tf.compat.v1.enable_eager_execution  |  TensorFlow v2.16.1 (original) (raw)

tf.compat.v1.enable_eager_execution

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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

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 TensorFlow Distributions: A Gentle Introduction

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:

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 to use to configure the environment in which operations are executed. Note thattf.compat.v1.ConfigProto is also used to configure graph execution (viatf.compat.v1.Session) and many options within tf.compat.v1.ConfigProtoare 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.