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# All tasks in the benchmark (100 tasks)
ALL_TASKS = [
"ETT_15T", "ETT_1D", "ETT_1H", "ETT_1W",
"LOOP_SEATTLE_1D", "LOOP_SEATTLE_1H", "LOOP_SEATTLE_5T",
"M_DENSE_1D", "M_DENSE_1H",
"SZ_TAXI_15T", "SZ_TAXI_1H",
"australian_tourism",
"bizitobs_l2c_1H", "bizitobs_l2c_5T",
"boomlet_1062", "boomlet_1209", "boomlet_1225", "boomlet_1230", "boomlet_1282",
"boomlet_1487", "boomlet_1631", "boomlet_1676", "boomlet_1855", "boomlet_1975",
"boomlet_2187", "boomlet_285", "boomlet_619", "boomlet_772", "boomlet_963",
"ecdc_ili",
"entsoe_15T", "entsoe_1H", "entsoe_30T",
"epf_be", "epf_de", "epf_fr", "epf_np", "epf_pjm",
"ercot_1D", "ercot_1H", "ercot_1M", "ercot_1W",
"favorita_stores_1D", "favorita_stores_1M", "favorita_stores_1W",
"favorita_transactions_1D", "favorita_transactions_1M", "favorita_transactions_1W",
"fred_md_2025/cee", "fred_md_2025/macro",
"fred_qd_2025/cee", "fred_qd_2025/macro",
"gvar",
"hermes",
"hierarchical_sales_1D", "hierarchical_sales_1W",
"hospital", "hospital_admissions_1D", "hospital_admissions_1W",
"jena_weather_10T", "jena_weather_1D", "jena_weather_1H",
"kdd_cup_2022_10T", "kdd_cup_2022_1D", "kdd_cup_2022_30T",
"m5_1D", "m5_1M", "m5_1W",
"proenfo_gfc12", "proenfo_gfc14", "proenfo_gfc17",
"redset_15T", "redset_1H", "redset_5T",
"restaurant",
"rohlik_orders_1D", "rohlik_orders_1W", "rohlik_sales_1D", "rohlik_sales_1W",
"rossmann_1D", "rossmann_1W",
"solar_1D", "solar_1W", "solar_with_weather_15T", "solar_with_weather_1H",
"uci_air_quality_1D", "uci_air_quality_1H",
"uk_covid_nation_1D/cumulative", "uk_covid_nation_1D/new",
"uk_covid_nation_1W/cumulative", "uk_covid_nation_1W/new",
"uk_covid_utla_1D/new", "uk_covid_utla_1W/cumulative",
"us_consumption_1M", "us_consumption_1Q", "us_consumption_1Y",
"walmart",
"world_co2_emissions", "world_life_expectancy", "world_tourism",
]
# Mini benchmark - representative subset (20 tasks)
MINI_TASKS = [
"jena_weather_1H",
"M_DENSE_1D",
"bizitobs_l2c_5T",
"rohlik_orders_1D",
"boomlet_1282",
"rossmann_1D",
"rossmann_1W",
"boomlet_1676",
"solar_with_weather_1H",
"boomlet_619",
"uci_air_quality_1H",
"uk_covid_nation_1D/cumulative",
"us_consumption_1Y",
"epf_np",
"world_co2_emissions",
"ETT_15T",
"ETT_1H",
"proenfo_gfc14",
"hospital_admissions_1D",
"hospital_admissions_1W",
]
# Frequency-based groupings
FREQUENCY_GROUPS = {
"Sub-hourly": [
# T (1 minute)
"boomlet_1225", "boomlet_1282", "boomlet_285", "boomlet_619", "boomlet_772", "boomlet_963",
