readout layer trained

verified with time-series forecasting task and plotted

1 files changed, 0 insertions, 36 deletions

diff --git a/neurobench_testing/custom_memristor_model.py b/neurobench_testing/custom_memristor_model.py
deleted file mode 100644
index eb91b99..0000000
--- a/neurobench_testing/custom_memristor_model.py
+++ /dev/null
@@ -1,36 +0,0 @@
-import torch
-import memtorch
-from memtorch.bh.memristor.Memristor import Memristor
-from memtorch.utils import clip, convert_range #idk if ill need this
-
-class MemtorchMemristor(Memristor):
-    def __init__(
-            self,
-            k_off       = 1.0,      # switching rate for off state
-            k_on        = -1.0,     # switching rate for on state
-            alpha_off   = 5,        # exponent controlling nonlinearity
-            alpha_on    = 5,        # exponent controlling nonlinearity
-            i_off       = 0.5e-3,   # threshhold current to trigger off state
-            i_on        = 0.5e-3,   # threshold current to trigger on state
-            r_on        = 1e3,      # maximum resistance
-            r_off       = 10e3,     # minimum resistance
-            p           = 2,        # window function exponent
-            **kwargs
-    ):
-        #initializing base memristor class
-        super(MemtorchMemristor, self).__init__(r_off=r_off, r_on=r_on, **kwargs)
-
-        # hyper parameters
-        self.k_off = k_off
-        self.k_on = k_on
-        self.alpha_off = alpha_off
-        self.alpha_on = alpha_on
-        self.i_on = i_on
-        self.i_off = i_off
-        self.p = p
-
-        #state variables
-        self.w = 0.5
-        self.g = 1/self.r_on
-
-    def window()