bug fix

.gitignore

@@ -1,3 +1,3 @@
-venv
-sent_clf_onnx
-sentiment_model_dir
+venv/
+sent_clf_onnx/
+sentiment_model_dir/

app.py

@@ -74,7 +74,10 @@ st.markdown(hide_streamlit_style, unsafe_allow_html=True)
 @st.cache(allow_output_mutation=True, suppress_st_warning=True, max_entries=None, ttl=None)
 def create_model_dir(chkpt, model_dir):
     if not os.path.exists(chkpt):
-        os.mkdir(model_dir)
+        try:
+            os.mkdir(path=model_dir)
+        except:
+            pass
         _model = AutoModelForSequenceClassification.from_pretrained(chkpt)
         _tokenizer = AutoTokenizer.from_pretrained(chkpt)
         _model.save_pretrained(model_dir)
@@ -95,8 +98,9 @@ if select_task=='README':
     st.header("NLP Summary")
 
 ############### Pre-Download & instantiate objects for sentiment analysis *********************** START **********************
-sent_chkpt = 'distilbert-base-uncased-finetuned-sst-2-english'
-sent_model_dir='sentiment_model_dir'
+
+sent_chkpt = "distilbert-base-uncased-finetuned-sst-2-english"
+sent_model_dir="sentiment_model_dir"
 #create model/token dir
 create_model_dir(chkpt=sent_chkpt, model_dir=sent_model_dir)
 

sentiment_onnx_classify.py

@@ -8,9 +8,9 @@ import transformers.convert_graph_to_onnx as onnx_convert
 from pathlib import Path
 import os
 
-chkpt='distilbert-base-uncased-finetuned-sst-2-english'
-model= AutoModelForSequenceClassification.from_pretrained(chkpt)
-tokenizer= AutoTokenizer.from_pretrained(chkpt)
+# chkpt='distilbert-base-uncased-finetuned-sst-2-english'
+# model= AutoModelForSequenceClassification.from_pretrained(chkpt)
+# tokenizer= AutoTokenizer.from_pretrained(chkpt)
 
 def create_onnx_model(_model, _tokenizer):
     """
@@ -24,7 +24,10 @@ def create_onnx_model(_model, _tokenizer):
 
     """
     if not os.path.exists('sent_clf_onnx'):
-        os.mkdir('sent_clf_onnx')
+        try:
+            os.mkdir('sent_clf_onnx')
+        except:
+            pass
         """ 
             Making ONNX model object
         """
@@ -50,9 +53,9 @@ def create_onnx_model(_model, _tokenizer):
 
 
 
-#create onnx & onnx_int_8 sessions
-session = ort.InferenceSession("sent_clf_onnx/sentiment_classifier_onnx.onnx")
-session_int8 = ort.InferenceSession("sent_clf_onnx/sentiment_classifier_onnx_int8.onnx")
+# #create onnx & onnx_int_8 sessions
+# session = ort.InferenceSession("sent_clf_onnx/sentiment_classifier_onnx.onnx")
+# session_int8 = ort.InferenceSession("sent_clf_onnx/sentiment_classifier_onnx_int8.onnx")
 
 # options=ort.SessionOptions()
 # options.inter_op_num_threads=1

zeroshot_clf.py

@@ -5,11 +5,11 @@ from transformers import AutoModelForSequenceClassification,AutoTokenizer
 import numpy as np
 import plotly.express as px
 
-chkpt='valhalla/distilbart-mnli-12-1'
-model=AutoModelForSequenceClassification.from_pretrained(chkpt)
-tokenizer=AutoTokenizer.from_pretrained('zero_shot_clf/')
+# chkpt='valhalla/distilbart-mnli-12-1'
+# model=AutoModelForSequenceClassification.from_pretrained(chkpt)
+# tokenizer=AutoTokenizer.from_pretrained('zero_shot_clf/')
 
-def zero_shot_classification(premise: str, labels: str, model= model, tokenizer= tokenizer):
+def zero_shot_classification(premise: str, labels: str, model, tokenizer):
     try:
         labels=labels.split(',')
         labels=[l.lower() for l in labels]