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Also, if all axes of an out_aval are auto, set the corresponding out_sharding to Unspecified during lowering, otherwise things go horribly wrong. This is actually a XLA bug but we can workaround it in JAX for now. PiperOrigin-RevId: 729307115
276 lines
7.8 KiB
Python
276 lines
7.8 KiB
Python
# Copyright 2021 The JAX Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# https://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import jax
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import jax.numpy as jnp
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import numpy as np
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from absl.testing import absltest
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from jax._src import test_util as jtu
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from jax.sharding import NamedSharding, PartitionSpec as P
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from jax.experimental.shard_alike import shard_alike
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from jax.experimental.shard_map import shard_map
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jax.config.parse_flags_with_absl()
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jtu.request_cpu_devices(8)
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class ShardAlikeDownstreamTest(jtu.JaxTestCase):
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def test_full_like(self):
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x = jnp.arange(16, dtype='float32').reshape(8, 2)
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mesh = jtu.create_mesh((8,), ("i",))
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x = jax.device_put(x, NamedSharding(mesh, P('i', None)))
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y = jnp.full_like(x, 1)
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self.assertEqual(x.sharding, y.sharding)
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class ShardAlikeTest(jtu.JaxTestCase):
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def setUp(self):
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super().setUp()
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def test_basic(self):
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mesh = jtu.create_mesh((2, 2), ('x', 'y'))
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np_inp = np.arange(16).reshape(8, 2)
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s = NamedSharding(mesh, P('x', 'y'))
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inp = jax.device_put(np_inp, s)
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@jax.jit
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def f(x):
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y = x * x
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z = y * 2
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_, z = shard_alike(x, z)
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return z * 2
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out = f(inp)
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self.assertEqual(out.sharding, s)
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self.assertArraysEqual(out, np_inp * np_inp * 4)
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def test_output_sharded_alike_input(self):
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mesh = jtu.create_mesh((2, 2), ('x', 'y'))
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np_inp = np.arange(16).reshape(8, 2)
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s = NamedSharding(mesh, P('x', 'y'))
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inp = jax.device_put(np_inp, s)
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@jax.jit
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def f(x):
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y = x * 2
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return shard_alike(x, y)[1]
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out = f(inp)
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self.assertEqual(out.sharding, s)
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self.assertArraysEqual(out, np_inp * 2)
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def test_arange_shard_alike_jit(self):
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mesh = jtu.create_mesh((2, 2), ('x', 'y'))
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np_inp = np.arange(16).reshape(8, 2)
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s = NamedSharding(mesh, P('x', 'y'))
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inp = jax.device_put(np_inp, s)
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@jax.jit
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def f(x):
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y = jnp.arange(16).reshape(8, 2)
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return shard_alike(x, y)[1]
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out = f(inp)
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self.assertEqual(out.sharding, s)
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self.assertArraysEqual(out, np_inp)
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def test_different_shapes(self):
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mesh = jtu.create_mesh((2, 1), ('x', 'y'))
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np_inp = np.arange(16).reshape(8, 2)
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s = NamedSharding(mesh, P('x',))
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inp = jax.device_put(np_inp, s)
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@jax.jit
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def f(x):
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y = x @ x.T
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return shard_alike(x, y)[1]
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with self.assertRaisesRegex(
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ValueError, 'The leaves shapes of `x` and `y` should match'):
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f(inp)
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def test_double_shard_alike(self):
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mesh = jtu.create_mesh((2, 2), ('x', 'y'))
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np_inp = np.arange(16).reshape(8, 2)
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s = NamedSharding(mesh, P('x', 'y'))
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inp = jax.device_put(np_inp, s)
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@jax.jit
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def f(x):
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y = x * 2
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_, y = shard_alike(x, y)
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z = y @ y.T
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a = jnp.arange(64).reshape(8, 8)
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return shard_alike(z, a)
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out1, out2 = f(inp)
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self.assertEqual(out1.sharding, NamedSharding(mesh, P('x')))
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self.assertEqual(out2.sharding, NamedSharding(mesh, P('x')))
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def test_shard_like_eager(self):
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mesh = jtu.create_mesh((4, 1), ('x', 'y'))
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np_inp = np.arange(16).reshape(8, 2)
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s = NamedSharding(mesh, P('x', 'y'))
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inp = jax.device_put(np_inp, s)
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def f(x):
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y = jnp.arange(16).reshape(8, 2)
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return shard_alike(x, y)[1]
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out = f(inp)
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self.assertTrue(out.sharding.is_equivalent_to(s, out.ndim))
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self.assertArraysEqual(out, np_inp)
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def test_shard_map(self):
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mesh = jtu.create_mesh((4, 2), ('x', 'y'))
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np_inp = np.arange(16).reshape(8, 2)
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s = NamedSharding(mesh, P('x', 'y'))
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inp = jax.device_put(np_inp, s)
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def g(x):
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return jax.lax.psum(x, 'x')
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@jax.jit
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def f(x):
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y = x @ x.T
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s_out = shard_map(g, mesh, in_specs=P('x', 'y'),
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out_specs=P(None, 'y'))(y)
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z = s_out.T @ s_out
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return shard_alike(y, z)
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out1, out2 = f(inp)
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# From options; P('x', 'y'), P('y'), shard_like chooses the better option.
