WpyQwq
643e22ecb9
- 引入 MemoryRouterXL 与 v5/v6 流式多线程训练/编码管线 - 修复 prepare_memory_router_dataset 候选池重建缺陷（mega 家族 3568x 加速，输出逐字节相同） - 修复 v5 被破坏的拒答与多跳标签（train 未知样本 319 -> 16319，multi_hop 平均正例 1.00 -> 2.00） - 同存储预算下 V2-128 v6 逐轴 22/22 通过：Top-1 41.12% -> 94.62%，未知拒答 0.00% -> 100.00% - 记录三条被实测推翻的显然优化（logits_to_keep=1 反而慢 55%、XL 容量未带来收益） - 记忆手术跨架构可移植性 14/14，读写关闭时与原生模型逐位相同
53 lines
2.7 KiB
PowerShell
53 lines
2.7 KiB
PowerShell
# Chain: wait for the v5 feature encoder, then train and score automatically.
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#
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# 1. wait for the encoder process to exit;
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# 2. verify the encoder wrote its real manifest (not the smoke placeholder);
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# 3. train the V2-512 control and the XL-512 candidate on the identical v5 data;
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# 4. score every router (old production, old v3-trained, new v5-trained) on the
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# frozen 21,920-episode v5 eval and write the percentage scorecard.
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param(
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[Parameter(Mandatory = $true)][int]$EncoderPid,
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[int]$Steps = 100000,
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[int]$PollSeconds = 30
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)
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$ErrorActionPreference = 'Stop'
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$Python = 'C:\Users\Administrator\miniconda3\envs\LLM\python.exe'
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$ForkRoot = 'H:\Memory\V2_dpskw'
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$CacheDir = 'H:\Memory\nm_cache\nm_router_v5\feature_cache'
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$Manifest = Join-Path $CacheDir 'manifest.json'
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Write-Output ("[{0}] waiting for encoder pid {1}" -f (Get-Date -Format 'HH:mm:ss'), $EncoderPid)
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while (Get-Process -Id $EncoderPid -ErrorAction SilentlyContinue) {
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Start-Sleep -Seconds $PollSeconds
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}
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Write-Output ("[{0}] encoder exited" -f (Get-Date -Format 'HH:mm:ss'))
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$manifest = Get-Content -LiteralPath $Manifest -Raw | ConvertFrom-Json
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if (-not $manifest.PSObject.Properties.Name.Contains('encoding')) {
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throw "manifest has no 'encoding' section: the encoder did not finish cleanly"
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}
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if ([int]$manifest.text_count -lt 2000000) {
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throw "encoder produced only $($manifest.text_count) texts"
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}
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Write-Output ("manifest ok: texts={0} dtype={1} grouping={2}" -f $manifest.text_count, $manifest.dtype, $manifest.encoding.grouping)
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# --- 3. train ---------------------------------------------------------------
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& pwsh -NoProfile -File (Join-Path $ForkRoot 'run_router_v5.ps1') -Steps $Steps
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if ($LASTEXITCODE -ne 0) { throw "v5 training failed with exit code $LASTEXITCODE" }
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# --- 4. score ---------------------------------------------------------------
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$env:PYTHONPATH = 'H:\Memory'
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Set-Location $ForkRoot
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$old = 'H:\Memory\dynamic_memory_lab\checkpoints'
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& $Python -m V2_dpskw.eval_router_v5 `
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--run "V2-128 deployed(v3)=$old\natural_memory_v2_qwen_router_entities\memory_router_v2.pt" `
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--run "V2-512 v3 best=$old\natural_memory_v2_router_512\router_best.pt" `
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--run "V2-512 v3 final=$old\natural_memory_v2_router_512\memory_router_v2.pt" `
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--run "V2-512 v5 best=$ForkRoot\checkpoints\router_v5_v2_512\router_best.pt" `
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--run "V2-512 v5 final=$ForkRoot\checkpoints\router_v5_v2_512\memory_router_v2.pt" `
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--run "XL-512 v5 best=$ForkRoot\checkpoints\router_v5_xl512\router_best.pt" `
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--run "XL-512 v5 final=$ForkRoot\checkpoints\router_v5_xl512\memory_router_xl.pt" `
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--output router_scorecard_v5.json --markdown router_scorecard_v5.md
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Write-Output ("[{0}] chain complete" -f (Get-Date -Format 'HH:mm:ss'))
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