Seal Phase4AF exact short fullgraph author GPU gate and APL integration audit
This commit is contained in:
Digital Drosophila Archive
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{
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"c0": -0.00025935108198051754,
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"cg": 0.004937935295309027,
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"cv": 0.9950124791926823,
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"gd": 0.9801986733067553,
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"metadata": {
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"constant_values_are_double": true,
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"float32_execution_note": "Brian NumPy scalar/array promotion and operation order must be matched separately; double coefficients alone do not assert float64 intermediate array arithmetic.",
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"g_expression": "gd * old_g",
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"hex": {
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"c0": "-0x1.0ff306a505980p-12",
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"cg": "0x1.439cce9a65d5bp-8",
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"cv": "0x1.fd7246927d28bp-1",
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"gd": "0x1.f5dc99badec5bp-1",
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"reset": "-0x1.a9fbe76c8b43ap-5",
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"seed_volt": "-0x1.6872b020c49bap-5",
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"threshold": "-0x1.70a3d70a3d70ap-5"
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},
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"names": {
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"c0": "_lio_8",
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"cg": "_lio_9",
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"cv": "_lio_10",
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"gd": "_lio_2"
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},
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"provenance": {
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"c0": {
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"code_object": "default_neurons_stateupdater_codeobject_1",
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"name": "_lio_8",
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"namespace_dtype": "float64",
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"source": "CodeObject.namespace"
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},
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"cg": {
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"code_object": "default_neurons_stateupdater_codeobject_1",
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"name": "_lio_9",
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"namespace_dtype": "float64",
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"source": "CodeObject.namespace"
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},
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"cv": {
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"code_object": "default_neurons_stateupdater_codeobject_1",
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"name": "_lio_10",
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"namespace_dtype": "float64",
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"source": "CodeObject.namespace"
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},
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"gd": {
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"code_object": "default_neurons_stateupdater_codeobject_1",
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"name": "_lio_2",
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"namespace_dtype": "float64",
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"source": "CodeObject.namespace"
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},
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"reset": {
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"code_object": "default_neurons_spike_resetter_codeobject_1",
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"name": "v_rst",
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"namespace_dtype": "float64",
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"source": "CodeObject.namespace"
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},
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"seed_volt": {
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"source": "common request interface: unchanged v_th + 1 mV"
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},
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"threshold": {
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"code_object": "default_neurons_spike_thresholder_codeobject_1",
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"name": "v_th",
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"namespace_dtype": "float64",
