split venv_t5 into venv_t5_530 and venv_t5_550 for tiered transformers 5.x support
This commit is contained in:
Roland Tannous
parent
d2140fbbe8
commit
1cc77061ab
5 changed files with 123 additions and 5 deletions
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@ -181,11 +181,8 @@ def _setup_log_capture(resp_queue: Any) -> None:
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def _activate_transformers_version(model_name: str) -> None:
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"""Activate the correct transformers version BEFORE any ML imports."""
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# Ensure backend is on path for utils imports
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backend_path = str(Path(__file__).resolve().parent.parent.parent)
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if backend_path not in sys.path:
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sys.path.insert(0, backend_path)
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from utils.transformers_version import activate_transformers_for_subprocess
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activate_transformers_for_subprocess(model_name)
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@ -35,8 +35,6 @@ from utils.hardware import apply_gpu_ids
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def _activate_transformers_version(model_name: str) -> None:
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"""Activate the correct transformers version BEFORE any ML imports."""
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# Ensure backend is on path for utils imports
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backend_path = str(Path(__file__).resolve().parent.parent.parent)
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if backend_path not in sys.path:
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sys.path.insert(0, backend_path)
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@ -374,6 +374,7 @@ def run_training_process(
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)
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return
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<<<<<<< HEAD
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# ── 1a. Auto-enable trust_remote_code for NemotronH/Nano models ──
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# NemotronH has config parsing bugs in transformers that require
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# trust_remote_code=True as a workaround. Other transformers 5.x models
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@ -385,6 +386,22 @@ def run_training_process(
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if (
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any(sub in _lowered for sub in _NEMOTRON_TRUST_SUBSTRINGS)
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and (_lowered.startswith("unsloth/") or _lowered.startswith("nvidia/"))
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=======
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# ── 1a. Auto-enable trust_remote_code for unsloth/* transformers 5.x models ──
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# Some newer architectures (e.g. NemotronH) have config parsing bugs in
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# transformers that require trust_remote_code=True as a workaround.
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# Only auto-enable for unsloth/* prefixed models (trusted source).
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# Exclude Gemma 4 since it is a native transformers 5.5 model and
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# trust_remote_code=True would bypass the compiler (disabling fused CE).
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from utils.transformers_version import get_transformers_tier
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_lowered = model_name.lower()
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_tier = get_transformers_tier(model_name)
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if (
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_tier != "default"
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and _lowered.startswith("unsloth/")
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and _tier != "550" # Gemma 4 is native t5.5 — trust_remote_code bypasses compiler
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>>>>>>> 970219a3 (split venv_t5 into venv_t5_530 and venv_t5_550 for tiered transformers 5.x support)
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and not config.get("trust_remote_code", False)
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):
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config["trust_remote_code"] = True
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@ -1701,6 +1701,89 @@ if ($stackExit -ne 0) {
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exit 1
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}
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# ── Pre-install transformers 5.x into .venv_t5_530/ and .venv_t5_550/ ──
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# Models like GLM-4.7-Flash, Qwen3 MoE need transformers>=5.3.0.
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# Gemma 4 models need transformers>=5.5.0.
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# Pre-install into separate directories to avoid runtime pip overhead.
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# The training subprocess prepends the appropriate dir to sys.path.
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Write-Host ""
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# Clean up legacy single .venv_t5 directory
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$VenvT5Legacy = Join-Path $env:USERPROFILE ".unsloth\studio\.venv_t5"
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if (Test-Path $VenvT5Legacy) { Remove-Item -Recurse -Force $VenvT5Legacy }
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$prevEAP_t5 = $ErrorActionPreference
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$ErrorActionPreference = "Continue"
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# --- .venv_t5_530 (transformers 5.3.0) ---
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substep "pre-installing transformers 5.3.0 for newer model support..."
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$VenvT5_530Dir = Join-Path $env:USERPROFILE ".unsloth\studio\.venv_t5_530"
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if (Test-Path $VenvT5_530Dir) { Remove-Item -Recurse -Force $VenvT5_530Dir }
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New-Item -ItemType Directory -Path $VenvT5_530Dir -Force | Out-Null
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foreach ($pkg in @("transformers==5.3.0", "huggingface_hub==1.8.0", "hf_xet==1.4.2")) {
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if ($script:UnslothVerbose) {
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Fast-Install --target $VenvT5_530Dir --no-deps $pkg
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$t5PkgExit = $LASTEXITCODE
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$output = ""
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} else {
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$output = Fast-Install --target $VenvT5_530Dir --no-deps $pkg | Out-String
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$t5PkgExit = $LASTEXITCODE
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}
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if ($t5PkgExit -ne 0) {
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Write-Host "[FAIL] Could not install $pkg into .venv_t5_530/" -ForegroundColor Red
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Write-Host $output -ForegroundColor Red
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$ErrorActionPreference = $prevEAP_t5
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exit 1
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}
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}
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if ($script:UnslothVerbose) {
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Fast-Install --target $VenvT5_530Dir tiktoken
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$tiktokenInstallExit = $LASTEXITCODE
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$output = ""
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} else {
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$output = Fast-Install --target $VenvT5_530Dir tiktoken | Out-String
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$tiktokenInstallExit = $LASTEXITCODE
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}
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if ($tiktokenInstallExit -ne 0) {
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substep "Could not install tiktoken into .venv_t5_530/ -- Qwen tokenizers may fail" "Yellow"
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}
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step "transformers" "5.3.0 pre-installed"
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# --- .venv_t5_550 (transformers 5.5.0) ---
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substep "pre-installing transformers 5.5.0 for Gemma 4 support..."
