182 lines
6.9 KiB
Python
182 lines
6.9 KiB
Python
|
"""Implementation of __array_function__ overrides from NEP-18."""
|
||
|
|
import collections
|
||
|
|
import functools
|
||
|
|
import os
|
||
|
|
|
||
|
|
from .._utils import set_module
|
||
|
|
from .._utils._inspect import getargspec
|
||
|
|
from numpy.core._multiarray_umath import (
|
||
|
|
add_docstring, _get_implementing_args, _ArrayFunctionDispatcher)
|
||
|
|
|
||
|
|
|
||
|
|
ARRAY_FUNCTIONS = set()
|
||
|
|
|
||
|
|
array_function_like_doc = (
|
||
|
|
"""like : array_like, optional
|
||
|
|
Reference object to allow the creation of arrays which are not
|
||
|
|
NumPy arrays. If an array-like passed in as ``like`` supports
|
||
|
|
the ``__array_function__`` protocol, the result will be defined
|
||
|
|
by it. In this case, it ensures the creation of an array object
|
||
|
|
compatible with that passed in via this argument."""
|
||
|
|
)
|
||
|
|
|
||
|
|
def set_array_function_like_doc(public_api):
|
||
|
|
if public_api.__doc__ is not None:
|
||
|
|
public_api.__doc__ = public_api.__doc__.replace(
|
||
|
|
"${ARRAY_FUNCTION_LIKE}",
|
||
|
|
array_function_like_doc,
|
||
|
|
)
|
||
|
|
return public_api
|
||
|
|
|
||
|
|
|
||
|
|
add_docstring(
|
||
|
|
_ArrayFunctionDispatcher,
|
||
|
|
"""
|
||
|
|
Class to wrap functions with checks for __array_function__ overrides.
|
||
|
|
|
||
|
|
All arguments are required, and can only be passed by position.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
dispatcher : function or None
|
||
|
|
The dispatcher function that returns a single sequence-like object
|
||
|
|
of all arguments relevant. It must have the same signature (except
|
||
|
|
the default values) as the actual implementation.
|
||
|
|
If ``None``, this is a ``like=`` dispatcher and the
|
||
|
|
``_ArrayFunctionDispatcher`` must be called with ``like`` as the
|
||
|
|
first (additional and positional) argument.
|
||
|
|
implementation : function
|
||
|
|
Function that implements the operation on NumPy arrays without
|
||
|
|
overrides. Arguments passed calling the ``_ArrayFunctionDispatcher``
|
||
|
|
will be forwarded to this (and the ``dispatcher``) as if using
|
||
|
|
``*args, **kwargs``.
|
||
|
|
|
||
|
|
Attributes
|
||
|
|
----------
|
||
|
|
_implementation : function
|
||
|
|
The original implementation passed in.
|
||
|
|
""")
|
||
|
|
|
||
|
|
|
||
|
|
# exposed for testing purposes; used internally by _ArrayFunctionDispatcher
|
||
|
|
add_docstring(
|
||
|
|
_get_implementing_args,
|
||
|
|
"""
|
||
|
|
Collect arguments on which to call __array_function__.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
relevant_args : iterable of array-like
|
||
|
|
Iterable of possibly array-like arguments to check for
|
||
|
|
__array_function__ methods.
|
||
|
|
|
||
|
|
Returns
|
||
|
|
-------
|
||
|
|
Sequence of arguments with __array_function__ methods, in the order in
|
||
|
|
which they should be called.
|
||
|
|
""")
|
||
|
|
|
||
|
|
|
||
|
|
ArgSpec = collections.namedtuple('ArgSpec', 'args varargs keywords defaults')
|
||
|
|
|
||
|
|
|
||
|
|
def verify_matching_signatures(implementation, dispatcher):
|
||
|
|
"""Verify that a dispatcher function has the right signature."""
