mirror of
https://github.com/ROCm/jax.git
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f66f6ec98a
Limit jax._src.lib to shims around jaxlib and nothing else. The goal of this change is to avoid a dependency cycle between the rest of jax and jax._src.lib in a Bazel build. This allows the types for jax._src.lib to be inferred by pytype in isolation without referring to the rest of JAX. PiperOrigin-RevId: 512922397
1038 lines
31 KiB
Python
1038 lines
31 KiB
Python
# Copyright 2022 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 functools
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import textwrap
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import unittest
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from typing import Any, Callable, Sequence
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from absl.testing import absltest
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import jax
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from jax import lax
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from jax import tree_util
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from jax._src import core
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from jax._src import debugging
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from jax._src import dispatch
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from jax._src import effects
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from jax._src import sharding
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from jax._src import test_util as jtu
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from jax._src import util
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from jax._src import xla_bridge
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from jax._src.lib import xla_client
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from jax.config import config
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from jax.experimental import maps
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from jax.experimental import pjit
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from jax.interpreters import mlir
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from jax.experimental.maps import xmap
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from jax.experimental import io_callback
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import jax.numpy as jnp
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from jax.sharding import Mesh
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import numpy as np
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config.parse_flags_with_absl()
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debug_print = debugging.debug_print
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def _format_multiline(text):
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return textwrap.dedent(text).lstrip()
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prev_xla_flags = None
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def setUpModule():
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global prev_xla_flags
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# This will control the CPU devices. On TPU we always have 2 devices
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prev_xla_flags = jtu.set_host_platform_device_count(2)
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# Reset to previous configuration in case other test modules will be run.
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def tearDownModule():
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prev_xla_flags()
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callback_p = core.Primitive("callback")
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callback_p.multiple_results = True
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map, unsafe_map = util.safe_map, map
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@callback_p.def_impl
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def callback_impl(*args, callback: Callable[..., Any], result_avals,
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effect: debugging.DebugEffect):
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del result_avals, effect
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return callback(*args)
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@callback_p.def_effectful_abstract_eval
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def callback_abstract_eval(*flat_avals, callback: Callable[..., Any],
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effect: debugging.DebugEffect,
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result_avals: Sequence[core.ShapedArray]):
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del flat_avals, callback
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return result_avals, {effect}
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def callback(f, result_shape, *args, ordered: bool = False, **kwargs):
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flat_result_shapes, out_tree = tree_util.tree_flatten(result_shape)
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flat_args, in_tree = tree_util.tree_flatten((args, kwargs))
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flat_result_avals = [
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core.ShapedArray(s.shape, s.dtype) for s in flat_result_shapes
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]
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effect = (
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debugging.ordered_debug_effect if ordered else debugging.debug_effect)
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flat_args, in_tree = tree_util.tree_flatten((args, kwargs))
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def _flat_callback(*flat_args):
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args, kwargs = tree_util.tree_unflatten(in_tree, flat_args)
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return tree_util.tree_leaves(f(*args, **kwargs))
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out_flat = callback_p.bind(
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*flat_args,
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callback=_flat_callback,
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effect=effect,
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result_avals=flat_result_avals)
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return tree_util.tree_unflatten(out_tree, out_flat)
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def callback_lowering(ctx, *args, effect, callback, **params):
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def _callback(*flat_args):
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return tuple(
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callback_p.impl(*flat_args, effect=effect, callback=callback, **params))
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if effects.ordered_effects.contains(effect):
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token = ctx.tokens_in.get(effect)[0]
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result, token, keepalive = mlir.emit_python_callback(
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ctx, _callback, token, list(args), ctx.avals_in, ctx.avals_out, True)
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ctx.set_tokens_out(mlir.TokenSet({effect: (token,)}))
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else:
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result, token, keepalive = mlir.emit_python_callback(
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ctx, _callback, None, list(args), ctx.avals_in, ctx.avals_out, True)
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ctx.module_context.add_keepalive(keepalive)
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return result
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mlir.register_lowering(callback_p, callback_lowering, platform="cpu")
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mlir.register_lowering(callback_p, callback_lowering, platform="gpu")
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mlir.register_lowering(callback_p, callback_lowering, platform="tpu")
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@jtu.pytest_mark_if_available('pjrt_c_api_unimplemented') # host callback
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class PythonCallbackTest(jtu.JaxTestCase):
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def tearDown(self):
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super().tearDown()
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dispatch.runtime_tokens.clear()
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def test_callback_with_scalar_values(self):
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if xla_bridge.get_backend().runtime_type == 'stream_executor':
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raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
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@jax.jit
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def f(x):
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return callback(lambda x: x + np.float32(1.),
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core.ShapedArray(x.shape, x.dtype), x)
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out = f(0.)