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$VenvT5_550Dir = Join-Path $env:USERPROFILE ".unsloth\studio\.venv_t5_550"
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if (Test-Path $VenvT5_550Dir) { Remove-Item -Recurse -Force $VenvT5_550Dir }
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New-Item -ItemType Directory -Path $VenvT5_550Dir -Force | Out-Null
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foreach ($pkg in @("transformers==5.5.0", "huggingface_hub==1.8.0", "hf_xet==1.4.2")) {
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if ($script:UnslothVerbose) {
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Fast-Install --target $VenvT5_550Dir --no-deps $pkg
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$t5PkgExit = $LASTEXITCODE
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$output = ""
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} else {
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$output = Fast-Install --target $VenvT5_550Dir --no-deps $pkg | Out-String
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$t5PkgExit = $LASTEXITCODE
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}
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if ($t5PkgExit -ne 0) {
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Write-Host "[FAIL] Could not install $pkg into .venv_t5_550/" -ForegroundColor Red
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Write-Host $output -ForegroundColor Red
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$ErrorActionPreference = $prevEAP_t5
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exit 1
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}
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}
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if ($script:UnslothVerbose) {
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Fast-Install --target $VenvT5_550Dir tiktoken
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$tiktokenInstallExit = $LASTEXITCODE
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$output = ""
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} else {
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$output = Fast-Install --target $VenvT5_550Dir tiktoken | Out-String
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$tiktokenInstallExit = $LASTEXITCODE
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}
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if ($tiktokenInstallExit -ne 0) {
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substep "Could not install tiktoken into .venv_t5_550/ -- Qwen tokenizers may fail" "Yellow"
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}
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$ErrorActionPreference = $prevEAP_t5
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step "transformers" "5.5.0 pre-installed"
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} else {
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step "python" "dependencies up to date"
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# Restore ErrorActionPreference (was lowered for pip/python section)
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@ -548,6 +548,29 @@ fi
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if [ "$_SKIP_PYTHON_DEPS" = false ]; then
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install_python_stack
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# ── 6b. Pre-install transformers 5.x into .venv_t5_530/ and .venv_t5_550/ ──
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# Models like GLM-4.7-Flash, Qwen3 MoE need transformers>=5.3.0.
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# Gemma 4 models need transformers>=5.5.0.
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# Pre-install into separate directories to avoid runtime pip overhead.
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# The training subprocess prepends the appropriate dir to sys.path.
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# Clean up legacy single .venv_t5 directory
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[ -d "$STUDIO_HOME/.venv_t5" ] && rm -rf "$STUDIO_HOME/.venv_t5"
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mkdir -p "$VENV_T5_530_DIR"
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run_quiet "install transformers 5.3.0" fast_install --target "$VENV_T5_530_DIR" --no-deps "transformers==5.3.0"
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run_quiet "install huggingface_hub for t5_530" fast_install --target "$VENV_T5_530_DIR" --no-deps "huggingface_hub==1.8.0"
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run_quiet "install hf_xet for t5_530" fast_install --target "$VENV_T5_530_DIR" --no-deps "hf_xet==1.4.2"
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run_quiet "install tiktoken for t5_530" fast_install --target "$VENV_T5_530_DIR" "tiktoken"
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step "transformers" "5.3.0 pre-installed"
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mkdir -p "$VENV_T5_550_DIR"
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run_quiet "install transformers 5.5.0" fast_install --target "$VENV_T5_550_DIR" --no-deps "transformers==5.5.0"
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run_quiet "install huggingface_hub for t5_550" fast_install --target "$VENV_T5_550_DIR" --no-deps "huggingface_hub==1.8.0"
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run_quiet "install hf_xet for t5_550" fast_install --target "$VENV_T5_550_DIR" --no-deps "hf_xet==1.4.2"
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run_quiet "install tiktoken for t5_550" fast_install --target "$VENV_T5_550_DIR" "tiktoken"
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step "transformers" "5.5.0 pre-installed"
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else
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step "python" "dependencies up to date"
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verbose_substep "python deps check: installed=$_PKG_NAME@${INSTALLED_VER:-unknown} latest=${LATEST_VER:-unknown}"
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