|---| | [ View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.21.0/tensorflow/python/framework/ops.py#L4917-L4992) | Enables eager execution for the lifetime of this program. tf.compat.v1.enable_eager_execution( config=None, device_policy=None, execution_mode=None ) -> None
## Migrate to TF2
> [!CAUTION] > **Caution:** This API was designed for TensorFlow v1. Continue reading for details on how to migrate from this API to a native TensorFlow v2 equivalent. See the [TensorFlow v1 to TensorFlow v2 migration guide](https://www.tensorflow.org/guide/migrate) for instructions on how to migrate the rest of your code. This function is not necessary if you are using TF2. Eager execution is enabled by default.

## Description ### Used in the notebooks | Used in the tutorials | |---| | - [TensorFlow Constrained Optimization Example Using CelebA Dataset](https://www.tensorflow.org/responsible_ai/fairness_indicators/tutorials/Fairness_Indicators_TFCO_CelebA_Case_Study) - [TensorFlow Distributions: A Gentle Introduction](https://www.tensorflow.org/probability/examples/TensorFlow_Distributions_Tutorial) | 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`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/Session)) and return concrete values (as opposed to symbolic references to a node in a computational graph). #### For example: tf.compat.v1.enable_eager_execution() # 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).


| ## Args || |---|---| | `config` | (Optional.) A [`tf.compat.v1.ConfigProto`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/ConfigProto) to use to configure the environment in which operations are executed. Note that [`tf.compat.v1.ConfigProto`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/ConfigProto) is also used to configure graph execution (via [`tf.compat.v1.Session`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/Session)) and many options within [`tf.compat.v1.ConfigProto`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/ConfigProto) are not implemented (or are irrelevant) when eager execution is enabled. | | `device_policy` | (Optional.) Policy controlling how operations requiring inputs on a specific device (e.g., a GPU 0) handle inputs on a different device (e.g. GPU 1 or CPU). When set to None, an appropriate value will be picked automatically. The value picked may change between TensorFlow releases. Valid values:
- DEVICE_PLACEMENT_EXPLICIT: raises an error if the placement is not correct. - DEVICE_PLACEMENT_WARN: copies the tensors which are not on the right device but logs a warning. - DEVICE_PLACEMENT_SILENT: silently copies the tensors. Note that this may hide performance problems as there is no notification provided when operations are blocked on the tensor being copied between devices. - DEVICE_PLACEMENT_SILENT_FOR_INT32: silently copies int32 tensors, raising errors on the other ones. | | `execution_mode` | (Optional.) Policy controlling how operations dispatched are actually executed. When set to None, an appropriate value will be picked automatically. The value picked may change between TensorFlow releases. Valid values: - SYNC: executes each operation synchronously. - ASYNC: executes each operation asynchronously. These operations may return "non-ready" handles. |


| ## Raises || |---|---| | `ValueError` | If eager execution is enabled after creating/executing a TensorFlow graph, or if options provided conflict with a previous call to this function. |