#! /usr/bin/env python3
# -*- coding: utf-8 -*-
# File : dsl_functions.py
# Author : Jiayuan Mao
# Email : maojiayuan@gmail.com
# Date : 10/19/2022
#
# This file is part of Project Concepts.
# Distributed under terms of the MIT license.
"""Data structures representing functions in a DSL.
Most importantly, this file contains the following classes:
- :class:`FunctionType`: the underlying type of a function, including argument types and return types.
- :class:`Function`: the function object, which is a callable object that can be used in expressions. They have names and types.
This file also implements a data structure for overloaded functions: :class:`OverloadedFunctionType`.
Internally, it contains a list of :class:`FunctionType` objects, and it is used to represent overloaded functions.
There are a few argument resolution methods implemented for both :class:`FunctionType` and :class:`OverloadedFunctionType`.
"""
import itertools
import contextlib
import inspect
import re
from typing import TYPE_CHECKING, Any, Union, Sequence, Tuple, List, Dict, Optional, Callable
from dataclasses import dataclass
import jacinle
from jacinle.utils.cache import cached_property
from jacinle.utils.defaults import option_context
from jacinle.utils.printing import indent_text
from concepts.dsl.dsl_types import TypeBase, ObjectType, ValueType, SequenceType, TupleType, VariableSizedSequenceType, ConstantType, UnionType, Variable
from concepts.dsl.dsl_types import FormatContext, get_format_context
if TYPE_CHECKING:
from concepts.dsl.expression import Expression, FunctionApplicationExpression
__all__ = [
'FunctionArgumentResolutionError', 'FunctionArgumentResolutionContext', 'get_function_argument_resolution_context',
'FunctionArgumentUnset', 'AnonymousFunctionArgumentGenerator',
'FunctionArgumentType', 'FunctionArgumentListType', 'FunctionReturnType', 'FunctionType',
'OverloadedFunctionResolution', 'OverloadedFunctionAmbiguousResolutions', 'OverloadedFunctionType',
'FunctionTyping',
'FunctionOverriddenCallList', 'FunctionDerivedExpressionList', 'FunctionResolvedFromRecord', 'Function',
]
[docs]
class FunctionArgumentResolutionError(Exception):
"""Exception raised when the function argument resolution fails."""
pass
[docs]
class FunctionArgumentResolutionContext(option_context(
'_FunctionArgumentResolutionContext',
check_missing=True, check_type=True, check_overloaded_ambiguity=True, exc_verbose=True
)):
"""A context manager for controlling the function argument resolution.
Attributes:
check_missing (bool): whether to check if the function argument is missing.
check_type (bool): whether to check if the function argument type is correct.
check_overloaded_ambiguity (bool): whether to check if the function argument resolution is ambiguous.
exc_verbose (bool):wWhether to print verbose error message.
"""
[docs]
@contextlib.contextmanager
def exc(self, exc_type=None, from_=None):
if self.exc_verbose:
yield
else:
if exc_type is None:
exc_type = FunctionArgumentResolutionError
if from_ is not None:
raise exc_type() from from_
raise exc_type()
get_function_argument_resolution_context: Callable[[], FunctionArgumentResolutionContext] = FunctionArgumentResolutionContext.get_default
"""Get the current function argument resolution context."""
FunctionArgumentUnset = object()
"""A placeholder indicating that the argument is not specified."""
[docs]
class AnonymousFunctionArgumentGenerator(object):
"""A generator for anonymous function arguments."""
[docs]
def __init__(self, template='_t{i:d}'):
self.template = template
self.counter = 0
@property
def nr_generated(self) -> int:
return self.counter
[docs]
def gen(self, n: Optional[int] = None) -> Union[str, List[str]]:
if n is None:
self.counter += 1
return self.template.format(i=self.counter)
return [self.gen() for _ in range(n)]
FunctionArgumentType = Union[ObjectType, ValueType, 'FunctionType', SequenceType]
"""Acceptable types for function arguments. See the documentation of `FunctionType` for more details."""
