code: def synth_dbunch(a=2, b=3, bs=16, n_train=10, n_valid=2, cuda=False):
      def get_data(n):
          x = torch.randn(bs * n, 1)
          return TensorDataset(
              x, a * x + b + 0.1 * torch.randn(bs * n, 1)
          )
  
      train_ds = get_data(n_train)
      valid_ds = get_data(n_valid)
      device = default_device() if cuda else None
      train_dl = TfmdDL(train_ds, bs=bs, shuffle=True, num_workers=0)
      valid_dl = TfmdDL(valid_ds, bs=bs, num_workers=0)
      return DataLoaders(train_dl, valid_dl, device=device)
  
imports: from __future__ import annotations
  from .imports import *
  from .data.all import *
  from .optimizer import *
  from .learner import *
  from .callback.core import *
  from torch.utils.data import TensorDataset
  from torch.utils.data import TensorDataset
label_desc: Use image node_id 1 for calling a global function with example usage: synth_dbunch(a, b, bs, n_train, n_valid, cuda) and returns: DataLoaders, TensorDataset