diff --git a/modneflib/modnef/modnef_torch/modnef_neurons/modnef_torch_neuron.py b/modneflib/modnef/modnef_torch/modnef_neurons/modnef_torch_neuron.py
index 73225949001afeb0d5700f6f4a5c15c78b2079aa..0a1acd91e0af892d9b43ca10623d5d6203af65dc 100644
--- a/modneflib/modnef/modnef_torch/modnef_neurons/modnef_torch_neuron.py
+++ b/modneflib/modnef/modnef_torch/modnef_neurons/modnef_torch_neuron.py
@@ -10,6 +10,8 @@ Descriptions: ModNEF torch neuron interface builder
import torch
from modnef.quantizer import *
+from snntorch._neurons import SpikingNeuron
+from snntorch.surrogate import fast_sigmoid
_quantizer = {
"FixedPointQuantizer" : FixedPointQuantizer,
@@ -17,7 +19,7 @@ _quantizer = {
"DynamicScaleFactorQuantizer" : DynamicScaleFactorQuantizer
}
-class ModNEFNeuron():
+class ModNEFNeuron(SpikingNeuron):
"""
ModNEF torch neuron interface
@@ -42,7 +44,27 @@ class ModNEFNeuron():
create and return the corresponding modnef archbuilder module from internal neuron parameters
"""
- def __init__(self, quantizer : Quantizer):
+ def __init__(self,
+ threshold,
+ reset_mechanism,
+ quantizer : Quantizer,
+ spike_grad=fast_sigmoid(slope=25)):
+
+ SpikingNeuron.__init__(
+ self=self,
+ threshold=threshold,
+ reset_mechanism=reset_mechanism,
+ spike_gard=spike_grad,
+ surrogate_disable=False,
+ init_hidden=False,
+ inhibition=False,
+ learn_threshold=False,
+ state_quant=False,
+ output=False,
+ graded_spikes_factor=1.0,
+ learn_graded_spikes_factor=False
+ )
+
self.hardware_estimation_flag = False
self.quantization_flag = False
@@ -61,7 +83,20 @@ class ModNEFNeuron():
raise NotImplementedError()
- def quantize_weight(self):
+ def init_quantizer(self):
+
+ params = list(self.parameters())
+
+ w1 = params[0].data
+
+ if len(params)==2:
+ w2 = params[0].data
+ else:
+ w2 = torch.zeros((1))
+
+ self.quantizer.init_quantizer(w1, w2)
+
+ def quantize_weight(self, unscaled : bool = False):
"""
synaptic weight quantization
@@ -70,9 +105,10 @@ class ModNEFNeuron():
NotImplementedError()
"""
- raise NotImplementedError()
+ for param in self.parameters():
+ param.data = self.quantizer(param.data, unscale=unscaled)
- def quantize_parameters(self):
+ def quantize_hp(self):
"""
neuron hyper-parameters quantization
"""
diff --git a/modneflib/modnef/modnef_torch/modnef_neurons/srlif_model/shiftlif.py b/modneflib/modnef/modnef_torch/modnef_neurons/srlif_model/shiftlif.py
index 9bb6d1df8eeff1ab9044378d73e3625e4a9e4438..195e965f8f99ef994bca289886b182ad7af402fa 100644
--- a/modneflib/modnef/modnef_torch/modnef_neurons/srlif_model/shiftlif.py
+++ b/modneflib/modnef/modnef_torch/modnef_neurons/srlif_model/shiftlif.py
@@ -11,14 +11,14 @@ Based on snntorch.Leaky and snntroch.LIF class
import torch.nn as nn
import torch
-from snntorch import LIF
+from snntorch.surrogate import fast_sigmoid
import modnef.arch_builder as builder
from modnef.arch_builder.modules.utilities import *
from ..modnef_torch_neuron import ModNEFNeuron, _quantizer
from math import log, ceil
from modnef.quantizer import DynamicScaleFactorQuantizer
-class ShiftLIF(LIF, ModNEFNeuron):
+class ShiftLIF(ModNEFNeuron):
"""
ModNEFTorch Shift LIF neuron model
@@ -86,7 +86,7 @@ class ShiftLIF(LIF, ModNEFNeuron):
out_features,
beta,
threshold=1.0,
- spike_grad=None,
+ spike_grad=fast_sigmoid(slope=25),
reset_mechanism="subtract",
quantizer=DynamicScaleFactorQuantizer(8)
):
@@ -117,24 +117,13 @@ class ShiftLIF(LIF, ModNEFNeuron):
