class_docstr: Implements the TF backend ops for a PC auto-batching VM.
docstr: Returns the first (batch) dimension of `value`.
docstr_tok: ["Returns","the","first","(","batch",")","dimension","of","`","value","`","."]
code: def batch_size(self, value, name=None):
      """Returns the first (batch) dimension of `value`."""
      with tf.name_scope(name or "VM.batch_size"):
          value = tf.convert_to_tensor(value=value, name="value")
          return _get_leftmost_dim_size(value)
  
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 8 for calling the TensorFlowBackend obj's underlying member method code with example usage: obj.batch_size(value, name) and returns: _get_leftmost_dim_size