View source on GitHub |
Enables / disables eager execution of tf.function
s.
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)
Args | |
---|---|
run_eagerly
|
Boolean. Whether to run functions eagerly. |