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"source": "CodeObject.namespace"
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}
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},
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"units": "SI volts and dimensionless coefficients",
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"voltage_expression": "c0 + ((cg * old_g) + (cv * old_v))"
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},
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"reset": -0.052000000000000005,
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"seed_volt": -0.044,
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"threshold": -0.045
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}
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@@ -0,0 +1,116 @@
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[
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{
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"active": true,
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"code_objects": [],
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"name": "default_neurons",
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"order": 0,
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"type": "NeuronGroup",
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"when": "start"
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},
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{
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"active": true,
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"code_objects": [],
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"name": "default_synapses",
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"order": 0,
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"type": "Synapses",
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"when": "start"
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},
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{
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"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",
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"active": true,
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"code_objects": [
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{
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"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 v = _array_default_neurons_v.copy()\n dt = _array_defaultclock_dt[0]\n g = _array_default_neurons_g.copy()\n not_refractory = _array_default_neurons_not_refractory.copy()\n t = _array_defaultclock_t[0]\n rfc = _array_default_neurons_rfc\n lastspike = _array_default_neurons_lastspike\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_not_refractory[:] = not_refractory\n _array_default_neurons_g[:] = g\n _array_default_neurons_v[:] = v\n",
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"name": "default_neurons_stateupdater_codeobject"
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}
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],
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"name": "default_neurons_stateupdater",
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"order": 0,
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"type": "StateUpdater",
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"when": "groups"
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},
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{
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"active": true,
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"code_objects": [],
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||||
"name": "oracle_common_requests",
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"order": 0,
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"type": "NetworkOperation",
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"when": "before_thresholds"
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},
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{
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"abstract_code": "_cond = (v > v_th) and not_refractory",
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"active": true,
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"code_objects": [
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{
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"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 not_refractory = _array_default_neurons_not_refractory\n v = _array_default_neurons_v\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",
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"name": "default_neurons_spike_thresholder_codeobject"
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}
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],
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"name": "default_neurons_spike_thresholder",
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"order": 0,
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"type": "Thresholder",