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self.assertEqual(out, 1.)
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def test_callback_with_wrong_number_of_args(self):
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@jax.jit
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def f():
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# Calling a function that expects `x` with no arguments
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return callback(lambda x: np.ones(4, np.float32),
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core.ShapedArray((4,), np.float32))
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with self.assertRaises(RuntimeError):
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f()
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jax.effects_barrier()
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def test_callback_with_wrong_number_of_returned_values(self):
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@jax.jit
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def f():
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# Calling a function with a return value that expects no return values
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return callback(lambda: np.ones(4, np.float32), ())
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with self.assertRaises(RuntimeError):
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f()
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jax.effects_barrier()
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@jax.jit
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def g():
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# Calling a function with a return value that expects no return values
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return callback(lambda: None, (core.ShapedArray(
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(1,), np.float32), core.ShapedArray((2,), np.float32)))
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with self.assertRaises(RuntimeError):
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g()
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jax.effects_barrier()
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def test_callback_with_wrong_shape_outputs(self):
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@jax.jit
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def f():
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# Calling a function expected a (1,) shaped return value but getting ()
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return callback(lambda: np.float32(1.), core.ShapedArray((1,),
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np.float32))
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with self.assertRaises(RuntimeError):
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f()
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jax.effects_barrier()
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def test_callback_with_wrong_dtype_outputs(self):
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def _cb():
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return np.array([1], np.float64)
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@jax.jit
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def f():
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# Calling a function expected a f32 return value but getting f64
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return callback(_cb, core.ShapedArray((1,), np.float32))
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with self.assertRaises(RuntimeError):
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f()
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jax.effects_barrier()
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def test_callback_with_single_return_value(self):
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if xla_bridge.get_backend().runtime_type == 'stream_executor':
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raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
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@jax.jit
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def f():
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return callback(lambda: np.ones(4, np.float32),
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core.ShapedArray((4,), np.float32))
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out = f()
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jax.effects_barrier()
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np.testing.assert_allclose(out, np.ones(4, np.float32))
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def test_callback_with_multiple_return_values(self):
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if xla_bridge.get_backend().runtime_type == 'stream_executor':
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raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
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@jax.jit
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def f():
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return callback(lambda: (np.ones(4, np.float32), np.ones(5, np.int32)),
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(core.ShapedArray(
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(4,), np.float32), core.ShapedArray((5,), np.int32)))
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x, y = f()
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jax.effects_barrier()
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np.testing.assert_allclose(x, np.ones(4, np.float32))
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np.testing.assert_allclose(y, np.ones(5, np.int32))
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def test_callback_with_multiple_arguments_and_return_values(self):
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if xla_bridge.get_backend().runtime_type == 'stream_executor':
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raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
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def _callback(x, y, z):
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return (x, y + z)
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@jax.jit
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def f(x, y, z):
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return callback(_callback, (core.ShapedArray(
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(3,), x.dtype), core.ShapedArray((3,), x.dtype)), x, y, z)
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x, y = f(jnp.ones(3), jnp.arange(3.), jnp.arange(3.) + 1.)
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np.testing.assert_allclose(x, np.ones(3))
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np.testing.assert_allclose(y, np.array([1., 3., 5]))
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def test_send_recv_zero_dim_arrays(self):
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def _callback(x):
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return x
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@jax.jit
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def f(x):
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return callback(_callback, core.ShapedArray((0,), np.float32), x)
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if jax.default_backend() == "tpu":
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with self.assertRaisesRegex(
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NotImplementedError,
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"Callbacks with zero-dimensional values not supported on TPU."):
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f(jnp.zeros(0, jnp.float32))
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jax.effects_barrier()
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else:
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np.testing.assert_allclose(
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f(jnp.zeros(0, jnp.float32)), np.zeros(0, np.float32))
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def test_callback_with_pytree_arguments_and_return_values(self):
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if xla_bridge.get_backend().runtime_type == 'stream_executor':
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raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
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def _callback(x):
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return dict(y=[x])
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@jax.jit
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def f(x):
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return callback(_callback, dict(y=[core.ShapedArray((), np.float32)]),
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[x])
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out = f(jnp.float32(2.))
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jax.effects_barrier()
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self.assertEqual(out, dict(y=[2.]))
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def test_callback_inside_of_while_loop_of_scalars(self):
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if xla_bridge.get_backend().runtime_type == 'stream_executor':
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raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
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def _callback(x):
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return (x + 1.).astype(x.dtype)
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@jax.jit
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def f(x):
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def cond(x):
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return x < 10
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def body(x):
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return callback(_callback, core.ShapedArray((), x.dtype), x)
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return lax.while_loop(cond, body, x)
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out = f(0.)
