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Running
on
CPU Upgrade
Running
on
CPU Upgrade
Add few-shot info in graphs
Browse files
app.py
CHANGED
@@ -319,19 +319,20 @@ def toggle_all_categories(action: str) -> list[gr.CheckboxGroup]:
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def plot_size_vs_score(df: pd.DataFrame, hidden_df: pd.DataFrame) -> go.Figure:
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df2 = hidden_df.iloc[df.index]
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df2 = df2[df2["#Params (B)"] > 0]
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-
df2 = df2[["model_name_for_query", "#Params (B)", "AVG"]]
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df2["AVG"] = df2["AVG"].astype(float)
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-
df2 = df2.
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df2["model_name_without_org_name"] = df2["Model"].str.split("/").str[-1]
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fig = px.scatter(
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df2,
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x="#Params (B)",
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y="AVG",
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text="model_name_without_org_name",
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hover_data=["Model"],
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)
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fig.update_traces(
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-
hovertemplate="<b>%{customdata[0]}</b><br>#Params: %{x:.2f}B<br>AVG: %{y:.4f}<extra></extra>",
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textposition="top right",
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)
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fig.update_layout(yaxis_range=[0, 1])
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@@ -345,20 +346,21 @@ TASK_AVG_NAME_MAP = {
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def plot_average_scores(df: pd.DataFrame, hidden_df: pd.DataFrame) -> go.Figure:
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df2 = hidden_df.iloc[df.index]
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df2 = df2[["model_name_for_query"] + list(TASK_AVG_NAME_MAP.keys())]
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df2 = df2.rename(columns={"model_name_for_query": "Model"})
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df2 = df2.rename(columns=TASK_AVG_NAME_MAP)
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df2 = df2
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fig = go.Figure()
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-
for i, (name, row) in enumerate(df2.iterrows()):
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visible = True if i < 3 else "legendonly" # Display only the first 3 models
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fig.add_trace(
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go.Scatterpolar(
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r=row.values,
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theta=row.index,
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fill="toself",
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name=name,
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hovertemplate="%{theta}: %{r}",
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visible=visible,
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)
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def plot_size_vs_score(df: pd.DataFrame, hidden_df: pd.DataFrame) -> go.Figure:
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df2 = hidden_df.iloc[df.index]
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df2 = df2[df2["#Params (B)"] > 0]
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+
df2 = df2[["model_name_for_query", "#Params (B)", "AVG", "Few-shot"]]
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df2["AVG"] = df2["AVG"].astype(float)
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+
df2["Few-shot"] = df2["Few-shot"].astype(int)
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df2 = df2.rename(columns={"model_name_for_query": "Model", "Few-shot": "n-shot"})
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df2["model_name_without_org_name"] = df2["Model"].str.split("/").str[-1]
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fig = px.scatter(
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df2,
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x="#Params (B)",
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y="AVG",
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text="model_name_without_org_name",
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+
hover_data=["Model", "n-shot"],
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)
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fig.update_traces(
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+
hovertemplate="<b>%{customdata[0]}</b><br>#Params: %{x:.2f}B<br>n-shot: %{customdata[1]}<br>AVG: %{y:.4f}<extra></extra>",
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textposition="top right",
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)
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fig.update_layout(yaxis_range=[0, 1])
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def plot_average_scores(df: pd.DataFrame, hidden_df: pd.DataFrame) -> go.Figure:
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df2 = hidden_df.iloc[df.index]
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df2 = df2[["model_name_for_query", "Few-shot"] + list(TASK_AVG_NAME_MAP.keys())]
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df2 = df2.rename(columns={"model_name_for_query": "Model", "Few-shot": "n-shot"})
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df2 = df2.rename(columns=TASK_AVG_NAME_MAP)
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df2["n-shot"] = df2["n-shot"].astype(int)
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df2 = df2.set_index(["Model", "n-shot"]).astype(float)
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fig = go.Figure()
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for i, ((name, n_shot), row) in enumerate(df2.iterrows()):
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visible = True if i < 3 else "legendonly" # Display only the first 3 models
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fig.add_trace(
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go.Scatterpolar(
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r=row.values,
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theta=row.index,
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fill="toself",
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name=f"{name} ({n_shot}-shot)",
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hovertemplate="%{theta}: %{r}",
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visible=visible,
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)
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