1 files changed, 65 insertions, 0 deletions
diff --git a/modules/sd_models_config.py b/modules/sd_models_config.py
new file mode 100644
index 00000000..ea773a10
--- /dev/null
+++ b/modules/sd_models_config.py
@@ -0,0 +1,65 @@
+import re
+import os
+
+from modules import shared, paths
+
+sd_configs_path = shared.sd_configs_path
+sd_repo_configs_path = os.path.join(paths.paths['Stable Diffusion'], "configs", "stable-diffusion")
+
+
+config_default = shared.sd_default_config
+config_sd2 = os.path.join(sd_repo_configs_path, "v2-inference.yaml")
+config_sd2v = os.path.join(sd_repo_configs_path, "v2-inference-v.yaml")
+config_inpainting = os.path.join(sd_configs_path, "v1-inpainting-inference.yaml")
+config_instruct_pix2pix = os.path.join(sd_configs_path, "instruct-pix2pix.yaml")
+config_alt_diffusion = os.path.join(sd_configs_path, "alt-diffusion-inference.yaml")
+
+re_parametrization_v = re.compile(r'-v\b')
+
+
+def guess_model_config_from_state_dict(sd, filename):
+    fn = os.path.basename(filename)
+
+    sd2_cond_proj_weight = sd.get('cond_stage_model.model.transformer.resblocks.0.attn.in_proj_weight', None)
+    diffusion_model_input = sd.get('model.diffusion_model.input_blocks.0.0.weight', None)
+    roberta_weight = sd.get('cond_stage_model.roberta.embeddings.word_embeddings.weight', None)
+
+    if sd2_cond_proj_weight is not None and sd2_cond_proj_weight.shape[1] == 1024:
+        if re.search(re_parametrization_v, fn) or "v2-1_768" in fn:
+            return config_sd2v
+        else:
+            return config_sd2
+
+    if diffusion_model_input is not None:
+        if diffusion_model_input.shape[1] == 9:
+            return config_inpainting
+        if diffusion_model_input.shape[1] == 8:
+            return config_instruct_pix2pix
+
+    if roberta_weight is not None:
+        return config_alt_diffusion
+
+    return config_default
+
+
+def find_checkpoint_config(state_dict, info):
+    if info is None:
+        return guess_model_config_from_state_dict(state_dict, "")
+
+    config = find_checkpoint_config_near_filename(info)
+    if config is not None:
+        return config
+
+    return guess_model_config_from_state_dict(state_dict, info.filename)
+
+
+def find_checkpoint_config_near_filename(info):
+    if info is None:
+        return None
+
+    config = os.path.splitext(info.filename)[0] + ".yaml"
+    if os.path.exists(config):
+        return config
+
+    return None
+