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"when": "thresholds"
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},
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{
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"abstract_code": "_to_record_i = _source_i\n_to_record_t = _source_t",
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"active": true,
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"code_objects": [
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{
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"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_t = _array_defaultclock_t[0]\n _source_i = _array_default_neurons_i[_idx]\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",
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"name": "spikemonitor_codeobject"
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}
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],
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"name": "spikemonitor",
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"order": 1,
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"type": "SpikeMonitor",
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"when": "thresholds"
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},
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{
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"abstract_code": "g += w\n",
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"active": true,
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"code_objects": [
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{
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"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",
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"name": "default_synapses_pre_push_spikes"
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},
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{
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"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 not_refractory = _array_default_neurons_not_refractory[_postsynaptic_idx]\n w = _array_default_synapses_w[_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",
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"name": "default_synapses_pre_codeobject"
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}
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],
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"name": "default_synapses_pre",
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||||
"order": -1,
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"type": "SynapticPathway",
|
||||
"when": "synapses"
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||||
},
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||||
{
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||||
"abstract_code": "v = v_rst; w = 0; g = 0 * mV",
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"active": true,
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"code_objects": [
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{
|
||||
"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_v[_idx] = v\n _array_default_neurons_g[_idx] = g\n",
|
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"name": "default_neurons_spike_resetter_codeobject"
|
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}
|
||||
],
|
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"name": "default_neurons_spike_resetter",
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"order": 0,
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"type": "Resetter",
|
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"when": "resets"
|
||||
},
|
||||
{
|
||||
"active": true,
|
||||
"code_objects": [],
|
||||
"name": "oracle_streaming_end",
|
||||
"order": 0,
|
||||
"type": "NetworkOperation",
|
||||
"when": "end"
|
||||
},
|
||||
{
|
||||
"active": true,
|
||||
"code_objects": [],
|
||||
"name": "zz_fullgraph_queue_installer",
|
||||
"order": 1000000,
|
||||
"type": "QueueInstaller",
|
||||
"when": "end"
|
||||
}
|
||||
]
|
||||
@@ -0,0 +1,15 @@
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{
|
||||
"codegen": "numpy",
|
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"packages": {
|
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"brian2": "2.5.1",
|
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"cython": "0.29.33",
|
||||
"numpy": "1.22.3",
|
||||
"pandas": "1.4.3",
|
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"pyarrow": "11.0.0",
|
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"scipy": "1.8.1",
|
||||
"sympy": "1.12"
|
||||
},
|
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"platform": "Linux-5.15.0-194-generic-x86_64-with-glibc2.35",
|
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"precision": "float64",
|
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"python": "3.10.12 (main, Aug 31 2026, 10:18:17) [GCC 11.4.0]"
|
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}
|
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@@ -0,0 +1,116 @@
