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Commit 961faf5

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Alexander Ororbia
committed
cleaned up help for exp/alpha-syn
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+14
-6
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2 files changed

+14
-6
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ngclearn/components/synapses/alphaSynapse.py

+9-4
Original file line numberDiff line numberDiff line change
@@ -134,16 +134,20 @@ def load(self, directory, **kwargs):
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@classmethod
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def help(cls): ## component help function
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properties = {
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"synapse_type": "STPDenseSynapse - performs a synaptic transformation of inputs to produce "
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"synapse_type": "AlphaSynapse - performs a synaptic transformation of inputs to produce "
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"output signals (e.g., a scaled linear multivariate transformation); "
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"this synapse is dynamic, adapting via a form of short-term plasticity"
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"this synapse is dynamic, changing according to an alpha function"
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}
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compartment_props = {
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"inputs":
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{"inputs": "Takes in external input signal values"},
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{"inputs": "Takes in external input signal values"
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"v" : "Post-synaptic voltage dependence (comes from a wired-to spiking cell) "},
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"states":
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{"weights": "Synapse efficacy/strength parameter values",
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"biases": "Base-rate/bias parameter values",
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"g_syn" : "Synaptic conductnace",
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"h_syn" : "Intermediate synaptic conductance",
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"i_syn" : "Total electrical current",
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"key": "JAX PRNG key"},
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"outputs":
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{"outputs": "Output of synaptic transformation"},
@@ -161,7 +165,8 @@ def help(cls): ## component help function
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info = {cls.__name__: properties,
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"compartments": compartment_props,
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"dynamics": "outputs = g_syn * (v - syn_rest); "
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"dgsyn_dt = (W * inputs) * g_syn_bar - g_syn/tau_syn ",
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"dhsyn_dt = (W * inputs) * g_syn_bar - h_syn/tau_syn ",
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"dgsyn_dt = -g_syn/tau_syn + h_syn",
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"hyperparameters": hyperparams}
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return info
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ngclearn/components/synapses/exponentialSynapse.py

+5-2
Original file line numberDiff line numberDiff line change
@@ -127,16 +127,19 @@ def load(self, directory, **kwargs):
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@classmethod
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def help(cls): ## component help function
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properties = {
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"synapse_type": "STPDenseSynapse - performs a synaptic transformation of inputs to produce "
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"synapse_type": "ExponentialSynapse - performs a synaptic transformation of inputs to produce "
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"output signals (e.g., a scaled linear multivariate transformation); "
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"this synapse is dynamic, adapting via a form of short-term plasticity"
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"this synapse is dynamic, evolving according to an exponential kernel"
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}
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compartment_props = {
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"inputs":
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{"inputs": "Takes in external input signal values"},
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"states":
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{"weights": "Synapse efficacy/strength parameter values",
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"biases": "Base-rate/bias parameter values",
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"g_syn" : "Synaptic conductnace",
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"h_syn" : "Intermediate synaptic conductance",
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"i_syn" : "Total electrical current",
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"key": "JAX PRNG key"},
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"outputs":
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{"outputs": "Output of synaptic transformation"},

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