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update to new sn1
Browse files- dashboard.py +9 -8
dashboard.py
CHANGED
@@ -8,7 +8,7 @@ from opendashboards.assets import io, inspect, metric, plot
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# cache individual file loads
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# Hotkey churn
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-
DEFAULT_PROJECT = "
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DEFAULT_FILTERS = {"tags": {"$in": [f'1.1.{i}' for i in range(10)]}}
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DEFAULT_SELECTED_HOTKEYS = None
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DEFAULT_SRC = 'followup'
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@@ -23,7 +23,7 @@ st.set_page_config(
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'About': """
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This dashboard is part of the OpenTensor project. \n
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To see runs in wandb, go to: \n
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https://wandb.ai/opentensor-dev/
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"""
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},
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layout = "centered"
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@@ -82,7 +82,8 @@ with tab1:
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st.dataframe(df_long.head(num_rows) if use_long_checkbox else df.head(num_rows),
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use_container_width=True)
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step_types = ['all']+['augment','followup','answer']#list(df.name.unique())
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### UID Health ###
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# TODO: Live time - time elapsed since moving_averaged_score for selected UID was 0 (lower bound so use >Time)
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@@ -93,8 +94,8 @@ with tab2:
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st.subheader("UID :violet[Health]")
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st.info(f"Showing UID health metrics for **{n_runs} selected runs**")
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uid_src = st.radio('Select
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df_uid = df_long[df_long.
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metric.uids(df_uid, uid_src)
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uids = st.multiselect('UID:', sorted(df_uid['uids'].unique()), key='uid')
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@@ -154,8 +155,8 @@ with tab3:
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msg_col1, msg_col2 = st.columns(2)
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# completion_src = msg_col1.radio('Select one:', ['followup', 'answer'], horizontal=True, key='completion_src')
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completion_src = st.radio('Select
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df_comp = df_long[df_long.
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completion_info.info(f"Showing **{completion_src}** completions for **{n_runs} selected runs**")
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@@ -204,7 +205,7 @@ with tab3:
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df_comp,
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completion_col='completions',
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uid_col='uids',
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time_col='
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length_opt=completion_length_radio,
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)
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# cache individual file loads
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# Hotkey churn
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DEFAULT_PROJECT = "alpha-validators"
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DEFAULT_FILTERS = {"tags": {"$in": [f'1.1.{i}' for i in range(10)]}}
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DEFAULT_SELECTED_HOTKEYS = None
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DEFAULT_SRC = 'followup'
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'About': """
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This dashboard is part of the OpenTensor project. \n
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To see runs in wandb, go to: \n
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https://wandb.ai/opentensor-dev/alpha-validators/table?workspace=default
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"""
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},
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layout = "centered"
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st.dataframe(df_long.head(num_rows) if use_long_checkbox else df.head(num_rows),
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use_container_width=True)
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# step_types = ['all']+['augment','followup','answer']#list(df.name.unique())
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step_types = ['all']+list(df.task.unique())
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### UID Health ###
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# TODO: Live time - time elapsed since moving_averaged_score for selected UID was 0 (lower bound so use >Time)
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st.subheader("UID :violet[Health]")
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st.info(f"Showing UID health metrics for **{n_runs} selected runs**")
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uid_src = st.radio('Select task type:', step_types, horizontal=True, key='uid_src')
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df_uid = df_long[df_long.task.str.contains(uid_src)] if uid_src != 'all' else df_long
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metric.uids(df_uid, uid_src)
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uids = st.multiselect('UID:', sorted(df_uid['uids'].unique()), key='uid')
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msg_col1, msg_col2 = st.columns(2)
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# completion_src = msg_col1.radio('Select one:', ['followup', 'answer'], horizontal=True, key='completion_src')
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completion_src = st.radio('Select task type:', step_types, horizontal=True, key='completion_src')
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df_comp = df_long[df_long.task.str.contains(completion_src)] if completion_src != 'all' else df_long
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completion_info.info(f"Showing **{completion_src}** completions for **{n_runs} selected runs**")
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df_comp,
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completion_col='completions',
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uid_col='uids',
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time_col='timings',
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length_opt=completion_length_radio,
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)
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