code: def make_dataset(input_dim, size):
      return TensorDataset(
          torch.randn(size, input_dim),
          torch.randint(0, 2, (size, 1), dtype=torch.float32),
      )
  
imports: import unittest
  from typing import List
  import pytorch_lightning
  import torch
  import torch.nn
  import torch.optim
  from reagent.reporting import CompoundReporter, ReporterBase
  from reagent.training import MultiStageTrainer, ReAgentLightningModule
  from torch.utils.data import DataLoader, TensorDataset
label_desc: Use image node_id 1 for calling a global function with example usage: make_dataset(input_dim, size) and returns: TensorDataset