ynhe commited on
Commit
9e18eee
1 Parent(s): 949c917

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +2 -2
app.py CHANGED
@@ -38,7 +38,7 @@ def add_new_eval(
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  model_name = model_name_textbox
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  else:
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  model_name = revision_name_textbox
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- model_name_list = csv_data['name']
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  name_list = [name.split(']')[0][1:] for name in model_name_list]
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  if revision_name_textbox not in name_list:
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  col = csv_data.shape[0]
@@ -81,7 +81,7 @@ def calculate_selected_score(df, selected_columns):
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  def get_final_score(df, selected_columns):
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  normalize_df = get_normalized_df(df)
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  #final_score = normalize_df.drop('name', axis=1).sum(axis=1)
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- for name in normalize_df.drop('name', axis=1):
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  normalize_df[name] = normalize_df[name]*DIM_WEIGHT[name]
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  quality_score = normalize_df[QUALITY_LIST].sum(axis=1)/sum([DIM_WEIGHT[i] for i in QUALITY_LIST])
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  semantic_score = normalize_df[SEMANTIC_LIST].sum(axis=1)/sum([DIM_WEIGHT[i] for i in SEMANTIC_LIST ])
 
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  model_name = model_name_textbox
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  else:
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  model_name = revision_name_textbox
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+ model_name_list = csv_data['Model Name']
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  name_list = [name.split(']')[0][1:] for name in model_name_list]
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  if revision_name_textbox not in name_list:
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  col = csv_data.shape[0]
 
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  def get_final_score(df, selected_columns):
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  normalize_df = get_normalized_df(df)
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  #final_score = normalize_df.drop('name', axis=1).sum(axis=1)
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+ for name in normalize_df.drop('Model Name', axis=1):
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  normalize_df[name] = normalize_df[name]*DIM_WEIGHT[name]
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  quality_score = normalize_df[QUALITY_LIST].sum(axis=1)/sum([DIM_WEIGHT[i] for i in QUALITY_LIST])
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  semantic_score = normalize_df[SEMANTIC_LIST].sum(axis=1)/sum([DIM_WEIGHT[i] for i in SEMANTIC_LIST ])