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[
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{
|
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"active": true,
|
||||
"code_objects": [],
|
||||
"name": "default_neurons",
|
||||
"order": 0,
|
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"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 v = _array_default_neurons_v.copy()\n dt = _array_defaultclock_dt[0]\n g = _array_default_neurons_g.copy()\n not_refractory = _array_default_neurons_not_refractory.copy()\n t = _array_defaultclock_t[0]\n rfc = _array_default_neurons_rfc\n lastspike = _array_default_neurons_lastspike\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_not_refractory[:] = not_refractory\n _array_default_neurons_g[:] = g\n _array_default_neurons_v[:] = v\n",
|
||||
"name": "default_neurons_stateupdater_codeobject_1"
|
||||
}
|
||||
],
|
||||
"name": "default_neurons_stateupdater",
|
||||
"order": 0,
|
||||
"type": "StateUpdater",
|
||||
"when": "groups"
|
||||
},
|
||||
{
|
||||
"active": true,
|
||||
"code_objects": [],
|
||||
"name": "oracle_common_requests",
|
||||
"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 not_refractory = _array_default_neurons_not_refractory\n v = _array_default_neurons_v\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"
|
||||
}
|
||||
],
|
||||
"name": "default_neurons_spike_thresholder",
|
||||
"order": 0,
|
||||
"type": "Thresholder",
|
||||
"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_t = _array_defaultclock_t[0]\n _source_i = _array_default_neurons_i[_idx]\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_1"
|
||||
}
|
||||
],
|
||||
"name": "spikemonitor",
|
||||
"order": 1,
|
||||
"type": "SpikeMonitor",
|
||||
"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"
|
||||
},
|
||||
{
|
||||
"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 not_refractory = _array_default_neurons_not_refractory[_postsynaptic_idx]\n w = _array_default_synapses_w[_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"
|
||||
}
|
||||
],
|
||||
"name": "default_synapses_pre",
|
||||
"order": -1,
|
||||
"type": "SynapticPathway",
|
||||
"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_v[_idx] = v\n _array_default_neurons_g[_idx] = g\n",
|
||||
"name": "default_neurons_spike_resetter_codeobject_1"
|
||||
}
|
||||
],
|
||||
"name": "default_neurons_spike_resetter",
|
||||
"order": 0,
|
||||
"type": "Resetter",
|
||||
"when": "resets"
|
||||
},
|
||||
{
|
||||
"active": true,
|
||||
"code_objects": [],
|
||||
"name": "oracle_streaming_end",
|
||||
"order": 0,
|
||||
"type": "NetworkOperation",
|
||||
"when": "end"
|
||||
},
|
||||
{
|
||||
"active": true,
|
||||
"code_objects": [],
|
||||
"name": "zz_fullgraph_queue_installer",
|
||||
"order": 1000000,
|
||||
"type": "QueueInstaller",
|
||||
"when": "end"
|
||||
}
|
||||
]
|
||||
@@ -0,0 +1,47 @@
|
||||
{
|
||||
"apl_overlay": false,
|
||||
"author_sha256": "fc45837d7122c6ce2a7f3f2f23c515992e4b232aadb919efabb72337fac88e4e",
|
||||
"budget_limit_bytes": 16106127360,
|
||||
"budget_root": "/data/digital-drosophila/experiments/phase4af-author-fullgraph",
|
||||
"common_interface_preserved": true,
|
||||
"graph_hashes": {
|
||||
"completeness.csv": "fb9033398abb7585ae63472ced9d8c8cab787f69965dc9ce5fa409ab105bc1bc",
|
||||
"connectivity.parquet": "1362c1102b74f5552f4b01fca956574fd6252f749e31493c4a00a1bc9eab00b3",
|
||||
"dst.npy": "ce20f7433f78442c717ad2a7b5394cf4a3b109d990b4be0788040b7b0f4ed150",
|
||||
"edge_id.npy": "49260615ff2b6432ce3dea9ce2c7ab8f83d06c2fb7491e58e08355fcedf86a30",
|
||||
"nodes.npy": "5b511a98e8fbf8d65bbc70b93e75ecae19366f650b7842a45611bfad62ed83dc",
|
||||
"ptr.npy": "fe43420f11e6242a11f8199ae7f097cab4b8a6db181d36f2a46b9e46670acbb4",
|
||||
"signed_raw.npy": "f9884ccb8930b32420b27c69271df78034a8350fe5a5c9b76a63c259268efc09",
|
||||
"src.npy": "bfd625ce690fc21eb0a8b9dede831688ab73b789045ba83ddf4baeefeddf1fc3"
|
||||
},
|
||||
"poi_used": false,
|
||||
"sealed_ae_oracle_sha256": "32eb1c42383068ce52701d2139a376ce155ad7072cde019949f8ca2d55492409",
|
||||
"source_order": "canonical CSR; local edge index equals original edge_id",
|
||||
"spec": {
|
||||
"all_requests_at_tick": 0,
|
||||
"apl_overlay": false,
|
||||
"budget_root": "/data/digital-drosophila/experiments/phase4af-author-fullgraph",
|
||||
"dt_ms": 0.1,
|
||||
"duration_ms": 10.0,
|
||||
"graph_dir": "/data/digital-drosophila/experiments/phase4af-author-fullgraph/graph",
|
||||
"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
|
||||
},
|
||||
"name": "no_input",
|
||||
"output_budget_bytes": 16106127360,
|
||||
"precision": "float64",
|
||||
"seed_nodes": [],
|
||||
"steps": 100,
|
||||
"training": false
|
||||
},
|
||||
"spec_sha256": "fff36581c10c1c31b5e4f438f6d7271effa474afc95f4cbe28887ace0c81d6ca",
|
||||
"training": false
|
||||
}
|
||||
@@ -0,0 +1,28 @@
|
||||
{
|
||||
"complete_marker": "summary.json with complete=true; partial memmaps alone are not a completed trial",
|
||||
"event_file": "events.bin",
|
||||
"event_order": "tick then canonical neuron_idx",
|
||||
