warpscale
Python SDK to report PyTorch training progress to Warpscale.
Install
pip install warpscale
Use
import warpscale
# Once, after dist.init_process_group() — without a live process group there is
# no rank to elect an emitter from, and nothing is reported.
warpscale.init(total_steps=40_000, total_epochs=3, framework="fsdp", precision="bf16")
# Call on every rank; rank 0 emits, the rest are no-ops.
for epoch in range(epochs):
for batch in loader:
... # one optimizer step
warpscale.step()
warpscale.epoch()
warpscale.checkpoint_started()
save_checkpoint() # incl. the async dcp.async_save tail
warpscale.checkpoint_persisted()
Launch
torchrun sets WORLD_SIZE itself and needs nothing extra. A run with no
process group must declare WORLD_SIZE=1 for its lone process to be elected:
WORLD_SIZE=1 warpscale run python train.py
A script that starts its own ranks with mp.spawn is not supported — before
init_process_group() every sibling looks like the lone process, so none is
elected and nothing is reported. Use torchrun.
1 maintainer
Metadata
1 maintainer
Release files for warpscale 0.2.0
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| File | Size | Uploaded | Provenance | Actions |
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Total release size: 31.2 kB
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