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jax.effects_barrier()
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self.assertEqual(out, 10.)
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def test_callback_inside_of_while_loop(self):
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if xla_bridge.get_backend().runtime_type == 'stream_executor':
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raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
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def _callback(x):
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return (x + 1.).astype(x.dtype)
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@jax.jit
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def f(x):
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def cond(x):
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return jnp.any(x < 10)
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def body(x):
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return callback(_callback, core.ShapedArray(x.shape, x.dtype), x)
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return lax.while_loop(cond, body, x)
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out = f(jnp.arange(5.))
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jax.effects_barrier()
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np.testing.assert_allclose(out, jnp.arange(10., 15.))
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def test_callback_inside_of_cond_of_scalars(self):
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if xla_bridge.get_backend().runtime_type == 'stream_executor':
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raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
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def _callback1(x):
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return (x + 1.).astype(x.dtype)
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def _callback2(x):
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return (x - 1.).astype(x.dtype)
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@jax.jit
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def f(pred, x):
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def true_fun(x):
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return callback(_callback1, core.ShapedArray((), x.dtype), x)
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def false_fun(x):
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return callback(_callback2, core.ShapedArray((), x.dtype), x)
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return lax.cond(pred, true_fun, false_fun, x)
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out = f(True, 1.)
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jax.effects_barrier()
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self.assertEqual(out, 2.)
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out = f(False, 1.)
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jax.effects_barrier()
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self.assertEqual(out, 0.)
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def test_callback_inside_of_cond(self):
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if xla_bridge.get_backend().runtime_type == 'stream_executor':
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raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
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def _callback1(x):
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return x + 1.
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def _callback2(x):
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return x - 1.
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@jax.jit
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def f(pred, x):
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def true_fun(x):
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return callback(_callback1, core.ShapedArray(x.shape, x.dtype), x)
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def false_fun(x):
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return callback(_callback2, core.ShapedArray(x.shape, x.dtype), x)
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return lax.cond(pred, true_fun, false_fun, x)
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out = f(True, jnp.ones(2))
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jax.effects_barrier()
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np.testing.assert_allclose(out, jnp.ones(2) * 2.)
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out = f(False, jnp.ones(2))
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jax.effects_barrier()
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np.testing.assert_allclose(out, jnp.zeros(2))
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def test_callback_inside_of_scan_of_scalars(self):
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if xla_bridge.get_backend().runtime_type == 'stream_executor':
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raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
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def _callback(x):
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return (x + 1.).astype(x.dtype)
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@jax.jit
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def f(x):
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def body(x, _):
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x = callback(_callback, core.ShapedArray(x.shape, x.dtype), x)
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return x, ()
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return lax.scan(body, x, jnp.arange(10))[0]
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out = f(0.)
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jax.effects_barrier()
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self.assertEqual(out, 10.)
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def test_callback_inside_of_scan(self):
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if xla_bridge.get_backend().runtime_type == 'stream_executor':
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raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
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def _callback(x):
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return x + 1.
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@jax.jit
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def f(x):
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def body(x, _):
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x = callback(_callback, core.ShapedArray(x.shape, x.dtype), x)
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return x, ()
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return lax.scan(body, x, jnp.arange(10))[0]
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out = f(jnp.arange(2.))
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jax.effects_barrier()
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np.testing.assert_allclose(out, jnp.arange(2.) + 10.)
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def test_callback_inside_of_pmap_of_scalars(self):
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if xla_bridge.get_backend().runtime_type == 'stream_executor':
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raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
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def _callback(x):
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return (x + 1.).astype(x.dtype)
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@jax.pmap
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def f(x):
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return callback(_callback, core.ShapedArray(x.shape, x.dtype), x)
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out = f(jnp.arange(jax.local_device_count(), dtype=jnp.float32))
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jax.effects_barrier()
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np.testing.assert_allclose(
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out, np.arange(jax.local_device_count(), dtype=np.float32) + 1.)
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def test_callback_inside_of_pmap(self):
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if xla_bridge.get_backend().runtime_type == 'stream_executor':
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raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
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def _callback(x):
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return x + 1.
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@jax.pmap
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def f(x):
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return callback(_callback, core.ShapedArray(x.shape, x.dtype), x)
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out = f(
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jnp.arange(2 * jax.local_device_count(),
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dtype=jnp.float32).reshape([-1, 2]))
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jax.effects_barrier()
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np.testing.assert_allclose(
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out,
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np.arange(2 * jax.local_device_count()).reshape([-1, 2]) + 1.)