"event_record": [
|
||||
[
|
||||
"step",
|
||||
"<i4"
|
||||
],
|
||||
[
|
||||
"neuron_idx",
|
||||
"<i4"
|
||||
]
|
||||
],
|
||||
"g_file": "g-history.float64.npy",
|
||||
"history_shape": [
|
||||
100,
|
||||
166700
|
||||
],
|
||||
"queue_file": "queue.jsonl",
|
||||
"queue_joint_bytes": "b'phase4af-queue-v1\\0' + struct.pack('<qq',tick,count) + all ordered <i8 edge IDs + all uint8 acceptance bits",
|
||||
"queue_separate_hashes": "SHA256 of each pure byte sequence without header",
|
||||
"ref_dtype": "little-endian int32",
|
||||
"ref_file": "ref-history.int32.npy",
|
||||
"v_file": "v-history.float64.npy",
|
||||
"v_g_dtype": "little-endian float64",
|
||||
"voltage_unit": "SI volt"
|
||||
}
|
||||
@@ -0,0 +1,34 @@
|
||||
{
|
||||
"membrane_tau_ms": {
|
||||
"author": 20.0,
|
||||
"case": 20.0
|
||||
},
|
||||
"refractory_ms": {
|
||||
"author": 2.2,
|
||||
"case": 2.2
|
||||
},
|
||||
"reset_potential_mv": {
|
||||
"author": -52.0,
|
||||
"case": -52.0
|
||||
},
|
||||
"resting_potential_mv": {
|
||||
"author": -52.0,
|
||||
"case": -52.0
|
||||
},
|
||||
"synaptic_delay_ms": {
|
||||
"author": 1.8,
|
||||
"case": 1.8
|
||||
},
|
||||
"synaptic_tau_ms": {
|
||||
"author": 5.0,
|
||||
"case": 5.0
|
||||
},
|
||||
"threshold_mv": {
|
||||
"author": -45.0,
|
||||
"case": -45.0
|
||||
},
|
||||
"w_syn_mv_per_anatomical_synapse": {
|
||||
"author": 0.275,
|
||||
"case": 0.275
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,18 @@
|
||||
{
|
||||
"acceptance_observed_after_thresholds_before_synaptic_writes": true,
|
||||
"advance_calls": 100,
|
||||
"all_other_queue_methods_forwarded": true,
|
||||
"due_count_matches_presynaptic_spikes_and_original_outdegrees": true,
|
||||
"edge_id_identity_verified_for_all_edges": true,
|
||||
"fullgraph_unwrapped_repeat_performed": false,
|
||||
"hash_header_hex": "70686173653461662d71756575652d763100",
|
||||
"installations": [
|
||||
"default_synapses_pre_codeobject",
|
||||
"default_synapses_pre_codeobject_1"
|
||||
],
|
||||
"limit": "Current full-graph streaming proxy is audited by forwarding logic and per-tick counts; no separate unwrapped full-graph run is claimed.",
|
||||
"original_order_not_sorted_or_filtered": true,
|
||||
"peek_calls": 100,
|
||||
"prior_evidence": "Phase4AE exact wrapped/unwrapped checks; current bounded-hash adapter preserves the same forwarding contract",
|
||||
"same_peek_object_returned": true
|
||||
}
|
||||
@@ -0,0 +1,100 @@
|
||||
{"accepted_count": 0, "accepted_mask_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "count": 0, "joint_sha256": "c968219c6747392b239a8442ad552e67098f80d3b2fc8c6ba74f96eaf690f4c1", "ordered_edge_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "tick": 0}
|
||||
{"accepted_count": 0, "accepted_mask_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "count": 0, "joint_sha256": "e294b8d71b1420e298c2d72e432faa0a69f04ca4d36d874a98911b4541c44a99", "ordered_edge_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "tick": 1}
|
||||
{"accepted_count": 0, "accepted_mask_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "count": 0, "joint_sha256": "7123f7609b7cc6b2e97616005c3950e779dcb75a17fe00d6ec99e17a5556f3fd", "ordered_edge_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "tick": 2}
|
||||
{"accepted_count": 0, "accepted_mask_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "count": 0, "joint_sha256": "074038cc65b6a42a3b378d6a1449888560d4fc90bb29a02faa16ebaf0a1c738d", "ordered_edge_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "tick": 3}
|
||||
{"accepted_count": 0, "accepted_mask_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "count": 0, "joint_sha256": "08e047ac443d78be53d15e8a4e73647ce7dc8b64a53d53f64066caea97cc3396", "ordered_edge_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "tick": 4}
|
||||
{"accepted_count": 0, "accepted_mask_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "count": 0, "joint_sha256": "6cc34d52eff1dc4a015a905972653ee936c73cd034f72774d9636b06d45cdd63", "ordered_edge_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "tick": 5}
|
||||
{"accepted_count": 0, "accepted_mask_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "count": 0, "joint_sha256": "23e1a6fa18b3e97b889ca9b9aa2b69efd9aca7bef1b1ec4ea808631bef791801", "ordered_edge_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "tick": 6}
|
||||
{"accepted_count": 0, "accepted_mask_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "count": 0, "joint_sha256": "e06a21003db51f9cb1827cc5d48deaba660bb5e8bc6f3c06991c0242aa795b00", "ordered_edge_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "tick": 7}
|
||||
{"accepted_count": 0, "accepted_mask_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "count": 0, "joint_sha256": "edac9b28a62d4b86ae0c5b0a2b48aa782945cfdc94e65ed1440e7a5a6d219d75", "ordered_edge_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "tick": 8}
|
||||
{"accepted_count": 0, "accepted_mask_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "count": 0, "joint_sha256": "774f88fca2c65aa72249df7a0f7bdb392cf218bc279e05d653b18124a27b66c2", "ordered_edge_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "tick": 9}
