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lixuejing
commited on
Commit
·
33c99fd
1
Parent(s):
463d2fc
update
Browse files- app.py +22 -8
- src/display/css_html_js.py +1 -1
app.py
CHANGED
@@ -103,11 +103,13 @@ def update_table(
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hidden_df: pd.DataFrame,
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columns: list,
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query: str,
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):
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print("query", query)
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#filtered_df = filter_models(df=hidden_df, type_query=type_query, size_query=size_query, precision_query=precision_query, hide_models=hide_models)
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-
filtered_df = filter_queries(query, hidden_df)
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-
df = select_columns(filtered_df, columns)
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return df
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@@ -120,19 +122,19 @@ def search_table(df: pd.DataFrame, query: str) -> pd.DataFrame:
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return df[(df[AutoEvalColumn.dummy.name].str.contains(query, case=False))]
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def select_columns(df: pd.DataFrame, columns: list) -> pd.DataFrame:
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always_here_cols = [c.name for c in fields(
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dummy_col = [
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#AutoEvalColumn.model_type_symbol.name,
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#AutoEvalColumn.model.name,
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# We use COLS to maintain sorting
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filtered_df = df[
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always_here_cols + [c for c in
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]
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return filtered_df
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-
def filter_queries(query: str, filtered_df: pd.DataFrame):
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"""Added by Abishek"""
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final_df = []
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if query != "":
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@@ -146,7 +148,7 @@ def filter_queries(query: str, filtered_df: pd.DataFrame):
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if len(final_df) > 0:
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filtered_df = pd.concat(final_df)
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filtered_df = filtered_df.drop_duplicates(
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subset=[
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)
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return filtered_df
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@@ -287,6 +289,8 @@ with demo:
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#filter_columns_size,
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#hide_models,
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search_bar,
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],
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leaderboard_table,
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)
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@@ -303,6 +307,8 @@ with demo:
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#filter_columns_size,
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#hide_models,
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search_bar,
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],
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leaderboard_table,
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)
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@@ -321,6 +327,8 @@ with demo:
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#filter_columns_size,
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#hide_models,
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search_bar,
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],
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leaderboard_table,
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queue=True,
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@@ -416,6 +424,8 @@ with demo:
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#filter_columns_size,
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#hide_models,
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search_bar,
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],
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leaderboard_table,
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)
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@@ -432,6 +442,8 @@ with demo:
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#filter_columns_size,
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#hide_models,
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search_bar,
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],
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leaderboard_table,
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)
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@@ -450,6 +462,8 @@ with demo:
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#filter_columns_size,
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#hide_models,
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search_bar,
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],
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leaderboard_table,
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queue=True,
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hidden_df: pd.DataFrame,
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columns: list,
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query: str,
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allcolumns: list,
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allcols: list,
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):
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print("query", query)
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#filtered_df = filter_models(df=hidden_df, type_query=type_query, size_query=size_query, precision_query=precision_query, hide_models=hide_models)
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filtered_df = filter_queries(query, hidden_df,allcolums)
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df = select_columns(filtered_df, columns, allcolumns, allcols)
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return df
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return df[(df[AutoEvalColumn.dummy.name].str.contains(query, case=False))]
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+
def select_columns(df: pd.DataFrame, columns: list, allcolumns=AutoEvalColum, ALLCOLS=COLS) -> pd.DataFrame:
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always_here_cols = [c.name for c in fields(allcolumns) if c.never_hidden]
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dummy_col = [allcolumns.dummy.name]
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#AutoEvalColumn.model_type_symbol.name,
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#AutoEvalColumn.model.name,
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# We use COLS to maintain sorting
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filtered_df = df[
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always_here_cols + [c for c in ALLCOLS if c in df.columns and c in columns] + dummy_col
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]
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return filtered_df
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+
def filter_queries(query: str, filtered_df: pd.DataFrame, allcolumns):
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"""Added by Abishek"""
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final_df = []
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if query != "":
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if len(final_df) > 0:
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filtered_df = pd.concat(final_df)
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filtered_df = filtered_df.drop_duplicates(
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subset=[allcolumns.model.name, allcolumns.precision.name, allcolumns.revision.name]
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)
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return filtered_df
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#filter_columns_size,
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#hide_models,
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search_bar,
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+
AutoEvalColumn,
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COLS,
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],
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leaderboard_table,
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)
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#filter_columns_size,
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#hide_models,
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search_bar,
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+
AutoEvalColumn,
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COLS,
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],
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leaderboard_table,
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)
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#filter_columns_size,
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#hide_models,
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search_bar,
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+
AutoEvalColumn,
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COLS,
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],
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leaderboard_table,
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queue=True,
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#filter_columns_size,
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#hide_models,
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search_bar,
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AutoEvalColumnQuota,
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QUOTACOLS,
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],
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leaderboard_table,
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)
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#filter_columns_size,
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#hide_models,
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search_bar,
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+
AutoEvalColumnQuota,
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+
QUOTACOLS,
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],
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leaderboard_table,
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)
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#filter_columns_size,
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#hide_models,
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search_bar,
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+
AutoEvalColumnQuota,
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QUOTACOLS,
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],
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leaderboard_table,
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queue=True,
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src/display/css_html_js.py
CHANGED
@@ -5,7 +5,7 @@ custom_css = """
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}
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#models-to-add-text {
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-
font-size:
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}
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#citation-button span {
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}
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#models-to-add-text {
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font-size: 18px !important;
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}
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#citation-button span {
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