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@jtu.pytest_mark_if_available('pjrt_c_api_unimplemented') # host callback
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class PurePythonCallbackTest(jtu.JaxTestCase):
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def tearDown(self):
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super().tearDown()
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dispatch.runtime_tokens.clear()
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def test_pure_callback_passes_ndarrays_without_jit(self):
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if xla_bridge.get_backend().runtime_type == 'stream_executor':
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raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
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def cb(x):
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self.assertIs(type(x), np.ndarray)
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return x
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def f(x):
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return jax.pure_callback(cb, x, x)
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f(jnp.array(2.))
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def test_simple_pure_callback(self):
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if xla_bridge.get_backend().runtime_type == 'stream_executor':
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raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
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@jax.jit
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def f(x):
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return jax.pure_callback(lambda x: (x * 2.).astype(x.dtype), x, x)
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self.assertEqual(f(2.), 4.)
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def test_can_dce_pure_callback(self):
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if jax.default_backend() == "tpu":
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raise unittest.SkipTest("DCE doesn't currently happen on TPU")
|
|
|
|
log = []
|
|
def _callback(x):
|
|
# Should never happen!
|
|
log.append("hello world")
|
|
return (x * 2.).astype(x.dtype)
|
|
|
|
@jax.jit
|
|
def f(x):
|
|
_ = jax.pure_callback(_callback, x, x)
|
|
return x * 2.
|
|
_ = f(2.)
|
|
self.assertEmpty(log)
|
|
|
|
def test_callback_with_wrong_number_of_args(self):
|
|
|
|
@jax.jit
|
|
def f():
|
|
# Calling a function that expects `x` with no arguments
|
|
return jax.pure_callback(lambda x: np.ones(4, np.float32),
|
|
core.ShapedArray((4,), np.float32))
|
|
|
|
with self.assertRaises(RuntimeError):
|
|
f()
|
|
jax.effects_barrier()
|
|
|
|
def test_callback_with_wrong_number_of_returned_values(self):
|
|
|
|
@jax.jit
|
|
def f(x):
|
|
# Calling a function with two return values that expects one return value
|
|
return jax.pure_callback(lambda x: (x, np.ones(4, np.float32)), x, x)
|
|
|
|
with self.assertRaises(RuntimeError):
|
|
f(2.)
|
|
jax.effects_barrier()
|
|
|
|
@jax.jit
|
|
def g():
|
|
return jax.pure_callback(lambda: (), (
|
|
core.ShapedArray((1,), np.float32), core.ShapedArray((2,), np.float32)))
|
|
|
|
with self.assertRaises(RuntimeError):
|
|
g()
|
|
jax.effects_barrier()
|
|
|
|
def test_callback_with_wrong_shape_outputs(self):
|
|
|
|
@jax.jit
|
|
def f():
|
|
# Calling a function expected a (1,) shaped return value but getting ()
|
|
return jax.pure_callback(lambda: np.float32(1.),
|
|
core.ShapedArray((1,), np.float32))
|
|
|
|
with self.assertRaises(RuntimeError):
|
|
f()
|
|
jax.effects_barrier()
|
|
|
|
def test_callback_with_wrong_dtype_outputs(self):
|
|
|
|
def _cb():
|
|
return np.array([1], np.float64)
|
|
|
|
@jax.jit
|
|
def f():
|
|
# Calling a function expected a f32 return value but getting f64
|
|
return callback(_cb, core.ShapedArray((1,), np.float32))
|
|
|
|
with self.assertRaises(RuntimeError):
|
|
f()
|
|
jax.effects_barrier()
|
|
|
|
def test_callback_with_wrongly_specified_64_bit_dtype(self):
|
|
if config.jax_enable_x64:
|
|
raise unittest.SkipTest("Test only needed when 64-bit mode disabled.")
|
|
|
|
@jax.jit
|
|
def f():
|
|
return jax.pure_callback(lambda: np.float64(1.),
|
|
core.ShapedArray((), np.float64))
|
|
|
|
with self.assertRaises(ValueError):
|
|
f()
|
|
jax.effects_barrier()
|
|
|
|
def test_can_vmap_pure_callback(self):
|
|
if xla_bridge.get_backend().runtime_type == 'stream_executor':
|
|
raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
|
|
|
|
@jax.jit
|
|
@jax.vmap
|
|
def f(x):
|
|
return jax.pure_callback(np.sin, x, x)
|
|
out = f(jnp.arange(4.))
|
|
np.testing.assert_allclose(out, np.sin(np.arange(4.)))
