code: def _normal_log_pdf(x):
      two_pi = tf.convert_to_tensor(2 * np.pi, dtype=x.dtype)
      return -0.5 * (tf.math.log(two_pi) + tf.square(x))
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import sigmoid
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import reparameterization
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import special_math
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.math.generic import log_sub_exp
label_desc: Use image node_id 2 for calling a global function with example usage: _normal_log_pdf(x) and returns: unknown