Validate isolated author LIF semantics without changing frozen models
This commit is contained in:
+26
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+4
@@ -0,0 +1,4 @@
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+102
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||||
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|
||||
"matches": true
|
||||
}
|
||||
},
|
||||
"platform": "Linux-5.15.0-194-generic-x86_64-with-glibc2.35",
|
||||
"python": "3.10.12",
|
||||
"python_executable": "/data/digital-drosophila/experiments/phase4ad-author-semantics/environment/.venv/bin/python",
|
||||
"python_patch_matches": false
|
||||
}
|
||||
+127
@@ -0,0 +1,127 @@
|
||||
[
|
||||
{
|
||||
"active": true,
|
||||
"code_objects": [],
|
||||
"name": "default_neurons",
|
||||
"order": 0,
|
||||
"type": "NeuronGroup",
|
||||
"when": "start"
|
||||
},
|
||||
{
|
||||
"active": true,
|
||||
"code_objects": [],
|
||||
"name": "default_synapses",
|
||||
"order": 0,
|
||||
"type": "Synapses",
|
||||
"when": "start"
|
||||
},
|
||||
{
|
||||
"abstract_code": "not_refractory = timestep(t - lastspike, dt) >= timestep(rfc, dt)\n_g = g*exp(-dt*int(not_refractory)/tau)\n_v = g*tau*(-exp(dt*int(not_refractory)/t_mbr) + exp(dt*int(not_refractory)/tau))*exp(-dt*int(not_refractory)/t_mbr)*exp(-dt*int(not_refractory)/tau)/(t_mbr - tau) + v*exp(-dt*int(not_refractory)/t_mbr) + v_0 - v_0*exp(-dt*int(not_refractory)/t_mbr)\ng = _g\nv = _v",
|
||||
"active": true,
|
||||
"code_objects": [
|
||||
{
|
||||
"generated_code": "after_run:\n import numpy as _numpy\n from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n # EMPTY_CODE_BLOCK -- overwrite in child template\nbefore_run:\n import numpy as _numpy\n from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n # EMPTY_CODE_BLOCK -- overwrite in child template\nrun:\n import numpy as _numpy\n from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n # scalar code\n _vectorisation_idx = 1\n dt = _array_defaultclock_dt[0]\n _lio_1 = (- dt) / tau\n _lio_2 = exp(_lio_1)\n _lio_3 = tau / (t_mbr - tau)\n _lio_4 = dt / t_mbr\n _lio_5 = dt / tau\n _lio_6 = (- dt) / t_mbr\n _lio_7 = v_0 - v_0\n _lio_8 = v_0 - (v_0 * exp(_lio_6))\n _lio_9 = ((_lio_3 * ((- exp(_lio_4)) + exp(_lio_5))) * exp(_lio_6)) * exp(_lio_1)\n _lio_10 = exp(_lio_6)\n # vector code\n _vectorisation_idx = LazyArange(N)\n g = _array_default_neurons_g.copy()\n t = _array_defaultclock_t[0]\n dt = _array_defaultclock_dt[0]\n rfc = _array_default_neurons_rfc\n v = _array_default_neurons_v.copy()\n lastspike = _array_default_neurons_lastspike\n not_refractory = _array_default_neurons_not_refractory.copy()\n not_refractory = timestep(t - lastspike, dt) >= timestep(rfc, dt)\n _g = _numpy.where(not_refractory, _lio_2 * g, g)\n _v = _numpy.where(not_refractory, _lio_8 + ((_lio_9 * g) + (_lio_10 * v)), _lio_7 + v)\n g[not_refractory] = _g[not_refractory]\n v[not_refractory] = _v[not_refractory]\n _array_default_neurons_g[:] = g\n _array_default_neurons_v[:] = v\n _array_default_neurons_not_refractory[:] = not_refractory\n",
|
||||
"name": "default_neurons_stateupdater_codeobject",
|
||||
"type": "CallableProxyType"
|
||||
}
|
||||
],
|
||||
"name": "default_neurons_stateupdater",
|
||||
"order": 0,
|
||||
"type": "StateUpdater",
|
||||
