tf.compat.v1.executing_eagerly

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Checks whether the current thread has eager execution enabled.

tf.compat.v1.executing_eagerly()

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.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

Returns:

True if the current thread has eager execution enabled.