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inhib.go
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inhib.go
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// Copyright (c) 2019, The Emergent Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.
/*
inhib: This simulation explores how inhibitory interneurons can dynamically
control overall activity levels within the network, by providing both
feedforward and feedback inhibition to excitatory pyramidal neurons.
*/
package main
//go:generate core generate -add-types
import (
"fmt"
"math/rand"
"os"
"reflect"
"cogentcore.org/core/base/mpi"
"cogentcore.org/core/base/randx"
"cogentcore.org/core/core"
"cogentcore.org/core/icons"
"cogentcore.org/core/math32"
"cogentcore.org/core/tensor"
"cogentcore.org/core/tensor/table"
"github.com/emer/axon/v2/axon"
"github.com/emer/emergent/v2/econfig"
"github.com/emer/emergent/v2/egui"
"github.com/emer/emergent/v2/elog"
"github.com/emer/emergent/v2/emer"
"github.com/emer/emergent/v2/estats"
"github.com/emer/emergent/v2/etime"
"github.com/emer/emergent/v2/looper"
"github.com/emer/emergent/v2/netview"
"github.com/emer/emergent/v2/patgen"
"github.com/emer/emergent/v2/paths"
"github.com/emer/emergent/v2/relpos"
)
func main() {
sim := &Sim{}
sim.New()
sim.ConfigAll()
if sim.Config.GUI {
sim.RunGUI()
} else {
sim.RunNoGUI()
}
}
// see params.go for params
// Sim encapsulates the entire simulation model, and we define all the
// functionality as methods on this struct. This structure keeps all relevant
// state information organized and available without having to pass everything around
// as arguments to methods, and provides the core GUI interface (note the view tags
// for the fields which provide hints to how things should be displayed).
type Sim struct {
// simulation configuration parameters -- set by .toml config file and / or args
Config Config
// the network -- click to view / edit parameters for layers, paths, etc
Net *axon.Network `view:"no-inline"`
// all parameter management
Params emer.NetParams `view:"inline"`
// contains looper control loops for running sim
Loops *looper.Manager `view:"no-inline"`
// contains computed statistic values
Stats estats.Stats
// Contains all the logs and information about the logs.'
Logs elog.Logs
// the training patterns to use
Pats *table.Table `view:"no-inline"`
// axon timing parameters and state
Context axon.Context
// netview update parameters
ViewUpdate netview.ViewUpdate `view:"inline"`
// manages all the gui elements
GUI egui.GUI `view:"-"`
// a list of random seeds to use for each run
RandSeeds randx.Seeds `view:"-"`
}
// New creates new blank elements and initializes defaults
func (ss *Sim) New() {
econfig.Config(&ss.Config, "config.toml")
ss.Net = &axon.Network{}
ss.Params.Config(ParamSets, ss.Config.Params.Sheet, ss.Config.Params.Tag, ss.Net)
ss.Stats.Init()
ss.Pats = &table.Table{}
ss.RandSeeds.Init(100) // max 100 runs
ss.InitRandSeed(0)
ss.Context.Defaults()
}
////////////////////////////////////////////////////////////////////////////////////////////
// Configs
// ConfigAll configures all the elements using the standard functions
func (ss *Sim) ConfigAll() {
ss.ConfigPats()
ss.ConfigNet(ss.Net)
ss.ConfigLogs()
ss.ConfigLoops()
if ss.Config.Params.SaveAll {
ss.Config.Params.SaveAll = false
ss.Net.SaveParamsSnapshot(&ss.Params.Params, &ss.Config, ss.Config.Params.Good)
os.Exit(0)
}
}
func (ss *Sim) ConfigPats() {
dt := ss.Pats
dt.SetMetaData("name", "TrainPats")
dt.SetMetaData("desc", "Training patterns")