|
|
|
|
@jax.jit
|
|
def g(x):
|
|
return jax.pure_callback(np.sin, x, x)
|
|
out = jax.vmap(g, in_axes=1)(jnp.arange(8.).reshape((4, 2)))
|
|
np.testing.assert_allclose(out, np.sin(np.arange(8.).reshape((4, 2))).T)
|
|
|
|
@jax.jit
|
|
@functools.partial(jax.vmap, in_axes=(0, None))
|
|
def h(x, y):
|
|
out_shape = jax.ShapeDtypeStruct(x.shape, np.result_type(x.dtype, y.dtype))
|
|
return jax.pure_callback(lambda x, y: np.sin(x) + y, out_shape, x, y)
|
|
out = h(jnp.arange(4.), 4.)
|
|
self.assertArraysAllClose(out, np.sin(np.arange(4.)) + 4.,
|
|
rtol=1E-7, check_dtypes=False)
|
|
|
|
@jax.jit
|
|
@functools.partial(jax.vmap)
|
|
def h(x, y):
|
|
out_shape = jax.ShapeDtypeStruct(x.shape, np.result_type(x.dtype, y.dtype))
|
|
return jax.pure_callback(lambda x, y: np.sin(x) + y, out_shape, x, y)
|
|
out = h(jnp.arange(4.), jnp.arange(10., 14.))
|
|
self.assertArraysAllClose(out, np.sin(np.arange(4.)) + np.arange(10., 14.),
|
|
rtol=1E-7, check_dtypes=False)
|
|
|
|
def test_vmap_vectorized_callback(self):
|
|
if xla_bridge.get_backend().runtime_type == 'stream_executor':
|
|
raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
|
|
|
|
def cb(x):
|
|
self.assertTupleEqual(x.shape, ())
|
|
return np.sin(x)
|
|
|
|
@jax.jit
|
|
@jax.vmap
|
|
def f(x):
|
|
return jax.pure_callback(cb, x, x)
|
|
|
|
np.testing.assert_allclose(f(jnp.arange(4.)), np.sin(np.arange(4.)))
|
|
|
|
def cb2(x):
|
|
self.assertTupleEqual(x.shape, (4,))
|
|
return np.sin(x)
|
|
|
|
@jax.jit
|
|
@jax.vmap
|
|
def g(x):
|
|
return jax.pure_callback(cb2, x, x, vectorized=True)
|
|
|
|
np.testing.assert_allclose(g(jnp.arange(4.)), np.sin(np.arange(4.)))
|
|
|
|
@jax.jit
|
|
@functools.partial(jax.vmap, in_axes=(0, None))
|
|
def h(x, y):
|
|
return jax.pure_callback(lambda x, y: np.sin(x) + y, x, x, y,
|
|
vectorized=True)
|
|
out = h(jnp.arange(4.), 4.)
|
|
np.testing.assert_allclose(out, np.sin(np.arange(4.)) + 4.)
|
|
|
|
def test_vmap_vectorized_callback_errors_if_returns_wrong_shape(self):
|
|
|
|
def cb(x):
|
|
# Reduces over all dimension when it shouldn't
|
|
return np.sin(x).sum()
|
|
|
|
@jax.jit
|
|
@jax.vmap
|
|
def f(x):
|
|
return jax.pure_callback(cb, x, x, vectorized=True)
|
|
|
|
with self.assertRaises(RuntimeError):
|
|
f(jnp.arange(4.))
|
|
jax.effects_barrier()
|
|
|
|
def test_can_pmap_pure_callback(self):
|
|
if xla_bridge.get_backend().runtime_type == 'stream_executor':
|
|
raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
|
|
|
|
@jax.pmap
|
|
def f(x):
|
|
return jax.pure_callback(np.sin, x, x)
|
|
out = f(jnp.arange(float(jax.local_device_count())))
|
|
np.testing.assert_allclose(out, np.sin(np.arange(jax.local_device_count())))
|
|
|
|
def test_can_pjit_pure_callback_under_hard_xmap(self):
|
|
if xla_bridge.get_backend().runtime_type == 'stream_executor':
|
|
raise unittest.SkipTest(
|
|
'Host callback not supported for runtime type: stream_executor.'