FunctionArgumentListType = Union[Sequence[FunctionArgumentType], Sequence[Variable], Dict[str, FunctionArgumentType]]
"""Acceptable types for function argument lists. See the documentation of `FunctionType` for more details."""
FunctionReturnType = Union[ObjectType, ValueType, 'FunctionType', SequenceType]
"""Acceptable types for function return types. See the documentation of `FunctionType` for more details."""
[docs]
class FunctionType(TypeBase):
"""FunctionType defines the signature of a function."""
argument_types: Tuple[FunctionArgumentType, ...]
"""The types of the arguments."""
argument_names: Tuple[str, ...]
"""The names of the arguments."""
arguments: Tuple[Variable, ...]
"""The argument list composed of `Variable` instances."""
arguments_dict: Dict[str, FunctionArgumentType]
"""The arguments as a dict, as mappings from argument names to argument types."""
arguments_name2index: Dict[str, int]
"""The mapping from argument names to argument indices."""
return_type: FunctionReturnType
"""The return type of the function type."""
return_name: Optional[Union[str, Tuple[str, ...]]]
"""The name of the return value."""
is_generator_function: bool
"""Whether the function is a generator function."""
is_simple_arguments: bool
"""Whether all arguments are not batched-list types."""
is_singular_return: bool
"""Whether there is only one return value."""
is_cacheable: bool
"""Whether the function is cacheable."""
[docs]
def __init__(
self,
arguments: FunctionArgumentListType,
return_type: FunctionReturnType,
argument_names: Optional[Sequence[str]] = None,
return_name: Optional[Union[str, Sequence[str]]] = None,
is_generator_function: bool = False,
alias: Optional[str] = None
):
"""Initialize the function type.
There are four ways to specify the arguments of the function type:
1. A list of types, in which case the name of each argument is the index of the argument, using the format `#{index}`.
2. A list of types as the `arguments`, and a list of names as the `argument_names`.
3. A list of variables, in which case the name of each argument is the name of the variable.
4. A dictionary of {name: type}, in which case the order of the arguments is the order of the keys.
The return type can be either a single type or a tuple of types (multi-return types).
Args:
arguments: The arguments of the function type.
When it is a list, the name of the arguments will be automatically generated.
When it is a dict, the name of the arguments will be the keys of the dict.
return_type: The return type of the function type.
argument_names: The names of the arguments.
return_name: The name of the return value.
is_generator_function: Whether the function is a generator function.
alias: The alias name of the function type.
"""
self.arguments = None # noqa
self.arguments_dict = None # noqa
if isinstance(arguments, (list, tuple)):
if len(arguments) == 0:
self.arguments = tuple()
self.arguments_dict = dict()
self.argument_names = tuple()
self.argument_types = tuple()
elif isinstance(arguments[0], Variable):
assert argument_names is None, 'Cannot specify both `arguments` and `argument_names`.'
self.argument_types = tuple(arg.dtype for arg in arguments)
self.argument_names = tuple(arg.name for arg in arguments)
self.arguments = arguments
else:
if argument_names is None:
argument_names = tuple('_' + str(i) for i in range(len(arguments)))
else:
assert len(arguments) == len(argument_names), 'The length of `arguments` and `argument_names` must be the same.'
self.argument_types = tuple(arguments)
self.argument_names = tuple(argument_names)
elif isinstance(arguments, dict):
assert argument_names is None, 'Cannot specify both `arguments` and `argument_names`.'
self.argument_names = tuple(arguments.keys())
self.argument_types = tuple(arguments.values())
self.arguments_dict = arguments.copy()
else:
raise TypeError(f'Invalid argument types: {arguments}. Must be a list or a dict.')
if self.arguments is None:
self.arguments = tuple(Variable(name, dtype) for name, dtype in zip(self.argument_names, self.argument_types))
if self.arguments_dict is None:
self.arguments_dict = {name: dtype for name, dtype in zip(self.argument_names, self.argument_types)}
if isinstance(return_type, TupleType):
self.return_type = return_type
if return_name is None:
self.return_name = None
else:
self.return_name = tuple(return_name)
assert len(return_type.element_types) == len(self.return_name), 'The length of `return_type` and `return_name` must be the same.'