dt.AddStringColumn("Name")
dt.AddFloat32TensorColumn("Input", []int{10, 10}, "Y", "X")
dt.SetNumRows(10)
pc := dt.Columns[1].(*tensor.Float32)
patgen.PermutedBinaryRows(pc, int(ss.Config.Env.InputPct), 1, 0)
for i, v := range pc.Values {
if v > 0.5 {
pc.Values[i] = 0.5 + 0.5*rand.Float32()
}
}
}
func (ss *Sim) ReConfigNet() {
ss.Net.DeleteAll()
ss.ConfigNet(ss.Net)
// ss.GUI.NetView.Config()
}
func LayNm(n int) string {
return fmt.Sprintf("Layer%d", n)
}
func InhNm(n int) string {
return fmt.Sprintf("Inhib%d", n)
}
func LayByNm(net *axon.Network, n int) *axon.Layer {
return net.AxonLayerByName(LayNm(n))
}
func InhByNm(net *axon.Network, n int) *axon.Layer {
return net.AxonLayerByName(InhNm(n))
}
func (ss *Sim) ConfigNet(net *axon.Network) {
ctx := &ss.Context
net.InitName(net, "Inhib")
net.SetMaxData(ctx, 1)
net.SetRandSeed(ss.RandSeeds[0]) // init new separate random seed, using run = 0
sz := ss.Config.Params.HidSize
inlay := net.AddLayer2D(LayNm(0), sz.Y, sz.X, axon.InputLayer)
_ = inlay
for hi := 1; hi <= ss.Config.Params.NLayers; hi++ {
net.AddLayer2D(LayNm(hi), sz.Y, sz.X, axon.SuperLayer)
net.AddLayer2D(InhNm(hi), sz.Y, 2, axon.SuperLayer).AddClass("InhibLay")
}
full := paths.NewFull()
rndcut := paths.NewUniformRand()
rndcut.PCon = 0.1
for hi := 1; hi <= ss.Config.Params.NLayers; hi++ {
ll := LayByNm(net, hi-1)
tl := LayByNm(net, hi)
il := InhByNm(net, hi)
net.ConnectLayers(ll, tl, full, axon.ForwardPath).AddClass("Excite")
net.ConnectLayers(ll, il, full, axon.ForwardPath).AddClass("ToInhib")
net.ConnectLayers(tl, il, full, axon.BackPath).AddClass("ToInhib")
net.ConnectLayers(il, tl, full, axon.InhibPath)
net.ConnectLayers(il, il, full, axon.InhibPath)
// if hi > 1 {
// net.ConnectLayers(inlay, tl, rndcut, axon.ForwardPath).AddClass("RandSc")
// }
tl.SetRelPos(relpos.Rel{Rel: relpos.Above, Other: ll.Name(), YAlign: relpos.Front, XAlign: relpos.Middle})
il.SetRelPos(relpos.Rel{Rel: relpos.RightOf, Other: tl.Name(), YAlign: relpos.Front, Space: 1})
if hi < ss.Config.Params.NLayers {
nl := LayByNm(net, hi+1)
net.ConnectLayers(nl, il, full, axon.ForwardPath).AddClass("ToInhib")
net.ConnectLayers(tl, nl, full, axon.ForwardPath).AddClass("Excite")
net.ConnectLayers(nl, tl, full, axon.BackPath).AddClass("Excite")
}
}
net.Build(ctx)
net.Defaults()
net.Defaults()
ss.ApplyParams()
ss.Net.InitWts(ctx)
}
func (ss *Sim) ApplyParams() {
ss.Params.SetAll()
if ss.Config.Params.Network != nil {
ss.Params.SetNetworkMap(ss.Net, ss.Config.Params.Network)
}
}
////////////////////////////////////////////////////////////////////////////////
// Init, utils
// Init restarts the run, and initializes everything, including network weights
// and resets the epoch log table
func (ss *Sim) Init() {
if ss.Config.GUI {
ss.Stats.SetString("RunName", ss.Params.RunName(0)) // in case user interactively changes tag
}
ss.Loops.ResetCounters()
ss.InitRandSeed(0)
// ss.ConfigEnv() // re-config env just in case a different set of patterns was
// selected or patterns have been modified etc
ss.GUI.StopNow = false
ss.ApplyParams()
ss.NewRun()
ss.ViewUpdate.Update()
ss.ViewUpdate.RecordSyns()
}
// InitRandSeed initializes the random seed based on current training run number
func (ss *Sim) InitRandSeed(run int) {
ss.RandSeeds.Set(run)
ss.RandSeeds.Set(run, &ss.Net.Rand)
}
// ConfigLoops configures the control loops: Training, Testing
func (ss *Sim) ConfigLoops() {
man := looper.NewManager()
net := ss.Net
time := &ss.Context
man.AddStack(etime.Test).
AddTime(etime.Epoch, 1).
AddTime(etime.Trial, 10).
