class_docstr: Implements the TF backend ops for a PC auto-batching VM.
docstr: Implements a switch (branch_selector) { case ... } construct.
docstr_tok: ["Implements","a","switch","(","branch_selector",")","{","case","...","}","construct","."]
code: def switch_case(self, branch_selector, branch_callables, name=None):
      """Implements a switch (branch_selector) { case ... } construct."""
      with tf.name_scope("VM.switch_case"):
          with _control_flow_v2():
              return tf.switch_case(
                  branch_selector, branch_callables, name=name
              )
  
imports: import collections
  import contextlib
  import six
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.experimental.auto_batching import instructions
  from tensorflow_probability.python.experimental.auto_batching import xla
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow.python.ops import control_flow_util
label_desc: Use image node_id 19 for calling the TensorFlowBackend obj's underlying member method code with example usage: obj.switch_case(branch_selector, branch_callables, name) and returns: tf