| |
| """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: |
| 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() |
|
|