|
|
)
|
|
|
|
if not hasattr(xla_client.OpSharding.Type, 'MANUAL'):
|
|
raise unittest.SkipTest('Manual partitioning needed for pure_callback')
|
|
|
|
jtu.set_spmd_lowering_flag(True)
|
|
jtu.set_spmd_manual_lowering_flag(True)
|
|
try:
|
|
mesh = Mesh(np.array(jax.devices()), axis_names=('x',))
|
|
|
|
spec = jax.sharding.PartitionSpec('x')
|
|
|
|
def f(x):
|
|
axis_resources = {v: v for v in mesh.axis_names}
|
|
return xmap(
|
|
lambda x: jax.pure_callback(np.sin, x, x),
|
|
in_axes=(('x',),),
|
|
out_axes=('x',),
|
|
axis_resources=axis_resources,
|
|
axis_sizes=mesh.shape,
|
|
)(x)
|
|
|
|
def without_xmap_f(x):
|
|
return jax.pure_callback(np.sin, x, x)
|
|
|
|
with mesh:
|
|
inp = jnp.arange(float(jax.local_device_count()))
|
|
out = pjit.pjit(f, in_shardings=spec, out_shardings=spec)(inp)
|
|
np.testing.assert_allclose(
|
|
out, np.sin(np.arange(jax.local_device_count()))
|
|
)
|
|
|
|
if jax.local_device_count() > 1:
|
|
with self.assertRaisesRegex(
|
|
NotImplementedError, 'when all mesh axes are partitioned manually'
|
|
):
|
|
pjit.pjit(without_xmap_f, in_shardings=spec, out_shardings=spec)(
|
|
inp
|
|
)
|
|
|
|
finally:
|
|
jtu.restore_spmd_manual_lowering_flag()
|
|
jtu.restore_spmd_lowering_flag()
|
|
|
|
def test_cant_take_grad_of_pure_callback(self):
|
|
|
|
def sin(x):
|
|
return np.sin(x)
|
|
|
|
@jax.jit
|
|
@jax.grad
|
|
def f(x):
|
|
return jax.pure_callback(sin, x, x)
|
|
with self.assertRaisesRegex(
|
|
ValueError, "Pure callbacks do not support JVP."):
|
|
f(2.)
|
|
|
|
def test_can_take_grad_of_pure_callback_with_custom_jvp(self):
|
|
if xla_bridge.get_backend().runtime_type == 'stream_executor':
|
|
raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
|
|
|
|
@jax.custom_jvp
|
|
def sin(x):
|
|
return jax.pure_callback(np.sin, x, x)
|
|
|
|
@sin.defjvp
|
|
def sin_jvp(xs, ts):
|
|
(x,), (t,), = xs, ts
|
|
return sin(x), jax.pure_callback(np.cos, x, x) * t
|
|
|
|
@jax.jit
|
|
@jax.grad
|
|
def f(x):
|
|
return sin(x)
|
|
out = f(2.)
|
|
np.testing.assert_allclose(out, jnp.cos(2.))
|
|
|
|
def test_callback_inside_of_cond(self):
|
|
if xla_bridge.get_backend().runtime_type == 'stream_executor':
|
|
raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
|
|
|
|
def _callback1(x):
|
|
return x + 1.
|
|
|
|
def _callback2(x):
|
|
return x - 1.
|
|
|
|
@jax.jit
|
|
def f(pred, x):
|
|
|
|
def true_fun(x):
|
|
return jax.pure_callback(_callback1, x, x)
|
|
|
|
def false_fun(x):
|
|
return jax.pure_callback(_callback2, x, x)
|
|
|
|
return lax.cond(pred, true_fun, false_fun, x)
|
|
|
|
out = f(True, jnp.ones(2))
|
|
np.testing.assert_allclose(out, jnp.ones(2) * 2.)
|
|
out = f(False, jnp.ones(2))
|
|
np.testing.assert_allclose(out, jnp.zeros(2))
|
|
|
|
def test_callback_inside_of_scan(self):
|
|
if xla_bridge.get_backend().runtime_type == 'stream_executor':
|
|
raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
|
|
|
|
def _callback(x):
|
|
return x + 1.
|
|
|
|
@jax.jit
|
|
def f(x):
|
|
|
|
def body(x, _):
|
|
x = jax.pure_callback(_callback, x, x)
|
|
return x, ()
|
|
|
|
return lax.scan(body, x, jnp.arange(10))[0]
|
|
|
|
out = f(jnp.arange(2.))
|
|
np.testing.assert_allclose(out, jnp.arange(2.) + 10.)
|
|
|
|
def test_callback_inside_of_while_loop(self):
|
|
if xla_bridge.get_backend().runtime_type == 'stream_executor':
|
|
raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
|
|
|
|
def _cond_callback(x):
|
|
return np.any(x < 10)
|
|
|
|
def _callback(x):
|
|
return (x + 1.).astype(x.dtype)
|
|
|
|
@jax.jit
|
|
def f(x):
|
|
|
|
def cond(x):
|
|
return jax.pure_callback(
|
|
_cond_callback, jax.ShapeDtypeStruct((), np.bool_), x)
|
|
|
|
def body(x):
|
|
return jax.pure_callback(_callback, x, x)
|
|
|
|
return lax.while_loop(cond, body, x)
|
|
|
|
out = f(jnp.arange(5.))
|
|
np.testing.assert_allclose(out, jnp.arange(10., 15.))
