code: def _test_call(self, gpu):
      # This method only check if a given model can receive random input
      # data and return output data with the correct interface.
      nonlinearity = getattr(F, self.nonlinearity)
      min_action = np.full((self.action_size,), -0.01, dtype=np.float32)
      max_action = np.full((self.action_size,), 0.01, dtype=np.float32)
      model = self._make_model(
          n_input_channels=self.n_input_channels,
          action_size=self.action_size,
          bound_action=self.bound_action,
          min_action=min_action,
          max_action=max_action,
          nonlinearity=nonlinearity,
      )
  
      batch_size = 7
      x = np.random.rand(batch_size, self.n_input_channels).astype(
          np.float32
      )
      if gpu >= 0:
          model.to_gpu(gpu)
          x = chainer.cuda.to_gpu(x)
          min_action = chainer.cuda.to_gpu(min_action)
          max_action = chainer.cuda.to_gpu(max_action)
      y = model(x)
      self.assertTrue(
          isinstance(
              y,
              chainerrl.distribution.ContinuousDeterministicDistribution,
          )
      )
      a = y.sample()
      self.assertTrue(isinstance(a, chainer.Variable))
      self.assertEqual(a.shape, (batch_size, self.action_size))
      self.assertEqual(
          chainer.cuda.get_array_module(a),
          chainer.cuda.get_array_module(x),
      )
      if self.bound_action:
          self.assertTrue((a.array <= max_action).all())
          self.assertTrue((a.array >= min_action).all())
  
file_path: chainerrl/tests/policies_tests/test_deterministic_policy.py
imports: import unittest
  import chainer
  import chainer.functions
  from chainer import testing
  from chainer.testing import attr
  import numpy
  import chainerrl
label_desc: Use image node_id 2 for calling the TestDeterministicPolicy obj's underlying member method code with example usage: obj._test_call(gpu) without return types