debug
Browse filesSigned-off-by: n1ck-guo <heng.guo@intel.com>
app.py
CHANGED
@@ -386,17 +386,22 @@ def filter_models(
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filtered_df = filtered_df.loc[df[AutoEvalColumn.group_size.name].isin(group_dtype)]
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-
print(filtered_df['model_name_for_query'])
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numeric_interval = pd.IntervalIndex(sorted([NUMERIC_INTERVALS[s] for s in size_query]))
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params_column = pd.to_numeric(df[AutoEvalColumn.params.name], errors="coerce")
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mask = params_column.apply(lambda x: any(numeric_interval.contains(x)))
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filtered_df = filtered_df.loc[mask]
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numeric_interval_params = pd.IntervalIndex(sorted([NUMERIC_MODELSIZE[s] for s in params_query]))
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params_column_params = pd.to_numeric(df[AutoEvalColumn.model_size.name], errors="coerce")
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mask_params = params_column_params.apply(lambda x: any(numeric_interval_params.contains(x)))
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filtered_df = filtered_df.loc[mask_params]
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return filtered_df
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filtered_df = filtered_df.loc[df[AutoEvalColumn.group_size.name].isin(group_dtype)]
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+
print(filtered_df['model_name_for_query'].to_list())
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numeric_interval = pd.IntervalIndex(sorted([NUMERIC_INTERVALS[s] for s in size_query]))
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params_column = pd.to_numeric(df[AutoEvalColumn.params.name], errors="coerce")
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mask = params_column.apply(lambda x: any(numeric_interval.contains(x)))
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filtered_df = filtered_df.loc[mask]
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print('step 2')
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print(filtered_df['model_name_for_query'].to_list())
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numeric_interval_params = pd.IntervalIndex(sorted([NUMERIC_MODELSIZE[s] for s in params_query]))
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params_column_params = pd.to_numeric(df[AutoEvalColumn.model_size.name], errors="coerce")
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mask_params = params_column_params.apply(lambda x: any(numeric_interval_params.contains(x)))
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filtered_df = filtered_df.loc[mask_params]
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+
print('step 3')
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print(filtered_df['model_name_for_query'])
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return filtered_df
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