"user_code": "g = -g*int(not_refractory)/tau\nv = (g - v + v_0)*int(not_refractory)/t_mbr",
|
||||
"when": "groups"
|
||||
},
|
||||
{
|
||||
"active": true,
|
||||
"code_objects": [],
|
||||
"name": "oracle_seed_injection",
|
||||
"order": 0,
|
||||
"type": "NetworkOperation",
|
||||
"when": "before_thresholds"
|
||||
},
|
||||
{
|
||||
"abstract_code": "_cond = (v > v_th) and not_refractory",
|
||||
"active": true,
|
||||
"code_objects": [
|
||||
{
|
||||
"generated_code": "after_run:\n import numpy as _numpy\n from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n _array_default_neurons__spikespace[-1] = 0\nbefore_run:\n import numpy as _numpy\n from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n # EMPTY_CODE_BLOCK -- overwrite in child template\nrun:\n import numpy as _numpy\n from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n numpy_True = _numpy.bool_(True)\n numpy_False = _numpy.bool_(False)\n # scalar code\n _vectorisation_idx = 1\n # vector code\n _vectorisation_idx = LazyArange(N)\n v = _array_default_neurons_v\n not_refractory = _array_default_neurons_not_refractory\n _cond = (v > v_th) & not_refractory\n if _cond is True or _cond is numpy_True:\n _events = _numpy.arange(N)\n elif _cond is False or _cond is numpy_False:\n _events = _numpy.array([])\n else:\n _events, = _cond.nonzero()\n _array_default_neurons__spikespace[-1] = len(_events)\n _array_default_neurons__spikespace[:len(_events)] = _events\n # Set the neuron to refractory\n _array_default_neurons_not_refractory[_events] = False\n _array_default_neurons_lastspike[_events] = _array_defaultclock_t[0]\n",
|
||||
"name": "default_neurons_spike_thresholder_codeobject_1",
|
||||
"type": "CallableProxyType"
|
||||
}
|
||||
],
|
||||
"name": "default_neurons_spike_thresholder",
|
||||
"order": 0,
|
||||
"type": "Thresholder",
|
||||
"user_code": "_cond = v > v_th",
|
||||
"when": "thresholds"
|
||||
},
|
||||
{
|
||||
"abstract_code": "_to_record_i = _source_i\n_to_record_t = _source_t",
|
||||
"active": true,
|
||||
"code_objects": [
|
||||
{
|
||||
"generated_code": "after_run:\n import numpy as _numpy\n from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n # EMPTY_CODE_BLOCK -- overwrite in child template\nbefore_run:\n import numpy as _numpy\n from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n # EMPTY_CODE_BLOCK -- overwrite in child template\nrun:\n import numpy as _numpy\n from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n _n_events = _array_default_neurons__spikespace[-1]\n if _n_events > 0:\n _events = _array_default_neurons__spikespace[:_n_events]\n # Take subgroups into account\n if _source_start != 0 or _source_stop != _source_N:\n _events = _events[(_events >= _source_start) & (_events < _source_stop)]\n _n_events = len(_events)\n if _n_events > 0:\n _vectorisation_idx = 1\n _curlen = _array_spikemonitor_N[0]\n _newlen = _curlen + _n_events\n _owner.resize(_newlen)\n _array_spikemonitor_N[0] = _newlen\n _vectorisation_idx = _events\n _idx = _events\n _source_i = _array_default_neurons_i[_idx]\n _source_t = _array_defaultclock_t[0]\n _to_record_i = _source_i\n _to_record_t = _source_t\n _dynamic_array_spikemonitor_t[_curlen:_newlen] = _to_record_t\n _dynamic_array_spikemonitor_i[_curlen:_newlen] = _to_record_i\n _array_spikemonitor_count[_events - _source_start] += 1\n",
