code: def _test_mlp_regressor(self, activation="relu"):
      model = MLPRegressor(
          hidden_layer_sizes=(
              100,
              100,
              50,
          ),
          activation=activation,
      )
      np.random.seed(0)
      X = np.random.rand(100, 200)
      X = np.array(X, dtype=np.float32)
      y = np.random.rand(100)
  
      model.fit(X, y)
      torch_model = hummingbird.ml.convert(model, "torch")
      self.assertTrue(torch_model is not None)
      np.testing.assert_allclose(
          model.predict(X), torch_model.predict(X), rtol=1e-6, atol=1e-6
      )
  
imports: import unittest
  import warnings
  import numpy
  import torch
  from sklearn.neural_network import MLPClassifier, MLPRegressor
  import hummingbird.ml
  from hummingbird.ml import constants
  from hummingbird.ml._utils import tvm_installed
label_desc: Use image node_id 14 for calling the TestSklearnMLPClassifier obj's underlying member method code with example usage: obj._test_mlp_regressor(activation) without return types