# Copyright 2018 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from functools import partial from absl.testing import absltest from absl.testing import parameterized import numpy as np import numpy.random as npr from unittest import SkipTest import jax from jax._src import test_util as jtu from jax import numpy as jnp from jax.config import config config.parse_flags_with_absl() FLAGS = config.FLAGS npr.seed(0) class MultiBackendTest(jtu.JaxTestCase): """Tests jit targeting to different backends.""" @parameterized.named_parameters(jtu.cases_from_list( {"testcase_name": f"_backend={backend}", "backend": backend, } for backend in ['cpu', 'gpu', 'tpu', None] )) def testMultiBackend(self, backend): if backend not in ('cpu', jtu.device_under_test(), None): raise SkipTest("Backend is not CPU or the device under test") @partial(jax.jit, backend=backend) def fun(x, y): return jnp.matmul(x, y) x = npr.uniform(size=(10,10)) y = npr.uniform(size=(10,10)) z_host = np.matmul(x, y) z = fun(x, y) self.assertAllClose(z, z_host, rtol=1e-2) correct_platform = backend if backend else jtu.device_under_test() self.assertEqual(z.device_buffer.platform(), correct_platform) @parameterized.named_parameters(jtu.cases_from_list( {"testcase_name": f"_ordering={ordering}", "ordering": ordering,} for ordering in [('cpu', None), ('gpu', None), ('tpu', None), (None, None)])) def testMultiBackendNestedJit(self, ordering): outer, inner = ordering if outer not in ('cpu', jtu.device_under_test(), None): raise SkipTest("Backend is not CPU or the device under test") @partial(jax.jit, backend=outer) def fun(x, y): @partial(jax.jit, backend=inner) def infun(x, y): return jnp.matmul(x, y) return infun(x, y) + jnp.ones_like(x) x = npr.uniform(size=(10,10)) y = npr.uniform(size=(10,10)) z_host = np.matmul(x, y) + np.ones_like(x) z = fun(x, y) self.assertAllClose(z, z_host, rtol=1e-2) correct_platform = outer if outer else jtu.device_under_test() self.assertEqual(z.device_buffer.platform(), correct_platform) @parameterized.named_parameters(jtu.cases_from_list( {"testcase_name": f"_ordering={ordering}", "ordering": ordering,} for ordering in [ ('cpu', 'gpu'), ('gpu', 'cpu'), ('cpu', 'tpu'), ('tpu', 'cpu'), (None, 'cpu'), (None, 'gpu'), (None, 'tpu'), ])) def testMultiBackendNestedJitConflict(self, ordering): outer, inner = ordering if outer not in ('cpu', jtu.device_under_test(), None): raise SkipTest("Backend is not CPU or the device under test") if inner not in ('cpu', jtu.device_under_test(), None): raise SkipTest("Backend is not CPU or the device under test") if outer is None and inner == jtu.device_under_test(): raise SkipTest("(None, device) is allowed") @partial(jax.jit, backend=outer) def fun(x, y): @partial(jax.jit, backend=inner) def infun(x, y): return jnp.matmul(x, y) return infun(x, y) + jnp.ones_like(x) x = npr.uniform(size=(10,10)) y = npr.uniform(size=(10,10)) self.assertRaises(ValueError, lambda: fun(x, y)) @parameterized.named_parameters(jtu.cases_from_list( {"testcase_name": f"_backend={backend}", "backend": backend,} for backend in ['cpu', 'gpu', 'tpu'] )) def testGpuMultiBackendOpByOpReturn(self, backend): if backend not in ('cpu', jtu.device_under_test()): raise SkipTest("Backend is not CPU or the device under test") @partial(jax.jit, backend=backend) def fun(x, y): return jnp.matmul(x, y) x = npr.uniform(size=(10,10)) y = npr.uniform(size=(10,10)) z = fun(x, y) w = jnp.sin(z) self.assertEqual(z.device_buffer.platform(), backend) self.assertEqual(w.device_buffer.platform(), backend) @jtu.skip_on_devices("cpu") # test can only fail with non-cpu backends def testJitCpu(self): @partial(jax.jit, backend='cpu') def get_arr(scale): return scale + jnp.ones((2, 2)) x = get_arr(0.1) a = x / x.shape[0] b = x + jnp.ones_like(x) c = x + jnp.eye(2) self.assertEqual(a.device_buffer.device(), jax.devices('cpu')[0]) self.assertEqual(b.device_buffer.device(), jax.devices('cpu')[0]) self.assertEqual(c.device_buffer.device(), jax.devices('cpu')[0]) @jtu.skip_on_devices("cpu") # test can only fail with non-cpu backends def test_closed_over_values_device_placement(self): # see https://github.com/google/jax/issues/1431 def f(): return jnp.add(3., 4.) self.assertNotEqual(jax.jit(f)().device_buffer.device(), jax.devices('cpu')[0]) self.assertEqual(jax.jit(f, backend='cpu')().device_buffer.device(), jax.devices('cpu')[0]) @jtu.skip_on_devices("cpu") # test only makes sense on non-cpu backends def test_jit_on_nondefault_backend(self): cpus = jax.devices("cpu") self.assertNotEmpty(cpus) # Since we are not on CPU, some other backend will be the default default_dev = jax.devices()[0] self.assertNotEqual(default_dev.platform, "cpu") data_on_cpu = jax.device_put(1, device=cpus[0]) self.assertEqual(data_on_cpu.device_buffer.device(), cpus[0]) def my_sin(x): return jnp.sin(x) # jit without any device spec follows the data result1 = jax.jit(my_sin)(2) self.assertEqual(result1.device_buffer.device(), default_dev) result2 = jax.jit(my_sin)(data_on_cpu) self.assertEqual(result2.device_buffer.device(), cpus[0]) # jit with `device` spec places the data on the specified device result3 = jax.jit(my_sin, device=cpus[0])(2) self.assertEqual(result3.device_buffer.device(), cpus[0]) # jit with `backend` spec places the data on the specified backend result4 = jax.jit(my_sin, backend="cpu")(2) self.assertEqual(result4.device_buffer.device(), cpus[0]) @jtu.skip_on_devices("cpu") # test only makes sense on non-cpu backends def test_indexing(self): # https://github.com/google/jax/issues/2905 cpus = jax.devices("cpu") x = jax.device_put(np.ones(2), cpus[0]) y = x[0] self.assertEqual(y.device_buffer.device(), cpus[0]) @jtu.skip_on_devices("cpu") # test only makes sense on non-cpu backends def test_sum(self): # https://github.com/google/jax/issues/2905 cpus = jax.devices("cpu") x = jax.device_put(np.ones(2), cpus[0]) y = x.sum() self.assertEqual(y.device_buffer.device(), cpus[0]) if __name__ == "__main__": absltest.main(testLoader=jtu.JaxTestLoader())