class_docstr: A dataset which provides time series.
class_docstr_tok: ["A","dataset","which","provides","time","series","."]
docstr: Args:
      series: The multivariate time series.
docstr_tok: ["Args",":","series",":","The","multivariate","time","series","."]
code: def __init__(
      self,
      series: List[TimeSeries],
      prediction_length: int,
      freq: str,
      standardize: bool = True,
  ):
      """
      Args:
          series: The multivariate time series.
      """
      self.series = series
      self.prediction_length = prediction_length
      self.freq = freq
      self.standardize = standardize
      if self.standardize:
          self.means = torch.stack([s.mean for s in self.series], dim=0)
          self.stds = torch.stack([s.std for s in self.series], dim=0)
  
file_path: gluonts/src/gluonts/nursery/few_shot_prediction/src/meta/data/dataset.py
imports: from __future__ import annotations
  from dataclasses import dataclass
  from typing import List, Optional
  import pandas
  import torch
  from torch.utils.data import Dataset
label_desc: Use image node_id 1 to create a new TimeSeriesDataset object from inherited base classes: Dataset with example: obj = TimeSeriesDataset(series, prediction_length, freq, standardize)