59 lines
1.6 KiB
Python
59 lines
1.6 KiB
Python
from keras_core import activations
|
|
from keras_core.api_export import keras_core_export
|
|
from keras_core.layers.layer import Layer
|
|
|
|
|
|
@keras_core_export("keras_core.layers.LeakyReLU")
|
|
class LeakyReLU(Layer):
|
|
"""Leaky version of a Rectified Linear Unit activation layer.
|
|
|
|
This layer allows a small gradient when the unit is not active.
|
|
|
|
Formula:
|
|
|
|
``` python
|
|
f(x) = alpha * x if x < 0
|
|
f(x) = x if x >= 0
|
|
```
|
|
|
|
Example:
|
|
|
|
``` python
|
|
leaky_relu_layer = LeakyReLU(negative_slope=0.5)
|
|
input = np.array([-10, -5, 0.0, 5, 10])
|
|
result = leaky_relu_layer(input)
|
|
# result = [-5. , -2.5, 0. , 5. , 10.]
|
|
```
|
|
|
|
Args:
|
|
negative_slope: Float >= 0.0. Negative slope coefficient.
|
|
Defaults to 0.3.
|
|
**kwargs: Base layer keyword arguments, such as
|
|
`name` and `dtype`.
|
|
|
|
"""
|
|
|
|
def __init__(self, negative_slope=0.3, **kwargs):
|
|
super().__init__(**kwargs)
|
|
if negative_slope is None:
|
|
raise ValueError(
|
|
"The negative_slope value of a Leaky ReLU layer "
|
|
"cannot be None, Expecting a float. Received: "
|
|
f"negative_slope={negative_slope}"
|
|
)
|
|
self.supports_masking = True
|
|
self.negative_slope = negative_slope
|
|
|
|
def call(self, inputs):
|
|
return activations.leaky_relu(
|
|
inputs, negative_slope=self.negative_slope
|
|
)
|
|
|
|
def get_config(self):
|
|
config = super().get_config()
|
|
config.update({"negative_slope": self.negative_slope})
|
|
return config
|
|
|
|
def compute_output_shape(self, input_shape):
|
|
return input_shape
|