Add application file

app.py

@@ -0,0 +1,35 @@
+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 in Neural Machine Translation')
+title = st.text_input('English Text', 'I welcome you to the demonstration.')
+
+if st.button('En-Hi Teacher'):
+	time_1 = datetime.now()
+	#subprocess.run('source  ~/miniconda3/etc/profile.d/conda.sh && conda init bash')
+	file1 = open("translation/input-files/flores/eng.devtest","w")
+	file1.write(title)
+	file1.close()
+	subprocess.run('cd translation && bash -i translate-en-hi.sh && cd ..', shell=True)
+	time_2 = datetime.now()
+	time_interval = time_2 - time_1
+	file1 = open("translation/output-translation/flores/test-flores.hi","r")
+	st.write('Hindi Translation: ',file1.read())
+	
+	file1.close()
+	st.write('Inference Time: ',time_interval)
+	
+if st.button('En-Hi Student'):
+	#title = re.sub('([.,!?()])', r' \1 ', title)
+	#title = re.sub('\s{2,}', ' ', title)
+	time_1 = datetime.now()
+	zh2en = TransformerModel.from_pretrained('Student_en_hi/out_distill/tokenized.en-hi/', checkpoint_file='../../checkpoint_use.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)