weight.data, layer.bias.data if weight_init == "Normal" or type(layer) == torch.nn.LayerNorm: normal_(w, mean=0.0, std=0.01) - normal_(b, mean=0.0, std=0.005) + normal_(b, mean=0.0, std=0) elif weight_init == 'XavierUniform': xavier_uniform_(w) zeros_(b) -- cgit v1.2.1 From 44ab954fabb9c1273366ebdca47f8da394d61aab Mon Sep 17 00:00:00 2001 From: random_thoughtss Date: Sat, 29 Oct 2022 10:02:56 -0700 Subject: Fix latent upscale highres fix #3888 --- modules/processing.py | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) (limited to 'modules') diff --git a/modules/processing.py b/modules/processing.py index 548eec29..f18b7db2 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -653,6 +653,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): if opts.use_scale_latent_for_hires_fix: samples = torch.nn.functional.interpolate(samples, size=(self.height // opt_f, self.width // opt_f), mode="bilinear") + image_conditioning = self.txt2img_image_conditioning(samples) else: decoded_samples = decode_first_stage(self.sd_model, samples) @@ -674,6 +675,12 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): samples = self.sd_model.get_first_stage_encoding(self.sd_model.encode_first_stage(decoded_samples)) + image_conditioning = self.img2img_image_conditioning( + decoded_samples, + samples, + decoded_samples.new_ones(decoded_samples.shape[0], 1, decoded_samples.shape[2], decoded_samples.shape[3]) + ) + shared.state.nextjob() self.sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers, self.sampler_index, self.sd_model) @@ -684,11 +691,6 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): x = None devices.torch_gc() - image_conditioning = self.img2img_image_conditioning( - decoded_samples, - samples, - decoded_samples.new_ones(decoded_samples.shape[0], 1, decoded_samples.shape[2], decoded_samples.shape[3]) - ) samples = self.sampler.sample_img2img(self, samples, noise, conditioning, unconditional_conditioning, steps=self.steps, image_conditioning=image_conditioning) return samples -- cgit v1.2.1 From 6e2ce4e735db64afcd0fe637327ca4ec78335706 Mon Sep 17 00:00:00 2001 From: random_thoughtss Date: Sat, 29 Oct 2022 10:35:51 -0700 Subject: Added image conditioning to latent upscale. Only comuted if the mask weight is not 1.0 to avoid extra memory. Also includes some code cleanup. --- modules/processing.py | 29 +++++++++++------------------ 1 file changed, 11 insertions(+), 18 deletions(-) (limited to 'modules') diff --git a/modules/processing.py b/modules/processing.py index f18b7db2..ee0e9e34 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -134,11 +134,7 @@ class StableDiffusionProcessing(): # Dummy zero conditioning if we're not using inpainting model. # Still takes up a bit of memory, but no encoder call. # Pretty sure we can just make this a 1x1 image since its not going to be used besides its batch size. - return torch.zeros( - x.shape[0], 5, 1, 1, - dtype=x.dtype, - device=x.device - ) + return x.new_zeros(x.shape[0], 5, 1, 1) height = height or self.height width = width or self.width @@ -156,11 +152,7 @@ class StableDiffusionProcessing(): def img2img_image_conditioning(self, source_image, latent_image, image_mask = None): if self.sampler.conditioning_key not in {'hybrid', 'concat'}: # Dummy zero conditioning if we're not using inpainting model. - return torch.zeros( - latent_image.shape[0], 5, 1, 1, - dtype=latent_image.dtype, - device=latent_image.device - ) + return latent_image.new_zeros(latent_image.shape[0], 5, 1, 1) # Handle the different mask inputs if image_mask is not None: @@ -174,11 +166,10 @@ class StableDiffusionProcessing(): # Inpainting model uses a discretized mask as input, so we round to either 1.0 or 0.0 conditioning_mask = torch.round(conditioning_mask) else: - conditioning_mask = torch.ones(1, 1, *source_image.shape[-2:]) + conditioning_mask = source_image.new_ones(1, 1, *source_image.shape[-2:]) # Create another latent image, this time with a masked version of the original input. # Smoothly interpolate between the masked and unmasked latent conditioning image using a parameter. - conditioning_mask = conditioning_mask.to(source_image.device) conditioning_image = torch.lerp( source_image, source_image * (1.0 - conditioning_mask), @@ -653,7 +644,13 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): if opts.use_scale_latent_for_hires_fix: samples = torch.nn.functional.interpolate(samples, size=(self.height // opt_f, self.width // opt_f), mode="bilinear") - image_conditioning = self.txt2img_image_conditioning(samples) + + # Avoid making the inpainting conditioning unless necessary as + # this does need some extra compute to decode / encode the image again. + if getattr(self, "inpainting_mask_weight", shared.opts.inpainting_mask_weight) < 1.0: + image_conditioning = self.img2img_image_conditioning(decode_first_stage(self.sd_model, samples), samples) + else: + image_conditioning = self.txt2img_image_conditioning(samples) else: decoded_samples = decode_first_stage(self.sd_model, samples) @@ -675,11 +672,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): samples = self.sd_model.get_first_stage_encoding(self.sd_model.encode_first_stage(decoded_samples)) - image_conditioning = self.img2img_image_conditioning( - decoded_samples, - samples, - decoded_samples.new_ones(decoded_samples.shape[0], 1, decoded_samples.shape[2], decoded_samples.shape[3]) - ) + image_conditioning = self.img2img_image_conditioning(decoded_samples, samples) shared.state.nextjob() -- cgit v1.2.1 From 39f55c3c35873bc7dd9792cb2155746a1c3d4292 Mon Sep 17 00:00:00 2001 From: random_thoughtss Date: Sat, 29 Oct 2022 14:13:02 -0700 Subject: Re-add explicit device move --- modules/processing.py | 1 + 1 file changed, 1 insertion(+) (limited to 'modules') diff --git a/modules/processing.py b/modules/processing.py index ee0e9e34..d07e3db9 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -170,6 +170,7 @@ class StableDiffusionProcessing(): # Create another latent image, this time with a masked version of the original input. # Smoothly interpolate between the masked and unmasked latent conditioning image using a parameter. + conditioning_mask = conditioning_mask.to(source_image.device).to(source_image.dtype) conditioning_image = torch.lerp( source_image, source_image * (1.0 - conditioning_mask), -- cgit v1.2.1 From 71571e3f055237d71ba2d47756846ad1d73be00c Mon Sep 17 00:00:00 2001 From: random_thoughtss Date: Sun, 30 Oct 2022 00:35:40 -0700 Subject: Replaced master branch fix with updated fix. --- modules/processing.py | 2 -- 1 file changed, 2 deletions(-) (limited to 'modules') diff --git a/modules/processing.py b/modules/processing.py index 3dd44d3a..512c484f 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -688,8 +688,6 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): noise = create_random_tensors(samples.shape[1:], seeds=seeds, subseeds=subseeds, subseed_strength=subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self) - image_conditioning = self.txt2img_image_conditioning(x) - # GC now before running the next img2img to prevent running out of memory x = None devices.torch_gc() -- cgit v1.2.1 From d9e4e4d7a09d4aee8ce249a3c8e91ce165b10fa5 Mon Sep 17 00:00:00 2001 From: random_thoughtss Date: Sun, 30 Oct 2022 15:33:02 -0700 Subject: Fix non-square full resolution inpainting. --- modules/masking.