Spaces:
Running
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CPU Upgrade
Running
on
CPU Upgrade
Commit
·
39e3785
1
Parent(s):
e2b2289
chart loading issue
Browse files
app.py
CHANGED
@@ -19,49 +19,41 @@ from tabs.data_exploration import create_exploration_tab, filter_and_display
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def create_app():
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df = load_data()
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-
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MODELS = [x.strip() for x in df["Model"].unique().tolist()]
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with gr.Blocks(
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theme=gr.themes.Soft(font=[gr.themes.GoogleFont("sans-serif")])
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) as app:
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with gr.Tabs() as tabs:
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-
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with gr.Tab("Leaderboard"):
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lb_output, lb_plot1, lb_plot2 = create_leaderboard_tab(
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df, CATEGORIES, METHODOLOGY, HEADER_CONTENT, CARDS
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)
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with gr.Tab("Model Comparison"):
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mc_info, mc_plot = create_model_comparison_tab(df, HEADER_CONTENT)
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with gr.Tab("Data Exploration"):
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exp_outputs = create_exploration_tab(df)
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# Initial
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fn=lambda: filter_leaderboard(
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df, "All", list(CATEGORIES.keys())[0], "Performance"
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),
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outputs=[lb_output, lb_plot1, lb_plot2],
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)
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fn=lambda: compare_models(
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df, [df.sort_values("Model Avg", ascending=False).iloc[0]["Model"]]
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),
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outputs=[mc_info, mc_plot],
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)
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fn=lambda: filter_and_display(
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MODELS[0],
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DATASETS[0],
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min(SCORES),
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max(SCORES),
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0,
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0,
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0,
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),
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outputs=exp_outputs[:-1],
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)
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def create_app():
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df = load_data()
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MODELS = [x.strip() for x in df["Model"].unique().tolist()]
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with gr.Blocks(
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theme=gr.themes.Soft(font=[gr.themes.GoogleFont("sans-serif")])
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) as app:
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with gr.Tabs() as tabs:
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+
with gr.Tab("Leaderboard", id=0) as tab1:
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lb_output, lb_plot1, lb_plot2 = create_leaderboard_tab(
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df, CATEGORIES, METHODOLOGY, HEADER_CONTENT, CARDS
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)
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with gr.Tab("Model Comparison", id=1) as tab2:
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mc_info, mc_plot = create_model_comparison_tab(df, HEADER_CONTENT)
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+
with gr.Tab("Data Exploration", id=2) as tab3:
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exp_outputs = create_exploration_tab(df)
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# Initial data loading
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tab1.select(
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fn=lambda: filter_leaderboard(
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df, "All", list(CATEGORIES.keys())[0], "Performance"
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),
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outputs=[lb_output, lb_plot1, lb_plot2],
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)
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tab2.select(
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fn=lambda: compare_models(
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df, [df.sort_values("Model Avg", ascending=False).iloc[0]["Model"]]
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),
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outputs=[mc_info, mc_plot],
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)
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tab3.select(
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fn=lambda: filter_and_display(
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MODELS[0], DATASETS[0], min(SCORES), max(SCORES), 0, 0, 0
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),
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outputs=exp_outputs[:-1],
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)
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