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embeddings.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:617a2de31c505ca771ef354528371573d36d065a6fb9ba4b191f71f277162790
+size 101164120

generate-embeddings.py

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+#!/usr/bin/python3
+
+""" Work in progress
+Plan:
+   Read in fullword.json for list of works and token
+   Generate "proper" embedding for each token, and store in tensor file
+   Generate a tensor array of distance to every other token/embedding
+   Save it out
+"""
+
+
+import sys
+import json
+import torch
+from safetensors.torch import save_file
+from transformers import CLIPProcessor,CLIPModel
+
+clipsrc="openai/clip-vit-large-patch14"
+processor=None
+model=None
+
+device=torch.device("cuda")
+
+
+def init():
+    global processor
+    global model
+    # Load the processor and model
+    print("loading processor from "+clipsrc,file=sys.stderr)
+    processor = CLIPProcessor.from_pretrained(clipsrc)
+    print("done",file=sys.stderr)
+    print("loading model from "+clipsrc,file=sys.stderr)
+    model = CLIPModel.from_pretrained(clipsrc)
+    print("done",file=sys.stderr)
+
+    model = model.to(device)
+
+# Expect SINGLE WORD ONLY
+def standard_embed_calc(text):
+    inputs = processor(text=text, return_tensors="pt")
+    inputs.to(device)
+    with torch.no_grad():
+        text_features = model.get_text_features(**inputs)
+    embedding = text_features[0]
+    return embedding
+
+
+init()
+
+print("read in words from json now",file=sys.stderr)
+with open("fullword.json","r") as f:
+    tokendict = json.load(f)
+
+print("generate embeddings for each now",file=sys.stderr)
+count=1
+all_embeddings = []
+for word in tokendict.keys():
+    emb = standard_embed_calc(word)
+    emb=emb.unsqueeze(0) # stupid matrix magic to make the cat work
+    all_embeddings.append(emb)
+    count+=1
+    if (count %100) ==0:
+        print(count)
+
+embs = torch.cat(all_embeddings,dim=0)
+print("Shape of result = ",embs.shape)
+print("Saving all the things...")
+save_file({"embeddings": embs}, "embeddings.safetensors")
+
+
+print("calculate distances now")
+
+