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules') diff --git a/modules/masking.py b/modules/masking.py index fd8d9241..a5c4d2da 100644 --- a/modules/masking.py +++ b/modules/masking.py @@ -49,7 +49,7 @@ def expand_crop_region(crop_region, processing_width, processing_height, image_w ratio_processing = processing_width / processing_height if ratio_crop_region > ratio_processing: - desired_height = (x2 - x1) * ratio_processing + desired_height = (x2 - x1) / ratio_processing desired_height_diff = int(desired_height - (y2-y1)) y1 -= desired_height_diff//2 y2 += desired_height_diff - desired_height_diff//2 -- cgit v1.2.1 From 36966e3200943dbf890b5338cfa939df552d3c47 Mon Sep 17 00:00:00 2001 From: Muhammad Rizqi Nur Date: Mon, 31 Oct 2022 15:38:58 +0700 Subject: Fix #4035 --- modules/sd_models.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules') diff --git a/modules/sd_models.py b/modules/sd_models.py index f86dc3ed..a29c8c1a 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -201,7 +201,7 @@ def load_model_weights(model, checkpoint_info): if shared.opts.sd_checkpoint_cache > 0: checkpoints_loaded[checkpoint_info] = model.state_dict().copy() - while len(checkpoints_loaded) > shared.opts.sd_checkpoint_cache: + while len(checkpoints_loaded) > shared.opts.sd_checkpoint_cache + 1: checkpoints_loaded.popitem(last=False) # LRU else: print(f"Loading weights [{sd_model_hash}] from cache") -- cgit v1.2.1 From bf7a699845675eefdabb9cfa40c55398976274ae Mon Sep 17 00:00:00 2001 From: Muhammad Rizqi Nur Date: Mon, 31 Oct 2022 16:27:27 +0700 Subject: Fix #4035 for real now --- modules/sd_models.py | 13 +++++++------ 1 file changed, 7 insertions(+), 6 deletions(-) (limited to 'modules') diff --git a/modules/sd_models.py b/modules/sd_models.py index a29c8c1a..b2dd005a 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -165,6 +165,9 @@ def load_model_weights(model, checkpoint_info): checkpoint_file = checkpoint_info.filename sd_model_hash = checkpoint_info.hash + if shared.opts.sd_checkpoint_cache > 0 and hasattr(model, "sd_checkpoint_info"): + checkpoints_loaded[model.sd_checkpoint_info] = model.state_dict().copy() + if checkpoint_info not in checkpoints_loaded: print(f"Loading weights [{sd_model_hash}] from {checkpoint_file}") @@ -198,16 +201,14 @@ def load_model_weights(model, checkpoint_info): model.first_stage_model.load_state_dict(vae_dict) model.first_stage_model.to(devices.dtype_vae) - - if shared.opts.sd_checkpoint_cache > 0: - checkpoints_loaded[checkpoint_info] = model.state_dict().copy() - while len(checkpoints_loaded) > shared.opts.sd_checkpoint_cache + 1: - checkpoints_loaded.popitem(last=False) # LRU else: print(f"Loading weights [{sd_model_hash}] from cache") - checkpoints_loaded.move_to_end(checkpoint_info) model.load_state_dict(checkpoints_loaded[checkpoint_info]) + if shared.opts.sd_checkpoint_cache > 0: + while len(checkpoints_loaded) > shared.opts.sd_checkpoint_cache: + checkpoints_loaded.popitem(last=False) # LRU + model.sd_model_hash = sd_model_hash model.sd_model_checkpoint = checkpoint_file model.sd_checkpoint_info = checkpoint_info -- cgit v1.2.1 From a9e979977a8e3999b01b6a086bb1332ab7ab308b Mon Sep 17 00:00:00 2001 From: Artem Zagidulin Date: Wed, 2 Nov 2022 19:05:01 +0300 Subject: process_one --- modules/processing.py | 3 +++ modules/scripts.py | 16 ++++++++++++++++ 2 files changed, 19 insertions(+) (limited to 'modules') diff --git a/modules/processing.py b/modules/processing.py index 3a364b5f..72a2ee4e 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -509,6 +509,9 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: if len(prompts) == 0: break + if p.scripts is not None: + p.scripts.process_one(p) + with devices.autocast(): uc = prompt_parser.get_learned_conditioning(shared.sd_model, len(prompts) * [p.negative_prompt], p.steps) c = prompt_parser.get_multicond_learned_conditioning(shared.sd_model, prompts, p.steps) diff --git a/modules/scripts.py b/modules/scripts.py index 533db45c..9f82efea 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -70,6 +70,13 @@ class Script: pass + def process_one(self, p, *args): + """ + Same as process(), but called for every iteration + """ + + pass + def postprocess(self, p, processed, *args): """ This function is called after processing ends for AlwaysVisible scripts. @@ -294,6 +301,15 @@ class ScriptRunner: print(f"Error running process: {script.filename}", file=sys.stderr) print(traceback.format_exc(), file=sys.stderr) + def process_one(self, p): + for script in self.alwayson_scripts: + try: + script_args = p.script_args[script.args_from:script.args_to] + script.process_one(p, *script_args) + except Exception: + print(f"Error running process_one: {script.filename}", file=sys.stderr) + print(traceback.format_exc(), file=sys.stderr) + def postprocess(self, p, processed): for script in self.alwayson_scripts: try: -- cgit v1.2.1 From f1b6ac64e451036fb4dfabe66d79488c56c06776 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kyu=E2=99=A5?