class_docstr: Implements the TF backend ops for a PC auto-batching VM.
docstr: Returns an all-True mask `Tensor` with shape `[size]`.
docstr_tok: ["Returns","an","all-True","mask","`","Tensor","`","with","shape","`","[","size","]","`","."]
code: def full_mask(self, size, name=None):
      """Returns an all-True mask `Tensor` with shape `[size]`."""
      with tf.name_scope(name or "VM.full_mask"):
          size = tf.convert_to_tensor(value=size, name="size")
          return tf.ones(size, dtype=tf.bool)
  
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 12 for calling the TensorFlowBackend obj's underlying member method code with example usage: obj.full_mask(size, name) and returns: tf