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Update app.py
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app.py
CHANGED
@@ -86,8 +86,10 @@ def calculate_selected_score(df, selected_columns):
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return selected_quality_score
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# print(selected_semantic_score,selected_quality_score )
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selected_score = (selected_quality_score * QUALITY_WEIGHT + selected_semantic_score * SEMANTIC_WEIGHT) / (QUALITY_WEIGHT + SEMANTIC_WEIGHT)
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if selected_score.isna().any().any():
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selected_score = [0.0 for _ in range(len(selected_score))]
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return selected_score
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def get_final_score(df, selected_columns):
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@@ -157,7 +159,7 @@ def enable_all():
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def on_filter_model_size_method_change(selected_columns):
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updated_data = get_all_df(selected_columns)
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print(updated_data)
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# columns:
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selected_columns = [item for item in TASK_INFO if item in selected_columns]
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present_columns = MODEL_INFO + selected_columns
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return selected_quality_score
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# print(selected_semantic_score,selected_quality_score )
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selected_score = (selected_quality_score * QUALITY_WEIGHT + selected_semantic_score * SEMANTIC_WEIGHT) / (QUALITY_WEIGHT + SEMANTIC_WEIGHT)
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if selected_score.isna().any().any():
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selected_score = [0.0 for _ in range(len(selected_score))]
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print( selected_score.isna().any().any(),selected_score)
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return selected_score
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def get_final_score(df, selected_columns):
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def on_filter_model_size_method_change(selected_columns):
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updated_data = get_all_df(selected_columns)
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#print(updated_data)
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# columns:
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selected_columns = [item for item in TASK_INFO if item in selected_columns]
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present_columns = MODEL_INFO + selected_columns
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