code: def setUp(self) -> None:
      super().setUp()
      X = torch.randn((10, 10))
      Y = torch.randn((10, 2))
      self.dataset = SupervisedDataset(
          X=X,
          Y=Y,
          feature_names=[f"x{i}" for i in range(10)],
          outcome_names=["y1", "y2"],
      )
  
imports: from __future__ import annotations
  from unittest.mock import patch
  import torch
  from ax.models.torch.botorch_modular.input_constructors.covar_modules import covar_module_argparse
  from ax.models.torch.botorch_modular.kernels import ScaleMaternKernel
  from ax.utils.common.testutils import TestCase
  from botorch.models.gp_regression import SingleTaskGP
  from botorch.models.multitask import MultiTaskGP
  from botorch.utils.datasets import SupervisedDataset
  from gpytorch.kernels.kernel import Kernel
  from gpytorch.priors import GammaPrior
label_desc: Use image node_id 1 for calling the CovarModuleArgparseTest obj's underlying member method code with example usage: obj.setUp() without return types