|
|
|
|
def test_callback_inside_of_pmap(self):
|
|
if xla_bridge.get_backend().runtime_type == 'stream_executor':
|
|
raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
|
|
|
|
def _callback(x):
|
|
return x + 1.
|
|
|
|
@jax.pmap
|
|
def f(x):
|
|
return jax.pure_callback(_callback, x, x)
|
|
|
|
out = f(
|
|
jnp.arange(2 * jax.local_device_count(),
|
|
dtype=jnp.float32).reshape([-1, 2]))
|
|
np.testing.assert_allclose(
|
|
out,
|
|
np.arange(2 * jax.local_device_count()).reshape([-1, 2]) + 1.)
|
|
|
|
def test_callback_inside_xmap(self):
|
|
if xla_bridge.get_backend().runtime_type == 'stream_executor':
|
|
raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
|
|
|
|
def _callback(x):
|
|
return (x + 1.).astype(x.dtype)
|
|
|
|
def f(x):
|
|
return jax.pure_callback(_callback, x, x)
|
|
|
|
f = maps.xmap(f, in_axes=['a'], out_axes=['a'],
|
|
axis_resources={'a': 'dev'})
|
|
with jax.sharding.Mesh(np.array(jax.devices()), ['dev']):
|
|
out = f(np.arange(40.))
|
|
np.testing.assert_allclose(out, jnp.arange(1., 41.))
|
|
|
|
def test_vectorized_callback_inside_xmap(self):
|
|
if xla_bridge.get_backend().runtime_type == 'stream_executor':
|
|
raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
|
|
|
|
def _callback(x):
|
|
return (x + 1.).astype(x.dtype)
|
|
|
|
def f(x):
|
|
return jax.pure_callback(_callback, x, x, vectorized=True)
|
|
|
|
f = maps.xmap(f, in_axes=['a'], out_axes=['a'],
|
|
axis_resources={'a': 'dev'})
|
|
with jax.sharding.Mesh(np.array(jax.devices()), ['dev']):
|
|
out = f(np.arange(40.))
|
|
np.testing.assert_allclose(out, jnp.arange(1., 41.))
|
|
|
|
def test_array_layout_is_preserved(self):
|
|
if xla_bridge.get_backend().runtime_type == 'stream_executor':
|
|
raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
|
|
|
|
def g(x):
|
|
return jax.pure_callback(lambda x: x, x, x)
|
|
|
|
x = np.arange(6, dtype=np.int32).reshape((3, 2))
|
|
np.testing.assert_allclose(g(x), x)
|
|
|
|
@jtu.pytest_mark_if_available('pjrt_c_api_unimplemented') # host callback
|
|
class IOPythonCallbackTest(jtu.JaxTestCase):
|
|
|
|
def setUp(self):
|
|
super().setUp()
|
|
if xla_bridge.get_backend().runtime_type == 'stream_executor':
|
|
raise unittest.SkipTest('Host callback not supported for runtime type: stream_executor.')
|
|
|
|
def tearDown(self):
|
|
super().tearDown()
|
|
dispatch.runtime_tokens.clear()
|
|
|
|
def test_io_callback_can_mutate_state(self):
|
|
x = 0
|
|
def cb():
|
|
nonlocal x
|
|
x += 1
|
|
return np.array(x, np.int32)
|
|
|
|
def f():
|
|
return io_callback(cb, jax.ShapeDtypeStruct((), jnp.int32))
|
|
f()
|
|
jax.effects_barrier()
|
|
self.assertEqual(x, 1)
|
|
f()
|
|
jax.effects_barrier()
|
|
self.assertEqual(x, 2)
|
|
|
|
def test_io_callback_can_be_batched_if_unordered(self):
|
|
_mut = 0
|
|
def cb(x):
|
|
nonlocal _mut
|
|
_mut += 1
|
|
return x
|
|
|
|
x = jnp.arange(4)
|
|
def f(x):
|
|
return io_callback(cb, jax.ShapeDtypeStruct((), x.dtype), x)
|
|
jax.vmap(f)(x)
|
|
jax.effects_barrier()
|
|
self.assertEqual(_mut, 4)
|
|
jax.vmap(f)(x)
|
|
jax.effects_barrier()
|
|
self.assertEqual(_mut, 8)
|
|
|
|
def test_cannot_call_ordered_io_in_pmap(self):
|
|
def f(x):
|
|
return io_callback(
|
|
lambda x: x, jax.ShapeDtypeStruct((), jnp.int32), x, ordered=True)
|
|
with self.assertRaisesRegex(
|
|
ValueError, "Ordered effects not supported in `pmap`"):
|
|
jax.pmap(f)(jnp.arange(jax.local_device_count()))
|
|
|
|
def test_cannot_call_ordered_io_in_xmap(self):
|
|
def f(x):
|
|
return io_callback(
|
|
lambda x: x, jax.ShapeDtypeStruct((), jnp.int32), x, ordered=True)
|
|
with self.assertRaisesRegex(
|
|
ValueError, "Cannot `vmap` ordered IO callback"):