|
||||
"name": "spikemonitor_codeobject",
|
||||
"type": "CallableProxyType"
|
||||
}
|
||||
],
|
||||
"name": "spikemonitor",
|
||||
"order": 1,
|
||||
"type": "SpikeMonitor",
|
||||
"user_code": "None",
|
||||
"when": "thresholds"
|
||||
},
|
||||
{
|
||||
"abstract_code": "g += w\n",
|
||||
"active": true,
|
||||
"code_objects": [
|
||||
{
|
||||
"generated_code": "after_run:\n import numpy as _numpy\n from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n # EMPTY_CODE_BLOCK -- overwrite in child template\nbefore_run:\n import numpy as _numpy\n from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n _owner.initialise_queue()\nrun:\n import numpy as _numpy\n from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n _owner.push_spikes()\n",
|
||||
"name": "default_synapses_pre_push_spikes",
|
||||
"type": "CallableProxyType"
|
||||
},
|
||||
{
|
||||
"generated_code": "after_run:\n import numpy as _numpy\n from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n # EMPTY_CODE_BLOCK -- overwrite in child template\nbefore_run:\n import numpy as _numpy\n from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n # EMPTY_CODE_BLOCK -- overwrite in child template\nrun:\n import numpy as _numpy\n from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n _spiking_synapses = _queue.peek()\n if len(_spiking_synapses):\n # scalar code\n # vector code\n _idx = _spiking_synapses\n _vectorisation_idx = _idx\n # Abstract code: g += w\n _postsynaptic_idx = _array_default_synapses__synaptic_post[_idx]\n w = _array_default_synapses_w[_idx]\n not_refractory = _array_default_neurons_not_refractory[_postsynaptic_idx]\n _numpy.add.at(_array_default_neurons_g, _postsynaptic_idx[not_refractory], w[not_refractory])\n # Advance the spike queue\n _queue.advance()\n",
|
||||
"name": "default_synapses_pre_codeobject_1",
|
||||
"type": "CallableProxyType"
|
||||
}
|
||||
],
|
||||
"name": "default_synapses_pre",
|
||||
"order": -1,
|
||||
"type": "SynapticPathway",
|
||||
"user_code": "None",
|
||||
"when": "synapses"
|
||||
},
|
||||
{
|
||||
"abstract_code": "v = v_rst; w = 0; g = 0 * mV",
|
||||
"active": true,
|
||||
"code_objects": [
|
||||
{
|
||||
"generated_code": "after_run:\n import numpy as _numpy\n from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n # EMPTY_CODE_BLOCK -- overwrite in child template\nbefore_run:\n import numpy as _numpy\n from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n # EMPTY_CODE_BLOCK -- overwrite in child template\nrun:\n import numpy as _numpy\n from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n # scalar code\n _vectorisation_idx = 1\n w = 0\n # vector code\n _idx = _array_default_neurons__spikespace[:_array_default_neurons__spikespace[-1]]\n _vectorisation_idx = _idx\n v = v_rst\n g = 0.0\n _array_default_neurons_g[_idx] = g\n _array_default_neurons_v[_idx] = v\n",
|
||||
"name": "default_neurons_spike_resetter_codeobject_1",
|
||||
"type": "CallableProxyType"
|
||||
}
|
||||
],
|
||||
"name": "default_neurons_spike_resetter",
|
||||
"order": 0,
|
||||
"type": "Resetter",
|
||||
"user_code": "None",
|
||||
"when": "resets"
|
||||
},
|
||||
{
|
||||
"abstract_code": "_to_record_v = _source_v\n_to_record_g = _source_g\n_to_record_lastspike = _source_lastspike\n_to_record_not_refractory = _source_not_refractory",
