Enables eager execution for the lifetime of this program.

Used in the notebooks

Used in the tutorials

Eager execution provides an imperative interface to TensorFlow. With eager execution enabled, TensorFlow functions execute operations immediately (as opposed to adding to a graph to be executed later in a tf.compat.v1.Session) and return concrete values (as opposed to symbolic references to a node in a computational graph).

For example:


# After eager execution is enabled, operations are executed as they are
# defined and Tensor objects hold concrete values, which can be accessed as
# numpy.ndarray`s through the numpy() method.
assert tf.multiply(6, 7).numpy() == 42

Eager execution cannot be enabled after TensorFlow APIs have been used to create or execute graphs. It is typically recommended to invoke this function at program startup and not in a library (as most libraries should be usable both with and without eager execution).

config (Optional.) A tf.compat.v1.ConfigProto to use to configure the environment in which operations are executed. Note that tf.compat.v1.ConfigProto is also used to configure graph execution (via