Given an arbitrary function, wrap it so that it does variable sharing.
Compat aliases for migration
See Migration guide for more details.
tf.make_template( name_, func_, create_scope_now_=False, unique_name_=None, custom_getter_=None, **kwargs )
func_ in a Template and partially evaluates it. Templates are functions that create variables the first time they are called and reuse them thereafter. In order for
func_ to be compatible with a
Template it must have the following properties:
tf.compat.v1.get_variable. If a trainable variable is created using
tf.Variable, then a ValueError will be thrown. Variables that are intended to be locals can be created by specifying
tf.compat.v1.global_variablesto capture variables that are defined outside of the scope of the function.
make_template. In general you will get a ValueError telling you that you are trying to reuse a variable that doesn't exist if you make a mistake.
In the following example, both
w will be scaled by the same
y. It is important to note that if we didn't assign
scalar_name and used a different name for z and w that a
ValueError would be thrown because it couldn't reuse the variable.
def my_op(x, scalar_name): var1 = tf.compat.v1.get_variable(scalar_name, shape=, initializer=tf.compat.v1.constant_initializer(1)) return x * var1 scale_by_y = tf.compat.v1.make_template('scale_by_y', my_op, scalar_name='y') z = scale_by_y(input1) w = scale_by_y(input2)
As a safe-guard, the returned function will raise a
ValueError after the first call if trainable variables are created by calling
If all of these are true, then 2 properties are enforced by the template:
def my_op(x, scalar_name): var1 = tf.compat.v1.get_variable(scalar_name, shape=, initializer=tf.compat.v1.constant_initializer(1)) return x * var1 with tf.compat.v1.variable_scope('scope') as vs: scale_by_y = tf.compat.v1.make_template('scale_by_y', my_op, scalar_name='y') z = scale_by_y(input1) w = scale_by_y(input2) # Creates a template that reuses the variables above. with tf.compat.v1.variable_scope(vs, reuse=True): scale_by_y2 = tf.compat.v1.make_template('scale_by_y', my_op, scalar_name='y') z2 = scale_by_y2(input1) w2 = scale_by_y2(input2)
Depending on the value of
create_scope_now_, the full variable scope may be captured either at the time of first call or at the time of construction. If this option is set to True, then all Tensors created by repeated calls to the template will have an extra trailing _N+1 to their name, as the first time the scope is entered in the Template constructor no Tensors are created.
create_scope_now_have a trailing underscore to reduce the likelihood of collisions with kwargs.
| || A name for the scope created by this template. If necessary, the name will be made unique by appending |
| ||The function to wrap.|
| ||Boolean controlling whether the scope should be created when the template is constructed or when the template is called. Default is False, meaning the scope is created when the template is called.|
| ||When used, it overrides name_ and is not made unique. If a template of the same scope/unique_name already exists and reuse is false, an error is raised. Defaults to None.|
| || Optional custom getter for variables used in |
| || Keyword arguments to apply to |
| A function to encapsulate a set of variables which should be created once and reused. An enclosing scope will be created either when |
| || if |
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