code: def get_dataset(
      src_name: str,
      tgt_name: str,
      n_src_instances_train: int,
      n_tgt_instances_train: int,
      n_src_instances_eval: int,
      n_tgt_instances_eval: int,
      src_eval_size: int,
      tgt_eval_size: int,
  ):
      src_dataset = BenchmarkDataset.create_dataset(
          dataset=src_name,
          freq=_freqs[src_name],
          n_instances_train=n_src_instances_train,
          n_instances_eval=n_src_instances_eval,
          eval_size=src_eval_size,
          window_size=_window_size[_freqs[src_name]],
      )
      tgt_dataset = BenchmarkDataset.create_dataset(
          dataset=tgt_name,
          freq=_freqs[tgt_name],
          n_instances_train=n_tgt_instances_train,
          n_instances_eval=n_tgt_instances_eval,
          eval_size=tgt_eval_size,
          train_size=tgt_eval_size,
          window_size=_window_size[_freqs[tgt_name]],
      )
      return src_dataset, tgt_dataset
  
file_path: gluonts/src/gluonts/nursery/daf/__main__.py
imports: from pathlib import Path
  from copy import deepcopy
  import json
  import numpy
  import pandas
  import torch
  from .dataset import FourierDataset, BenchmarkDataset, DomAdaptDataset
  from .estimator import AttentionEstimator, AdversarialEstimator, DomAdaptEstimator, AdversarialDomAdaptEstimator
  from .engine import AttentionTrainer, AttentionEvaluator, DomAdaptTrainer, DomAdaptEvaluator, AdversarialDomAdaptTrainer, AdversarialDomAdaptEvaluator
  from .cli import NestedArgumentParser, NestedNamespace
label_desc: Use image node_id 3 for calling a global function with example usage: get_dataset(src_name, tgt_name, n_src_instances_train, n_tgt_instances_train, n_src_instances_eval, n_tgt_instances_eval, src_eval_size, tgt_eval_size) and returns: src_dataset,  tgt_dataset