ModuleNotFoundError: No module named 'gluonts.dataset.rolling_dataset'

[satyrmipt]

Description

Looking for feature implemented here: #844
Previously it could be found here: https://ts.gluon.ai/v0.11.x/api/gluonts/gluonts.dataset.rolling_dataset.html
Currently the code
from gluonts.dataset.rolling_dataset import StepStrategy, generate_rolling_dataset
returns
ModuleNotFoundError: No module named 'gluonts.dataset.rolling_dataset'

To Reproduce

1. Google colab
2. pip install "gluonts[torch]==0.15"
   Result:

Requirement already satisfied: gluonts==0.15 in /usr/local/lib/python3.10/dist-packages (from gluonts[torch]==0.15) (0.15.0)
Requirement already satisfied: numpy~=1.16 in /usr/local/lib/python3.10/dist-packages (from gluonts==0.15->gluonts[torch]==0.15) (1.26.4)
Requirement already satisfied: pandas<3,>=1.0 in /usr/local/lib/python3.10/dist-packages (from gluonts==0.15->gluonts[torch]==0.15) (2.1.4)
Requirement already satisfied: pydantic<3,>=1.7 in /usr/local/lib/python3.10/dist-packages (from gluonts==0.15->gluonts[torch]==0.15) (2.9.1)
Requirement already satisfied: tqdm~=4.23 in /usr/local/lib/python3.10/dist-packages (from gluonts==0.15->gluonts[torch]==0.15) (4.66.5)
Requirement already satisfied: toolz~=0.10 in /usr/local/lib/python3.10/dist-packages (from gluonts==0.15->gluonts[torch]==0.15) (0.12.1)
Requirement already satisfied: typing-extensions~=4.0 in /usr/local/lib/python3.10/dist-packages (from gluonts==0.15->gluonts[torch]==0.15) (4.12.2)
Requirement already satisfied: torch<3,>=1.9 in /usr/local/lib/python3.10/dist-packages (from gluonts[torch]==0.15) (2.4.0+cu121)
Requirement already satisfied: lightning<2.2,>=2.0 in /usr/local/lib/python3.10/dist-packages (from gluonts[torch]==0.15) (2.1.4)
Requirement already satisfied: pytorch-lightning<2.2,>=2.0 in /usr/local/lib/python3.10/dist-packages (from gluonts[torch]==0.15) (2.1.4)
Requirement already satisfied: scipy~=1.10 in /usr/local/lib/python3.10/dist-packages (from gluonts[torch]==0.15) (1.13.1)
Requirement already satisfied: PyYAML<8.0,>=5.4 in /usr/local/lib/python3.10/dist-packages (from lightning<2.2,>=2.0->gluonts[torch]==0.15) (6.0.2)
Requirement already satisfied: fsspec<2025.0,>=2022.5.0 in /usr/local/lib/python3.10/dist-packages (from fsspec[http]<2025.0,>=2022.5.0->lightning<2.2,>=2.0->gluonts[torch]==0.15) (2024.6.1)
Requirement already satisfied: lightning-utilities<2.0,>=0.8.0 in /usr/local/lib/python3.10/dist-packages (from lightning<2.2,>=2.0->gluonts[torch]==0.15) (0.11.7)
Requirement already satisfied: packaging<25.0,>=20.0 in /usr/local/lib/python3.10/dist-packages (from lightning<2.2,>=2.0->gluonts[torch]==0.15) (24.1)
Requirement already satisfied: torchmetrics<3.0,>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from lightning<2.2,>=2.0->gluonts[torch]==0.15) (1.4.2)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas<3,>=1.0->gluonts==0.15->gluonts[torch]==0.15) (2.8.2)
Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas<3,>=1.0->gluonts==0.15->gluonts[torch]==0.15) (2024.2)
Requirement already satisfied: tzdata>=2022.1 in /usr/local/lib/python3.10/dist-packages (from pandas<3,>=1.0->gluonts==0.15->gluonts[torch]==0.15) (2024.1)
Requirement already satisfied: annotated-types>=0.6.0 in /usr/local/lib/python3.10/dist-packages (from pydantic<3,>=1.7->gluonts==0.15->gluonts[torch]==0.15) (0.7.0)
Requirement already satisfied: pydantic-core==2.23.3 in /usr/local/lib/python3.10/dist-packages (from pydantic<3,>=1.7->gluonts==0.15->gluonts[torch]==0.15) (2.23.3)
Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch<3,>=1.9->gluonts[torch]==0.15) (3.16.0)
Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch<3,>=1.9->gluonts[torch]==0.15) (1.13.2)
Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch<3,>=1.9->gluonts[torch]==0.15) (3.3)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch<3,>=1.9->gluonts[torch]==0.15) (3.1.4)
Requirement already satisfied: aiohttp!=4.0.0a0,!=4.0.0a1 in /usr/local/lib/python3.10/dist-packages (from fsspec[http]<2025.0,>=2022.5.0->lightning<2.2,>=2.0->gluonts[torch]==0.15) (3.10.5)
Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from lightning-utilities<2.0,>=0.8.0->lightning<2.2,>=2.0->gluonts[torch]==0.15) (71.0.4)
Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.2->pandas<3,>=1.0->gluonts==0.15->gluonts[torch]==0.15) (1.16.0)
Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch<3,>=1.9->gluonts[torch]==0.15) (2.1.5)
Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.10/dist-packages (from sympy->torch<3,>=1.9->gluonts[torch]==0.15) (1.3.0)
Requirement already satisfied: aiohappyeyeballs>=2.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<2025.0,>=2022.5.0->lightning<2.2,>=2.0->gluonts[torch]==0.15) (2.4.0)
Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<2025.0,>=2022.5.0->lightning<2.2,>=2.0->gluonts[torch]==0.15) (1.3.1)
Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<2025.0,>=2022.5.0->lightning<2.2,>=2.0->gluonts[torch]==0.15) (24.2.0)
Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<2025.0,>=2022.5.0->lightning<2.2,>=2.0->gluonts[torch]==0.15) (1.4.1)
Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<2025.0,>=2022.5.0->lightning<2.2,>=2.0->gluonts[torch]==0.15) (6.1.0)
Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<2025.0,>=2022.5.0->lightning<2.2,>=2.0->gluonts[torch]==0.15) (1.11.1)
Requirement already satisfied: async-timeout<5.0,>=4.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<2025.0,>=2022.5.0->lightning<2.2,>=2.0->gluonts[torch]==0.15) (4.0.3)
Requirement already satisfied: idna>=2.0 in /usr/local/lib/python3.10/dist-packages (from yarl<2.0,>=1.0->aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<2025.0,>=2022.5.0->lightning<2.2,>=2.0->gluonts[torch]==0.15) (3.8)