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self.assertEqual(out1.sharding, s)
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self.assertEqual(out2.sharding, s)
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def test_grad(self):
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mesh = jtu.create_mesh((4,), ('x',))
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np_inp = np.arange(8.)
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s = NamedSharding(mesh, P('x'))
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inp = jax.device_put(np_inp, s)
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def _cb(s):
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self.assertFalse(s.is_fully_replicated)
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self.assertLen(s.device_set, mesh.size)
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self.assertEqual(s.shard_shape(np_inp.shape), (2,))
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def f(x):
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y = jnp.arange(8.)
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x_, y_ = shard_alike(x, y)
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jax.debug.inspect_array_sharding(y_, callback=_cb)
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z = x_ + y_
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return jnp.sum(z)
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jax.grad(f)(inp) # doesn't crash
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jax.grad(jax.jit(f))(inp) # doesn't crash
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def test_shard_input_as_output(self):
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mesh = jtu.create_mesh((4,), ('x',))
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np_inp = np.arange(8.)
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s = NamedSharding(mesh, P('x'))
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@jax.jit
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def f(x):
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y = jax.lax.with_sharding_constraint(x, s)
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z = y * 2
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return shard_alike(x, z)
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with jtu.count_pjit_cpp_cache_miss() as count:
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f(np_inp)
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out1, out2 = f(np_inp)
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self.assertEqual(count(), 1)
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self.assertTrue(s.is_equivalent_to(out1.sharding, np_inp.ndim))
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self.assertTrue(s.is_equivalent_to(out2.sharding, np_inp.ndim))
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@jax.jit
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def g(x):
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z = x * 2
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return shard_alike(x, z)
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arr = jax.device_put(np_inp, s)
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with jtu.count_pjit_cpp_cache_miss() as count:
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g(arr)
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out3, out4 = g(arr)
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self.assertEqual(count(), 1)
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self.assertEqual(out3.sharding, s)
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self.assertEqual(out4.sharding, s)
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def test_shard_alike_inputs(self):
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mesh = jtu.create_mesh((2,), ('x',))
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np_inp = np.arange(8.)
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s = NamedSharding(mesh, P('x'))
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arr = jax.device_put(np_inp, s)
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def f(x, y):
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return shard_alike(x, y)
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eager_out1, eager_out2 = f(arr, np_inp)
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self.assertEqual(eager_out1.sharding, s)
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self.assertEqual(eager_out2.sharding, s)
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out1, out2 = jax.jit(f)(arr, np_inp)
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self.assertEqual(out1.sharding, s)
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self.assertEqual(out2.sharding, s)
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def test_vmap_one_mapped(self):
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mesh = jtu.create_mesh((2, 2), ('x', 'y'))
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np_inp = np.arange(2)
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s = NamedSharding(mesh, P('y'))
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inp = jax.device_put(np_inp, s)
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@jax.jit
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def f(x):
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def _shard_slice_like_arg(s):
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sharded_s, _ = shard_alike(s, x)
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return sharded_s
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replicated_x = jnp.tile(x, [8, 1]) # shape == (8, 2)
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return jax.vmap(_shard_slice_like_arg, in_axes=0)(replicated_x)
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out = f(inp)
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self.assertEqual(out.sharding, NamedSharding(mesh, P(None, 'y')))
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self.assertArraysEqual(out, np.tile(np_inp, [8, 1]))
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def test_vmap_both_mapped(self):
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mesh = jtu.create_mesh((2, 2), ('x', 'y'))
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np_inp = np.arange(16).reshape(8, 2)
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s = NamedSharding(mesh, P('x', 'y'))
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inp1 = jax.device_put(np_inp, s)
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np_inp2 = np.arange(16).reshape(2, 8)
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inp2 = jax.device_put(np_inp2, NamedSharding(mesh, P('y', 'x')))
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@jax.jit
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def f(x, y):
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return jax.vmap(shard_alike, in_axes=(0, 1))(x, y)
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out1, out2 = f(inp1, inp2)
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self.assertEqual(out1.sharding, s)
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self.assertEqual(out2.sharding, s)
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self.assertArraysEqual(out1, np_inp)
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self.assertArraysEqual(out2, np_inp2.T)
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def test_sharding_preserverd_single_device(self):
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mesh = jax.sharding.Mesh([jax.devices()[0]], "x")
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s = NamedSharding(mesh, P("x"))
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x = jax.device_put(np.arange(8), s)
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_, y = shard_alike(x, jnp.arange(8))
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self.assertTrue(y.sharding.is_equivalent_to(s, y.ndim))
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if __name__ == '__main__':
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absltest.main(testLoader=jtu.JaxTestLoader())
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