|
||||
{"accepted_count": 0, "accepted_mask_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "count": 0, "joint_sha256": "afeec73ef25ffb8e49aa6b858c2c02a06650811f023089afab529d8becc74948", "ordered_edge_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "tick": 10}
|
||||
{"accepted_count": 0, "accepted_mask_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "count": 0, "joint_sha256": "c32e5a8b81dacf319969d8c8433fb93bcd44ad90fa6d0d9ead07a3fa28b78cfe", "ordered_edge_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "tick": 11}
|
||||
{"accepted_count": 0, "accepted_mask_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "count": 0, "joint_sha256": "ec69cb4e6f3e14414cde71621c9176bbb0a8f548dc8f34f4c66232348cef6fcb", "ordered_edge_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "tick": 12}
|
||||
{"accepted_count": 0, "accepted_mask_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "count": 0, "joint_sha256": "42b78ffcb666e6a12e49964ff5bcc0cd5ad49b8ae7dfeeb18888293164ad408e", "ordered_edge_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "tick": 13}
|
||||
{"accepted_count": 0, "accepted_mask_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "count": 0, "joint_sha256": "076242d2543c0bf8f88b6f6c33af5aefc502c92e2297cd062077c74a7d3ead82", "ordered_edge_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "tick": 14}
|
||||
{"accepted_count": 0, "accepted_mask_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "count": 0, "joint_sha256": "fafb364e0138fb24c2c107607b618437955e09556c51de9e4a8334e11f08eee9", "ordered_edge_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "tick": 15}
|
||||
{"accepted_count": 0, "accepted_mask_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "count": 0, "joint_sha256": "785abe13dcf8e20f28f7316f940382d38a96adeaa94819814a274c1fe294952f", "ordered_edge_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "tick": 16}
|
||||
{"accepted_count": 0, "accepted_mask_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "count": 0, "joint_sha256": "16cdc730f8d0f7d0f7f22a18655f5a48dcb63577cc20955df6da97498bccab8d", "ordered_edge_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "tick": 17}
|
||||
{"accepted_count": 0, "accepted_mask_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "count": 0, "joint_sha256": "18b8429d8fe46d8ff3795f7784d26bde1e9ac21b6c4b88f53ceed2b8842443b8", "ordered_edge_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "tick": 18}
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{"accepted_count": 0, "accepted_mask_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "count": 0, "joint_sha256": "dc51cf7ffbcd533649749d3c0cdbc59213b70dc1834d2bcb1820672196d7ec0d", "ordered_edge_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "tick": 96}
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{"accepted_count": 0, "accepted_mask_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "count": 0, "joint_sha256": "93106d81bc6277fe6a8c63064cdf80f18df02b8d4be16ededd4d5e1fb7045a73", "ordered_edge_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "tick": 97}
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||||
{"accepted_count": 0, "accepted_mask_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "count": 0, "joint_sha256": "4701025f7b08feef96e3b5223148c6abd53882c2f62b6c44bf3165054688a2e1", "ordered_edge_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "tick": 98}
|
||||
{"accepted_count": 0, "accepted_mask_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "count": 0, "joint_sha256": "4ea3b36ccf7a276f40d127d33fc103f8a5d24b22579c23a8ebb0699f37c2115e", "ordered_edge_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "tick": 99}
|
||||
@@ -0,0 +1 @@
|
||||
tick,neuron_idx,attempted,accepted,rejected
|
||||
|
@@ -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_common_requests (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_streaming_end (NetworkOperation) | -- | 100. us (every step) | end | 0 | yes \nzz_fullgraph_queue_installer (QueueInstaller) | -- | 100. us (every step) | end | 1000000 | yes "
|
||||
}
|
||||
@@ -0,0 +1,34 @@
|
||||
{
|
||||
"accepted_arrivals": 0,
|
||||
"applicable_requests": 0,
|
||||
"backend": "Brian2 2.5.1 numpy",
|
||||
"complete": true,
|
||||
"completed_ticks": 100,
|
||||
"due_arrivals": 0,
|
||||
"edges": 25582938,
|
||||
"events_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855",
|
||||
"name": "no_input",
|
||||
"neurons": 166700,
|
||||
"no_apl_overlay": true,
|
||||
"no_poi": true,
|
||||
"no_training": true,
|
||||
"nodes": 166700,
|
||||
"output_budget_bytes": 16106127360,
|
||||
"output_budget_root": "/data/digital-drosophila/experiments/phase4af-author-fullgraph",
|
||||
"output_bytes_before_summary": 1355602439,
|
||||
"pass_all": true,
|
||||
"pass_all_scope": "CPU input, streaming, and internal self-checks only; GPU equivalence is not assessed here",
|
||||
"pending_arrivals_limit": "Queue arrivals beyond the final recorded tick are outside this comparison window.",
|
||||
"precision": "float64",
|
||||
