Add ETT datasets (awslabs#3149)

*Description of changes:* Add electricity transformer datasets from
https://github.com/zhouhaoyi/ETDataset


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**Please tag this pr with at least one of these labels to make our
release process faster:** BREAKING, new feature, bug fix, other change,
dev setup

src/gluonts/dataset/repository/_ett_small.py

@@ -0,0 +1,69 @@
+# Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License").
+# You may not use this file except in compliance with the License.
+# A copy of the License is located at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# or in the "license" file accompanying this file. This file is distributed
+# on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either
+# express or implied. See the License for the specific language governing
+# permissions and limitations under the License.
+
+from pathlib import Path
+
+import pandas as pd
+from gluonts.dataset import DatasetWriter
+from gluonts.dataset.common import MetaData, TrainDatasets
+
+
+# Currently data from only two regions are made public.
+NUM_REGIONS = 2
+
+
+def generate_ett_small_dataset(
+    dataset_path: Path,
+    dataset_writer: DatasetWriter,
+    base_file_name: str,
+    freq: str,
+    prediction_length: int,
+):
+    dfs = []
+    for i in range(NUM_REGIONS):
+        df = pd.read_csv(
+            f"https://raw.githubusercontent.com/zhouhaoyi/ETDataset"
+            f"/main/ETT-small/{base_file_name}{i+1}.csv"
+        )
+        df["date"] = df["date"].astype("datetime64[ms]")
+        dfs.append(df)
+
+    test = []
+    for df in dfs:
+        start = pd.Period(df["date"][0], freq=freq)
+        for col in df.columns:
+            if col in ["date"]:
+                continue
+            test.append(
+                {
+                    "start": start,
+                    "target": df[col].values,
+                }
+            )
+
+    train = []
+    for df in dfs:
+        start = pd.Period(df["date"][0], freq=freq)
+        for col in df.columns:
+            if col in ["date"]:
+                continue
+            train.append(
+                {
+                    "start": start,
+                    "target": df[col].values[:-prediction_length],
+                }
+            )
+
+    metadata = MetaData(freq=freq, prediction_length=prediction_length)
+    dataset = TrainDatasets(metadata=metadata, train=train, test=test)
+    dataset.save(str(dataset_path), writer=dataset_writer, overwrite=True)

src/gluonts/dataset/repository/datasets.py

@@ -25,6 +25,7 @@
 from ._artificial import generate_artificial_dataset
 from ._airpassengers import generate_airpassengers_dataset
 from ._ercot import generate_ercot_dataset
+from ._ett_small import generate_ett_small_dataset
 from ._gp_copula_2019 import generate_gp_copula_dataset
 from ._lstnet import generate_lstnet_dataset
 from ._m3 import generate_m3_dataset
@@ -243,6 +244,18 @@ def get_download_path() -> Path:
         dataset_name="vehicle_trips_without_missing",
     ),
     "ercot": partial(generate_ercot_dataset),
+    "ett_small_15min": partial(
+        generate_ett_small_dataset,
+        base_file_name="ETTm",
+        freq="15min",
+        prediction_length=24,
+    ),
+    "ett_small_1h": partial(
+        generate_ett_small_dataset,
+        base_file_name="ETTh",
+        freq="1h",
+        prediction_length=24,
+    ),
 }