description: Enables / disables eager execution of tf.functions.

tf.config.run_functions_eagerly

Enables / disables eager execution of tf.functions.

tf.config.run_functions_eagerly(
    run_eagerly
)

Calling tf.config.run_functions_eagerly(True) will make all invocations of tf.function run eagerly instead of running as a traced graph function.

This can be useful for debugging.

>>> def my_func(a):
...  print("Python side effect")
...  return a + a
>>> a_fn = tf.function(my_func)

>>> # A side effect the first time the function is traced
>>> a_fn(tf.constant(1))
Python side effect
<tf.Tensor: shape=(), dtype=int32, numpy=2>

>>> # No further side effect, as the traced function is called
>>> a_fn(tf.constant(2))
<tf.Tensor: shape=(), dtype=int32, numpy=4>

>>> # Now, switch to eager running
>>> tf.config.run_functions_eagerly(True)
>>> # Side effect, as the function is called directly
>>> a_fn(tf.constant(2))
Python side effect
<tf.Tensor: shape=(), dtype=int32, numpy=4>

>>> # Turn this back off
>>> tf.config.run_functions_eagerly(False)

Note: This flag has no effect on functions passed into tf.data transformations as arguments. tf.data functions are never executed eagerly and are always executed as a compiled Tensorflow Graph.

Args

run_eagerly Boolean. Whether to run functions eagerly.