# 5T (5 minutes)
"LOOP_SEATTLE_5T", "bizitobs_l2c_5T", "redset_5T",
"boomlet_1062", "boomlet_1209", "boomlet_1230", "boomlet_1487",
# 10T (10 minutes)
"jena_weather_10T", "kdd_cup_2022_10T",
# 15T (15 minutes)
"ETT_15T", "SZ_TAXI_15T", "entsoe_15T", "redset_15T", "solar_with_weather_15T",
# 30T (30 minutes)
"entsoe_30T", "kdd_cup_2022_30T", "boomlet_1631", "boomlet_1676",
],
"Hourly": [
"ETT_1H", "LOOP_SEATTLE_1H", "M_DENSE_1H", "SZ_TAXI_1H",
"bizitobs_l2c_1H", "entsoe_1H", "ercot_1H",
"epf_be", "epf_de", "epf_fr", "epf_np", "epf_pjm",
"jena_weather_1H",
"proenfo_gfc12", "proenfo_gfc14", "proenfo_gfc17",
"redset_1H", "solar_with_weather_1H", "uci_air_quality_1H",
"boomlet_1855", "boomlet_1975", "boomlet_2187",
],
"Daily": [
"ETT_1D", "LOOP_SEATTLE_1D", "M_DENSE_1D",
"ercot_1D", "kdd_cup_2022_1D", "solar_1D",
"favorita_stores_1D", "favorita_transactions_1D",
"hierarchical_sales_1D", "m5_1D",
"restaurant",
"rohlik_orders_1D", "rohlik_sales_1D", "rossmann_1D",
"jena_weather_1D", "uci_air_quality_1D",
"hospital_admissions_1D",
"uk_covid_nation_1D/cumulative", "uk_covid_nation_1D/new", "uk_covid_utla_1D/new",
],
"Weekly": [
"ETT_1W", "ercot_1W", "solar_1W",
"favorita_stores_1W", "favorita_transactions_1W",
"hierarchical_sales_1W", "m5_1W",
"hermes", "walmart",
"rohlik_orders_1W", "rohlik_sales_1W", "rossmann_1W",
"ecdc_ili",
"hospital_admissions_1W",
"uk_covid_nation_1W/cumulative", "uk_covid_nation_1W/new", "uk_covid_utla_1W/cumulative",
],
"Monthly+": [
# Monthly
"ercot_1M",
"favorita_stores_1M", "favorita_transactions_1M", "m5_1M",
"fred_md_2025/cee", "fred_md_2025/macro",
"hospital",
"us_consumption_1M",
# Quarterly
"australian_tourism", "gvar",
"fred_qd_2025/cee", "fred_qd_2025/macro",
"us_consumption_1Q",
# Yearly
"us_consumption_1Y",
"world_co2_emissions", "world_life_expectancy", "world_tourism",
],
}
# Domain-based groupings
DOMAIN_GROUPS = {
"Energy": [
"ETT_15T", "ETT_1D", "ETT_1H", "ETT_1W",
"entsoe_15T", "entsoe_1H", "entsoe_30T",
"epf_be", "epf_de", "epf_fr", "epf_np", "epf_pjm",
"ercot_1D", "ercot_1H", "ercot_1M", "ercot_1W",
"kdd_cup_2022_10T", "kdd_cup_2022_1D", "kdd_cup_2022_30T",
"proenfo_gfc12", "proenfo_gfc14", "proenfo_gfc17",
"solar_1D", "solar_1W", "solar_with_weather_15T", "solar_with_weather_1H",
],
"Retail": [
"favorita_stores_1D", "favorita_stores_1M", "favorita_stores_1W",
"favorita_transactions_1D", "favorita_transactions_1M", "favorita_transactions_1W",
