File size: 7,048 Bytes
b0e6781
 
 
 
2e7bc8b
b0e6781
 
5a03d31
b0e6781
 
 
11356c3
2e7bc8b
b0e6781
 
f3cadf1
 
11356c3
f3cadf1
 
 
 
 
 
 
 
 
 
 
 
 
b0e6781
f3cadf1
b0e6781
f3cadf1
 
 
 
 
b0e6781
f3cadf1
 
 
 
 
 
 
 
 
b0e6781
 
f3cadf1
b0e6781
f3cadf1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
b0e6781
11356c3
b0e6781
 
 
2e7bc8b
 
b0e6781
 
2e7bc8b
b0e6781
f3cadf1
b0e6781
 
 
 
 
 
f3cadf1
 
2e7bc8b
 
 
 
 
 
 
b0e6781
 
 
 
2e7bc8b
 
 
 
 
b0e6781
 
 
 
 
 
 
 
 
2e7bc8b
b0e6781
 
 
 
 
 
2e7bc8b
b0e6781
f3cadf1
b0e6781
 
 
 
 
 
 
 
 
 
 
 
 
 
 
11356c3
 
b0e6781
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
import streamlit as st
import datasets
import numpy as np

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")
                        
            # with col2:
            #     with st.container():
            #         custom_css = """
            #                     <style>
            #                     .my-container-question {
            #                     background-color: #F5EEF8;
            #                     padding: 10px;
            #                     border-radius: 10px;
            #                     height: auto;
            #                     }
            #                     </style>
            #                     """
            #         st.markdown(custom_css, unsafe_allow_html=True)
                    
            #         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"""<div class="my-container-question">
            #                                 <p>QUESTION: {dataset[index]['instruction']['text']}</p>
            #                                 <p>CHOICES: {choices_text}</p>
            #                                 </div>
            #                                 """
            #         else:
            #             question_text = f"""<div class="my-container-question">
            #                             <p>QUESTION: {dataset[index]['instruction']['text']}</p>
            #                             </div>"""
                    
                    
            #         st.markdown(question_text, unsafe_allow_html=True)
                
                # with st.container():
                #     custom_css = """
                #                 <style>
                #                 .my-container-answer {
                #                 background-color: #F9EBEA;
                #                 padding: 10px;
                #                 border-radius: 10px;
                #                 height: auto;
                #                 }
                #                 </style>
                #                 """
                #     st.markdown(custom_css, unsafe_allow_html=True)
                #     st.markdown(f"""<div class="my-container-answer">
                #                 <p>CORRECT ANSWER: {dataset[index]['answer']['text']}</p>
                #                 </div>""", unsafe_allow_html=True)
            
            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']}"""
            
            # 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>{question_text.replace('(A)', '<br>(A)').replace('(B)', '<br>(B)').replace('(C)', '<br>(C)')}
                       </td>
                       <td><b>{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:
                            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>{dataset[index][model]['model_prediction']}</td>
                            </tr>"""
                        except:
                            print(f"{model} is not in {dataset_name}")
                            continue
                else:
                    for model in model_lists:
                        try:
                            s += f"""<tr>
                                <td>{display_model_names[model]}</td>
                                <td>{dataset[index][model]['text']}</td>
                                <td>{dataset[index][model]['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:40%">QUESTION</th>
                        <th style="width:40%">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()