tf.get_static_value

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Returns the constant value of the given tensor, if efficiently calculable.

tf.get_static_value(
    tensor, partial=False
)

This function attempts to partially evaluate the given tensor, and returns its value as a numpy ndarray if this succeeds.

Example usage:

a = tf.constant(10)
tf.get_static_value(a)
10
b = tf.constant(20)
tf.get_static_value(tf.add(a, b))
30

# `tf.Variable` is not supported.
c = tf.Variable(30)
print(tf.get_static_value(c))
None

Using partial option is most relevant when calling get_static_value inside a tf.function. Setting it to True will return the results but for the values that cannot be evaluated will be None. For example:

class Foo:
  def __init__(self):
    self.a = tf.Variable(1)
    self.b = tf.constant(2)

  @tf.function
  def bar(self, partial):
    packed = tf.raw_ops.Pack(values=[self.a, self.b])
    static_val = tf.get_static_value(packed, partial=partial)
    tf.print(static_val)

f = Foo()
f.bar(partial=True)  # `array([None, array(2, dtype=int32)], dtype=object)`
f.bar(partial=False)  # `None`

Compatibility(V1): If constant_value(tensor) returns a non-None result, it will no longer be possible to feed a different value for tensor. This allows the result of this function to influence the graph that is constructed, and permits static shape optimizations.