# NB(Jiayuan Mao @ 2024/03/10): I commented out this behavior but I'm not sure if it's correct.
# if len(return_type.element_types) == 1:
# self.return_type = self.return_type.element_types[0]
# if self.return_name is not None:
# self.return_name = self.return_name[0]
else:
if return_name is not None and not isinstance(return_name, str):
raise ValueError(f'Invalid return name: {return_name}. Must be a string when the function has a singular return type')
self.return_type = return_type
self.return_name = return_name
self.is_generator_function = is_generator_function
self.is_simple_arguments = all(not isinstance(arg, VariableSizedSequenceType) for arg in self.argument_types)
self.is_singular_return = not isinstance(self.return_type, TupleType)
self.is_cacheable = self._gen_is_cacheable()
super().__init__(self._gen_typename(), alias=alias)
def _gen_typename(self) -> str:
if self.is_generator_function:
return '(' + ', '.join([str(arg) for arg in self.arguments]) + ') -> Gen[' + str(self.return_type) + ']'
return '(' + ', '.join([str(arg) for arg in self.arguments]) + ') -> ' + str(self.return_type)
def _gen_is_cacheable(self):
if self.is_generator_function:
return False
for arg_def in self.arguments:
if isinstance(arg_def, ValueType):
return False
return True
@property
def nr_arguments(self) -> int:
"""Return the number of arguments."""
return len(self.argument_types)
@cached_property
def nr_object_arguments(self) -> int:
"""Return the number of arguments that are ObjectType-ed."""
return len(list(filter(lambda x: isinstance(x, ValueType), self.argument_types)))
@cached_property
def nr_value_arguments(self) -> int:
"""Return the number of arguments that are ValueType-ed."""
return len(list(filter(lambda x: isinstance(x, ValueType), self.argument_types)))
@cached_property
def nr_variable_arguments(self) -> int:
"""Return the number of arguments that are VariableType-ed (i.e. is ValueType-ed but not ConstantType-ed."""
return len(list(filter(lambda x: isinstance(x, ValueType) and not isinstance(x, ConstantType), self.argument_types)))
@cached_property
def nr_constant_arguments(self) -> int:
"""Return the number of arguments that are ConstantType-ed."""
return len(list(filter(lambda x: isinstance(x, ConstantType), self.argument_types)))
@cached_property
def arguments_name2index(self):
assert self.argument_names is not None
return {v: k for k, v in enumerate(self.argument_names)}
[docs]
@classmethod
def from_annotation(cls, function: Callable, sig: Optional[inspect.Signature] = None) -> Union['FunctionType', 'OverloadedFunctionType']:
"""Create a FunctionType from a function annotation.
Args:
function: The function.
sig: The signature of the function.
Returns:
Union[FunctionType, OverloadedFunctionType]: The function type.
"""
if sig is None:
sig = inspect.signature(function)
argument_types = list()
argument_names = list()
for i, (name, param) in enumerate(sig.parameters.items()):
if i == 0 and name == 'self':
continue # is an instancemethod.
if i == 0 and name == 'cls':
continue # is a classmethod.
argument_names.append(name)
argument_types.append(param.annotation)
return_type = sig.return_annotation
if inspect._empty in argument_types or return_type is inspect._empty:
raise FunctionArgumentResolutionError(f'Incomplete argument and return type annotation for {function}.')
function_type = cls(argument_types, return_type, argument_names=argument_names)
for arg_type in function_type.argument_types:
if isinstance(arg_type, UnionType):
return OverloadedFunctionType.from_function_type_with_union_arguments(function_type)
return function_type
[docs]
def resolve_args(self, *args: Any, **kwargs: Any) -> List[Any]:
"""Resolve the arguments to the function type.
If you want to specify a specific "positional" argument by its index, use `_{index}` as the name of the argument.
