rocm_jax/jax/api_util.py
Matthew Johnson b9d72a480f improve concreteness error from arguments
also tweak some error message wording
2021-05-03 17:37:34 -07:00

306 lines
11 KiB
Python

# 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.
import operator
from functools import partial
from typing import Any, Dict, Iterable, Tuple, Union, Optional
import numpy as np
from . import core
from ._src import dtypes
from .tree_util import (tree_flatten, tree_unflatten, tree_multimap,
tree_structure, treedef_children, treedef_is_leaf)
from ._src.tree_util import _replace_nones
from . import linear_util as lu
from ._src.util import safe_map, WrapHashably, WrapKwArgs, Hashable
from .core import unit
from ._src import traceback_util
traceback_util.register_exclusion(__file__)
map = safe_map
def _ensure_index(x: Any) -> Union[int, Tuple[int, ...]]:
"""Ensure x is either an index or a tuple of indices."""
try:
return operator.index(x)
except TypeError:
return tuple(map(operator.index, x))
def _ensure_index_tuple(x: Any) -> Tuple[int, ...]:
"""Convert x to a tuple of indices."""
try:
return (operator.index(x),)
except TypeError:
return tuple(map(operator.index, x))
def _ensure_str(x: str) -> str:
if not isinstance(x, str):
raise TypeError(f"argument is not a string: {x}")
return x
def _ensure_str_tuple(x: Union[str, Iterable[str]]) -> Tuple[str, ...]:
"""Convert x to a tuple of strings."""
if isinstance(x, str):
return (x,)
else:
return tuple(map(_ensure_str, x))
@lu.transformation_with_aux
def flatten_fun(in_tree, *args_flat):
py_args, py_kwargs = tree_unflatten(in_tree, args_flat)
ans = yield py_args, py_kwargs
yield tree_flatten(ans)
def apply_flat_fun(fun, io_tree, *py_args):
in_tree_expected, out_tree = io_tree
args, in_tree = tree_flatten((py_args, {}))
if in_tree != in_tree_expected:
raise TypeError("Expected {}, got {}".format(in_tree_expected, in_tree))
ans = fun(*args)
return tree_unflatten(out_tree, ans)
@lu.transformation_with_aux
def flatten_fun_nokwargs(in_tree, *args_flat):
py_args = tree_unflatten(in_tree, args_flat)
ans = yield py_args, {}
yield tree_flatten(ans)
def apply_flat_fun_nokwargs(fun, io_tree, py_args):
in_tree_expected, out_tree = io_tree
args, in_tree = tree_flatten(py_args)
if in_tree != in_tree_expected:
raise TypeError("Expected {}, got {}".format(in_tree_expected, in_tree))
ans = fun(*args)
return tree_unflatten(out_tree, ans)
PyTreeDef = Any
def flattened_fun_in_tree(fn: lu.WrappedFun) -> Optional[Tuple[PyTreeDef, bool]]:
# This implementation relies on internal details of linear_util.py's
# WrappedFun, but it's for the worthy cause of better user error messages.
# It can fail (i.e. return None) if its WrappedFun argument is not transformed
# with flatten_fun or flatten_fun_nokwargs, which could happen e.g. when
# core.eval_jaxpr encounters a call primitive (though at that point we're just
# round-tripping jaxprs and the user errors in question are impossible).
assert isinstance(flatten_fun, partial) and len(flatten_fun.args) == 1
assert (isinstance(flatten_fun_nokwargs, partial) and
len(flatten_fun_nokwargs.args) == 1)
flat_xforms = {flatten_fun.args[0], flatten_fun_nokwargs.args[0]}
try:
(in_tree, has_kwargs), = ((args[0], f is flatten_fun.args[0])
for f, args in fn.transforms if f in flat_xforms)
except ValueError:
return None
else:
return in_tree, has_kwargs
@lu.transformation_with_aux
def flatten_fun_nokwargs2(in_tree, *args_flat):
py_args = tree_unflatten(in_tree, args_flat)
pair = yield py_args, {}
if not isinstance(pair, (list, tuple)) or len(pair) != 2:
raise TypeError("expected function with aux output to return a two-element "
f"tuple, but got type {type(pair)} with value {repr(pair)}")
ans, aux = pair
ans_flat, ans_tree = tree_flatten(ans)
aux_flat, aux_tree = tree_flatten(aux)
yield (ans_flat, aux_flat), (ans_tree, aux_tree)
def argnums_partial(f, dyn_argnums, args):
dyn_argnums = _ensure_index_tuple(dyn_argnums)
fixed_args = tuple(unit if i in dyn_argnums else wrap_hashably(arg)
for i, arg in enumerate(args))
dyn_args = tuple(args[i] for i in dyn_argnums)
return _argnums_partial(f, dyn_argnums, fixed_args), dyn_args
def argnums_partial_except(f: lu.WrappedFun, static_argnums: Tuple[int, ...],
args: Tuple[Any], *, allow_invalid: bool):
"""Version of ``argnums_partial`` that checks hashability of static_argnums."""
if not static_argnums:
return f, args
dyn_argnums = tuple(i for i in range(len(args)) if i not in static_argnums)
dyn_args = tuple(args[i] for i in dyn_argnums)
fixed_args = [unit] * len(args) # type: ignore
for i in static_argnums:
# TODO(shoyer): set allow_invalid=True permanently after enabling
# static_argnames.
if allow_invalid and i >= len(args):
continue
static_arg = args[i]
try:
hash(static_arg)
except TypeError:
raise ValueError(
"Non-hashable static arguments are not supported, as this can lead "
f"to unexpected cache-misses. Static argument (index {i}) of type "
f"{type(static_arg)} for function {f.__name__} is non-hashable.")
