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import streamlit as st | |
import datasets | |
import numpy as np | |
import html | |
def show_examples(category_name, dataset_name, model_lists, display_model_names): | |
st.divider() | |
sample_folder = f"./examples/{category_name}/{dataset_name}" | |
dataset = datasets.load_from_disk(sample_folder) | |
for index in range(len(dataset)): | |
with st.container(): | |
st.markdown(f'##### Example-{index+1}') | |
col1, col2 = st.columns([0.3, 0.7], vertical_alignment="center") | |
# with col1: | |
st.audio(f'{sample_folder}/sample_{index}.wav', format="audio/wav") | |
if dataset_name in ['CN-College-Listen-MCQ-Test', 'DREAM-TTS-MCQ-Test']: | |
choices = dataset[index]['other_attributes']['choices'] | |
if isinstance(choices, str): | |
choices_text = choices | |
elif isinstance(choices, list): | |
choices_text = ' '.join(i for i in choices) | |
question_text = f"""{dataset[index]['instruction']['text']} {choices_text}""" | |
else: | |
question_text = f"""{dataset[index]['instruction']['text']}""" | |
question_text = html.escape(question_text) | |
# st.divider() | |
with st.container(): | |
custom_css = """ | |
<style> | |
.my-container-table, p.my-container-text { | |
background-color: #fcf8dc; | |
padding: 10px; | |
border-radius: 5px; | |
font-size: 13px; | |
# height: 50px; | |
word-wrap: break-word | |
} | |
</style> | |
""" | |
st.markdown(custom_css, unsafe_allow_html=True) | |
model_lists.sort() | |
s = f"""<tr> | |
<td><b>REFERENCE</td> | |
<td><b>{html.escape(question_text.replace('(A)', '<br>(A)').replace('(B)', '<br>(B)').replace('(C)', '<br>(C)'))} | |
</td> | |
<td><b>{html.escape(dataset[index]['answer']['text'])} | |
</td> | |
</tr> | |
""" | |
if dataset_name in ['CN-College-Listen-MCQ-Test', 'DREAM-TTS-MCQ-Test']: | |
for model in model_lists: | |
try: | |
model_prediction = dataset[index][model]['model_prediction'] | |
model_prediction = model_prediction.replace('<','').replace('>','').replace('\n','(newline)').replace('*','') | |
s += f"""<tr> | |
<td>{display_model_names[model]}</td> | |
<td> | |
{dataset[index][model]['text'].replace('Choices:', '<br>Choices:').replace('(A)', '<br>(A)').replace('(B)', '<br>(B)').replace('(C)', '<br>(C)') | |
} | |
</td> | |
<td>{html.escape(model_prediction)}</td> | |
</tr>""" | |
except: | |
print(f"{model} is not in {dataset_name}") | |
continue | |
else: | |
for model in model_lists: | |
print(dataset[index][model]['model_prediction']) | |
try: | |
model_prediction = dataset[index][model]['model_prediction'] | |
model_prediction = model_prediction.replace('<','').replace('>','').replace('\n','(newline)').replace('*','') | |
s += f"""<tr> | |
<td>{display_model_names[model]}</td> | |
<td>{html.escape(dataset[index][model]['text'])}</td> | |
<td>{html.escape(model_prediction)}</td> | |
</tr>""" | |
except: | |
print(f"{model} is not in {dataset_name}") | |
continue | |
body_details = f"""<table style="table-layout: fixed; width:100%"> | |
<thead> | |
<tr style="text-align: center;"> | |
<th style="width:20%">MODEL</th> | |
<th style="width:30%">QUESTION</th> | |
<th style="width:50%">MODEL PREDICTION</th> | |
</tr> | |
{s} | |
</thead> | |
</table>""" | |
st.markdown(f"""<div class="my-container-table"> | |
{body_details} | |
</div>""", unsafe_allow_html=True) | |
st.text("") | |
st.divider() | |