Args:
*args: The positional arguments.
**kwargs: The keyword arguments.
Returns:
A list of argument values.
"""
resolution_context = get_function_argument_resolution_context()
# Construct a mapping from the name of arguments to their indices.
name2index = {f'#{i}': i for i in range(self.nr_arguments)}
name2index.update(self.arguments_name2index)
arguments = [FunctionArgumentUnset for _ in range(self.nr_arguments)]
if len(args) + len(kwargs) > self.nr_arguments:
with resolution_context.exc():
raise FunctionArgumentResolutionError(f'Function {self} takes {len(self.argument_types)} arguments, got {len(args) + len(kwargs)}.')
for i in range(len(args)):
arguments[i] = args[i]
for k, v in kwargs.items():
if k not in name2index:
with resolution_context.exc():
raise FunctionArgumentResolutionError(f'Got unknown keyword argument: {k} when invoking function {self}.')
i = name2index[k]
if arguments[i] is not FunctionArgumentUnset:
with resolution_context.exc():
raise FunctionArgumentResolutionError(f'Got duplicated argument for keyword argument: {k} when invoking function {self}.')
arguments[i] = v
if resolution_context.check_missing:
for i in range(self.nr_arguments):
if arguments[i] is FunctionArgumentUnset:
with resolution_context.exc():
raise FunctionArgumentResolutionError(f'Missing argument {self.argument_names[i]} when invoking function {self}.')
if resolution_context.check_type:
from concepts.dsl.expression import get_types
argument_types = get_types(arguments)
for i in range(self.nr_arguments):
if argument_types[i] is not FunctionArgumentUnset and not argument_types[i].downcast_compatible(self.argument_types[i]):
with resolution_context.exc():
raise FunctionArgumentResolutionError(f'Typecheck failed for argument {self.argument_names[i]} while invoking the function {self}.\nInvoked with types: {argument_types}.')
return arguments
[docs]
@dataclass
class OverloadedFunctionResolution(object):
"""The data structure for storing the result of resolving an overloaded function."""
type_index: int
"""The index of the function type that matches the expected signature."""
ftype: FunctionType
"""The function type that matches the expected signature."""
arguments: List[Any]
"""The resolved arguments."""
[docs]
class OverloadedFunctionAmbiguousResolutions(list, List[OverloadedFunctionResolution]):
pass
[docs]
class OverloadedFunctionType(TypeBase):
types: Tuple[FunctionType]
[docs]
def __init__(
self,
types: Sequence[Union['OverloadedFunctionType', FunctionType]],
alias: Optional[str] = None
):
types_flatten: List[FunctionType] = list()
for ftype in types:
if isinstance(ftype, OverloadedFunctionType):
types_flatten.extend(ftype.types)
else:
assert isinstance(type, FunctionType)
types_flatten.append(ftype)
self.types = tuple(types_flatten)
super().__init__(self._gen_typename(), alias=alias)
def _gen_typename(self) -> str:
return 'Overloaded{' + ','.join([x.typename for x in self.types]) + '}'
@property
def nr_types(self) -> int:
"""Return the number of sub-types."""
return len(self.types)
[docs]
@classmethod
def from_function_type_with_union_arguments(cls, function_type: FunctionType):
"""Create an OverloadedFunctionType from a FunctionType with Union-Typed arguments."""
product_bases = list()
for arg_type in function_type.argument_types:
if isinstance(arg_type, UnionType):
product_bases.append(arg_type.types)
else:
product_bases.append([arg_type])
product_types = tuple(
FunctionType(
arg_type, function_type.return_type,
argument_names=function_type.argument_names
) for arg_type in itertools.product(*product_bases)
)
return cls(product_types, alias=function_type.typename)
[docs]
def resolve_type_and_args(self, *args: Any, **kwargs: Any) -> Union[OverloadedFunctionResolution, OverloadedFunctionAmbiguousResolutions]:
"""Resolve the exact sub-function type being called and the argument list.
Args:
*args: The positional arguments.
