Add support for clip g vision model to CLIPVisionLoader.

comfy/clip_vision.py

@@ -50,18 +50,22 @@ def convert_to_transformers(sd, prefix):
         if "{}proj".format(prefix) in sd_k:
             sd['visual_projection.weight'] = sd.pop("{}proj".format(prefix)).transpose(0, 1)
 
-        sd = transformers_convert(sd, prefix, "vision_model.", 32)
+        sd = transformers_convert(sd, prefix, "vision_model.", 48)
     return sd
 
 def load_clipvision_from_sd(sd, prefix="", convert_keys=False):
     if convert_keys:
         sd = convert_to_transformers(sd, prefix)
-    if "vision_model.encoder.layers.30.layer_norm1.weight" in sd:
+    if "vision_model.encoder.layers.47.layer_norm1.weight" in sd:
+        json_config = os.path.join(os.path.dirname(os.path.realpath(__file__)), "clip_vision_config_g.json")
+    elif "vision_model.encoder.layers.30.layer_norm1.weight" in sd:
         json_config = os.path.join(os.path.dirname(os.path.realpath(__file__)), "clip_vision_config_h.json")
     else:
         json_config = os.path.join(os.path.dirname(os.path.realpath(__file__)), "clip_vision_config_vitl.json")
     clip = ClipVisionModel(json_config)
     m, u = clip.load_sd(sd)
+    if len(m) > 0:
+        print("missing clip vision:", m)
     u = set(u)
     keys = list(sd.keys())
     for k in keys:
@@ -72,4 +76,7 @@ def load_clipvision_from_sd(sd, prefix="", convert_keys=False):
 
 def load(ckpt_path):
     sd = load_torch_file(ckpt_path)
-    return load_clipvision_from_sd(sd)
+    if "visual.transformer.resblocks.0.attn.in_proj_weight" in sd:
+        return load_clipvision_from_sd(sd, prefix="visual.", convert_keys=True)
+    else:
+        return load_clipvision_from_sd(sd)

comfy/clip_vision_config_g.json

+{
+  "attention_dropout": 0.0,
+  "dropout": 0.0,
+  "hidden_act": "gelu",
+  "hidden_size": 1664,
+  "image_size": 224,
+  "initializer_factor": 1.0,
+  "initializer_range": 0.02,
+  "intermediate_size": 8192,
+  "layer_norm_eps": 1e-05,
+  "model_type": "clip_vision_model",
+  "num_attention_heads": 16,
+  "num_channels": 3,
+  "num_hidden_layers": 48,
+  "patch_size": 14,
+  "projection_dim": 1280,
+  "torch_dtype": "float32"
+}