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#!/bin/env python
""" Work in progress
Plan:
Similar to generate-embeddings.py
However, instead of reading from a dictionary, just generate by pure
numeric tokenID
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)
def embed_from_inputs(inputs):
with torch.no_grad():
text_features = model.get_text_features(**inputs)
embedding = text_features[0]
return embedding
init()
inputs = processor(text="dummy", return_tensors="pt")
inputs.to(device)
all_embeddings = []
for id in range(49405):
inputs.input_ids[0][1]=id
emb=embed_from_inputs(inputs)
emb=emb.unsqueeze(0) # stupid matrix magic to make the cat work
all_embeddings.append(emb)
if (id %100) ==0:
print(id)
embs = torch.cat(all_embeddings,dim=0)
print("Shape of result = ",embs.shape)
print("Saving all the things...")
save_file({"embeddings": embs}, "embeddings.safetensors")
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