| import streamlit as st | |
| import pandas as pd | |
| import numpy as np | |
| import re | |
| from datetime import datetime | |
| import subprocess | |
| from fairseq.models.transformer import TransformerModel | |
| time_interval=0 | |
| st.title('Knowledge Distillation for Multi-Domain Neural Machine Translation') | |
| title = st.text_input('English Text', 'We are not inclined to entertain this petition under Article 32 of the Constitution of India.') | |
| if st.button('Law En-Hi Teacher'): | |
| time_1 = datetime.now() | |
| zh2en = TransformerModel.from_pretrained('law/out/tokenized.en-hi/', checkpoint_file='../../checkpoint_best.pt',bpe='subword_nmt', bpe_codes='/home/sakharam/RnD/translation/en-hi/bpe-codes/codes.en',tokenizer='moses') | |
| time_2 = datetime.now() | |
| time_interval = time_2 - time_1 | |
| st.write('Hindi Translation: ',zh2en.translate([title.lower()])[0]) | |
| st.write('Inference Time: ',time_interval) | |
| if st.button('Sports En-Hi Teacher'): | |
| time_1 = datetime.now() | |
| zh2en = TransformerModel.from_pretrained('sports/out/tokenized.en-hi/', checkpoint_file='../../checkpoint_best.pt',bpe='subword_nmt', bpe_codes='/home/sakharam/RnD/translation/en-hi/bpe-codes/codes.en',tokenizer='moses') | |
| time_2 = datetime.now() | |
| time_interval = time_2 - time_1 | |
| st.write('Hindi Translation: ',zh2en.translate([title.lower()])[0]) | |
| st.write('Inference Time: ',time_interval) | |
| if st.button('Tourism En-Hi Teacher'): | |
| time_1 = datetime.now() | |
| zh2en = TransformerModel.from_pretrained('tourism/out/tokenized.en-hi/', checkpoint_file='../../checkpoint_best.pt',bpe='subword_nmt', bpe_codes='/home/sakharam/RnD/translation/en-hi/bpe-codes/codes.en',tokenizer='moses') | |
| time_2 = datetime.now() | |
| time_interval = time_2 - time_1 | |
| st.write('Hindi Translation: ',zh2en.translate([title.lower()])[0]) | |
| st.write('Inference Time: ',time_interval) | |
| if st.button('Multi-Domain En-Hi Student'): | |
| time_1 = datetime.now() | |
| zh2en = TransformerModel.from_pretrained('multi/out/tokenized.en-hi/', checkpoint_file='../../checkpoint_best.pt',bpe='subword_nmt', bpe_codes='/home/sakharam/RnD/translation/en-hi/bpe-codes/codes.en',tokenizer='moses') | |
| time_2 = datetime.now() | |
| time_interval = time_2 - time_1 | |
| st.write('Hindi Translation: ',zh2en.translate([title.lower()])[0]) | |
| st.write('Inference Time: ',time_interval) | |