= <3ad4gum@gmail.com> Date: Wed, 2 Nov 2022 17:24:42 +0100 Subject: Added option to preview Created images on batch completion. --- modules/shared.py | 25 ++++++++++++++++--------- modules/ui.py | 2 +- 2 files changed, 17 insertions(+), 10 deletions(-) (limited to 'modules') diff --git a/modules/shared.py b/modules/shared.py index d8e99f85..d4cf32a4 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -146,6 +146,9 @@ class State: self.interrupted = True def nextjob(self): + if opts.show_progress_every_n_steps == -1: + self.do_set_current_image() + self.job_no += 1 self.sampling_step = 0 self.current_image_sampling_step = 0 @@ -186,17 +189,21 @@ class State: """sets self.current_image from self.current_latent if enough sampling steps have been made after the last call to this""" def set_current_image(self): + if self.sampling_step - self.current_image_sampling_step >= opts.show_progress_every_n_steps and opts.show_progress_every_n_steps > 0: + self.do_set_current_image() + + def do_set_current_image(self): if not parallel_processing_allowed: return + if self.current_latent is None: + return + + if opts.show_progress_grid: + self.current_image = sd_samplers.samples_to_image_grid(self.current_latent) + else: + self.current_image = sd_samplers.sample_to_image(self.current_latent) - if self.sampling_step - self.current_image_sampling_step >= opts.show_progress_every_n_steps and self.current_latent is not None: - if opts.show_progress_grid: - self.current_image = sd_samplers.samples_to_image_grid(self.current_latent) - else: - self.current_image = sd_samplers.sample_to_image(self.current_latent) - - self.current_image_sampling_step = self.sampling_step - + self.current_image_sampling_step = self.sampling_step state = State() @@ -351,7 +358,7 @@ options_templates.update(options_section(('interrogate', "Interrogate Options"), options_templates.update(options_section(('ui', "User interface"), { "show_progressbar": OptionInfo(True, "Show progressbar"), - "show_progress_every_n_steps": OptionInfo(0, "Show image creation progress every N sampling steps. Set 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 32, "step": 1}), + "show_progress_every_n_steps": OptionInfo(0, "Show image creation progress every N sampling steps. Set to 0 to disable. Set to -1 to show after completion of batch.", gr.Slider, {"minimum": -1, "maximum": 32, "step": 1}), "show_progress_grid": OptionInfo(True, "Show previews of all images generated in a batch as a grid"), "return_grid": OptionInfo(True, "Show grid in results for web"), "do_not_show_images": OptionInfo(False, "Do not show any images in results for web"), diff --git a/modules/ui.py b/modules/ui.py index 2609857e..29de1e10 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -276,7 +276,7 @@ def check_progress_call(id_part): image = gr_show(False) preview_visibility = gr_show(False) - if opts.show_progress_every_n_steps > 0: + if opts.show_progress_every_n_steps != 0: shared.state.set_current_image() image = shared.state.current_image -- cgit v1.2.1 From de64146ad2fc2030a4cd3545676f9e18c93b8b18 Mon Sep 17 00:00:00 2001 From: Artem Zagidulin Date: Wed, 2 Nov 2022 21:30:50 +0300 Subject: add number of itter --- modules/processing.py | 2 +- modules/scripts.py | 6 +++--- 2 files changed, 4 insertions(+), 4 deletions(-) (limited to 'modules') diff --git a/modules/processing.py b/modules/processing.py index 72a2ee4e..17f4a5ec 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -510,7 +510,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: break if p.scripts is not None: - p.scripts.process_one(p) + p.scripts.process_one(p, n) with devices.autocast(): uc = prompt_parser.get_learned_conditioning(shared.sd_model, len(prompts) * [p.negative_prompt], p.steps) diff --git a/modules/scripts.py b/modules/scripts.py index 9f82efea..7aa0d56a 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -70,7 +70,7 @@ class Script: pass - def process_one(self, p, *args): + def process_one(self, p, n, *args): """ Same as process(), but called for every iteration """ @@ -301,11 +301,11 @@ class ScriptRunner: print(f"Error running process: {script.filename}", file=sys.stderr) print(traceback.format_exc(), file=sys.stderr) - def process_one(self, p): + def process_one(self, p, n): for script in self.alwayson_scripts: try: script_args = p.script_args[script.args_from:script.args_to] - script.process_one(p, *script_args) + script.process_one(p, n, *script_args) except Exception: print(f"Error running process_one: {script.filename}", file=sys.stderr) print(traceback.format_exc(), file=sys.stderr) -- cgit v1.2.1 From 2ac25ea64f31fd0e7dea35d27a52f3646618c3b6 Mon Sep 17 00:00:00 2001 From: digburn Date: Wed, 2 Nov 2022 21:52:23 +0000 Subject: fix: Add required parameter to API extras route --- modules/api/models.py | 1 + 1 file changed, 1 insertion(+) (limited to 'modules') diff --git a/modules/api/models.py b/modules/api/models.py index 9ee42a17..9069c0ac 100644 --- a/modules/api/models.py +++ b/modules/api/models.py @@ -131,6 +131,7 @@ class ExtrasBaseRequest(BaseModel): upscaler_1: str = Field(default="None", title="Main upscaler", description=f"The name of the main upscaler to use, it has to be one of this list: {' , '.join([x.name for x in sd_upscalers])}") upscaler_2: str = Field(default="None", title="Secondary upscaler", description=f"The name of the secondary upscaler to use, it has to be one of this list: {' , '.join([x.name for x in sd_upscalers])}") extras_upscaler_2_visibility: float = Field(default=0, title="Secondary upscaler visibility", ge=0, le=1, allow_inf_nan=False, description="Sets the visibility of secondary upscaler, values should be between 0 and 1.") + upscale_first: bool = Field(default=True, title="Upscale first", description="Should the upscaler run before restoring faces?") class ExtraBaseResponse(BaseModel): html_info: str = Field(title="HTML info", description="A series of HTML tags containing the process info.") -- cgit v1.2.1 From 313e14de04d9955c6ad077341feceb0fc7f2f1d3 Mon Sep 17 00:00:00 2001 From: Chris OBryan <13701027+cobryan05@users.noreply.github.com> Date: Wed, 2 Nov 2022 21:37:43 -0500 Subject: extras - skip unnecessary second hash of image There is no need to re-hash the input image each iteration of the loop. This also reverts PR #4026 as it was determined the cache hits it avoids were actually valid. --- modules/extras.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) (limited to 'modules') diff --git a/modules/extras.py b/modules/extras.py index 8e2ab35c..71b93a06 100644 --- a/modules/extras.py +++ b/modules/extras.py @@ -136,12 +136,13 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_ def run_upscalers_blend(params: List[UpscaleParams], image: Image.Image, info: str) -> Tuple[Image.Image, str]: blended_result: Image.Image = None + image_hash: str = hash(np.array(image.getdata()).tobytes()) for upscaler in params: upscale_args = (upscaler.upscaler_idx, upscaling_resize, resize_mode, upscaling_resize_w, upscaling_resize_h, upscaling_crop) - cache_key = LruCache.Key(image_hash=hash(np.array(image.getdata()).tobytes()), + cache_key = LruCache.Key(image_hash=image_hash, info_hash=hash(info), - args_hash=hash((upscale_args, upscale_first))) + args_hash=hash(upscale_args)) cached_entry = cached_images.get(cache_key) if cached_entry is None: res = upscale(image, *upscale_args) -- cgit v1.2.1 From 7a2e36b583ef9eaefa44322e16faff6f9f1af169 Mon Sep 17 00:00:00 