tf.executing_eagerly

TensorFlow 1 version

View source on GitHub

Checks whether the current thread has eager execution enabled.

tf.executing_eagerly()

Eager execution is enabled by default and this API returns True in most of cases. However, this API might return False in the following use cases.

• Executing inside tf.function, unless under tf.init_scope or tf.config.experimental_run_functions_eagerly(True) is previously called.
• Executing inside a transformation function for tf.dataset.
• tf.compat.v1.disable_eager_execution() is called.

General case:

print(tf.executing_eagerly())
True

Inside tf.function:

@tf.function
def fn():
  with tf.init_scope():
    print(tf.executing_eagerly())
  print(tf.executing_eagerly())
fn()
True
False

Inside tf.function after

tf.config.experimental_run_functions_eagerly(True) is called:

tf.config.experimental_run_functions_eagerly(True) @tf.function ... def fn(): ... with tf.init_scope(): ... print(tf.executing_eagerly()) ... print(tf.executing_eagerly()) fn() True True tf.config.experimental_run_functions_eagerly(False)

Inside a transformation function for tf.dataset:

def data_fn(x):
  print(tf.executing_eagerly())
  return x
dataset = tf.data.Dataset.range(100)
dataset = dataset.map(data_fn)
False