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f1a4107 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 | #!/usr/bin/env python3
"""Tiny 2-device sharding probe for uzu/lalamo TP semantics.
Usage on Kaggle T4x2:
python scripts/tiny_sharding_probe.py
Usage on CPU with 2 forced devices:
FORCE_2_CPU=1 python scripts/tiny_sharding_probe.py
"""
from __future__ import annotations
import json
import os
if os.environ.get("FORCE_2_CPU") == "1":
os.environ.setdefault("XLA_FLAGS", "--xla_force_host_platform_device_count=2")
import jax
import jax.numpy as jnp
import numpy as np
from jax.sharding import AxisType, Mesh, NamedSharding, PartitionSpec as P
def main() -> None:
devices = jax.devices()
report = {"devices": [str(device) for device in devices], "cases": [], "ok": False}
if len(devices) < 2:
report["error"] = f"need >=2 devices, got {len(devices)}"
print(json.dumps(report, indent=2))
raise SystemExit(1)
mesh = Mesh(np.asarray(devices[:2]), ("tensor",), axis_types=(AxisType.Explicit,))
base = jnp.asarray(np.arange(64, dtype=np.float32).reshape(8, 8))
def record(name: str, expect_error: bool, expected: str, fn) -> None:
try:
fn()
except Exception as error: # noqa: BLE001 - probe records the exact runtime error
message = str(error)
passed = expect_error and expected in message
report["cases"].append(
{"name": name, "expected": expected, "ok": passed, "error": message[:500]}
)
else:
report["cases"].append(
{"name": name, "expected": expected, "ok": not expect_error, "error": None}
)
def column_sharded_matmul() -> None:
sharding = NamedSharding(mesh, P(None, "tensor"))
with jax.set_mesh(mesh):
x = jax.device_put(base, sharding)
_ = x @ x.T
def row_sharded_matmul() -> None:
sharding = NamedSharding(mesh, P("tensor", None))
with jax.set_mesh(mesh):
x = jax.device_put(base, sharding)
_ = x @ x.T
def replicated_reshard_matmul() -> None:
sharded = NamedSharding(mesh, P(None, "tensor"))
replicated = NamedSharding(mesh, P())
with jax.set_mesh(mesh):
x = jax.device_put(base, sharded)
x_rep = jax.device_put(x, replicated)
result = x_rep @ x_rep.T
expected = base @ base.T
diff = float(jnp.max(jnp.abs(result - expected)))
report["reshard_max_abs_diff"] = diff
if diff > 1e-4:
raise RuntimeError(f"reshard mismatch: {diff}")
record("column_sharded_matmul", True, "Contracting dimensions are sharded", column_sharded_matmul)
record("row_sharded_matmul", True, "illegally sharded", row_sharded_matmul)
record("replicated_reshard_matmul", False, "", replicated_reshard_matmul)
report["ok"] = all(case["ok"] for case in report["cases"])
print(json.dumps(report, indent=2))
raise SystemExit(0 if report["ok"] else 1)
if __name__ == "__main__":
main()
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