2001 From: Bruno Seoane Date: Thu, 3 Nov 2022 00:51:22 -0300 Subject: Add config and lists endpoints --- modules/api/api.py | 97 ++++++++++++++++++++++++++++++++++++++++++++++++--- modules/api/models.py | 70 +++++++++++++++++++++++++++++++++++-- 2 files changed, 159 insertions(+), 8 deletions(-) (limited to 'modules') diff --git a/modules/api/api.py b/modules/api/api.py index 71c9c160..ed2dce5d 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -2,14 +2,17 @@ import base64 import io import time import uvicorn -from gradio.processing_utils import decode_base64_to_file, decode_base64_to_image -from fastapi import APIRouter, Depends, HTTPException +from threading import Lock +from gradio.processing_utils import encode_pil_to_base64, decode_base64_to_file, decode_base64_to_image +from fastapi import APIRouter, Depends, FastAPI, HTTPException import modules.shared as shared from modules.api.models import * from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images -from modules.sd_samplers import all_samplers, sample_to_image, samples_to_image_grid +from modules.sd_samplers import all_samplers from modules.extras import run_extras, run_pnginfo - +from modules.sd_models import checkpoints_list +from modules.realesrgan_model import get_realesrgan_models +from typing import List def upscaler_to_index(name: str): try: @@ -37,7 +40,7 @@ def encode_pil_to_base64(image): class Api: - def __init__(self, app, queue_lock): + def __init__(self, app: FastAPI, queue_lock: Lock): self.router = APIRouter() self.app = app self.queue_lock = queue_lock @@ -48,6 +51,19 @@ class Api: self.app.add_api_route("/sdapi/v1/png-info", self.pnginfoapi, methods=["POST"], response_model=PNGInfoResponse) self.app.add_api_route("/sdapi/v1/progress", self.progressapi, methods=["GET"], response_model=ProgressResponse) self.app.add_api_route("/sdapi/v1/interrupt", self.interruptapi, methods=["POST"]) + self.app.add_api_route("/sdapi/v1/options", self.get_config, methods=["GET"], response_model=OptionsModel) + self.app.add_api_route("/sdapi/v1/options", self.set_config, methods=["POST"]) + self.app.add_api_route("/sdapi/v1/cmd-flags", self.get_cmd_flags, methods=["GET"], response_model=FlagsModel) + self.app.add_api_route("/sdapi/v1/info", self.get_info, methods=["GET"]) + self.app.add_api_route("/sdapi/v1/samplers", self.get_samplers, methods=["GET"], response_model=List[SamplerItem]) + self.app.add_api_route("/sdapi/v1/upscalers", self.get_upscalers, methods=["GET"], response_model=List[UpscalerItem]) + self.app.add_api_route("/sdapi/v1/sd-models", self.get_sd_models, methods=["GET"], response_model=List[SDModelItem]) + self.app.add_api_route("/sdapi/v1/hypernetworks", self.get_hypernetworks, methods=["GET"], response_model=List[HypernetworkItem]) + self.app.add_api_route("/sdapi/v1/face-restorers", self.get_face_restorers, methods=["GET"], response_model=List[FaceRestorerItem]) + self.app.add_api_route("/sdapi/v1/realesrgan-models", self.get_realesrgan_models, methods=["GET"], response_model=List[RealesrganItem]) + self.app.add_api_route("/sdapi/v1/prompt-styles", self.get_promp_styles, methods=["GET"], response_model=List[PromptStyleItem]) + self.app.add_api_route("/sdapi/v1/artist-categories", self.get_artists_categories, methods=["GET"], response_model=List[str]) + self.app.add_api_route("/sdapi/v1/artists", self.get_artists, methods=["GET"], response_model=List[ArtistItem]) def text2imgapi(self, txt2imgreq: StableDiffusionTxt2ImgProcessingAPI): sampler_index = sampler_to_index(txt2imgreq.sampler_index) @@ -190,6 +206,77 @@ class Api: shared.state.interrupt() return {} + + def get_config(self): + options = {} + for key in shared.opts.data.keys(): + metadata = shared.opts.data_labels.get(key) + if(metadata is not None): + options.update({key: shared.opts.data.get(key, shared.opts.data_labels.get(key).default)}) + else: + options.update({key: shared.opts.data.get(key, None)}) + + return options + + def set_config(self, req: OptionsModel): + reqDict = vars(req) + for o in reqDict: + setattr(shared.opts, o, reqDict[o]) + + shared.opts.save(shared.config_filename) + return + + def get_cmd_flags(self): + return vars(shared.cmd_opts) + + def get_info(self): + + return { + "hypernetworks": [{"name": name, "path": shared.hypernetworks[name]} for name in shared.hypernetworks], + "face_restorers": [{"name":x.name(), "cmd_dir": getattr(x, "cmd_dir", None)} for x in shared.face_restorers], + "realesrgan_models":[{"name":x.name,"path":x.data_path, "scale":x.scale} for x in get_realesrgan_models(None)], + "promp_styles":[shared.prompt_styles.styles[k] for k in shared.prompt_styles.styles], + "artists_categories": shared.artist_db.cats, + # "artists": [{"name":x[0], "score":x[1], "category":x[2]} for x in shared.artist_db.artists] + } + + def get_samplers(self): + return [{"name":sampler[0], "aliases":sampler[2], "options":sampler[3]} for sampler in all_samplers] + + def get_upscalers(self): + upscalers = [] + + for upscaler in shared.sd_upscalers: + u = upscaler.scaler + upscalers.append({"name":u.name, "model_name":u.model_name, "model_path":u.model_path, "model_url":u.model_url}) + + return upscalers + + def get_sd_models(self): + return [{"title":x.title, "model_name":x.model_name, "hash":x.hash, "filename": x.filename, "config": x.config} for x in checkpoints_list.values()] + + def get_hypernetworks(self): + return [{"name": name, "path": shared.hypernetworks[name]} for name in shared.hypernetworks] + + def get_face_restorers(self): + return [{"name":x.name(), "cmd_dir": getattr(x, "cmd_dir", None)} for x in shared.face_restorers] + + def get_realesrgan_models(self): + return [{"name":x.name,"path":x.data_path, "scale":x.scale} for x in get_realesrgan_models(None)] + + def get_promp_styles(self): + styleList = [] + for k in shared.prompt_styles.styles: + style = shared.prompt_styles.styles[k] + styleList.append({"name":style[0], "prompt": style[1], "negative_prompr": style[2]}) + + return styleList + + def get_artists_categories(self): + return shared.artist_db.cats + + def get_artists(self): + return [{"name":x[0], "score":x[1], "category":x[2]} for x in shared.artist_db.artists] def launch(self, server_name, port): self.app.include_router(self.router) diff --git a/modules/api/models.py b/modules/api/models.py index 9ee42a17..b54b188a 100644 --- a/modules/api/models.py +++ b/modules/api/models.py @@ -1,11 +1,10 @@ import inspect -from click import prompt from pydantic import BaseModel, Field, create_model -from typing import Any, Optional +from typing import Any, Optional, Union from typing_extensions