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tf.compat.v1.executing_eagerly

Checks whether the current thread has eager execution enabled.

Eager execution is typically enabled via tf.compat.v1.enable_eager_execution, but may also be enabled within the context of a Python function via tf.contrib.eager.py_func.

When eager execution is enabled, returns True in most cases. However, this API might return False in the following use cases.

tf.compat.v1.enable_eager_execution()

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.run_functions_eagerly(True) is called:

tf.config.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.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
Returns
True if the current thread has eager execution enabled.

© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/compat/v1/executing_eagerly