AddTime(etime.Cycle, 200)
axon.LooperStdPhases(man, &ss.Context, ss.Net, 150, 199) // plus phase timing
for m, _ := range man.Stacks {
man.Stacks[m].Loops[etime.Cycle].Main.Add("Cycle", func() {
net.Cycle(time)
time.CycleInc()
})
}
for m, loops := range man.Stacks {
curMode := m // For closures.
for _, loop := range loops.Loops {
loop.OnStart.Add("SetTimeVal", func() {
time.Mode = curMode
})
}
}
for m, _ := range man.Stacks {
mode := m // For closures
stack := man.Stacks[mode]
stack.Loops[etime.Trial].OnStart.Add("ApplyInputs", func() {
ss.ApplyInputs()
})
stack.Loops[etime.Trial].OnEnd.Add("StatCounters", ss.StatCounters)
stack.Loops[etime.Trial].OnEnd.Add("TrialStats", ss.TrialStats)
}
/////////////////////////////////////////////
// Logging
man.AddOnEndToAll("Log", ss.Log)
axon.LooperResetLogBelow(man, &ss.Logs)
////////////////////////////////////////////
// GUI
if !ss.Config.GUI {
if ss.Config.Log.NetData {
man.GetLoop(etime.Test, etime.Trial).Main.Add("NetDataRecord", func() {
ss.GUI.NetDataRecord(ss.ViewUpdate.Text)
})
}
} else {
axon.LooperUpdateNetView(man, &ss.ViewUpdate, ss.Net, ss.NetViewCounters)
axon.LooperUpdatePlots(man, &ss.GUI)
}
if ss.Config.Debug {
mpi.Println(man.DocString())
}
ss.Loops = man
}
// ApplyInputs applies input patterns from given environment.
// It is good practice to have this be a separate method with appropriate
// args so that it can be used for various different contexts
// (training, testing, etc).
func (ss *Sim) ApplyInputs() {
ctx := &ss.Context
net := ss.Net
net.InitExt(ctx) // clear any existing inputs -- not strictly necessary if always
ly := net.AxonLayerByName("Layer0")
pat := ss.Pats.Tensor("Input", rand.Intn(10))
ly.ApplyExt(ctx, 0, pat)
net.ApplyExts(ctx)
}
// NewRun intializes a new run of the model, using the TrainEnv.Run counter
// for the new run value
func (ss *Sim) NewRun() {
ctx := &ss.Context
ss.InitRandSeed(0)
ctx.Reset()
ctx.Mode = etime.Test
ss.Net.InitWts(ctx)
ss.InitStats()
ss.StatCounters()
ss.Logs.ResetLog(etime.Test, etime.Epoch)
}
////////////////////////////////////////////////////////////////////////////////////////////
// Stats
// InitStats initializes all the statistics.
// called at start of new run
func (ss *Sim) InitStats() {
ss.Stats.SetInt("Run", 0)
}
// StatCounters saves current counters to Stats, so they are available for logging etc
// Also saves a string rep of them for ViewUpdate.Text
func (ss *Sim) StatCounters() {
ctx := &ss.Context
mode := ctx.Mode
ss.Loops.Stacks[mode].CtrsToStats(&ss.Stats)
ss.Stats.SetInt("Cycle", int(ctx.Cycle))
}
func (ss *Sim) NetViewCounters(tm etime.Times) {
if ss.ViewUpdate.View == nil {
return
}
ss.StatCounters()
ss.ViewUpdate.Text = ss.Stats.Print([]string{"Trial", "Cycle"})
}
// TrialStats computes the trial-level statistics.
// Aggregation is done directly from log data.