3. from gluonts.dataset.rolling_dataset import StepStrategy, generate_rolling_dataset
   Result:

ModuleNotFoundError                       Traceback (most recent call last)
[<ipython-input-3-496fc7eec3ae>](https://localhost:8080/#) in <cell line: 10>()
      8 
      9 from gluonts.dataset.pandas import PandasDataset
---> 10 from gluonts.dataset.rolling_dataset import StepStrategy, generate_rolling_dataset
     11 
     12 with open("/content/drive/MyDrive/Colab Notebooks/quantgem/params.yaml") as params:

ModuleNotFoundError: No module named 'gluonts.dataset.rolling_dataset'

Environment

• Operating system: google colab

• DISTRIB_ID=Ubuntu
  DISTRIB_RELEASE=22.04
  DISTRIB_CODENAME=jammy
  DISTRIB_DESCRIPTION="Ubuntu 22.04.3 LTS"
  PRETTY_NAME="Ubuntu 22.04.3 LTS"
  NAME="Ubuntu"
  VERSION_ID="22.04"
  VERSION="22.04.3 LTS (Jammy Jellyfish)"
  VERSION_CODENAME=jammy
  ID=ubuntu
  ID_LIKE=debian
  HOME_URL="https://www.ubuntu.com/"
  SUPPORT_URL="https://help.ubuntu.com/"
  BUG_REPORT_URL="https://bugs.launchpad.net/ubuntu/"
  PRIVACY_POLICY_URL="https://www.ubuntu.com/legal/terms-and-policies/privacy-policy"
  UBUNTU_CODENAME=jammy

• Python version: Python 3.10.12

• GluonTS version: gluonts==0.15 in /usr/local/lib/python3.10/dist-packages (from gluonts[torch]==0.15) (0.15.0)

• MXNet version: no MXNet

[satyrmipt]

Looks like rolling dataset approach changed somewhere between recommended version (0.12.*) and 0.15. The later one allows you to create rolling dataset as

gluon_ds=PandasDataset.from_long_dataframe(
    dataframe=normal_df,
    target='target',
    item_id='item_id',
    freq=FREQ
)

splitter = OffsetSplitter(offset=offset)
train_ds, test_template = splitter.split(gluon_ds)

test_ds = test_template.generate_instances(
    prediction_length=PREDICTION_LENGTH,
    windows=ROLL_PERIODS,
    distance=ROLLING_STEP_SIZE
)
print(train_ds)
print(test_ds)