"queue_sha256": "487cd06e47971aef19030eba81cd910a252354752fe9d275857d832420f28c86",
|
||||
"ref_rejected_requests": 0,
|
||||
"requests": 0,
|
||||
"scope": "Only this fixed short numerical trajectory; not olfactory CAL, long-run equivalence, physiological validation, or learning.",
|
||||
"single_continuous_run": true,
|
||||
"source_and_graph_inputs_unchanged": true,
|
||||
"spikes": 0,
|
||||
"steps": 100,
|
||||
"steps_completed": 100,
|
||||
"steps_expected": 100,
|
||||
"weights_sha256": "462839ffc3feb8f6c278044488082b1c8e410e7f23229d6b5e29d1b7042416a1"
|
||||
}
|
||||
@@ -0,0 +1,100 @@
|
||||
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|
||||
{"accepted_arrivals": 0, "applicable_requests": 0, "due_arrivals": 0, "event_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "ref_rejected_requests": 0, "requests": 0, "spikes": 0, "tick": 1}
|
||||
{"accepted_arrivals": 0, "applicable_requests": 0, "due_arrivals": 0, "event_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "ref_rejected_requests": 0, "requests": 0, "spikes": 0, "tick": 2}
|
||||
{"accepted_arrivals": 0, "applicable_requests": 0, "due_arrivals": 0, "event_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "ref_rejected_requests": 0, "requests": 0, "spikes": 0, "tick": 3}
|
||||
{"accepted_arrivals": 0, "applicable_requests": 0, "due_arrivals": 0, "event_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "ref_rejected_requests": 0, "requests": 0, "spikes": 0, "tick": 4}
|
||||
{"accepted_arrivals": 0, "applicable_requests": 0, "due_arrivals": 0, "event_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "ref_rejected_requests": 0, "requests": 0, "spikes": 0, "tick": 5}
|
||||
{"accepted_arrivals": 0, "applicable_requests": 0, "due_arrivals": 0, "event_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "ref_rejected_requests": 0, "requests": 0, "spikes": 0, "tick": 6}
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||||
{"accepted_arrivals": 0, "applicable_requests": 0, "due_arrivals": 0, "event_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "ref_rejected_requests": 0, "requests": 0, "spikes": 0, "tick": 7}
|
||||
{"accepted_arrivals": 0, "applicable_requests": 0, "due_arrivals": 0, "event_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "ref_rejected_requests": 0, "requests": 0, "spikes": 0, "tick": 8}
|
||||
{"accepted_arrivals": 0, "applicable_requests": 0, "due_arrivals": 0, "event_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "ref_rejected_requests": 0, "requests": 0, "spikes": 0, "tick": 9}
|
||||
{"accepted_arrivals": 0, "applicable_requests": 0, "due_arrivals": 0, "event_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "ref_rejected_requests": 0, "requests": 0, "spikes": 0, "tick": 10}
|
||||
{"accepted_arrivals": 0, "applicable_requests": 0, "due_arrivals": 0, "event_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "ref_rejected_requests": 0, "requests": 0, "spikes": 0, "tick": 11}
|
||||
{"accepted_arrivals": 0, "applicable_requests": 0, "due_arrivals": 0, "event_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "ref_rejected_requests": 0, "requests": 0, "spikes": 0, "tick": 12}
|
||||
{"accepted_arrivals": 0, "applicable_requests": 0, "due_arrivals": 0, "event_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "ref_rejected_requests": 0, "requests": 0, "spikes": 0, "tick": 13}
|
||||
{"accepted_arrivals": 0, "applicable_requests": 0, "due_arrivals": 0, "event_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "ref_rejected_requests": 0, "requests": 0, "spikes": 0, "tick": 14}
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|
||||
{"accepted_arrivals": 0, "applicable_requests": 0, "due_arrivals": 0, "event_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "ref_rejected_requests": 0, "requests": 0, "spikes": 0, "tick": 93}
|
||||
{"accepted_arrivals": 0, "applicable_requests": 0, "due_arrivals": 0, "event_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "ref_rejected_requests": 0, "requests": 0, "spikes": 0, "tick": 94}
|
||||
{"accepted_arrivals": 0, "applicable_requests": 0, "due_arrivals": 0, "event_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "ref_rejected_requests": 0, "requests": 0, "spikes": 0, "tick": 95}
|
||||
{"accepted_arrivals": 0, "applicable_requests": 0, "due_arrivals": 0, "event_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "ref_rejected_requests": 0, "requests": 0, "spikes": 0, "tick": 96}
|
||||
{"accepted_arrivals": 0, "applicable_requests": 0, "due_arrivals": 0, "event_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "ref_rejected_requests": 0, "requests": 0, "spikes": 0, "tick": 97}
|
||||
{"accepted_arrivals": 0, "applicable_requests": 0, "due_arrivals": 0, "event_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "ref_rejected_requests": 0, "requests": 0, "spikes": 0, "tick": 98}
|
||||
{"accepted_arrivals": 0, "applicable_requests": 0, "due_arrivals": 0, "event_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", "ref_rejected_requests": 0, "requests": 0, "spikes": 0, "tick": 99}
|
||||
Reference in New Issue
Block a user