61 lines
2.0 KiB
Python
61 lines
2.0 KiB
Python
|
from keras_core import backend
|
||
|
|
from keras_core import layers
|
||
|
|
from keras_core import operations as ops
|
||
|
|
from keras_core.api_export import keras_core_export
|
||
|
|
|
||
|
|
|
||
|
|
@keras_core_export("keras_core.layers.GaussianNoise")
|
||
|
|
class GaussianNoise(layers.Layer):
|
||
|
|
"""Apply additive zero-centered Gaussian noise.
|
||
|
|
|
||
|
|
This is useful to mitigate overfitting
|
||
|
|
(you could see it as a form of random data augmentation).
|
||
|
|
Gaussian Noise (GS) is a natural choice as corruption process
|
||
|
|
for real valued inputs.
|
||
|
|
|
||
|
|
As it is a regularization layer, it is only active at training time.
|
||
|
|
|
||
|
|
Args:
|
||
|
|
stddev: Float, standard deviation of the noise distribution.
|
||
|
|
seed: Integer, optional random seed to enable deterministic behavior.
|
||
|
|
|
||
|
|
Call arguments:
|
||
|
|
inputs: Input tensor (of any rank).
|
||
|
|
training: Python boolean indicating whether the layer should behave in
|
||
|
|
training mode (adding noise) or in inference mode (doing nothing).
|
||
|
|
"""
|
||
|
|
|
||
|
|
def __init__(self, stddev, seed=None, name=None, dtype=None):
|
||
|
|
super().__init__(name=name, dtype=dtype)
|
||
|
|
if not 0 <= stddev <= 1:
|
||
|
|
raise ValueError(
|
||
|
|
f"Invalid value received for argument "
|
||
|
|
"`stddev`. Expected a float value between 0 and 1. "
|
||
|
|
f"Received: stddev={stddev}"
|
||
|
|
)
|
||
|
|
self.stddev = stddev
|
||
|
|
self.seed = seed
|
||
|
|
self.seed_generator = backend.random.SeedGenerator(seed)
|
||
|
|
self.supports_masking = True
|
||
|
|
|
||
|
|
def call(self, inputs, training=False):
|
||
|
|
if training and self.stddev > 0:
|
||
|
|
return inputs + backend.random.normal(
|
||
|
|
shape=ops.shape(inputs),
|
||
|
|
mean=0.0,
|
||
|
|
stddev=self.stddev,
|
||
|
|
seed=self.seed_generator,
|
||
|
|
)
|
||
|
|
return inputs
|
||
|
|
|
||
|
|
def compute_output_shape(self, input_shape):
|
||
|
|
return input_shape
|
||
|
|
|
||
|
|
def get_config(self):
|
||
|
|
base_config = super().get_config()
|
||
|
|
config = {
|
||
|
|
"stddev": self.stddev,
|
||
|
|
"seed": self.seed,
|
||
|
|
}
|
||
|
|
return {**base_config, **config}
|