import Literal from inflection import underscore from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img -from modules.shared import sd_upscalers +from modules.shared import sd_upscalers, opts, parser API_NOT_ALLOWED = [ "self", @@ -165,3 +164,68 @@ class ProgressResponse(BaseModel): eta_relative: float = Field(title="ETA in secs") state: dict = Field(title="State", description="The current state snapshot") current_image: str = Field(default=None, title="Current image", description="The current image in base64 format. opts.show_progress_every_n_steps is required for this to work.") + +fields = {} +for key, value in opts.data.items(): + metadata = opts.data_labels.get(key) + optType = opts.typemap.get(type(value), type(value)) + + if (metadata is not None): + fields.update({key: (Optional[optType], Field( + default=metadata.default ,description=metadata.label))}) + else: + fields.update({key: (Optional[optType], Field())}) + +OptionsModel = create_model("Options", **fields) + +flags = {} +_options = vars(parser)['_option_string_actions'] +for key in _options: + if(_options[key].dest != 'help'): + flag = _options[key] + _type = str + if(_options[key].default != None): _type = type(_options[key].default) + flags.update({flag.dest: (_type,Field(default=flag.default, description=flag.help))}) + +FlagsModel = create_model("Flags", **flags) + +class SamplerItem(BaseModel): + name: str = Field(title="Name") + aliases: list[str] = Field(title="Aliases") + options: dict[str, str] = Field(title="Options") + +class UpscalerItem(BaseModel): + name: str = Field(title="Name") + model_name: str | None = Field(title="Model Name") + model_path: str | None = Field(title="Path") + model_url: str | None = Field(title="URL") + +class SDModelItem(BaseModel): + title: str = Field(title="Title") + model_name: str = Field(title="Model Name") + hash: str = Field(title="Hash") + filename: str = Field(title="Filename") + config: str = Field(title="Config file") + +class HypernetworkItem(BaseModel): + name: str = Field(title="Name") + path: str | None = Field(title="Path") + +class FaceRestorerItem(BaseModel): + name: str = Field(title="Name") + cmd_dir: str | None = Field(title="Path") + +class RealesrganItem(BaseModel): + name: str = Field(title="Name") + path: str | None = Field(title="Path") + scale: int | None = Field(title="Scale") + +class PromptStyleItem(BaseModel): + name: str = Field(title="Name") + prompt: str | None = Field(title="Prompt") + negative_prompt: str | None = Field(title="Negative Prompt") + +class ArtistItem(BaseModel): + name: str = Field(title="Name") + score: float = Field(title="Score") + category: str = Field(title="Category") \ No newline at end of file -- cgit v1.2.1 From 743fffa3d6c2e9e6bb5f48093a4c88f3b53e001d Mon Sep 17 00:00:00 2001 From: Bruno Seoane Date: Thu, 3 Nov 2022 00:52:01 -0300 Subject: Remove unused endpoint --- modules/api/api.py | 12 ------------ 1 file changed, 12 deletions(-) (limited to 'modules') diff --git a/modules/api/api.py b/modules/api/api.py index ed2dce5d..a49f3755 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -54,7 +54,6 @@ class Api: self.app.add_api_route("/sdapi/v1/options", self.get_config, methods=["GET"], response_model=OptionsModel) self.app.add_api_route("/sdapi/v1/options", self.set_config, methods=["POST"]) self.app.add_api_route("/sdapi/v1/cmd-flags", self.get_cmd_flags, methods=["GET"], response_model=FlagsModel) - self.app.add_api_route("/sdapi/v1/info", self.get_info, methods=["GET"]) self.app.add_api_route("/sdapi/v1/samplers", self.get_samplers, methods=["GET"], response_model=List[SamplerItem]) self.app.add_api_route("/sdapi/v1/upscalers", self.get_upscalers, methods=["GET"], response_model=List[UpscalerItem]) self.app.add_api_route("/sdapi/v1/sd-models", self.get_sd_models, methods=["GET"], response_model=List[SDModelItem]) @@ -229,17 +228,6 @@ class Api: def get_cmd_flags(self): return vars(shared.cmd_opts) - def get_info(self): - - return { - "hypernetworks": [{"name": name, "path": shared.hypernetworks[name]} for name in shared.hypernetworks], - "face_restorers": [{"name":x.name(), "cmd_dir": getattr(x, "cmd_dir", None)} for x in shared.face_restorers], - "realesrgan_models":[{"name":x.name,"path":x.data_path, "scale":x.scale} for x in get_realesrgan_models(None)], - "promp_styles":[shared.prompt_styles.styles[k] for k in shared.prompt_styles.styles], - "artists_categories": shared.artist_db.cats, - # "artists": [{"name":x[0], "score":x[1], "category":x[2]} for x in shared.artist_db.artists] - } - def get_samplers(self): return [{"name":sampler[0], "aliases":sampler[2], "options":sampler[3]} for sampler in all_samplers] -- cgit v1.2.1 From e33d6cbddd08870e348d10a58af41fb677a39fd6 Mon Sep 17 00:00:00 2001 From: Ju1-js <40339350+Ju1-js@users.noreply.github.com> Date: Wed, 2 Nov 2022 21:04:49 -0700 Subject: Make extension manager Remote links open a new tab --- modules/ui_extensions.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules') diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py index ab807722..a81de9a7 100644 --- a/modules/ui_extensions.py +++ b/modules/ui_extensions.py @@ -86,7 +86,7 @@ def extension_table(): code += f""" - {html.escape(ext.remote or '')} + {html.escape(ext.remote or '')} {ext_status} """ -- cgit v1.2.1 From b2c48091db394c2b7d375a33f18d90c924cd4363 Mon Sep 17 00:00:00 2001 From: Gur Date: Fri, 4 Nov 2022 06:55:03 +0800 Subject: fixed api compatibility with python 3.8 --- modules/api/models.py | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) (limited to 'modules') diff --git a/modules/api/models.py b/modules/api/models.py index 9ee42a17..29a934ba 100644 --- a/modules/api/models.py +++ b/modules/api/models.py @@ -6,6 +6,7 @@ from typing_extensions import Literal from inflection import underscore from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img from modules.shared import sd_upscalers +from typing import List API_NOT_ALLOWED = [ "self", @@ -109,12 +110,12 @@ StableDiffusionImg2ImgProcessingAPI = PydanticModelGenerator( ).generate_model() class TextToImageResponse(BaseModel): - images: list[str] = Field(default=None, title="Image", description="The generated image in base64 format.") + images: List[str] = Field(default=None, title="Image", description="The generated image in base64 format.") parameters: dict info: str class ImageToImageResponse(BaseModel): - images: list[str] = Field(default=None, title="Image", description="The generated image in base64 format.") + images: List[str] = Field(default=None, title="Image", description="The generated image in