tf.keras.constraints.NonNeg
Constrains the weights to be non-negative.
Inherits From: Constraint
Methods
from_config
@classmethod
from_config(
config
)
Instantiates a weight constraint from a configuration dictionary.
Example:
constraint = UnitNorm() config = constraint.get_config() constraint = UnitNorm.from_config(config)
| Args | |
|---|---|
config | A Python dictionary, the output of get_config(). |
| Returns | |
|---|---|
A keras.constraints.Constraint instance. |
get_config
get_config()
Returns a Python dict of the object config.
A constraint config is a Python dictionary (JSON-serializable) that can be used to reinstantiate the same object.
| Returns | |
|---|---|
| Python dict containing the configuration of the constraint object. |
__call__
__call__(
w
)
Applies the constraint to the input weight variable.
By default, the inputs weight variable is not modified. Users should override this method to implement their own projection function.
| Args | |
|---|---|
w | Input weight variable. |
| Returns | |
|---|---|
| Projected variable (by default, returns unmodified inputs). |
© 2022 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/keras/constraints/NonNeg