|
||||
"active": true,
|
||||
"code_objects": [
|
||||
{
|
||||
"generated_code": "after_run:\n import numpy as _numpy\n from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n # EMPTY_CODE_BLOCK -- overwrite in child template\nbefore_run:\n import numpy as _numpy\n from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n # EMPTY_CODE_BLOCK -- overwrite in child template\nrun:\n import numpy as _numpy\n from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n # Resize dynamic arrays\n _new_len = len(_dynamic_array_oracle_end_state_t) + 1\n _owner.resize(_new_len)\n # Store values\n _dynamic_array_oracle_end_state_t[-1] = _array_defaultclock_t[0]\n # scalar code\n _vectorisation_idx = 1\n # vector code\n _vectorisation_idx = _array_oracle_end_state__indices\n _idx = _array_oracle_end_state__indices\n _source_not_refractory = _array_default_neurons_not_refractory[_idx]\n _source_g = _array_default_neurons_g[_idx]\n _source_v = _array_default_neurons_v[_idx]\n _source_lastspike = _array_default_neurons_lastspike[_idx]\n _to_record_v = _source_v\n _to_record_g = _source_g\n _to_record_lastspike = _source_lastspike\n _to_record_not_refractory = _source_not_refractory\n _dynamic_array_oracle_end_state_v[-1, :] = _to_record_v\n _dynamic_array_oracle_end_state_g[-1, :] = _to_record_g\n _dynamic_array_oracle_end_state_lastspike[-1, :] = _to_record_lastspike\n _dynamic_array_oracle_end_state_not_refractory[-1, :] = _to_record_not_refractory\n",
|
||||
"name": "oracle_end_state_codeobject",
|
||||
"type": "CallableProxyType"
|
||||
}
|
||||
],
|
||||
"name": "oracle_end_state",
|
||||
"order": 0,
|
||||
"type": "StateMonitor",
|
||||
"user_code": "None",
|
||||
"when": "end"
|
||||
}
|
||||
]
|
||||
@@ -0,0 +1,123 @@
|
||||
{
|
||||
"author_commit": "91bdd1e7dcf193f3e7ca5a8933497fcef63b7960",
|
||||
"author_sha256": "fc45837d7122c6ce2a7f3f2f23c515992e4b232aadb919efabb72337fac88e4e",
|
||||
"config": {
|
||||
"author_precisions": [
|
||||
"float64",
|
||||
"float32"
|
||||
],
|
||||
"comparison": {
|
||||
"exact_spike_events_required_for_oracle_validation": true,
|
||||
"float32_state_max_abs_tolerance_mv": 0.001,
|
||||
"float64_state_max_abs_tolerance_mv": 1e-08,
|
||||
"precision_cross_comparison_may_diverge_but_must_be_reported": true
|
||||
},
|
||||
"component_policies": [
|
||||
"frozen",
|
||||
"reset_g_only",
|
||||
"refractory_gate_only",
|
||||
"reset_and_refractory"
|
||||
],
|
||||
"dt_ms": 0.1,
|
||||
"duration_ms": 1000.0,
|
||||
"experiment": "experiments/phase4ad-author-semantics",
|
||||
"human_authorization": "\u5141\u8bb8\u72ec\u7acb\u65b0\u6a21\u578b\u5206\u652f\u6d4b\u8bd5\u52a8\u529b\u5b66\u5047\u8bbe",
|
||||
"late_start_ms": 500.0,
|
||||
"model": {
|
||||
"dt_ms": 0.1,
|
||||
"membrane_tau_ms": 20.0,
|
||||
"refractory_ms": 2.2,
|
||||
"reset_potential_mv": -52.0,
|
||||
"resting_potential_mv": -52.0,
|
||||
"synaptic_delay_ms": 1.8,
|
||||
"synaptic_tau_ms": 5.0,
|
||||
"threshold_mv": -45.0,
|
||||
"w_syn_mv_per_anatomical_synapse": 0.275
|
||||
},
|
||||
"model_directory": "models/male-cns-lif/author-semantics-lab-v1",
|
||||
"motifs": [
|
||||
"pair",
|
||||
"trio",
|
||||
"five",
|
||||
"feedforward",
|
||||
"no_input"
|
||||
],
|
||||
"name": "author-semantics-lab-v1",
|
||||
