class_docstr: Implements the TF backend ops for a PC auto-batching VM.
docstr: Gets the eager/immediate value of `t`, or `None` if `t` is a Tensor.
docstr_tok: ["Gets","the","eager\/immediate","value","of","`","t","`",",","or","`","None","`","if","`","t","`","is","a","Tensor","."]
code: def static_value(self, t):
      """Gets the eager/immediate value of `t`, or `None` if `t` is a Tensor."""
      if tf.executing_eagerly():
          return t.numpy()
      return None
  
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 9 for calling the TensorFlowBackend obj's underlying member method code with example usage: obj.static_value(t) and returns: None, t