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#!/usr/bin/python3
""" Work in progress
Plan:
Generate two embeddings, from text prompts.
Create comparative graph of their values
"""
import sys
import json
import torch
from transformers import CLIPProcessor,CLIPModel
import PyQt5
import matplotlib
matplotlib.use('QT5Agg') # Set the backend to TkAgg
import matplotlib.pyplot as plt
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()
text1 = input("First word or prompt? ")
text2 = input("Second word or prompt? ")
print("generating embeddings for each now")
emb1 = standard_embed_calc(text1)
emb2 = standard_embed_calc(text2)
graph1=emb1.tolist()
graph2=emb2.tolist()
fig, ax = plt.subplots()
# Plot the two lists on the same graph using the read labels
ax.plot(graph1, label=text1[:20])
ax.plot(graph2, label=text2[:20])
# Add labels, title, and legend
#ax.set_xlabel('Index')
ax.set_ylabel('Values')
ax.set_title('Comparative Graph of Two Embeddings')
ax.legend()
# Display the graph
print("Pulling up the graph")
plt.show()
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