Dagobert42 commited on
Commit
e8a5261
·
1 Parent(s): 52bd259

fix session state init

Browse files
Files changed (1) hide show
  1. app.py +12 -5
app.py CHANGED
@@ -1,9 +1,16 @@
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  import streamlit as st
 
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  from random import choice
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  from annotated_text import annotated_text
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  from resources import *
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  from helpers import *
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  base_model = "xlnet-base-cased"
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  sentences = load_sentences()
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  baseline_classifier = load_model(f"Dagobert42/{base_model}-biored-finetuned")
@@ -18,19 +25,19 @@ It was tagged by a model which was trained on 200 examples from the original dat
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  It is very possible that there should be some mistakes.
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  """)
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- txt = sentences[st.session_state.counter]
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- st.write("Example with data augmentation:" if st.session_state.augment else "Example without data augmentation:")
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- tokens = augmented_classifier(txt) if st.session_state.augment else baseline_classifier(txt)
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  annotated_text(annotate_sentence(txt, tokens))
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  st.write(annotate_sentence(txt, tokens))
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  st.write("Now try the augmented model. Hopefully it's a bit better :)")
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- st.session_state.augment = st.toggle("augmentations on" if st.session_state.augment else "augmentations off")
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  st.write("Or load another sentence")
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  def refresh_example():
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- st.session_state.counter += 1
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  st.button( ":twisted_rightwards_arrows:", on_click=refresh_example)
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  import streamlit as st
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+ from streamlit import session_state
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  from random import choice
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  from annotated_text import annotated_text
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  from resources import *
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  from helpers import *
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+ if "counter" not in session_state:
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+ session_state.counter = 0
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+
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+ if "augment" not in session_state:
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+ session_state.augment = False
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+
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  base_model = "xlnet-base-cased"
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  sentences = load_sentences()
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  baseline_classifier = load_model(f"Dagobert42/{base_model}-biored-finetuned")
 
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  It is very possible that there should be some mistakes.
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  """)
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+ txt = sentences[session_state.counter]
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+ st.write("Example with data augmentation:" if session_state.augment else "Example without data augmentation:")
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+ tokens = augmented_classifier(txt) if session_state.augment else baseline_classifier(txt)
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  annotated_text(annotate_sentence(txt, tokens))
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  st.write(annotate_sentence(txt, tokens))
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  st.write("Now try the augmented model. Hopefully it's a bit better :)")
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+ session_state.augment = st.toggle("augmentations on" if session_state.augment else "augmentations off")
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  st.write("Or load another sentence")
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  def refresh_example():
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+ session_state.counter += 1
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  st.button( ":twisted_rightwards_arrows:", on_click=refresh_example)
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