**kwargs: The keyword arguments.
Returns:
A :class:`OverloadedFunctionResolution` object if the resolution is unambiguous, or a :class:`OverloadedFunctionAmbiguousResolutions` object if the resolution is ambiguous.
The ambiguity resolution object will only be returned if the ``check_overloaded_ambiguity`` flag is set to False in the :class:`FunctionArgumentResolutionContext`.
- The :class:`OverloadedFunctionResolution` object contains the index of the sub-function type being called, the sub-function type, and the resolved argument list.
- The :class:`OverloadedFunctionAmbiguousResolutions` object contains a list of :class:`OverloadedFunctionResolution` objects.
"""
resolution_context = get_function_argument_resolution_context()
success_results = list()
exceptions = list()
for i, ftype in enumerate(self.types):
try:
arguments = ftype.resolve_args(*args, **kwargs)
success_results.append(OverloadedFunctionResolution(i, ftype, arguments))
except FunctionArgumentResolutionError as e:
exceptions.append(e)
if len(success_results) == 1:
return success_results[0]
elif len(success_results) == 0:
with resolution_context.exc():
fmt = 'Failed to resolve overloaded function{}.\n'.format('' if self.typename is None else ' ' + self.typename)
fmt += 'Detailed messages are:\n'
for ftype, r in zip(self.types, exceptions):
this_fmt = 'Trying ' + str(ftype) + ':\n'
this_fmt += indent_text(str(r))
fmt += indent_text(this_fmt) + '\n'
raise FunctionArgumentResolutionError(fmt.rstrip())
else:
if resolution_context.check_overloaded_ambiguity:
with resolution_context.exc():
fmt = 'Got ambiguous application of overloaded function{}.\n'.format('' if self.typename is None else ' ' + self.typename)
fmt += 'Candidates are:\n'
for r in success_results:
fmt += indent_text(str(r[1])) + '\n'
fmt += 'Invoked with arguments: {}.'.format(str(success_results[0][2]))
raise FunctionArgumentResolutionError(fmt)
else:
return OverloadedFunctionAmbiguousResolutions(success_results)
class _FunctionTypingSugarInner(object):
def __init__(self, return_type):
self.return_type = return_type
def __call__(self, *args, **kwargs):
if len(args) == 0 and len(kwargs) == 0:
return FunctionType(tuple(), self.return_type)
elif len(args) != 0:
assert len(kwargs) == 0, 'Only support all positional arguments or all positional keyword arguments.'
return FunctionType(args, self.return_type)
elif len(kwargs) != 0:
assert len(args) == 0, 'Only support all positional arguments or all positional keyword arguments.'
return FunctionType(tuple(kwargs.values()), self.return_type, tuple(kwargs.keys()))
raise ValueError('Unreachable.')
class _FunctionTypingSugar(object):
def __getitem__(self, return_type):
return _FunctionTypingSugarInner(return_type)
"""FunctionTyping is a language-sugar constructor for function types.
For example: `FunctionTypingp[BOOL](INT64, INT64)` creates a function type with two INT64 arguments and a BOOL return type."""
FunctionTyping = _FunctionTypingSugar()
[docs]
class FunctionOverriddenCallList(list, List[Callable]):
"""A data structure that holds multiple overridden __call__ implementations for a function.
This is only useful when we are partial evaluating a function (and when the actual function type can not be resolved.)
"""
pass
[docs]
class FunctionDerivedExpressionList(list, List['Expression']):
"""A data structure that holds multiple derived expressions for a function."""
pass
[docs]
@dataclass
class FunctionResolvedFromRecord(object):
function: Callable
ftype_index: Union[int, Tuple[int, ...]]
[docs]
class Function(object):
"""A function object holds a function type and an optional overridden __call__.
The function object holds an additional field called `overridden_call`, which isa callable function.
This field is used to override the __call__ method of the function object.
By default, the __call__ function returns a FunctionApplication object, which contains the name of the function
and a list of arguments. However, when `overridden_call` is set, the __call__ method will return the result of
calling `overridden_call` with the arguments.
