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Fix the test and add custom min/max reductions for uncommon MPI types (#2060)
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@@ -30,27 +30,51 @@ class TestMPIDistributed(mlx_distributed_tests.MLXDistributedCommonTestCase):
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def test_all_reduce(self):
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world = mx.distributed.init()
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dtypes = [
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mx.int8,
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mx.uint8,
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mx.int16,
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mx.uint16,
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mx.int32,
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mx.uint32,
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mx.float32,
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mx.float16,
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mx.bfloat16,
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mx.complex64,
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(mx.int8, 0),
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(mx.uint8, 0),
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(mx.int16, 0),
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(mx.uint16, 0),
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(mx.int32, 0),
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(mx.uint32, 0),
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(mx.float32, 1e-6),
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(mx.float16, 5e-3),
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(mx.bfloat16, 1e-1),
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(mx.complex64, 1e-6),
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]
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for dt in dtypes:
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x = mx.ones((2, 2, 4), dtype=dt)
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y = mx.distributed.all_sum(x)
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self.assertTrue(mx.all(y == world.size()))
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sizes = [
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(7,),
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(10,),
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(1024,),
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(1024, 1024),
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]
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key = mx.random.key(0)
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group = world.split(world.rank() % 2)
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sub = world.split(world.rank() % 2)
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for dt in dtypes:
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x = mx.ones((2, 2, 4), dtype=dt)
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y = mx.distributed.all_sum(x, group=sub)
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self.assertTrue(mx.all(y == sub.size()))
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for dt, rtol in dtypes:
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for sh in sizes:
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for g in [world, group]:
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x = (
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mx.random.uniform(shape=(g.size(),) + sh, key=key) * 10
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).astype(dt)
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# All sum
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y = mx.distributed.all_sum(x[g.rank()], group=g)
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z = x.sum(0)
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maxrelerror = (y - z).abs()
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if rtol > 0:
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maxrelerror /= z.abs()
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maxrelerror = maxrelerror.max()
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self.assertLessEqual(maxrelerror, rtol)
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# All max
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y = mx.distributed.all_max(x[g.rank()], group=g)
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z = x.max(0)
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self.assertTrue(mx.all(y == z))
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# All min
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y = mx.distributed.all_min(x[g.rank()], group=g)
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z = x.min(0)
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self.assertTrue(mx.all(y == z))
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def test_all_gather(self):
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world = mx.distributed.init()
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@@ -124,22 +148,6 @@ class TestMPIDistributed(mlx_distributed_tests.MLXDistributedCommonTestCase):
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x = mx.distributed.recv_like(x, neighbor, group=pairs)
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mx.eval(y, x)
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def test_min_max(self):
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world = mx.distributed.init()
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base = mx.arange(16).reshape(4, 4)
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x = base + world.rank() * 32
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def _test_reduction(reduction: str = "all_max"):
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target = base + ((world.size() - 1) * 16) * (reduction == "max")
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reducer = getattr(mx.distributed, reduction)
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y = reducer(x)
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self.assertTrue(mx.allclose(y, target))
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for reduction in ["all_max", "all_min"]:
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_test_reduction(reduction)
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if __name__ == "__main__":
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unittest.main()
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@@ -51,16 +51,25 @@ class TestRingDistributed(mlx_distributed_tests.MLXDistributedCommonTestCase):
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x = (
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mx.random.uniform(shape=(world.size(),) + sh, key=key) * 10
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).astype(dt)
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for reduction in reductions:
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reducer_distributed = getattr(mx.distributed, f"all_{reduction}")
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y = reducer_distributed(x[world.rank()])
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reducer = getattr(mx, reduction)
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z = reducer(x, axis=0)
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mx.eval(y, z)
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# All sum
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y = mx.distributed.all_sum(x[world.rank()])
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z = x.sum(0)
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maxrelerror = (y - z).abs()
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if rtol > 0:
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maxrelerror /= z.abs()
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maxrelerror = maxrelerror.max()
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self.assertLessEqual(maxrelerror, rtol)
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maxrelerror = ((y - z).abs() / z.abs()).max()
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self.assertLessEqual(maxrelerror, rtol)
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# All max
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y = mx.distributed.all_max(x[world.rank()])
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z = x.max(0)
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self.assertTrue(mx.all(y == z))
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# All min
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y = mx.distributed.all_min(x[world.rank()])
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z = x.min(0)
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self.assertTrue(mx.all(y == z))
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def test_all_gather(self):
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world = mx.distributed.init()
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