base64 format.") parameters: dict info: str @@ -146,10 +147,10 @@ class FileData(BaseModel): name: str = Field(title="File name") class ExtrasBatchImagesRequest(ExtrasBaseRequest): - imageList: list[FileData] = Field(title="Images", description="List of images to work on. Must be Base64 strings") + imageList: List[FileData] = Field(title="Images", description="List of images to work on. Must be Base64 strings") class ExtrasBatchImagesResponse(ExtraBaseResponse): - images: list[str] = Field(title="Images", description="The generated images in base64 format.") + images: List[str] = Field(title="Images", description="The generated images in base64 format.") class PNGInfoRequest(BaseModel): image: str = Field(title="Image", description="The base64 encoded PNG image") -- cgit v1.2.1 From 8eb64dab3e9e40531f6a3fa606a1c23a62987249 Mon Sep 17 00:00:00 2001 From: digburn <115176097+digburn@users.noreply.github.com> Date: Fri, 4 Nov 2022 00:35:18 +0000 Subject: fix: correct default val of upscale_first to False --- modules/api/models.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules') diff --git a/modules/api/models.py b/modules/api/models.py index 9069c0ac..68fb45c6 100644 --- a/modules/api/models.py +++ b/modules/api/models.py @@ -131,7 +131,7 @@ class ExtrasBaseRequest(BaseModel): upscaler_1: str = Field(default="None", title="Main upscaler", description=f"The name of the main upscaler to use, it has to be one of this list: {' , '.join([x.name for x in sd_upscalers])}") upscaler_2: str = Field(default="None", title="Secondary upscaler", description=f"The name of the secondary upscaler to use, it has to be one of this list: {' , '.join([x.name for x in sd_upscalers])}") extras_upscaler_2_visibility: float = Field(default=0, title="Secondary upscaler visibility", ge=0, le=1, allow_inf_nan=False, description="Sets the visibility of secondary upscaler, values should be between 0 and 1.") - upscale_first: bool = Field(default=True, title="Upscale first", description="Should the upscaler run before restoring faces?") + upscale_first: bool = Field(default=False, title="Upscale first", description="Should the upscaler run before restoring faces?") class ExtraBaseResponse(BaseModel): html_info: str = Field(title="HTML info", description="A series of HTML tags containing the process info.") -- cgit v1.2.1 From 3780ad3ad837dd406da39eebd5d91009b5a58445 Mon Sep 17 00:00:00 2001 From: digburn Date: Fri, 4 Nov 2022 00:40:21 +0000 Subject: fix: loading models without vae from cache --- modules/sd_models.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) (limited to 'modules') diff --git a/modules/sd_models.py b/modules/sd_models.py index 5075fadb..ae427a5c 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -204,8 +204,9 @@ def load_model_weights(model, checkpoint_info, vae_file="auto"): checkpoints_loaded.popitem(last=False) # LRU else: - vae_name = sd_vae.get_filename(vae_file) - print(f"Loading weights [{sd_model_hash}] with {vae_name} VAE from cache") + vae_name = sd_vae.get_filename(vae_file) if vae_file else None + vae_message = f" with {vae_name} VAE" if vae_name else "" + print(f"Loading weights [{sd_model_hash}]{vae_message} from cache") checkpoints_loaded.move_to_end(checkpoint_key) model.load_state_dict(checkpoints_loaded[checkpoint_key]) -- cgit v1.2.1 From e533ff61c1baa4ad047f9c8dc05c17b64ee89ddf Mon Sep 17 00:00:00 2001 From: timntorres Date: Thu, 3 Nov 2022 22:28:22 -0700 Subject: Lift extras generate button a la #4246. --- modules/ui.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) (limited to 'modules') diff --git a/modules/ui.py b/modules/ui.py index 2609857e..6461002a 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1052,6 +1052,8 @@ def create_ui(wrap_gradio_gpu_call): extras_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, placeholder="Leave blank to save images to the default path.") show_extras_results = gr.Checkbox(label='Show result images', value=True) + submit = gr.Button('Generate', elem_id="extras_generate", variant='primary') + with gr.Tabs(elem_id="extras_resize_mode"): with gr.TabItem('Scale by'): upscaling_resize = gr.Slider(minimum=1.0, maximum=8.0, step=0.05, label="Resize", value=4) @@ -1079,8 +1081,6 @@ def create_ui(wrap_gradio_gpu_call): with gr.Group(): upscale_before_face_fix = gr.Checkbox(label='Upscale Before Restoring Faces', value=False) - submit = gr.Button('Generate', elem_id="extras_generate", variant='primary') - result_images, html_info_x, html_info = create_output_panel("extras", opts.outdir_extras_samples) submit.click( -- cgit v1.2.1 From 4dd898b8c15e342f817d3fb1c8dc9f2d5d111022 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Fri, 4 Nov 2022 08:38:11 +0300 Subject: do not mess with components' visibility for scripts; instead create group components and show/hide those; this will break scripts that create invisible components and rely on UI but the earlier i make this change the better --- modules/scripts.py | 34 ++++++++++++++++++---------------- 1 file changed, 18 insertions(+), 16 deletions(-) (limited to 'modules') diff --git a/modules/scripts.py b/modules/scripts.py index 533db45c..28ce07f4 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -18,6 +18,9 @@ class Script: args_to = None alwayson = False + """A gr.Group component that has all script's UI inside it""" + group = None + infotext_fields = None """if set in ui(), this is a list of pairs of gradio component + text; the text will be used when parsing infotext to set the value for the component; see ui.py's txt2img_paste_fields for an example @@ -218,8 +221,6 @@ class ScriptRunner: for control in controls: control.custom_script_source = os.path.basename(script.filename) - if not script.alwayson: - control.visible = False if script.infotext_fields is not None: self.infotext_fields += script.infotext_fields @@ -229,40 +230,41 @@ class ScriptRunner: script.args_to = len(inputs) for script in self.alwayson_scripts: - with gr.Group(): + with gr.Group() as group: create_script_ui(script, inputs, inputs_alwayson) + script.group = group + dropdown = gr.Dropdown(label="Script", elem_id="script_list", choices=["None"] + self.titles, value="None", type="index") dropdown.save_to_config = True inputs[0] = dropdown for script in self.selectable_scripts: - create_script_ui(script, inputs, inputs_alwayson) + with gr.Group(visible=False) as group: + create_script_ui(script, inputs, inputs_alwayson) + + script.group = group def select_script(script_index): - if 0 < script_index <= len(self.selectable_scripts): - script = self.selectable_scripts[script_index-1] - args_from = script.args_from - args_to = script.args_to - else: - args_from = 0 - args_to = 0 + selected_script = self.selectable_scripts[script_index - 1] if script_index>0 else None - return [ui.gr_show(True if i == 0 else args_from <= i < args_to or is_alwayson) for i, is_alwayson in enumerate(inputs_alwayson)] + return [gr.update(visible=selected_script == s) for s in self.selectable_scripts] def init_field(title): + """called when an initial value is set from ui-config.json to show script's UI components""" + if title == 'None': return + script_index = self.titles.index(title) - script = self.selectable_scripts[script_index] - for i in range(script.args_from, script.args_to): - inputs[i].visible = True + self.selectable_scripts[script_index].group.visible = True dropdown.init_field = init_field + dropdown.change( fn=select_script, inputs=[dropdown], - outputs=inputs + outputs=[script.group for script in self.selectable_scripts] ) return inputs -- cgit v1.2.1 From f2b69709eaff88fc3a2bd49585556ec0883bf5ea Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Fri, 4 Nov 2022 09:42:25 +0300 Subject: move option access checking to options class out of various places scattered through code --- modules/processing.py | 4 ++-- modules/shared.py | 11 +++++++++++ modules/ui.py | 20 +++++--------------- 3 files changed, 18 insertions(+), 17 deletions(-) (limited to 'modules') diff --git a/modules/processing.py b/modules/processing.py index 2168208c..a46e592d 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -418,13 +418,13 @@ def process_images(p: StableDiffusionProcessing) -> Processed: try: for k, v in p.override_settings.items(): - opts.data[k] = v # we don't call onchange for simplicity which makes changing model, hypernet impossible + setattr(opts, k, v) # we don't call onchange for simplicity which makes changing model, hypernet impossible res = process_images_inner(p) finally: for k, v in stored_opts.items(): - opts.data[k] = v + setattr(opts, k, v) return res diff --git a/modules/shared.py b/modules/shared.py index d8e99f85..024c771a 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -396,6 +396,15 @@ class Options: def __setattr__(self, key, value): if self.data is not None: if key in self.data or key in self.data_labels: + assert not cmd_opts.freeze_settings, "changing settings is disabled" + + comp_args = opts.data_labels[key].component_args + if isinstance(comp_args, dict) and comp_args.get('visible', True) is False: + raise RuntimeError(f"not possible to set {key} because it is restricted") + + if cmd_opts.hide_ui_dir_config and key in restricted_opts: + raise RuntimeError(f"not possible to set {key} because it is restricted") + self.data[key] = value return @@ -412,6 +421,8 @@ class Options: return super(Options, self).__getattribute__(item) def save(self, filename): + assert not cmd_opts.freeze_settings, "saving settings is disabled" + with open(filename, "w", encoding="utf8") as file: json.dump(self.data, file, indent=4) diff --git a/modules/ui.py b/modules/ui.py index b2b1c854..633b56ef 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1438,8 +1438,6 @@ def create_ui(wrap_gradio_gpu_call): def run_settings(*args): changed = 0 - assert not shared.cmd_opts.freeze_settings, "changing settings is disabled" - for key, value, comp in zip(opts.data_labels.keys(), args, components): if comp != dummy_component and not opts.same_type(value, opts.data_labels[key].default): return f"Bad value for setting {key}: {value}; expecting {type(opts.data_labels[key].default).__name__}", opts.dumpjson() @@ -1448,15 +1446,9 @@ def create_ui(wrap_gradio_gpu_call): if comp == dummy_component: continue - comp_args = opts.data_labels[key].component_args - if comp_args and isinstance(comp_args, dict) and comp_args.get('visible') is False: - continue - - if cmd_opts.hide_ui_dir_config and key in restricted_opts: - continue - oldval = opts.data.get(key, None) - opts.data[key] = value + + setattr(opts, key, value) if oldval != value: if opts.data_labels[key].onchange is not None: @@ -1469,17 +1461,15 @@ def create_ui(wrap_gradio_gpu_call): return f'{changed} settings changed.', opts.dumpjson() def run_settings_single(value, key): - assert not shared.cmd_opts.freeze_settings, "changing settings is disabled" - if not opts.same_type(value, opts.data_labels[key].default): return gr.update(visible=True), opts.dumpjson() oldval = opts.data.get(key, None) - if cmd_opts.hide_ui_dir_config and key in restricted_opts: + try: + setattr(opts, key, value) + except Exception: return gr.update(value=oldval), opts.dumpjson() - opts.data[key] = value - if oldval != value: if opts.data_labels[key].onchange is not None: opts.data_labels[key].onchange() -- cgit v1.2.1 From ccf1a15412ef6b518f9f54cc26a0ee5edf458108 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Fri, 4 Nov 2022 10:16:19 +0300 Subject: add an option to enable installing extensions with --listen or --share --- modules/shared.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) (limited to 'modules') diff --git a/modules/shared.py b/modules/shared.py index 024c771a..0a39cdf2 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -44,6 +44,7 @@ parser.add_argument("--precision", type=str, help="evaluate at this precision", parser.add_argument("--share", action='store_true', help="use share=True for gradio and make the UI accessible through their site") parser.add_argument("--ngrok", type=str, help="ngrok authtoken, alternative to gradio --share", default=None) parser.add_argument("--ngrok-region", type=str, help="The region in which ngrok should start.", default="us") +parser.add_argument("--enable-insecure-extension-access", action='store_true', help="enable extensions tab regardless of other options") parser.add_argument("--codeformer-models-path", type=str, help="Path to directory with codeformer model file(s).", default=os.path.join(models_path, 'Codeformer')) parser.add_argument("--gfpgan-models-path", type=str, help="Path to directory with GFPGAN model file(s).", default=os.path.join(models_path, 'GFPGAN')) parser.add_argument("--esrgan-models-path", type=str, help="Path to directory with ESRGAN model file(s).", default=os.path.join(models_path, 'ESRGAN')) @@ -99,7 +100,7 @@ restricted_opts = { "outdir_save", } -cmd_opts.disable_extension_access = cmd_opts.share or cmd_opts.listen +cmd_opts.disable_extension_access = (cmd_opts.share or cmd_opts.listen) and not cmd_opts.enable_insecure_extension_access devices.device, devices.device_interrogate, devices.device_gfpgan, devices.device_swinir, devices.device_esrgan, devices.device_scunet, devices.device_codeformer = \ (devices.cpu if any(y in cmd_opts.use_cpu for y in [x, 'all']) else devices.get_optimal_device() for x in ['sd', 'interrogate', 'gfpgan', 'swinir', 'esrgan', 'scunet', 'codeformer']) -- cgit v1.2.1 From 321e13ca176b256177c4a752d1f2bbee79b5532e Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Fri, 4 Nov 2022 10:35:30 +0300 Subject: produce a readable error message when setting an option fails on the settings screen --- modules/ui.py | 9 ++++----- 1 file changed, 4 insertions(+), 5 deletions(-) (limited to 'modules') diff --git a/modules/ui.py b/modules/ui.py index 633b56ef..3ac7540c 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1439,8 +1439,7 @@ def create_ui(wrap_gradio_gpu_call): changed = 0 for key, value, comp in zip(opts.data_labels.keys(), args, components): - if comp != dummy_component and not opts.same_type(value, opts.data_labels[key].default): - return f"Bad value for setting {key}: {value}; expecting {type(opts.data_labels[key].default).__name__}", opts.dumpjson() + assert comp == dummy_component or opts.same_type(value, opts.data_labels[key].default), f"Bad value for setting {key}: {value}; expecting {type(opts.data_labels[key].default).__name__}" for key, value, comp in zip(opts.data_labels.keys(), args, components): if comp == dummy_component: @@ -1458,7 +1457,7 @@ def create_ui(wrap_gradio_gpu_call): opts.save(shared.config_filename) - return f'{changed} settings changed.', opts.dumpjson() + return opts.dumpjson(), f'{changed} settings changed.' def run_settings_single(value, key): if not opts.same_type(value, opts.data_labels[key].default): @@ -1622,9 +1621,9 @@ def create_ui(wrap_gradio_gpu_call): text_settings = gr.Textbox(elem_id="settings_json", value=lambda: opts.dumpjson(), visible=False) settings_submit.click( - fn=run_settings, + fn=wrap_gradio_call(run_settings, extra_outputs=[gr.update()]), inputs=components, - outputs=[result, text_settings], + outputs=[text_settings, result], ) for i, k, item in quicksettings_list: -- cgit v1.2.1 From f674c488d9701e577e2aaf25e331fb44ada4f1ef Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Fri, 4 Nov 2022 10:45:34 +0300 Subject: bugfix: save image for hires fix BEFORE upscaling latent space --- modules/processing.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) (limited to 'modules') diff --git a/modules/processing.py b/modules/processing.py index a46e592d..7a2fc218 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -665,17 +665,17 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): images.save_image(image, self.outpath_samples, "", seeds[index], prompts[index], opts.samples_format, suffix="-before-highres-fix") if opts.use_scale_latent_for_hires_fix: + for i in range(samples.shape[0]): + save_intermediate(samples, i) + samples = torch.nn.functional.interpolate(samples, size=(self.height // opt_f, self.width // opt_f), mode="bilinear") - + # Avoid making the inpainting conditioning unless necessary as # this does need some extra compute to decode / encode the image again. if getattr(self, "inpainting_mask_weight", shared.opts.inpainting_mask_weight) < 1.0: image_conditioning = self.img2img_image_conditioning(decode_first_stage(self.sd_model, samples), samples) else: image_conditioning = self.txt2img_image_conditioning(samples) - - for i in range(samples.shape[0]): - save_intermediate(samples, i) else: decoded_samples = decode_first_stage(self.sd_model, samples) lowres_samples = torch.clamp((decoded_samples + 1.0) / 2.0, min=0.0, max=1.0) -- cgit v1.2.1 From 99043f33606d3057f83ea52a403e10cd29d1f7e7 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Fri, 4 Nov 2022 11:20:42 +0300 Subject: fix one of previous merges breaking the program --- modules/sd_models.py | 2 ++ 1 file changed, 2 insertions(+) (limited to 'modules') diff --git a/modules/sd_models.py b/modules/sd_models.py index 63e07a12..34c57bfa 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -167,6 +167,8 @@ def load_model_weights(model, checkpoint_info, vae_file="auto"): sd_vae.restore_base_vae(model) checkpoints_loaded[model.sd_checkpoint_info] = model.state_dict().copy() + vae_file = sd_vae.resolve_vae(checkpoint_file, vae_file=vae_file) + if checkpoint_info not in checkpoints_loaded: print(f"Loading weights [{sd_model_hash}] from {checkpoint_file}") -- cgit v1.2.1 From eeb07330131012c0294afb79165b90270679b9c7 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Fri, 4 Nov 2022 11:21:40 +0300 Subject: change process_one virtual function for script to process_batch, add extra args and docs --- modules/processing.py | 2 +- modules/scripts.py | 16 +++++++++++----- 2 files changed, 12 insertions(+), 6 deletions(-) (limited to 'modules') diff --git a/modules/processing.py b/modules/processing.py index e20d8fc4..03c9143d 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -502,7 +502,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: break if p.scripts is not None: - p.scripts.process_one(p, n) + p.scripts.process_batch(p, batch_number=n, prompts=prompts, seeds=seeds, subseeds=subseeds) with devices.autocast(): uc = prompt_parser.get_learned_conditioning(shared.sd_model, len(prompts) * [p.negative_prompt], p.steps) diff --git a/modules/scripts.py b/modules/scripts.py index 75e47cd2..366c90d7 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -73,9 +73,15 @@ class Script: pass - def process_one(self, p, n, *args): + def process_batch(self, p, *args, **kwargs): """ - Same as process(), but called for every iteration + Same as process(), but called for every batch. + + **kwargs will have those items: + - batch_number - index of current batch, from 0 to number of batches-1 + - prompts - list of prompts for current batch; you can change contents of this list but changing the number of entries will likely break things + - seeds - list of seeds for current batch + - subseeds - list of subseeds for current batch """ pass @@ -303,13 +309,13 @@ class ScriptRunner: print(f"Error running process: {script.filename}", file=sys.stderr) print(traceback.format_exc(), file=sys.stderr) - def process_one(self, p, n): + def process_batch(self, p, **kwargs): for script in self.alwayson_scripts: try: script_args = p.script_args[script.args_from:script.args_to] - script.process_one(p, n, *script_args) + script.process_batch(p, *script_args, **kwargs) except Exception: - print(f"Error running process_one: {script.filename}", file=sys.stderr) + print(f"Error running process_batch: {script.filename}", file=sys.stderr) print(traceback.format_exc(), file=sys.stderr) def postprocess(self, p, processed): -- cgit v1.2.1