swactor/crates/swactor-dp-mnist/pyproject.toml

[project]
name = "swactor-dp-mnist"
version = "0.1.0"
requires-python = ">=3.9"
dependencies = [
    "swactor",
    "torch",
    "torchvision",
    "numpy",
]

[tool.uv.sources]
swactor = { path = "../swactor-python", editable = true }

[[tool.uv.index]]
name = "pytorch-cpu"
url = "https://download.pytorch.org/whl/cpu"
feat: data parallel mnist example (#26) Add a data-parallel MNIST training example where swactor actors coordinate gradient averaging across workers. - crates/swactor-dp-mnist/worker.py: add `MnistNet` MLP and `MnistWorker` actor handling `train_batch`/`update`/`evaluate`/`save_model` over a sharded MNIST split with SGD - crates/swactor-dp-mnist/aggregator.py: add `Aggregator` actor that buffers per-worker gradients, averages them, fans out updates, then logs/evaluates on completion - crates/swactor-dp-mnist/run_training.py: spawn the Aggregator plus two MnistWorkers (identical initial weights, disjoint shards), run 750 rounds, and poll the inbox for `log`/`done` - crates/swactor-dp-mnist/pyproject.toml: declare torch/torchvision/numpy deps, an editable local `swactor` source, and the PyTorch CPU index - Cargo.toml: add a `[profile.bench]` retaining debug symbols (`debug = true`, `strip = false`) for profiling Signed-off-by: Zachery Aaron Shores-Chmielewski <zacheryasc@gmail.com> 2026-02-09 14:42:25 +00:00			`[project]`
			`name = "swactor-dp-mnist"`
			`version = "0.1.0"`
			`requires-python = ">=3.9"`
			`dependencies = [`
			`"swactor",`
			`"torch",`
			`"torchvision",`
			`"numpy",`
			`]`

			`[tool.uv.sources]`
			`swactor = { path = "../swactor-python", editable = true }`

			`[[tool.uv.index]]`
			`name = "pytorch-cpu"`
			`url = "https://download.pytorch.org/whl/cpu"`