"""
[docs]
def __init__(
self,
name: str,
ftype: Union[FunctionType, OverloadedFunctionType],
derived_expression: Optional[Union['Expression', FunctionDerivedExpressionList]] = None,
overridden_call: Optional[Union[Callable, FunctionOverriddenCallList]] = None,
resolved_from: Optional[FunctionResolvedFromRecord] = None,
function_body: Optional[Union[Callable, Sequence[Callable]]] = None
):
"""
Args:
name: the name of the function.
ftype: the function type.
derived_expression: the expression that this function is derived from.
overridden_call: the overridden call function.
resolved_from: the record of the function that this function is resolved from. This is used for handling
partial evaluation and function specialization (for overloadded functions).
function_body: the function body.
"""
self.ftype = ftype
self.derived_expression = derived_expression
self.overridden_call = overridden_call
self.resolved_from = resolved_from
if isinstance(self.ftype, OverloadedFunctionType) and isinstance(self.overridden_call, FunctionOverriddenCallList):
assert self.ftype.nr_types == len(self.overridden_call)
self.name = name
self.function_body = function_body # the function body defined during the declaration.
if self.derived_expression is None and self.overridden_call is not None:
if self.is_overloaded:
self.derived_expression = FunctionDerivedExpressionList()
for i in range(self.ftype.nr_types):
self.derived_expression.append(_gen_expression_from_overridden_call(self.ftype.types[i], self.overridden_call[i]))
else:
self.derived_expression = _gen_expression_from_overridden_call(ftype, self.overridden_call)
self.is_derived = self.derived_expression is not None
[docs]
def set_function_name(self, function_name: str):
"""Set the function name."""
self.name = function_name
[docs]
def set_function_body(self, function_body: Callable):
"""Set the function body."""
self.function_body = function_body
"""Argument and return type of the function (when the function is not an overloaded one)."""
@property
def arguments(self) -> Tuple[Variable]:
assert not self.is_overloaded
return self.ftype.arguments
@property
def nr_arguments(self) -> int:
assert not self.is_overloaded
return self.ftype.nr_arguments
@property
def return_type(self) -> FunctionReturnType:
assert not self.is_overloaded
return self.ftype.return_type
@property
def is_generator_function(self) -> bool:
return self.ftype.is_generator_function
"""When the function is overloaded, the following functions are used for get the "overridden calls" for each function type."""
@property
def is_overloaded(self) -> bool:
"""Return True if the function is overloaded."""
return isinstance(self.ftype, OverloadedFunctionType)
[docs]
def get_overridden_call(self, ftype_index: Optional[int] = None) -> Optional[Callable]:
"""Get the overridden call function."""
if isinstance(self.overridden_call, FunctionOverriddenCallList):
assert ftype_index is not None
return self.overridden_call[ftype_index]
return self.overridden_call
[docs]
def get_sub_function(self, ftype_index: int) -> 'Function':
assert self.is_overloaded
assert 0 <= ftype_index < self.ftype.nr_types
return type(self)(
self.name,
self.ftype.types[ftype_index],
self.get_overridden_call(ftype_index),
resolved_from=FunctionResolvedFromRecord(self, ftype_index),
function_body=self.function_body[ftype_index] if self.function_body is not None else None
)
@cached_property
def all_sub_functions(self) -> List['Function']:
assert self.is_overloaded
return [self.get_sub_function(i) for i in range(self.ftype.nr_types)]
[docs]
@classmethod
def from_function(cls, function: Callable, implementation: bool = True, sig: Optional[inspect.Signature] = None):
"""Create a function object from an actual Python function.
Args:
function: The function.
implementation: Whether the function is an implementation. Defaults to True.
sig: The signature of the function. Defaults to None.