func (ss *Sim) TrialStats() {
}
//////////////////////////////////////////////////////////////////////////////
// Logging
func (ss *Sim) ConfigLogs() {
ss.Stats.SetString("RunName", ss.Params.RunName(0)) // used for naming logs, stats, etc
ss.Logs.AddCounterItems(etime.Trial, etime.Cycle)
ss.Logs.AddStatStringItem(etime.AllModes, etime.AllTimes, "RunName")
axon.LogAddLayerGeActAvgItems(&ss.Logs, ss.Net, etime.Test, etime.Cycle)
ss.ConfigLogItems()
ss.Logs.PlotItems("Layer1_Act.Avg", "Layer1_SGi") // "Layer1_Gi",
ss.Logs.CreateTables()
ss.Logs.SetContext(&ss.Stats, ss.Net)
// don't plot certain combinations we don't use
// ss.Logs.NoPlot(etime.Train, etime.Cycle)
// ss.Logs.NoPlot(etime.Test, etime.Run)
// note: Analyze not plotted by default
// ss.Logs.SetMeta(etime.Train, etime.Run, "LegendCol", "RunName")
}
func (ss *Sim) ConfigLogItems() {
layers := ss.Net.LayersByType(axon.InputLayer, axon.SuperLayer)
for _, lnm := range layers {
clnm := lnm
ss.Logs.AddItem(&elog.Item{
Name: clnm + "_Spikes",
Type: reflect.Float64,
FixMin: true,
Write: elog.WriteMap{
etime.Scope(etime.Test, etime.Cycle): func(ctx *elog.Context) {
ly := ss.Net.AxonLayerByName(clnm)
ctx.SetFloat32(ly.AvgMaxVarByPool(&ss.Context, "Spike", 0, ctx.Di).Avg)
}}})
ss.Logs.AddItem(&elog.Item{
Name: clnm + "_Gi",
Type: reflect.Float64,
FixMin: true,
Write: elog.WriteMap{
etime.Scope(etime.Test, etime.Cycle): func(ctx *elog.Context) {
ly := ss.Net.AxonLayerByName(clnm)
ctx.SetFloat32(axon.NrnV(&ss.Context, ly.NeurStIndex, 0, axon.Gi))
}}})
ss.Logs.AddItem(&elog.Item{
Name: clnm + "_SGi",
Type: reflect.Float64,
FixMin: true,
Write: elog.WriteMap{
etime.Scope(etime.Test, etime.Cycle): func(ctx *elog.Context) {
ly := ss.Net.AxonLayerByName(clnm)
ctx.SetFloat32(ly.Pool(0, 0).Inhib.Gi)
}}})
ss.Logs.AddItem(&elog.Item{
Name: clnm + "_FFs",
Type: reflect.Float64,
FixMin: true,
Write: elog.WriteMap{
etime.Scope(etime.Test, etime.Cycle): func(ctx *elog.Context) {
ly := ss.Net.AxonLayerByName(clnm)
ctx.SetFloat32(ly.Pool(0, 0).Inhib.FFs)
}}})
ss.Logs.AddItem(&elog.Item{
Name: clnm + "_FBs",
Type: reflect.Float64,
FixMin: true,
Write: elog.WriteMap{
etime.Scope(etime.Test, etime.Cycle): func(ctx *elog.Context) {
ly := ss.Net.AxonLayerByName(clnm)
ctx.SetFloat32(ly.Pool(0, 0).Inhib.FBs)
}}})
ss.Logs.AddItem(&elog.Item{
Name: clnm + "_FSi",
Type: reflect.Float64,
FixMin: true,
Write: elog.WriteMap{
etime.Scope(etime.Test, etime.Cycle): func(ctx *elog.Context) {
ly := ss.Net.AxonLayerByName(clnm)
ctx.SetFloat32(ly.Pool(0, 0).Inhib.FSi)
}}})
ss.Logs.AddItem(&elog.Item{
Name: clnm + "_SSi",
Type: reflect.Float64,
FixMin: true,
Write: elog.WriteMap{
etime.Scope(etime.Test, etime.Cycle): func(ctx *elog.Context) {
ly := ss.Net.AxonLayerByName(clnm)
ctx.SetFloat32(ly.Pool(0, 0).Inhib.SSi)
}}})
ss.Logs.AddItem(&elog.Item{
Name: clnm + "_SSf",
Type: reflect.Float64,
FixMin: true,
Write: elog.WriteMap{
etime.Scope(etime.Test, etime.Cycle): func(ctx *elog.Context) {
ly := ss.Net.AxonLayerByName(clnm)
ctx.SetFloat32(ly.Pool(0, 0).Inhib.SSf)
}}})
ss.Logs.AddItem(&elog.Item{
Name: clnm + "_FSGi",
Type: reflect.Float64,
FixMin: true,
Write: elog.WriteMap{
etime.Scope(etime.Test, etime.Cycle): func(ctx *elog.Context) {
ly := ss.Net.AxonLayerByName(clnm)
ctx.SetFloat32(ly.Pool(0, 0).Inhib.FSGi)
}}})
ss.Logs.AddItem(&elog.Item{
Name: clnm + "_SSGi",
Type: reflect.Float64,
FixMin: true,
Write: elog.WriteMap{
etime.Scope(etime.Test, etime.Cycle): func(ctx *elog.Context) {
ly := ss.Net.AxonLayerByName(clnm)
ctx.SetFloat32(ly.Pool(0, 0).Inhib.SSGi)
}}})
}
}
// Log is the main logging function, handles special things for different scopes
func (ss *Sim) Log(mode etime.Modes, time etime.Times) {
if mode.String() != "Analyze" {
ss.Context.Mode = mode // Also set specifically in a Loop callback.
