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154 lines
4.7 KiB
Python
154 lines
4.7 KiB
Python
# Copyright © 2024 Apple Inc.
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import unittest
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import mlx.core as mx
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import mlx_distributed_tests
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class TestMPIDistributed(mlx_distributed_tests.MLXDistributedCommonTestCase):
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@classmethod
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def setUpClass(cls):
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world = mx.distributed.init(strict=True, backend="mpi")
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def test_groups(self):
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world = mx.distributed.init()
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self.assertEqual(world.size(), 8)
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self.assertTrue(0 <= world.rank() < 8)
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world2 = mx.distributed.init()
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self.assertEqual(world.size(), world2.size())
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self.assertEqual(world.rank(), world2.rank())
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sub = world.split(world.rank() % 2)
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self.assertEqual(sub.size(), 4)
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self.assertEqual(sub.rank(), world.rank() // 2)
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sub = world.split(world.rank() // 2)
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self.assertEqual(sub.size(), 2)
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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, 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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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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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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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.complex64,
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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_gather(x)
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self.assertEqual(y.shape, (world.size() * 2, 2, 4))
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self.assertTrue(mx.all(y == 1))
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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_gather(x, group=sub)
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self.assertEqual(y.shape, (sub.size() * 2, 2, 4))
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self.assertTrue(mx.all(y == 1))
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def test_mixed(self):
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# Make the following groups:
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# - world: 0 1 2 3 4 5 6 7
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# - sub_1: 0 1 0 1 0 1 0 1
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# - sub_2: 0 0 1 1 2 2 3 3
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#
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# The corresponding colors to make them are
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# - world: N/A
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# - sub_1: 0 0 1 1 2 2 3 3
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# - sub_2: 0 1 0 1 0 1 0 1
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world = mx.distributed.init()
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sub_1 = world.split(world.rank() // 2)
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sub_2 = world.split(world.rank() % 2)
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x = mx.ones((1, 8)) * world.rank()
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y = mx.distributed.all_sum(x, group=sub_1)
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z = mx.distributed.all_gather(y, group=sub_2)
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z_target = mx.arange(8).reshape(4, 2).sum(-1, keepdims=True)
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self.assertTrue(mx.all(z == z_target))
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def test_send_recv(self):
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world = mx.distributed.init()
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pairs = world.split(world.rank() // 2)
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neighbor = (pairs.rank() + 1) % 2
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send = pairs.rank() == 0
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x = mx.ones(10)
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for i in range(10):
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if send:
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mx.eval(mx.distributed.send(2 * x, neighbor, group=pairs))
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else:
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x = mx.distributed.recv_like(x, neighbor, group=pairs)
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mx.eval(x)
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send = not send
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self.assertTrue(mx.all(x == (1024 if pairs.rank() == 0 else 512)))
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# Check recv and computation in same eval:
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y = mx.ones((5, 5)) + mx.array(2.0)
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if send:
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x = mx.distributed.send(2 * x, neighbor, group=pairs)
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else:
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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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if __name__ == "__main__":
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unittest.main()
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