Bugfix
Browse files
app.py
CHANGED
@@ -2,12 +2,44 @@ import gradio as gr
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import pandas as pd
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import numpy as np
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# Read the CSV file
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df = pd.read_csv('passk.csv')
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#
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# Create a dictionary to map models to friendly names
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model_to_friendly = {
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@@ -20,35 +52,53 @@ def get_friendly_name(model):
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return model_to_friendly.get(model, model)
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# Create a pivot table
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pivot = df.pivot(index='
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# Function to update the table based on selected languages
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def update_table(selected_languages):
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if not selected_languages:
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return
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display_data = pivot[selected_languages].replace(np.nan, "-")
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display_data = display_data.applymap(lambda x: f"{x:.3f}" if isinstance(x, (int, float)) else x)
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# Create the Gradio interface
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with gr.Blocks() as app:
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gr.Markdown("# Model Leaderboard")
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with gr.Row():
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language_checkboxes = gr.CheckboxGroup(
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table = gr.Dataframe(
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headers=[
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col_count=(lambda: len(languages)),
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interactive=False
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)
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# Launch the app
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if __name__ == "__main__":
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import pandas as pd
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import numpy as np
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# Dictionary mapping file extensions to full language names
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extension_to_language = {
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"clj": "Clojure",
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"cpp": "C++",
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"cs": "C#",
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"d": "D",
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"elixir": "Elixir",
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"go": "Go",
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"hs": "Haskell",
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"java": "Java",
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"jl": "Julia",
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"js": "JavaScript",
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"lua": "Lua",
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"ml": "OCaml",
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"php": "PHP",
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"pl": "Perl",
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"r": "R",
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"rb": "Ruby",
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"rkt": "Racket",
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"rs": "Rust",
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"scala": "Scala",
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"sh": "Shell",
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"swift": "Swift",
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"ts": "TypeScript"
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}
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# Read the CSV file
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df = pd.read_csv('passk.csv')
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# Function to extract language and model from Dataset
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def extract_info(dataset):
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parts = dataset.split('-')
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language = parts[1]
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model = '-'.join(parts[2:-2])
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return pd.Series({'Language': language, 'Model': model})
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# Extract language and model information
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df[['Language', 'Model']] = df['Dataset'].apply(extract_info)
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# Create a dictionary to map models to friendly names
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model_to_friendly = {
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return model_to_friendly.get(model, model)
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# Create a pivot table
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pivot = df.pivot(index='Model', columns='Language', values='Estimate')
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# Get unique languages and models
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languages = sorted(pivot.columns)
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models = sorted(pivot.index)
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# Function to update the table based on selected languages
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def update_table(selected_languages):
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if not selected_languages:
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return pd.DataFrame({'Model': [get_friendly_name(model) for model in models]})
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display_data = pivot[selected_languages].replace(np.nan, "-")
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display_data = display_data.applymap(lambda x: f"{x:.3f}" if isinstance(x, (int, float)) else x)
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# Add the Model column as the first column
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display_data.insert(0, 'Model', [get_friendly_name(model) for model in display_data.index])
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# Reset the index to remove the model names from the index
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display_data = display_data.reset_index(drop=True)
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# Rename columns to full language names
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display_data.columns = ['Model'] + [extension_to_language.get(lang, lang) for lang in selected_languages]
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return display_data
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# Create the Gradio interface
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with gr.Blocks() as app:
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gr.Markdown("# Model Leaderboard")
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with gr.Row():
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language_checkboxes = gr.CheckboxGroup(
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choices=[f"{extension_to_language[lang]} ({lang})" for lang in languages],
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label="Select Languages",
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value=[f"{extension_to_language[lang]} ({lang})" for lang in languages]
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)
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table = gr.Dataframe(
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headers=['Model'] + [extension_to_language.get(lang, lang) for lang in languages],
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type="pandas"
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)
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def update_table_wrapper(selected_languages):
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# Extract language codes from the selected full names
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selected_codes = [lang.split('(')[-1].strip(')') for lang in selected_languages]
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return update_table(selected_codes)
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language_checkboxes.change(update_table_wrapper, inputs=[language_checkboxes], outputs=[table])
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# Launch the app
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if __name__ == "__main__":
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