print(f"initial value of beta ({beta}) has been change for {1-2**-self.shift} = 1-2**-{self.shift}")
beta = 1-2**-self.shift
- LIF.__init__(
- self=self,
- beta=beta,
- threshold=threshold,
- spike_grad=spike_grad,
- surrogate_disable=False,
- init_hidden=False,
- inhibition=False,
- learn_beta=False,
- learn_threshold=False,
- reset_mechanism=reset_mechanism,
- state_quant=False,
- output=False,
- graded_spikes_factor=1.0,
- learn_graded_spikes_factor=False,
- )
- ModNEFNeuron.__init__(self=self, quantizer=quantizer)
+ ModNEFNeuron.__init__(self=self,
+ threshold=threshold,
+ reset_mechanism=reset_mechanism,
+ spike_grad=spike_grad,
+ quantizer=quantizer
+ )
self.fc = nn.Linear(in_features, out_features, bias=False)
diff --git a/modneflib/modnef/quantizer/dynamic_scale_quantizer.py b/modneflib/modnef/quantizer/dynamic_scale_quantizer.py
index 2631170b678e8ece885ed61e4e16a2efe17340db..43a6aa1fca47cb9e36775b0596a95a0b9c61c6b9 100644
--- a/modneflib/modnef/quantizer/dynamic_scale_quantizer.py
+++ b/modneflib/modnef/quantizer/dynamic_scale_quantizer.py
@@ -96,7 +96,7 @@ class DynamicScaleFactorQuantizer(Quantizer):
is_initialize=config["is_initialize"]
)
- def init_from_weight(self, weight, rec_weight=torch.zeros((1))):
+ def init_quantizer(self, weight, rec_weight=torch.zeros((1))):
"""
initialize quantizer parameters from synaptic weight
diff --git a/modneflib/modnef/quantizer/fixed_point_quantizer.py b/modneflib/modnef/quantizer/fixed_point_quantizer.py
index 106a242180b8b83b5d47ebe1dbf0e4f7604f63cd..c48e690cdbc31e131a1351c02330c7a8fc3e148c 100644
--- a/modneflib/modnef/quantizer/fixed_point_quantizer.py
+++ b/modneflib/modnef/quantizer/fixed_point_quantizer.py
@@ -109,7 +109,7 @@ class FixedPointQuantizer(Quantizer):
is_initialize=config["is_initialize"]
)
- def init_from_weight(self, weight, rec_weight=torch.zeros((1))):
+ def init_quantizer(self, weight, rec_weight=torch.zeros((1))):
"""
initialize quantizer parameters from synaptic weight
diff --git a/modneflib/modnef/quantizer/min_max_quantizer.py b/modneflib/modnef/quantizer/min_max_quantizer.py
index 6ca813180dfc9d0de66ff4428564c6240b9f4649..ebc4ae9fb6cde07e030b35dad1a89f0c82f6ae00 100644
--- a/modneflib/modnef/quantizer/min_max_quantizer.py
+++ b/modneflib/modnef/quantizer/min_max_quantizer.py
@@ -105,7 +105,7 @@ class MinMaxQuantizer(Quantizer):
is_initialize=config["is_initialize"]
)
- def init_from_weight(self, weight, rec_weight=torch.zeros((1))):
+ def init_quantizer(self, weight, rec_weight=torch.zeros((1))):
"""
initialize quantizer parameters from synaptic weight
diff --git a/modneflib/modnef/quantizer/quantizer.py b/modneflib/modnef/quantizer/quantizer.py
index d75316275c5aef34558d855e9fd015c900748ece..6ab752eb28bb5c601293cfe46cd1ce7e05ff4e5a 100644
--- a/modneflib/modnef/quantizer/quantizer.py
+++ b/modneflib/modnef/quantizer/quantizer.py
@@ -77,7 +77,7 @@ class Quantizer():
raise NotImplementedError()
- def init_from_weight(self, weight, rec_weight=torch.zeros((1))):
+ def init_quantizer(self, weight, rec_weight=torch.zeros((1))):
"""
initialize quantizer parameters from synaptic weight
@@ -112,10 +112,10 @@ class Quantizer():
else:
tdata = data
+ qdata = self._quant(tdata)
+
if unscale:
- qdata = self._unquant(self._quant(tdata))
- else:
- qdata = self._quant(tdata)
+ qdata = self._unquant(qdata)
if isinstance(data, (int, float)):
return qdata.item()