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| """See the data as seen by your model.""" | |
| import pandas as pd | |
| import streamlit as st | |
| from src.subpages.page import Context, Page | |
| from src.utils import aggrid_interactive_table | |
| def convert_df(df): | |
| return df.to_csv().encode("utf-8") | |
| class RawDataPage(Page): | |
| name = "Raw data" | |
| icon = "qr-code" | |
| def render(self, context: Context): | |
| st.title(self.name) | |
| with st.expander("💡", expanded=True): | |
| st.write("See the data as seen by your model.") | |
| st.subheader("Dataset") | |
| st.code( | |
| f"Dataset: {context.ds_name}\nConfig: {context.ds_config_name}\nSplit: {context.ds_split_name}" | |
| ) | |
| st.write("**Data after processing and inference**") | |
| processed_df = ( | |
| context.df_tokens.drop("hidden_states", axis=1).drop("attention_mask", axis=1).round(3) | |
| ) | |
| cols = ( | |
| "ids input_ids token_type_ids word_ids losses tokens labels preds total_loss".split() | |
| ) | |
| if "token_type_ids" not in processed_df.columns: | |
| cols.remove("token_type_ids") | |
| processed_df = processed_df[cols] | |
| aggrid_interactive_table(processed_df) | |
| processed_df_csv = convert_df(processed_df) | |
| st.download_button( | |
| "Download csv", | |
| processed_df_csv, | |
| "processed_data.csv", | |
| "text/csv", | |
| ) | |
| st.write("**Raw data (exploded by tokens)**") | |
| raw_data_df = context.split.to_pandas().apply(pd.Series.explode) # type: ignore | |
| aggrid_interactive_table(raw_data_df) | |
| raw_data_df_csv = convert_df(raw_data_df) | |
| st.download_button( | |
| "Download csv", | |
| raw_data_df_csv, | |
| "raw_data.csv", | |
| "text/csv", | |
| ) | |