else:
fixed_args[i] = Hashable(static_arg) # type: ignore
return _argnums_partial(f, dyn_argnums, tuple(fixed_args)), dyn_args
@lu.transformation
def _argnums_partial(dyn_argnums, fixed_args, *dyn_args, **kwargs):
args = [None if arg is unit else arg.val for arg in fixed_args]
for i, arg in zip(dyn_argnums, dyn_args):
args[i] = arg
ans = yield args, kwargs
yield ans
def argnames_partial(f, dyn_argnames, kwargs):
dyn_argnames = _ensure_str_tuple(dyn_argnames)
fixed_kwargs = tuple((k, unit if k in dyn_argnames else wrap_hashably(v))
for k, v in kwargs.items())
dyn_kwargs = {k: kwargs[k] for k in dyn_argnames}
return _argnames_partial(f, WrapKwArgs(fixed_kwargs)), dyn_kwargs
def argnames_partial_except(f: lu.WrappedFun, static_argnames: Tuple[str, ...],
kwargs: Dict[str, Any]):
if not static_argnames:
return f, kwargs
dyn_kwargs = {k: v for k, v in kwargs.items() if k not in static_argnames}
fixed_kwargs: Dict[str, Any] = {}
for k, arg in kwargs.items():
if k in dyn_kwargs:
fixed_kwargs[k] = unit
else:
try:
hash(arg)
except TypeError:
raise ValueError(
"Non-hashable static arguments are not supported, as this can lead "
f"to unexpected cache-misses. Static argument (name {k}) of type "
f"{type(arg)} for function {f.__name__} is non-hashable.")
else:
fixed_kwargs[k] = Hashable(arg) # type: ignore
return _argnames_partial(f, WrapKwArgs(fixed_kwargs)), dyn_kwargs
@lu.transformation
def _argnames_partial(fixed_kwargs: WrapKwArgs, *args, **dyn_kwargs):
kwargs = {k: None if arg is unit else arg.val
for k, arg in fixed_kwargs.val.items()}
kwargs.update(dyn_kwargs)
ans = yield args, kwargs
yield ans
def donation_vector(donate_argnums, args, kwargs) -> Tuple[bool, ...]:
"""Returns a tuple with a boolean value for each leaf in args."""
res = []
for i, arg in enumerate(args):
donate = bool(i in donate_argnums)
res.extend((donate,) * tree_structure(arg).num_leaves)
res.extend((False,) * tree_structure(kwargs).num_leaves)
return tuple(res)
def rebase_donate_argnums(donate_argnums, static_argnums) -> Tuple[int, ...]:
"""Shifts donate to account for static.
>>> rebase_donate_argnums((3, 4), (0, 1))
(1, 2)
Args:
donate_argnums: An iterable of ints.
static_argnums: An iterable of ints.
Returns:
A tuple of unique, sorted integer values based on donate_argnums with each
element offset to account for static_argnums.
"""
if not (static_argnums or donate_argnums):
return tuple(sorted(donate_argnums))
static_argnums = sorted(set(static_argnums))
donate_argnums = sorted(set(donate_argnums))
i = j = o = 0
out = []
while j < len(donate_argnums):
if i < len(static_argnums) and static_argnums[i] == donate_argnums[j]:
raise ValueError(f"`static_argnums` {static_argnums} and "
f"`donate_argnums` {donate_argnums} cannot intersect.")
if i < len(static_argnums) and static_argnums[i] < donate_argnums[j]:
o += 1
i += 1
else:
out.append(donate_argnums[j] - o)
j += 1
return tuple(out)
def wrap_hashably(arg):
try:
hash(arg)
except TypeError:
return WrapHashably(arg) # e.g. ndarrays, DeviceArrays
else:
return Hashable(arg)
def flatten_axes(name, treedef, axis_tree, *, kws=False):
# given an axis spec tree axis_tree (a pytree with integers and Nones at the
# leaves, i.e. the Nones are to be considered leaves) that is a tree prefix of
# the given treedef, build a complete axis spec tree with the same structure
# and return the flattened result
# TODO(mattjj,phawkins): improve this implementation
proxy = object()
dummy = tree_unflatten(treedef, [object()] * treedef.num_leaves)
axes = []
add_leaves = lambda i, x: axes.extend([i] * len(tree_flatten(x)[0]))
try:
tree_multimap(add_leaves, _replace_nones(proxy, axis_tree), dummy)
except ValueError:
if kws:
# if keyword arguments are included in the tree, we make adapt the error
# message only to be about the positional arguments
treedef, leaf = treedef_children(treedef)
assert treedef_is_leaf(leaf)
axis_tree, _ = axis_tree
raise ValueError(f"{name} specification must be a tree prefix of the "
f"corresponding value, got specification {axis_tree} "
f"for value tree {treedef}.") from None
axes = [None if a is proxy else a for a in axes]
assert len(axes) == treedef.num_leaves
return axes
def _dtype(x):
try:
return dtypes.result_type(x)
except ValueError:
return dtypes.result_type(getattr(x, 'dtype'))
def shaped_abstractify(x):
try:
return core.raise_to_shaped(core.get_aval(x))
except TypeError:
pass
weak_type = getattr(x, 'weak_type', False)
named_shape = getattr(x, 'named_shape', {})
return core.ShapedArray(np.shape(x), _dtype(x), weak_type=weak_type,
named_shape=named_shape)
# This decorator exists to make it easier to monkey-patch APIs in JAX.
# By default it does nothing, but it can be monkey-patched to do other things.
def api_hook(fun, tag: str):
return fun