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David Rotermund 2022-05-01 01:35:47 +02:00 committed by GitHub
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@ -93,7 +93,7 @@ alpha_number_of_iterations
## Constructor ## Constructor
``` ```
def **__init__**( def __init__(
self, self,
number_of_input_neurons: int, number_of_input_neurons: int,
number_of_neurons: int, number_of_neurons: int,
@ -116,7 +116,7 @@ def **__init__**(
## Methods ## Methods
``` ```
def **initialize_weights**( def initialize_weights(
self, self,
is_pooling_layer: bool = False, is_pooling_layer: bool = False,
noise_amplitude: float = 0.01, noise_amplitude: float = 0.01,
@ -127,7 +127,7 @@ For the generation of the initital weights. Switches between normal initial rand
--- ---
``` ```
def **initialize_epsilon_xy**( def initialize_epsilon_xy(
self, self,
eps_xy_intitial: float, eps_xy_intitial: float,
) -> None: ) -> None:
@ -136,31 +136,31 @@ Creates initial epsilon xy matrices.
--- ---
``` ```
def **set_h_init_to_uniform**(self) -> None: def set_h_init_to_uniform(self) -> None:
``` ```
--- ---
``` ```
def **backup_epsilon_xy**(self) -> None: def backup_epsilon_xy(self) -> None:
def **restore_epsilon_xy**(self) -> None: def restore_epsilon_xy(self) -> None:
def **backup_weights(self)** -> None: def backup_weights(self) -> None:
def **restore_weights(self)** -> None: def restore_weights(self) -> None:
``` ```
--- ---
``` ```
def **threshold_epsilon_xy**(self, threshold: float) -> None: def threshold_epsilon_xy(self, threshold: float) -> None:
def **threshold_weights**(self, threshold: float) -> None: def threshold_weights(self, threshold: float) -> None:
``` ```
--- ---
``` ```
def **mean_epsilon_xy**(self) -> None: def mean_epsilon_xy(self) -> None:
``` ```
--- ---
``` ```
def **norm_weights**(self) -> None: def norm_weights(self) -> None:
``` ```
# Parameters in JSON file # Parameters in JSON file