|
||
|
|
implementation_spec = ArgSpec(*getargspec(implementation))
|
||
|
|
dispatcher_spec = ArgSpec(*getargspec(dispatcher))
|
||
|
|
|
||
|
|
if (implementation_spec.args != dispatcher_spec.args or
|
||
|
|
implementation_spec.varargs != dispatcher_spec.varargs or
|
||
|
|
implementation_spec.keywords != dispatcher_spec.keywords or
|
||
|
|
(bool(implementation_spec.defaults) !=
|
||
|
|
bool(dispatcher_spec.defaults)) or
|
||
|
|
(implementation_spec.defaults is not None and
|
||
|
|
len(implementation_spec.defaults) !=
|
||
|
|
len(dispatcher_spec.defaults))):
|
||
|
|
raise RuntimeError('implementation and dispatcher for %s have '
|
||
|
|
'different function signatures' % implementation)
|
||
|
|
|
||
|
|
if implementation_spec.defaults is not None:
|
||
|
|
if dispatcher_spec.defaults != (None,) * len(dispatcher_spec.defaults):
|
||
|
|
raise RuntimeError('dispatcher functions can only use None for '
|
||
|
|
'default argument values')
|
||
|
|
|
||
|
|
|
||
|
|
def array_function_dispatch(dispatcher=None, module=None, verify=True,
|
||
|
|
docs_from_dispatcher=False):
|
||
|
|
"""Decorator for adding dispatch with the __array_function__ protocol.
|
||
|
|
|
||
|
|
See NEP-18 for example usage.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
dispatcher : callable or None
|
||
|
|
Function that when called like ``dispatcher(*args, **kwargs)`` with
|
||
|
|
arguments from the NumPy function call returns an iterable of
|
||
|
|
array-like arguments to check for ``__array_function__``.
|
||
|
|
|
||
|
|
If `None`, the first argument is used as the single `like=` argument
|
||
|
|
and not passed on. A function implementing `like=` must call its
|
||
|
|
dispatcher with `like` as the first non-keyword argument.
|
||
|
|
module : str, optional
|
||
|
|
__module__ attribute to set on new function, e.g., ``module='numpy'``.
|
||
|
|
By default, module is copied from the decorated function.
|
||
|
|
verify : bool, optional
|
||
|
|
If True, verify the that the signature of the dispatcher and decorated
|
||
|
|
function signatures match exactly: all required and optional arguments
|
||
|
|
should appear in order with the same names, but the default values for
|
||
|
|
all optional arguments should be ``None``. Only disable verification
|
||
|
|
if the dispatcher's signature needs to deviate for some particular
|
||
|
|
reason, e.g., because the function has a signature like
|
||
|
|
``func(*args, **kwargs)``.
|
||
|
|
docs_from_dispatcher : bool, optional
|
||
|
|
If True, copy docs from the dispatcher function onto the dispatched
|
||
|
|
function, rather than from the implementation. This is useful for
|
||
|
|
functions defined in C, which otherwise don't have docstrings.
|
||
|
|
|
||
|
|
Returns
|
||
|
|
-------
|
||
|
|
Function suitable for decorating the implementation of a NumPy function.
|
||
|
|
|
||
|
|
"""
|
||
|
|
def decorator(implementation):
|
||
|
|
if verify:
|
||
|
|
if dispatcher is not None:
|
||
|
|
verify_matching_signatures(implementation, dispatcher)
|
||
|
|
else:
|
||
|
|
# Using __code__ directly similar to verify_matching_signature
|
||
|
|
co = implementation.__code__
|
||
|
|
last_arg = co.co_argcount + co.co_kwonlyargcount - 1
|
||
|
|
last_arg = co.co_varnames[last_arg]
|
||
|
|
if last_arg != "like" or co.co_kwonlyargcount == 0:
|
||
|
|
raise RuntimeError(
|
||
|
|
"__array_function__ expects `like=` to be the last "
|
||
|
|
"argument and a keyword-only argument. "
|
||
|
|
f"{implementation} does not seem to comply.")
|
||
|
|
|
||
|
|
if docs_from_dispatcher:
|
||
|
|
add_docstring(implementation, dispatcher.__doc__)
|
||
|
|
|
||
|
|
public_api = _ArrayFunctionDispatcher(dispatcher, implementation)
|
||
|
|
public_api = functools.wraps(implementation)(public_api)
|
||
|
|
|
||
|
|
if module is not None:
|
||
|
|
public_api.__module__ = module
|
||
|
|
|
||
|
|
ARRAY_FUNCTIONS.add(public_api)
|
||
|
|
|
||
|
|
return public_api
|
||
|
|
|
||
|
|
return decorator
|
||
|
|
|
||
|
|
|
||
|
|
def array_function_from_dispatcher(
|
||
|
|
implementation, module=None, verify=True, docs_from_dispatcher=True):
|
||
|
|
"""Like array_function_dispatcher, but with function arguments flipped."""
|
||
|
|
|
||
|
|
def decorator(dispatcher):
|
||
|
|
return array_function_dispatch(
|
||
|
|
dispatcher, module, verify=verify,
|
||
|
|
docs_from_dispatcher=docs_from_dispatcher)(implementation)
|
||
|
|
return decorator
|