Upload 2 files

openclip/calculate-distances-open.py

@@ -11,30 +11,38 @@ Plan:
 
 
 import sys
-import torch
-import open_clip
 
-from safetensors import safe_open
+if len(sys.argv) <3:
+    print("Need embedding file and a dictionary")
+    print("embedding filename must start with (mtype@stringname). ")
+    exit(1)
+
+embed_file=sys.argv[1]
+dictionary=sys.argv[2]
 
-#from transformers import CLIPProcessor,CLIPModel
+dot_index = embed_file.find(".")
+mstring=embed_file[:dot_index]
 
-device=torch.device("cuda")
+at_index = mstring.find("@")
 
-mtype='ViT-B-32'
-mname='laion2b_s34b_b79k'
+mtype=mstring[:at_index]
+mname=mstring[at_index+1:]
 
 print("Loading",mtype,mname)
 
+import torch
+import open_clip
+from safetensors import safe_open
+
+
 cmodel, _, preprocess = open_clip.create_model_and_transforms(mtype,
         pretrained=mname)
 tokenizer = open_clip.get_tokenizer(mtype)
 
-## model = model.to(device)
 
 
-#embed_file="embeddings.safetensors"
-embed_file=sys.argv[1]
-dictionary=sys.argv[2]
+device=torch.device("cuda")
+## cmodel.to(device)
 
 
 print(f"read in words from {dictionary} now",file=sys.stderr)

openclip/generate-embeddings-open.py

@@ -14,7 +14,6 @@ import torch
 import open_clip
 from safetensors.torch import save_file
 
-outfile="out.safetensors"
 
 
 """
@@ -22,14 +21,12 @@ outfile="out.safetensors"
     You MUST use the same settings when you READ from the output file as well!!
 """
 
-#mtype='ViT-B-32'
-#mname='laion2b_s34b_b79k'
-#mtype='ViT-g-14'
-#mname='laion2b_s12b_b42k'
-#mtype='ViT-H-14'
-#mname='laion2b_s32b_b79k'
+# See "list_models.txt" for full combination sets
+
+#mtype='ViT-L-14-336'
 mtype='ViT-L-14'
-mname='laion2b_s32b_b82k'
+mname='openai'
+
 #### Warning, this requires more than 4GB vram
 #mtype='ViT-H-14-quickgelu'
 #mname='dfn5b'
@@ -38,6 +35,9 @@ mname='laion2b_s32b_b82k'
 #   hf-hub:hf-internal-testing/tiny-open-clip-model'
 # for mname
 
+outfile=f"{mtype}-{mname}.safetensors"
+print("Will save to:")
+print("  ",outfile)
 print("Loading",mtype,mname)
 
 cmodel, _, preprocess = open_clip.create_model_and_transforms(