From 9c004e8393c5bc228a7ede122e39c859c38630a8 Mon Sep 17 00:00:00 2001
From: David Rotermund <54365609+davrot@users.noreply.github.com>
Date: Sun, 1 May 2022 01:24:00 +0200
Subject: [PATCH] Update README.md

---
 README.md | 73 +++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 73 insertions(+)

diff --git a/README.md b/README.md
index 2dde6c5..943e01f 100644
--- a/README.md
+++ b/README.md
@@ -27,6 +27,79 @@ pip install pybind11
 The Makefile uses clang as a compiler. If you want something else then you need to change the Makefile.
 The SbS.py autodetectes if the required C++ .so modules are in the same directory as the SbS.py file.  
 
+# SbS layer class
+
+## Variables
+
+epsilon_xy  
+epsilon_0  
+epsilon_t  
+weights  
+kernel_size  
+stride  
+dilation  
+padding  
+output_size  
+number_of_spikes  
+number_of_cpu_processes  
+number_of_neurons  
+number_of_input_neurons  
+h_initial  
+alpha_number_of_iterations  
+
+## Constructor 
+def **__init__**(  
+self,  
+number_of_input_neurons: int,  
+number_of_neurons: int,  
+input_size: list[int],  
+forward_kernel_size: list[int],  
+number_of_spikes: int,  
+epsilon_t: torch.Tensor,  
+epsilon_xy_intitial: float = 0.1,  
+epsilon_0: float = 1.0,  
+weight_noise_amplitude: float = 0.01,  
+is_pooling_layer: bool = False,  
+strides: list[int] = [1, 1],  
+dilation: list[int] = [0, 0],  
+padding: list[int] = [0, 0],  
+alpha_number_of_iterations: int = 0,  
+number_of_cpu_processes: int = 1,  
+) -> None:
+
+## Methods
+
+def **initialize_weights**(  
+self,  
+is_pooling_layer: bool = False,  
+noise_amplitude: float = 0.01,  
+) -> None:  
+For the generation of the initital weights. Switches between normal initial random weights and pooling weights.
+
+
+def **initialize_epsilon_xy**(  
+self,  
+eps_xy_intitial: float,  
+) -> None:  
+Creates initial epsilon xy matrices.
+
+def **set_h_init_to_uniform**(self) -> None:  
+
+def **backup_epsilon_xy**(self) -> None:  
+def **restore_epsilon_xy**(self) -> None:  
+def **backup_weights(self)** -> None:  
+def **restore_weights(self)** -> None:  
+
+
+def **threshold_epsilon_xy**(self, threshold: float) -> None:  
+def **threshold_weights**(self, threshold: float) -> None:  
+
+
+def **mean_epsilon_xy**(self) -> None:  
+
+def **norm_weights**(self) -> None:
+
+
 # Parameters in JSON file
 
 data_mode: str = field(default="")