suggestions and fixes from the PR

11 files changed, 16 insertions, 31 deletions

diff --git a/extensions-builtin/Lora/scripts/lora_script.py b/extensions-builtin/Lora/scripts/lora_script.py
index b70e2de7..13d297d7 100644
--- a/extensions-builtin/Lora/scripts/lora_script.py
+++ b/extensions-builtin/Lora/scripts/lora_script.py
@@ -53,7 +53,7 @@ script_callbacks.on_infotext_pasted(lora.infotext_pasted)
 

 

 shared.options_templates.update(shared.options_section(('extra_networks', "Extra Networks"), {

-    "sd_lora": shared.OptionInfo("None", "Add Lora to prompt", gr.Dropdown, lambda: {"choices": ["None"] + list(lora.available_loras)}, refresh=lora.list_available_loras),

+    "sd_lora": shared.OptionInfo("None", "Add Lora to prompt", gr.Dropdown, lambda: {"choices": ["None", *lora.available_loras]}, refresh=lora.list_available_loras),

 }))

 

 

diff --git a/extensions-builtin/SwinIR/swinir_model_arch.py b/extensions-builtin/SwinIR/swinir_model_arch.py
index de195d9b..73e37cfa 100644
--- a/extensions-builtin/SwinIR/swinir_model_arch.py
+++ b/extensions-builtin/SwinIR/swinir_model_arch.py
@@ -644,17 +644,13 @@ class SwinIR(nn.Module):
     """
 
     def __init__(self, img_size=64, patch_size=1, in_chans=3,
-                 embed_dim=96, depths=None, num_heads=None,
+                 embed_dim=96, depths=(6, 6, 6, 6), num_heads=(6, 6, 6, 6),
                  window_size=7, mlp_ratio=4., qkv_bias=True, qk_scale=None,
                  drop_rate=0., attn_drop_rate=0., drop_path_rate=0.1,
                  norm_layer=nn.LayerNorm, ape=False, patch_norm=True,
                  use_checkpoint=False, upscale=2, img_range=1., upsampler='', resi_connection='1conv',
                  **kwargs):
         super(SwinIR, self).__init__()
-
-        depths = depths or [6, 6, 6, 6]
-        num_heads = num_heads or [6, 6, 6, 6]
-
         num_in_ch = in_chans
         num_out_ch = in_chans
         num_feat = 64
diff --git a/extensions-builtin/SwinIR/swinir_model_arch_v2.py b/extensions-builtin/SwinIR/swinir_model_arch_v2.py
index 15777af9..3ca9be78 100644
--- a/extensions-builtin/SwinIR/swinir_model_arch_v2.py
+++ b/extensions-builtin/SwinIR/swinir_model_arch_v2.py
@@ -74,12 +74,9 @@ class WindowAttention(nn.Module):
     """

 

     def __init__(self, dim, window_size, num_heads, qkv_bias=True, attn_drop=0., proj_drop=0.,

-                 pretrained_window_size=None):

+                 pretrained_window_size=(0, 0)):

 

         super().__init__()

-

-        pretrained_window_size = pretrained_window_size or [0, 0]

-

         self.dim = dim

         self.window_size = window_size  # Wh, Ww

         self.pretrained_window_size = pretrained_window_size

@@ -701,17 +698,13 @@ class Swin2SR(nn.Module):
     """

 

     def __init__(self, img_size=64, patch_size=1, in_chans=3,

-                 embed_dim=96, depths=None, num_heads=None,

+                 embed_dim=96, depths=(6, 6, 6, 6), num_heads=(6, 6, 6, 6),

                  window_size=7, mlp_ratio=4., qkv_bias=True, 

                  drop_rate=0., attn_drop_rate=0., drop_path_rate=0.1,

                  norm_layer=nn.LayerNorm, ape=False, patch_norm=True,

                  use_checkpoint=False, upscale=2, img_range=1., upsampler='', resi_connection='1conv',

                  **kwargs):

         super(Swin2SR, self).__init__()

-

-        depths = depths or [6, 6, 6, 6]

-        num_heads = num_heads or [6, 6, 6, 6]

-

         num_in_ch = in_chans

         num_out_ch = in_chans

         num_feat = 64

diff --git a/modules/codeformer/codeformer_arch.py b/modules/codeformer/codeformer_arch.py
index ff1c0b4b..45c70f84 100644
--- a/modules/codeformer/codeformer_arch.py
+++ b/modules/codeformer/codeformer_arch.py
@@ -161,13 +161,10 @@ class Fuse_sft_block(nn.Module):
 class CodeFormer(VQAutoEncoder):
     def __init__(self, dim_embd=512, n_head=8, n_layers=9, 
                 codebook_size=1024, latent_size=256,
-                connect_list=None,
-                fix_modules=None):
+                connect_list=('32', '64', '128', '256'),
+                fix_modules=('quantize', 'generator')):
         super(CodeFormer, self).__init__(512, 64, [1, 2, 2, 4, 4, 8], 'nearest',2, [16], codebook_size)
 
-        connect_list = connect_list or ['32', '64', '128', '256']
-        fix_modules = fix_modules or ['quantize', 'generator']
-
         if fix_modules is not None:
             for module in fix_modules:
                 for param in getattr(self, module).parameters():
diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py
index e3f9eb13..8b6255e2 100644
--- a/modules/hypernetworks/ui.py
+++ b/modules/hypernetworks/ui.py
@@ -5,13 +5,13 @@ import modules.hypernetworks.hypernetwork
 from modules import devices, sd_hijack, shared

