code: def test_build(self, filters, strides):
      env = GymEnv(DummyDiscretePixelEnv())
      obs = env.reset()[0]
  
      with mock.patch(
          ("garage.tf.models." "cnn_mlp_merge_model.CNNModel"),
          new=SimpleCNNModel,
      ):
          with mock.patch(
              ("garage.tf.models." "cnn_mlp_merge_model.MLPMergeModel"),
              new=SimpleMLPMergeModel,
          ):
              qf = ContinuousCNNQFunction(
                  env_spec=env.spec, filters=filters, strides=strides
              )
      action_dim = env.action_space.shape
  
      obs = env.step(1).observation
      act = np.full(action_dim, 0.5)
  
      output1 = qf.get_qval([obs], [act])
  
      input_var1 = tf.compat.v1.placeholder(
          tf.float32, shape=(None,) + obs.shape
      )
      input_var2 = tf.compat.v1.placeholder(
          tf.float32, shape=(None,) + act.shape
      )
      q_vals = qf.build(input_var1, input_var2, "another")
  
      output2 = self.sess.run(
          q_vals, feed_dict={input_var1: [obs], input_var2: [act]}
      )
  
      expected_output = np.full((1,), 0.5)
  
      assert np.array_equal(output1, output2)
      assert np.array_equal(output2[0], expected_output)
  
imports: import pickle
  from unittest import mock
  import numpy
  import pytest
  import tensorflow
  from garage.envs import GymEnv
  from garage.tf.q_functions import ContinuousCNNQFunction
  from tests.fixtures import TfGraphTestCase
  from tests.fixtures.envs.dummy import DummyDictEnv, DummyDiscreteEnv, DummyDiscretePixelEnv
  from tests.fixtures.models import SimpleCNNModel, SimpleCNNModelWithMaxPooling, SimpleMLPMergeModel
label_desc: Use image node_id 7 for calling the TestContinuousCNNQFunction obj's underlying member method code with example usage: obj.test_build(filters, strides) without return types