"no_training_or_candidate": true,
|
||||
"phase": "4AD",
|
||||
"prior_experiment": "experiments/phase4ac-lif-semantics",
|
||||
"prior_model": "models/male-cns-lif/lif-semantics-audit-v1",
|
||||
"root": "/data/digital-drosophila",
|
||||
"seed_margin_mv": 1.0,
|
||||
"seed_node": 1381
|
||||
},
|
||||
"delay_steps": 18,
|
||||
"dt_ms": 0.1,
|
||||
"edge_ids": [
|
||||
1336648,
|
||||
1336655,
|
||||
1467340,
|
||||
1467355,
|
||||
1559765,
|
||||
1559772
|
||||
],
|
||||
"external_arrivals": {
|
||||
"events": 0,
|
||||
"ordering": "after default_synapses.pre"
|
||||
},
|
||||
"internal_voltage_unit": "volt",
|
||||
"nodes": [
|
||||
1197,
|
||||
1381,
|
||||
1511
|
||||
],
|
||||
"parameter_checks": {
|
||||
"membrane_tau_ms": {
|
||||
"author": 20.0,
|
||||
"config": 20.0
|
||||
},
|
||||
"refractory_ms": {
|
||||
"author": 2.2,
|
||||
"config": 2.2
|
||||
},
|
||||
"reset_potential_mv": {
|
||||
"author": -52.0,
|
||||
"config": -52.0
|
||||
},
|
||||
"resting_potential_mv": {
|
||||
"author": -52.0,
|
||||
"config": -52.0
|
||||
},
|
||||
"synaptic_delay_ms": {
|
||||
"author": 1.8,
|
||||
"config": 1.8
|
||||
},
|
||||
"synaptic_tau_ms": {
|
||||
"author": 5.0,
|
||||
"config": 5.0
|
||||
},
|
||||
"threshold_mv": {
|
||||
"author": -45.0,
|
||||
"config": -45.0
|
||||
},
|
||||
"w_syn_mv_per_anatomical_synapse": {
|
||||
"author": 0.275,
|
||||
"config": 0.275
|
||||
}
|
||||
},
|
||||
"precision": "float64",
|
||||
"preferences": {
|
||||
"codegen.target": "numpy",
|
||||
"core.default_float_dtype": "float64",
|
||||
"legacy.refractory_timing": false
|
||||
},
|
||||
"refractory_steps": 22,
|
||||
"returned_voltage_unit": "mV",
|
||||
"seed": {
|
||||
"injections": 0,
|
||||
"margin_mv": 1.0,
|
||||
"requested_global_node": 1381
|
||||
},
|
||||
"steps": 10000,
|
||||
"weight_rule": "raw_count multiplied by unchanged author w_syn; no sign inference"
|
||||
}
|
||||
@@ -0,0 +1,11 @@
|
||||
{
|
||||
"schedule": [
|
||||
"start",
|
||||
"groups",
|
||||
"thresholds",
|
||||
"synapses",
|
||||
"resets",
|
||||
"end"
|
||||
],
|
||||
"summary": " object | part of | Clock dt | when | order | active\n------------------------------------------------+---------------------------------+----------------------+-------------------+-------+-------\ndefault_neurons_stateupdater (StateUpdater) | default_neurons (NeuronGroup) | 100. us (every step) | groups | 0 | yes \noracle_seed_injection (NetworkOperation) | -- | 100. us (every step) | before_thresholds | 0 | yes \ndefault_neurons_spike_thresholder (Thresholder) | default_neurons (NeuronGroup) | 100. us (every step) | thresholds | 0 | yes \nspikemonitor (SpikeMonitor) | spikemonitor (SpikeMonitor) | 100. us (every step) | thresholds | 1 | yes \ndefault_synapses_pre (SynapticPathway) | default_synapses (Synapses) | 100. us (every step) | synapses | -1 | yes \ndefault_neurons_spike_resetter (Resetter) | default_neurons (NeuronGroup) | 100. us (every step) | resets | 0 | yes \noracle_end_state (StateMonitor) | oracle_end_state (StateMonitor) | 100. us (every step) | end | 0 | yes "
|
||||
}
|
||||
@@ -0,0 +1,7 @@
|
||||
{
|
||||
"applied_mv": -44.0,
|
||||
"injections": 1,
|
||||
"margin_mv": 1.0,
|
||||
"requested_global_node": 1381,
|
||||
"spiked_at_zero": true
|
||||
}
|
||||
Reference in New Issue
Block a user