 

 not_available = ["hardswish", "multiheadattention"]

-keys = [x for x in modules.hypernetworks.hypernetwork.HypernetworkModule.activation_dict.keys() if x not in not_available]

+keys = [x for x in modules.hypernetworks.hypernetwork.HypernetworkModule.activation_dict if x not in not_available]

 

 

 def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False, dropout_structure=None):

     filename = modules.hypernetworks.hypernetwork.create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure, activation_func, weight_init, add_layer_norm, use_dropout, dropout_structure)

 

-    return gr.Dropdown.update(choices=sorted(shared.hypernetworks.keys())), f"Created: {filename}", ""

+    return gr.Dropdown.update(choices=sorted(shared.hypernetworks)), f"Created: {filename}", ""

 

 

 def train_hypernetwork(*args):

diff --git a/modules/models/diffusion/uni_pc/uni_pc.py b/modules/models/diffusion/uni_pc/uni_pc.py
index f6c49f87..a227b947 100644
--- a/modules/models/diffusion/uni_pc/uni_pc.py
+++ b/modules/models/diffusion/uni_pc/uni_pc.py
@@ -275,8 +275,8 @@ def model_wrapper(
         A noise prediction model that accepts the noised data and the continuous time as the inputs.
     """
 
-    model_kwargs = model_kwargs or []
-    classifier_kwargs = classifier_kwargs or []
+    model_kwargs = model_kwargs or {}
+    classifier_kwargs = classifier_kwargs or {}
 
     def get_model_input_time(t_continuous):
         """
diff --git a/modules/scripts_postprocessing.py b/modules/scripts_postprocessing.py
index 6751406c..bac1335d 100644
--- a/modules/scripts_postprocessing.py
+++ b/modules/scripts_postprocessing.py
@@ -124,7 +124,7 @@ class ScriptPostprocessingRunner:
             script_args = args[script.args_from:script.args_to]

 

             process_args = {}

-            for (name, component), value in zip(script.controls.items(), script_args):  # noqa B007

+            for (name, _component), value in zip(script.controls.items(), script_args):

                 process_args[name] = value

 

             script.process(pp, **process_args)

diff --git a/modules/sd_hijack_clip.py b/modules/sd_hijack_clip.py
index c0c350f6..cc6e8c21 100644
--- a/modules/sd_hijack_clip.py
+++ b/modules/sd_hijack_clip.py
@@ -223,7 +223,7 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module):
             self.hijack.fixes = [x.fixes for x in batch_chunk]

 

             for fixes in self.hijack.fixes:

-                for position, embedding in fixes:  # noqa: B007

+                for _position, embedding in fixes:

                     used_embeddings[embedding.name] = embedding

 

             z = self.process_tokens(tokens, multipliers)

diff --git a/modules/shared.py b/modules/shared.py
index 913c9e63..ac67adc0 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -381,7 +381,7 @@ options_templates.update(options_section(('extra_networks', "Extra Networks"), {
     "extra_networks_card_width": OptionInfo(0, "Card width for Extra Networks (px)"),

     "extra_networks_card_height": OptionInfo(0, "Card height for Extra Networks (px)"),

     "extra_networks_add_text_separator": OptionInfo(" ", "Extra text to add before <...> when adding extra network to prompt"),

-    "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None"] + list(hypernetworks.keys())}, refresh=reload_hypernetworks),

+    "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None", hypernetworks]}, refresh=reload_hypernetworks),

 }))

 

 options_templates.update(options_section(('ui', "User interface"), {

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 47035332..9e1b2b9a 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -166,8 +166,7 @@ class EmbeddingDatabase:
         # textual inversion embeddings

         if 'string_to_param' in data:

             param_dict = data['string_to_param']

-            if hasattr(param_dict, '_parameters'):

-                param_dict = param_dict._parameters  # fix for torch 1.12.1 loading saved file from torch 1.11

+            param_dict = getattr(param_dict, '_parameters', param_dict)  # fix for torch 1.12.1 loading saved file from torch 1.11

             assert len(param_dict) == 1, 'embedding file has multiple terms in it'

             emb = next(iter(param_dict.items()))[1]

         # diffuser concepts

diff --git a/modules/ui.py b/modules/ui.py
index 83bfb7d8..7ee99473 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1230,8 +1230,8 @@ def create_ui():
                         train_embedding_name = gr.Dropdown(label='Embedding', elem_id="train_embedding", choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))

                         create_refresh_button(train_embedding_name, sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings, lambda: {"choices": sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())}, "refresh_train_embedding_name")

 

-                        train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', elem_id="train_hypernetwork", choices=list(shared.hypernetworks.keys()))

-                        create_refresh_button(train_hypernetwork_name, shared.reload_hypernetworks, lambda: {"choices": sorted(shared.hypernetworks.keys())}, "refresh_train_hypernetwork_name")

+                        train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', elem_id="train_hypernetwork", choices=sorted(shared.hypernetworks))

+                        create_refresh_button(train_hypernetwork_name, shared.reload_hypernetworks, lambda: {"choices": sorted(shared.hypernetworks)}, "refresh_train_hypernetwork_name")

 

                     with FormRow():

                         embedding_learn_rate = gr.Textbox(label='Embedding Learning rate', placeholder="Embedding Learning rate", value="0.005", elem_id="train_embedding_learn_rate")