code: def testValuesAreCorrectIdentity(self, feature_ndims, dims):
      amplitude = self.dtype(5.0)
      length_scale = self.dtype(0.2)
      kernel = exponentiated_quadratic.ExponentiatedQuadratic(
          amplitude, length_scale, feature_ndims=feature_ndims
      )
      input_shape = [dims] * feature_ndims
      identity_transformed_kernel = feature_transformed.FeatureTransformed(
          kernel,
          transformation_fn=lambda x, feature_ndims, param_expansion_ndims: x,
      )
      x = np.random.uniform(-1, 1, size=input_shape).astype(self.dtype)
      y = np.random.uniform(-1, 1, size=input_shape).astype(self.dtype)
      self.assertAllClose(
          _numpy_exp_quad(
              amplitude, length_scale, x, y, feature_ndims=feature_ndims
          ),
          self.evaluate(identity_transformed_kernel.apply(x, y)),
      )
  
file_path: probability/tensorflow_probability/python/math/psd_kernels/feature_transformed_test.py
imports: from absl.testing import parameterized
  import numpy
  from tensorflow_probability.python.bijectors import scale
  from tensorflow_probability.python.bijectors import scale_matvec_diag
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math.psd_kernels import exponentiated_quadratic
  from tensorflow_probability.python.math.psd_kernels import feature_transformed
  from tensorflow_probability.python.math.psd_kernels.internal import util
label_desc: Use image node_id 1 for calling the _FeatureTransformedTest obj's underlying member method code with example usage: obj.testValuesAreCorrectIdentity(feature_ndims, dims) without return types