"hermes",
"hierarchical_sales_1D", "hierarchical_sales_1W",
"m5_1D", "m5_1M", "m5_1W",
"restaurant",
"rohlik_orders_1D", "rohlik_orders_1W", "rohlik_sales_1D", "rohlik_sales_1W",
"rossmann_1D", "rossmann_1W",
"walmart",
],
"Nature": [
"jena_weather_10T", "jena_weather_1D", "jena_weather_1H",
"uci_air_quality_1D", "uci_air_quality_1H",
],
"Cloud": [
"bizitobs_l2c_1H", "bizitobs_l2c_5T",
"boomlet_1062", "boomlet_1209", "boomlet_1225", "boomlet_1230", "boomlet_1282",
"boomlet_1487", "boomlet_1631", "boomlet_1676", "boomlet_1855", "boomlet_1975",
"boomlet_2187", "boomlet_285", "boomlet_619", "boomlet_772", "boomlet_963",
"redset_15T", "redset_1H", "redset_5T",
],
"Health": [
"ecdc_ili",
"hospital", "hospital_admissions_1D", "hospital_admissions_1W",
"uk_covid_nation_1D/cumulative", "uk_covid_nation_1D/new",
"uk_covid_nation_1W/cumulative", "uk_covid_nation_1W/new",
"uk_covid_utla_1D/new", "uk_covid_utla_1W/cumulative",
],
"Econ": [
"australian_tourism",
"fred_md_2025/cee", "fred_md_2025/macro",
"fred_qd_2025/cee", "fred_qd_2025/macro",
"gvar",
"us_consumption_1M", "us_consumption_1Q", "us_consumption_1Y",
"world_co2_emissions", "world_life_expectancy", "world_tourism",
],
"Mobility": [
"LOOP_SEATTLE_1D", "LOOP_SEATTLE_1H", "LOOP_SEATTLE_5T",
"M_DENSE_1D", "M_DENSE_1H",
"SZ_TAXI_15T", "SZ_TAXI_1H",
],
}
# Task type groupings (overlapping: a multivariate task with covariates
# belongs to both "Covariate-informed" and "Multivariate").
# - Multivariate: target is a list of columns
# - Covariate-informed: known_dynamic_columns or past_dynamic_columns is non-empty
# - Univariate: neither of the above
TASK_TYPE_GROUPS = {
"Univariate": [
"LOOP_SEATTLE_1D", "LOOP_SEATTLE_1H", "LOOP_SEATTLE_5T",
"M_DENSE_1D", "M_DENSE_1H",
"SZ_TAXI_15T", "SZ_TAXI_1H",
"australian_tourism", "ecdc_ili",
"ercot_1D", "ercot_1H", "ercot_1M", "ercot_1W",
"hierarchical_sales_1D", "hierarchical_sales_1W",
"hospital", "hospital_admissions_1D", "hospital_admissions_1W",
"redset_15T", "redset_1H", "redset_5T",
"restaurant",
"solar_1D", "solar_1W",
"uk_covid_utla_1D/new", "uk_covid_utla_1W/cumulative",
"us_consumption_1M", "us_consumption_1Q", "us_consumption_1Y",
"world_co2_emissions", "world_life_expectancy", "world_tourism",
],
"Covariate-informed": [
"entsoe_15T", "entsoe_1H", "entsoe_30T",
"epf_be", "epf_de", "epf_fr", "epf_np", "epf_pjm",
"favorita_stores_1D", "favorita_stores_1M", "favorita_stores_1W",
"favorita_transactions_1D", "favorita_transactions_1M", "favorita_transactions_1W",
"fred_md_2025/cee", "fred_qd_2025/cee",
"gvar", "hermes",
"kdd_cup_2022_10T", "kdd_cup_2022_1D", "kdd_cup_2022_30T",
"m5_1D", "m5_1M", "m5_1W",
"proenfo_gfc12", "proenfo_gfc14", "proenfo_gfc17",
"rohlik_orders_1D", "rohlik_orders_1W", "rohlik_sales_1D", "rohlik_sales_1W",
"rossmann_1D", "rossmann_1W",
"solar_with_weather_15T", "solar_with_weather_1H",
"uci_air_quality_1D", "uci_air_quality_1H",
"uk_covid_nation_1D/cumulative", "uk_covid_nation_1D/new",
"uk_covid_nation_1W/cumulative", "uk_covid_nation_1W/new",
"walmart",
],
"Multivariate": [
"ETT_15T", "ETT_1D", "ETT_1H", "ETT_1W",
"bizitobs_l2c_1H", "bizitobs_l2c_5T",
"boomlet_1062", "boomlet_1209", "boomlet_1225", "boomlet_1230", "boomlet_1282",
"boomlet_1487", "boomlet_1631", "boomlet_1676", "boomlet_1855", "boomlet_1975",
"boomlet_2187", "boomlet_285", "boomlet_619", "boomlet_772", "boomlet_963",
"fred_md_2025/cee", "fred_md_2025/macro", "fred_qd_2025/cee", "fred_qd_2025/macro",
"gvar",
"jena_weather_10T", "jena_weather_1D", "jena_weather_1H",
"uci_air_quality_1D", "uci_air_quality_1H",
"uk_covid_nation_1D/cumulative", "uk_covid_nation_1D/new",
"uk_covid_nation_1W/cumulative", "uk_covid_nation_1W/new",
],
}
def get_task_group(group_type: str, group_value: str | None = None) -> list[str]:
"""Get the list of tasks for a given group type and value.
Args:
group_type: One of "full", "mini", "frequency", "domain", "task_type"
group_value: Required for "frequency", "domain", and "task_type" types
Returns:
List of task names belonging to the group
"""
if group_type == "full":
return ALL_TASKS
elif group_type == "mini":
return MINI_TASKS
elif group_type == "frequency":
if group_value is None:
raise ValueError("group_value required for frequency grouping")
return FREQUENCY_GROUPS[group_value]
elif group_type == "domain":
if group_value is None:
raise ValueError("group_value required for domain grouping")
return DOMAIN_GROUPS[group_value]
elif group_type == "task_type":
if group_value is None:
raise ValueError("group_value required for task_type grouping")
return TASK_TYPE_GROUPS[group_value]
else:
raise ValueError(f"Unknown group_type: {group_type}")
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