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import traceback |
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from io import StringIO |
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from typing import Optional |
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import gradio as gr |
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import pandas as pd |
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from utils import pipeline |
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from utils.models import list_models |
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from loguru import logger |
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def read_data(filepath: str) -> Optional[pd.DataFrame]: |
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if filepath.endswith('.xlsx'): |
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df = pd.read_excel(filepath) |
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elif filepath.endswith('.csv'): |
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df = pd.read_csv(filepath) |
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else: |
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raise Exception('File type not supported') |
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return df |
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def process( |
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task_name: str, |
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model_name: str, |
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pooling: str, |
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text: str, |
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file=None, |
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) -> (None, pd.DataFrame, str): |
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try: |
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logger.info(f'Processing {task_name} with {model_name} and {pooling}') |
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if file: |
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df = read_data(file.name) |
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elif text: |
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string_io = StringIO(text) |
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df = pd.read_csv(string_io) |
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assert len(df) >= 1, 'No input data' |
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else: |
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raise Exception('No input data') |
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if task_name == 'Originality': |
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df = pipeline.p0_originality(df, model_name, pooling) |
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elif task_name == 'Flexibility': |
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df = pipeline.p1_flexibility(df, model_name, pooling) |
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else: |
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raise Exception('Task not supported') |
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path = 'output.csv' |
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df.to_csv(path, index=False, encoding='utf-8-sig') |
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return None, df.iloc[:10], path |
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except: |
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error = traceback.format_exc() |
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logger.warning({ |
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'error': error, |
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'task_name': task_name, |
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'model_name': model_name, |
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'pooling': pooling, |
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'text': text, |
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'file': file, |
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}) |
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return {'Info': 'Something wrong', 'Error': traceback.format_exc()}, None, None |
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task_name_dropdown = gr.components.Dropdown( |
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label='Task Name', |
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value='Originality', |
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choices=['Originality', 'Flexibility'] |
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) |
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model_name_dropdown = gr.components.Dropdown( |
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label='Model Name', |
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value=list_models[0], |
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choices=list_models |
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) |
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pooling_dropdown = gr.components.Dropdown( |
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label='Pooling', |
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value='mean', |
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choices=['mean', 'cls'] |
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) |
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text_input = gr.components.Textbox( |
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value=open('data/example_xlm.csv', 'r').read(), |
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lines=10, |
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) |
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file_input = gr.components.File(label='Input File', file_types=['.csv', '.xlsx']) |
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text_output = gr.components.Textbox(label='Output') |
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dataframe_output = gr.components.Dataframe(label='DataFrame') |
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file_output = gr.components.File(label='Output File', file_types=['.csv', '.xlsx']) |
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app = gr.Interface( |
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fn=process, |
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inputs=[task_name_dropdown, model_name_dropdown, pooling_dropdown, text_input, file_input], |
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outputs=[text_output, dataframe_output, file_output], |
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description=open('data/description.txt', 'r').read(), |
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title='TransDis-CreativityAutoAssessment', |
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) |
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app.launch() |
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