|
|
maps.xmap(f, in_axes=([0],), out_axes=[0])(jnp.arange(16))
|
|
|
|
def test_cannot_call_ordered_io_in_vmap(self):
|
|
def f(x):
|
|
return io_callback(
|
|
lambda x: x, jax.ShapeDtypeStruct((), jnp.int32), x, ordered=True)
|
|
with self.assertRaisesRegex(
|
|
ValueError, "Cannot `vmap` ordered IO callback"):
|
|
jax.vmap(f)(jnp.arange(4))
|
|
|
|
def test_cannot_use_io_callback_in_jvp(self):
|
|
def f(x):
|
|
return io_callback(lambda x: x, jax.ShapeDtypeStruct((), jnp.float32), x)
|
|
with self.assertRaisesRegex(
|
|
ValueError, "IO callbacks do not support JVP."):
|
|
jax.jvp(f, (0.,), (1.,))
|
|
|
|
def test_cannot_use_io_callback_in_linearize(self):
|
|
def f(x):
|
|
return io_callback(lambda x: x, jax.ShapeDtypeStruct((), jnp.float32), x)
|
|
with self.assertRaisesRegex(
|
|
ValueError, "IO callbacks do not support JVP."):
|
|
jax.linearize(f, 0.)
|
|
|
|
def test_cannot_use_io_callback_in_transpose(self):
|
|
x = jnp.array(1.)
|
|
|
|
def f(x):
|
|
return io_callback(lambda x: x, jax.ShapeDtypeStruct((), x.dtype), x)
|
|
with self.assertRaisesRegex(
|
|
ValueError, "IO callbacks do not support transpose."):
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jax.linear_transpose(f, x)(x)
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|
|
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def test_cannot_vmap_of_cond_io_callback(self):
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def f(pred):
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def true_fun():
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io_callback(lambda: print("true"), None)
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def false_fun():
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|
io_callback(lambda: print("false"), None)
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|
return lax.cond(pred, false_fun, true_fun)
|
|
with self.assertRaisesRegex(NotImplementedError,
|
|
"IO effect not supported in vmap-of-cond."):
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|
jax.vmap(f)(jnp.array([True, True]))
|
|
|
|
def test_cannot_vmap_of_while_io_callback(self):
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|
def check(x):
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|
assert np.all(x < 5)
|
|
|
|
def f(i):
|
|
def cond(i):
|
|
return i < 5
|
|
def body(i):
|
|
io_callback(check, None, i)
|
|
return i + 1
|
|
return lax.while_loop(cond, body, i)
|
|
with self.assertRaisesRegex(NotImplementedError,
|
|
"IO effect not supported in vmap-of-while."):
|
|
jax.vmap(f)(jnp.array([0, 4]))
|
|
|
|
def test_cannot_use_io_callback_in_checkpoint(self):
|
|
@jax.grad
|
|
@jax.checkpoint
|
|
def f(x, y):
|
|
io_callback(lambda x: x, y, y)
|
|
return x
|
|
|
|
with self.assertRaisesRegex(NotImplementedError,
|
|
"Effects not supported in partial-eval of `checkpoint`"):
|
|
f(2., 3.)
|
|
|
|
def test_can_use_io_callback_in_pjit(self):
|
|
|
|
_mut = 0
|
|
def _cb(x):
|
|
nonlocal _mut
|
|
_mut = x.sum()
|
|
|
|
def f(x):
|
|
io_callback(_cb, None, x)
|
|
return x
|
|
|
|
mesh = jax.sharding.Mesh(np.array(jax.devices()), ['dev'])
|
|
if config.jax_array:
|
|
spec = sharding.NamedSharding(mesh, jax.sharding.PartitionSpec('dev'))
|
|
out_spec = sharding.NamedSharding(mesh, jax.sharding.PartitionSpec())
|
|
else:
|
|
spec = jax.sharding.PartitionSpec('dev')
|
|
out_spec = jax.sharding.PartitionSpec()
|
|
f = pjit.pjit(f, in_shardings=spec, out_shardings=out_spec)
|
|
with mesh:
|
|
f(jnp.arange(mesh.size))
|
|
jax.effects_barrier()
|
|
self.assertEqual(_mut, jnp.arange(mesh.size).sum())
|
|
|
|
if __name__ == "__main__":
|
|
absltest.main(testLoader=jtu.JaxTestLoader())
|