class_docstr: The logit-normal distribution.
class_docstr_tok: ["The","logit-normal","distribution","."]
code: def _sample_control_dependencies(self, x):
      assertions = []
      if not self.validate_args:
          return assertions
      assertions.append(
          assert_util.assert_non_negative(
              x, message="Sample must be non-negative."
          )
      )
      assertions.append(
          assert_util.assert_less_equal(
              x,
              tf.ones([], x.dtype),
              message="Sample must be less than or equal to `1`.",
          )
      )
      return assertions
  
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 kullback_leibler
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import transformed_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.math import special
label_desc: Use image node_id 13 for calling the LogitNormal obj's underlying member method code with example usage: obj._sample_control_dependencies(x) and returns: assertions, assertions