[BUG] Ensembles works incorrectly with HierarchicalPipeline

[alex-hse-repository]

🐛 Bug Report

Ensembles fails to works with HierarchicalPipeline, they lose hierarchical structure during forecast and don't use hierarchical structure in backtest

Expected behavior

You can run fit/forecast/backtest without errors and losing hierarchical structure

How To Reproduce

Code

import pandas as pd
from etna.metrics import SMAPE
from etna.models import SeasonalMovingAverageModel
from etna.pipeline import HierarchicalPipeline
from etna.ensembles import VotingEnsemble
from etna.datasets import TSDataset
from etna.reconciliation import BottomUpReconciliator


# Download data 'curl "https://robjhyndman.com/data/hier1_with_names.csv" --ssl-no-revoke -o "hier1_with_names.csv"'

df = pd.read_csv("hier1_with_names.csv")

# Prepare Dataframe

periods = len(df)
city_segments = list(filter(lambda name: name.count("-") == 2, df.columns))

df["timestamp"] = pd.date_range("2006-01-01", periods=periods, freq="MS")
df.set_index("timestamp", inplace=True)

hierarchical_df = []
for segment_name in city_segments:
    segment = df[segment_name]
    region, reason, city = segment_name.split(" - ")

    seg_df = pd.DataFrame(
        data={
            "timestamp": segment.index,
            "target": segment.values,
            "city_level": [city] * periods,
            "region_level": [region] * periods,
            "reason_level": [reason] * periods,
        },
    )
    hierarchical_df.append(seg_df)

hierarchical_df = pd.concat(hierarchical_df, axis=0)


# Create Dataset
hierarchical_df, hierarchical_structure = TSDataset.to_hierarchical_dataset(
    df=hierarchical_df, level_columns=["reason_level", "region_level", "city_level"]
)
hierarchical_ts = TSDataset(df=hierarchical_df, freq="MS", hierarchical_structure=hierarchical_structure)


# Create pipeline
pipeline_1 = HierarchicalPipeline(
    model=SeasonalMovingAverageModel(window=1, seasonality=1),
    reconciliator=BottomUpReconciliator(target_level="region_level", source_level="city_level"),
)
pipeline_2 = HierarchicalPipeline(
    model=SeasonalMovingAverageModel(window=1, seasonality=2),
    reconciliator=BottomUpReconciliator(target_level="region_level", source_level="city_level"),
)
pipeline_vote = VotingEnsemble(pipelines=[pipeline_1, pipeline_2])

bottom_up_metrics, _, _ = pipeline_vote.backtest(
    ts=hierarchical_ts, metrics=[SMAPE()], n_folds=3, aggregate_metrics=True
)

Error

ValueError: There are segments in y_pred that are not in y_true, for example: vfr_NT, vfr_QLD, hol_WA, hol_QLD, vfr_VIC

Environment

No response

Additional context

1. We have special backtest for hierarchical pipeline, it is not taken into account in ensembles
2. We lose hierarchical structure here in VotingEnsemble

Checklist

• Bug appears at the latest library version