66 lines
3 KiB
Bash
66 lines
3 KiB
Bash
# pipeline-parallel-inference — run profile (.env style)
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# ----------------------------------------------------------------------------
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# This is the single source of truth for the knobs that used to be scattered
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# across the binaries and one operator's shell. Copy it to set up a run:
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#
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# cp profiles/example.env profiles/local.env # untracked; put real secrets here
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# PP_PROFILE=profiles/local.env cargo run --bin pp-orchestrator -- --seed ...
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#
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# When PP_PROFILE is unset, profiles/local.env is loaded automatically if it
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# exists. The run scripts pick this up too (the binaries load it at startup).
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#
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# PRECEDENCE (lowest -> highest):
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# compiled default < this profile < real process env < CLI flag
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# i.e. anything already exported in your shell wins over the file, and a
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# --flag wins over everything. The profile only fills in what is unset.
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#
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# Lines are KEY=VALUE; `export ` prefix and surrounding quotes are tolerated;
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# `#` comments and blank lines are ignored.
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# ----------------------------------------------------------------------------
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# --- Networking / relay -----------------------------------------------------
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# Custom iroh relay the whole cluster homes onto (a swactor-iroh-relay on a
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# VPS). Leave unset to use the iroh default relays. Placeholder below — put
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# YOUR real relay only in profiles/local.env (gitignored), not here.
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#SWACTOR_IROH_RELAY_URL=https://relay.example.com
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# --- Topology ---------------------------------------------------------------
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# Number of pipeline stages (>= 2). pp-orchestrator also accepts --num-stages.
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#NUM_STAGES=2
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# --- Compute target (vast.ai / docker) --------------------------------------
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# Container image to run on each node. The run scripts already read PP_IMAGE;
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# pp-orchestrator's --image default now reads it too. Set to your registry tag.
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#PP_IMAGE=swactor-pp-gpu:latest
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# GPU class requested when leasing on vast.ai (pp-orchestrator --gpu overrides).
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#PP_GPU=RTX 3060
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# --- Workload (what each stage computes) ------------------------------------
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# Model identifier handed to the worker.
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#MODEL=
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# Python worker script + interpreter (per-stage compute). WORKER_SCRIPT is the
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# pp-worker default; pp-orchestrator --worker ships a script to remote nodes.
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#WORKER_SCRIPT=./pp_tinygrad_worker.py
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#WORKER_CMD=python3
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#PYTHON=python3
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# Stub mode: skip the real worker, echo activations (fast local smoke runs).
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#PP_WORKER_STUB=1
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# Inference request prompt + token budget (pp-orchestrator --prompt/--max-tokens).
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#MAX_TOKENS=64
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# --- Timeouts (seconds; sane defaults baked in — override only if needed) ---
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#PP_CONVERGE_TIMEOUT_SECS=1200
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#PP_WORKER_READY_TIMEOUT_SECS=1800
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#PP_NEIGHBOR_RESOLVE_TIMEOUT_SECS=1800
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#PP_PIPELINE_WIRED_TIMEOUT_SECS=1800
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#PP_AWAIT_RESPONSE_TIMEOUT_SECS=600
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#PP_RESOLVE_TIMEOUT_SECS=1200
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# --- Diagnostics / dashboards (optional) ------------------------------------
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#PP_DASHBOARD=1
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#PP_DASHBOARD_PORT=9090
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#SWACTOR_DIAG_COLLECTOR_URL=http://127.0.0.1:9080
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# Secrets (orchestrator / stage identity). Keep real values in local.env only.
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#PP_ORCH_SECRET=
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#PP_STAGE_SECRET=
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