Add example of using custom pipeline pools in Auto

CHANGELOG.md

@@ -8,7 +8,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ## Unreleased
 ### Added
 - Add `load_dataset` to public API ([#484](https://github.com/etna-team/etna/pull/484))
-- 
+- Add example of using custom pipeline pools in `Auto` ([#504](https://github.com/etna-team/etna/pull/504))
 - 
 - 
 - 

etna/auto/auto.py

@@ -23,6 +23,7 @@
 from etna.auto.optuna import ConfigSampler
 from etna.auto.optuna import Optuna
 from etna.auto.pool import Pool
+from etna.auto.pool import PoolGenerator
 from etna.auto.runner import AbstractRunner
 from etna.auto.runner import LocalRunner
 from etna.auto.utils import config_hash
@@ -214,7 +215,7 @@
         metric_aggregation: MetricAggregationStatistics = "mean",
         backtest_params: Optional[dict] = None,
         experiment_folder: Optional[str] = None,
-        pool: Union[Pool, List[BasePipeline]] = Pool.default,
+        pool: Union[Pool, PoolGenerator, List[BasePipeline]] = Pool.default,
         runner: Optional[AbstractRunner] = None,
         storage: Optional[BaseStorage] = None,
         metrics: Optional[List[Metric]] = None,
@@ -265,9 +266,11 @@
         self._pool_folder = f"{root_folder}pool"
 
     @staticmethod
-    def _make_pool(pool: Union[Pool, List[BasePipeline]], horizon: int) -> List[BasePipeline]:
+    def _make_pool(pool: Union[Pool, PoolGenerator, List[BasePipeline]], horizon: int) -> List[BasePipeline]:
         if isinstance(pool, Pool):
             list_pool: List[BasePipeline] = list(pool.value.generate(horizon=horizon))
+        elif isinstance(pool, PoolGenerator):
+            list_pool = list(pool.generate(horizon=horizon))
         else:
             list_pool = list(pool)
 

examples/README.md

@@ -87,6 +87,7 @@ We have prepared a set of tutorials for an easy introduction:
 - General AutoML
   - How `Auto` works
   - Example
+  - Using custom pipeline pool
 - Summary
 
 #### [Clustering](https://github.com/etna-team/etna/tree/master/examples/206-clustering.ipynb) 
@@ -133,6 +134,7 @@ We have prepared a set of tutorials for an easy introduction:
   - EmbeddingSegmentTransform
   - EmbeddingWindowTransform
 - Saving and loading models
+- Loading external pretrained models
 
 ### Advanced
 

tests/test_auto/test_auto.py

@@ -7,6 +7,7 @@
 from typing_extensions import Literal
 
 from etna.auto import Auto
+from etna.auto.auto import PoolGenerator
 from etna.auto.auto import _Callback
 from etna.auto.auto import _Initializer
 from etna.metrics import MAE
@@ -17,6 +18,29 @@
 from etna.transforms import LagTransform
 
 
+@pytest.fixture()
+def pool_generator():
+    pool = [
+        {
+            "_target_": "etna.pipeline.Pipeline",
+            "horizon": "${__aux__.horizon}",
+            "model": {"_target_": "etna.models.MovingAverageModel", "window": "${mult:${horizon},1}"},
+        },
+        {
+            "_target_": "etna.pipeline.Pipeline",
+            "horizon": "${__aux__.horizon}",
+            "model": {"_target_": "etna.models.NaiveModel", "lag": 1},
+        },
+    ]
+    pool_generator = PoolGenerator(pool)
+    return pool_generator
+
+
+@pytest.fixture()
+def pool_list():
+    return [Pipeline(MovingAverageModel(7), horizon=7), Pipeline(NaiveModel(1), horizon=7)]
+
+
 def test_objective(
     example_tsds,
     target_metric=MAE(),
@@ -118,11 +142,9 @@ def test_init_optuna(
     )
 
 
-def test_fit_without_tuning(
-    example_tsds,
-    optuna_storage,
-    pool=(Pipeline(MovingAverageModel(5), horizon=7), Pipeline(NaiveModel(1), horizon=7)),
-):
+@pytest.mark.parametrize("pool", ["pool_list", "pool_generator"])
+def test_fit_without_tuning_list(example_tsds, optuna_storage, pool, request):
+    pool = request.getfixturevalue(pool)
     auto = Auto(
         MAE(),
         pool=pool,
@@ -136,6 +158,8 @@ def test_fit_without_tuning(
     assert len(auto.summary()) == 2
     assert len(auto.top_k(k=5)) == 2
     assert len(auto.top_k(k=1)) == 1
+    if isinstance(pool, PoolGenerator):
+        pool = pool.generate(7)
     assert auto.top_k(k=1)[0].to_dict() == pool[0].to_dict()