}
ss.StatCounters()
dt := ss.Logs.Table(mode, time)
if dt == nil {
return
}
row := dt.Rows
switch {
case time == etime.Cycle:
row = ss.Stats.Int("Cycle")
case time == etime.Trial:
row = ss.Stats.Int("Trial")
}
ss.Logs.LogRow(mode, time, row) // also logs to file, etc
}
////////////////////////////////////////////////////////////////////////////////////////////
// Gui
// ConfigGUI configures the Cogent Core GUI interface for this simulation.
func (ss *Sim) ConfigGUI() {
title := "Axon Inhibition Test"
ss.GUI.MakeBody(ss, "inhib", title, `This tests inhibition based on interneurons and inhibition functions. See <a href="https://github.com/emer/emergent">emergent on GitHub</a>.</p>`)
ss.GUI.CycleUpdateInterval = 1 // 10
nv := ss.GUI.AddNetView("NetView")
nv.Params.MaxRecs = 300
nv.SetNet(ss.Net)
ss.ViewUpdate.Config(nv, etime.AlphaCycle, etime.AlphaCycle)
ss.GUI.ViewUpdate = &ss.ViewUpdate
nv.SceneXYZ().Camera.Pose.Pos.Set(0, 1, 2.75) // more "head on" than default which is more "top down"
nv.SceneXYZ().Camera.LookAt(math32.Vec3(0, 0, 0), math32.Vec3(0, 1, 0))
ss.GUI.AddPlots(title, &ss.Logs)
ss.GUI.Body.AddAppBar(func(tb *core.Toolbar) {
ss.GUI.AddToolbarItem(tb, egui.ToolbarItem{Label: "Init", Icon: icons.Update,
Tooltip: "Initialize everything including network weights, and start over. Also applies current params.",
Active: egui.ActiveStopped,
Func: func() {
ss.Init()
ss.GUI.UpdateWindow()
},
})
ss.GUI.AddLooperCtrl(tb, ss.Loops, []etime.Modes{etime.Test})
////////////////////////////////////////////////
core.NewSeparator(tb)
ss.GUI.AddToolbarItem(tb, egui.ToolbarItem{Label: "Reset RunLog",
Icon: icons.Reset,
Tooltip: "Reset the accumulated log of all Runs, which are tagged with the ParamSet used",
Active: egui.ActiveAlways,
Func: func() {
ss.Logs.ResetLog(etime.Train, etime.Run)
ss.GUI.UpdatePlot(etime.Train, etime.Run)
},
})
////////////////////////////////////////////////
core.NewSeparator(tb)
ss.GUI.AddToolbarItem(tb, egui.ToolbarItem{Label: "New Seed",
Icon: icons.Add,
Tooltip: "Generate a new initial random seed to get different results. By default, Init re-establishes the same initial seed every time.",
Active: egui.ActiveAlways,
Func: func() {
ss.RandSeeds.NewSeeds()
},
})
ss.GUI.AddToolbarItem(tb, egui.ToolbarItem{Label: "README",
Icon: "file-markdown",
Tooltip: "Opens your browser on the README file that contains instructions for how to run this model.",
Active: egui.ActiveAlways,
Func: func() {
core.TheApp.OpenURL("https://github.com/emer/axon/blob/master/examples/inhib/README.md")
},
})
})
ss.GUI.FinalizeGUI(false)
}
func (ss *Sim) RunGUI() {
ss.Init()
ss.ConfigGUI()
ss.GUI.Body.RunMainWindow()
}
func (ss *Sim) RunNoGUI() {
if ss.Config.Params.Note != "" {
mpi.Printf("Note: %s\n", ss.Config.Params.Note)
}
runName := ss.Params.RunName(0)
ss.Stats.SetString("RunName", runName) // used for naming logs, stats, etc
netName := ss.Net.Name()
elog.SetLogFile(&ss.Logs, ss.Config.Log.Trial, etime.Test, etime.Trial, "trl", netName, runName)
elog.SetLogFile(&ss.Logs, ss.Config.Log.Epoch, etime.Test, etime.Epoch, "epc", netName, runName)
netdata := ss.Config.Log.NetData
if netdata {
mpi.Printf("Saving NetView data from testing\n")
ss.GUI.InitNetData(ss.Net, 200)
}
ss.Init()
ss.Loops.Run(etime.Test)
ss.Logs.CloseLogFiles()
if netdata {
ss.GUI.SaveNetData(ss.Stats.String("RunName"))
}
}