"""
ftype = FunctionType.from_annotation(function, sig=sig)
return cls(function.__name__, ftype, function_body=function if implementation else None)
[docs]
def __call__(self, *args, **kwargs):
if self.overridden_call is not None:
if isinstance(self.ftype, OverloadedFunctionType):
ftype_index, function_type, resolved_args = self.ftype.resolve_type_and_args(*args, **kwargs)
return self.get_overridden_call(ftype_index)(*resolved_args)
else:
resolved_args = self.ftype.resolve_args(*args, **kwargs)
return self.overridden_call(*resolved_args)
if isinstance(self.ftype, OverloadedFunctionType):
ftype_index, function_type, resolved_args = self.ftype.resolve_type_and_args(*args, **kwargs)
function = Function(
self.name + f'_{ftype_index}',
function_type,
overridden_call=None, # Must be none.
resolved_from=FunctionResolvedFromRecord(self, ftype_index),
)
else:
resolved_args = self.ftype.resolve_args(*args, **kwargs)
function = self
from concepts.dsl.expression import FunctionApplicationExpression, cvt_expression_list
return FunctionApplicationExpression(function, cvt_expression_list(resolved_args, function.ftype.argument_types))
def __str__(self):
if self.is_derived and not self.is_overloaded:
with FormatContext(type_format_cls=False).as_default():
if get_format_context().function_format_lambda:
fmt = ''.join(['lam ' + str(n.name) + '.' for n in self.arguments])
with FormatContext(object_format_type=False).as_default():
fmt += str(self.derived_expression)
else:
fmt = 'def ' + self.name + '(' + ', '.join([str(x) for x in self.arguments]) + '): '
with FormatContext(object_format_type=False).as_default():
fmt += 'return ' + indent_text(str(self.derived_expression)).lstrip()
else:
if isinstance(self.ftype, OverloadedFunctionType):
fmt = '\n'.join([f'{func_type}' for func_type in self.ftype.types])
if self.name is not None:
fmt = re.sub(r'^' + re.escape(self.name) + ' (overloaded): ', '', fmt, flags=re.MULTILINE)
fmt = self.name + ': ' + '\n' + indent_text(fmt)
else:
fmt = f'{self.name}{self.ftype}'
return fmt
__repr__ = jacinle.repr_from_str
[docs]
def remap_arguments(self, remapping: List[int]) -> 'Function':
"""
Generate a new Function object with a different argument order.
Specifically, remapping is a permutation. The i-th argument to the new function will be the remapping[i]-th
argument in the old function.
Args:
remapping: The remapping.
Returns:
The new function.
"""
if isinstance(self.ftype, OverloadedFunctionType):
raise NotImplementedError('Argument remapping for overloaded functions are not implemented.')
new_argument_types = [self.ftype.argument_types[i] for i in remapping]
def new_overridden_call(*args):
remapped_args = [None for _ in range(len(args))]
for i, arg in enumerate(args):
remapped_args[remapping[i]] = arg
return self(*remapped_args)
return Function(
self.name,
FunctionType(
new_argument_types, self.ftype.return_type,
), overridden_call=new_overridden_call, resolved_from=self.resolved_from
)
[docs]
def partial(self, *args, execute_fully_bound_functions=False, **kwargs) -> Union['Function', 'FunctionApplicationExpression']:
if self.name == '__lambda__':
new_name = '__lambda__'
else:
new_name = f'{self.name}_partial'
new_overridden_call = None
new_resolved_from = None
if self.is_overloaded:
with FunctionArgumentResolutionContext(
check_missing=False,
check_overloaded_ambiguity=False
).as_default():
types_and_arguments = self.ftype.resolve_type_and_args(*args, **kwargs)
if not isinstance(types_and_arguments, OverloadedFunctionAmbiguousResolutions):
ftype_index, function_type, resolved_args = types_and_arguments
unmapped_arguments = [i for i, arg in enumerate(resolved_args) if arg is FunctionArgumentUnset]
if len(unmapped_arguments) == 0:
return self._apply_with_resolved_args(resolved_args, ftype_index, function_type)
new_type = _gen_partial_function_type(function_type, unmapped_arguments)
new_resolved_from = FunctionResolvedFromRecord(self, ftype_index)
else:
# Block BEGIN {{{
# If there is one specific resolution s.t. all variables are grounded, use it.
all_grounded_resolutions = list()
for ftype_index, function_type, resolved_args in types_and_arguments:
unmapped_arguments = [i for i, arg in enumerate(resolved_args) if arg is FunctionArgumentUnset]
if len(unmapped_arguments) == 0:
all_grounded_resolutions.append((ftype_index, function_type, resolved_args))
if len(all_grounded_resolutions) == 1:
ftype_index, function_type, resolved_args = all_grounded_resolutions[0]
return self._apply_with_resolved_args(resolved_args, ftype_index, function_type)
elif len(all_grounded_resolutions) > 1:
with get_function_argument_resolution_context().exc():
fmt = 'Got ambiguous application of overloaded function{}.\n'.format(
'' if self.name is None else ' ' + self.name)
fmt += 'Candidates are:\n'
for r in all_grounded_resolutions:
fmt += indent_text(str(r[1])) + '\n'
fmt += 'Invoked with arguments: {}.'.format(str(all_grounded_resolutions[0][2]))
raise FunctionArgumentResolutionError(fmt)
# }}} Block END.
possible_resolution_ids = list()
possible_resolutions = list()
possible_overridden_calls = list()
for ftype_index, function_type, resolved_args in types_and_arguments:
unmapped_arguments = [i for i, arg in enumerate(resolved_args) if arg is FunctionArgumentUnset]
new_subtype = _gen_partial_function_type(
function_type, unmapped_arguments
)
possible_resolution_ids.append(ftype_index)
possible_resolutions.append(new_subtype)
possible_overridden_calls.append(_gen_partial_overriden_call(
new_subtype, resolved_args, self
))
new_type = OverloadedFunctionType(possible_resolutions)
new_resolved_from = FunctionResolvedFromRecord(self, tuple(possible_resolution_ids))
new_overridden_call = FunctionOverriddenCallList(possible_overridden_calls)
else:
with FunctionArgumentResolutionContext(check_missing=False).as_default():
resolved_args = self.ftype.resolve_args(*args, **kwargs)
unmapped_arguments = [i for i, arg in enumerate(resolved_args) if arg is FunctionArgumentUnset]
if execute_fully_bound_functions:
if len(unmapped_arguments) == 0:
return self._apply_with_resolved_args(resolved_args)
new_type = _gen_partial_function_type(self.ftype, unmapped_arguments)
new_overridden_call = _gen_partial_overriden_call(
new_type, resolved_args, self
)
return Function(
new_name, new_type,
overridden_call=new_overridden_call, resolved_from=new_resolved_from
)
def _apply_with_resolved_args(
self, resolved_args,
resolved_ftype_id=None, resolved_function_type=None
):
if self.overridden_call is not None:
return self.get_overridden_call(resolved_ftype_id)(*resolved_args)
if isinstance(self.ftype, OverloadedFunctionType):
function = Function(
self.name + f'_{resolved_ftype_id}',
resolved_function_type,
overridden_call=None, # Must be none.
resolved_from=FunctionResolvedFromRecord(self, resolved_ftype_id)
)
else:
function = self
from concepts.dsl.expression import FunctionApplicationExpression, cvt_expression_list
return FunctionApplicationExpression(function, cvt_expression_list(resolved_args, function.ftype.argument_types))
def _gen_expression_from_overridden_call(ftype: FunctionType, overridden_call: Callable):
from concepts.dsl.expression import ExpressionDefinitionContext
ctx = ExpressionDefinitionContext()
with ctx.as_default():
arguments = [ctx[arg] for arg in ftype.arguments]
return overridden_call(*arguments)
def _gen_partial_function_type(old_type: FunctionType, unmapped_arguments):
new_argument_types = [old_type.argument_types[i] for i in unmapped_arguments]
new_return_type = old_type.return_type
new_argument_names = None
if old_type.argument_names is not None:
new_argument_names = [old_type.argument_names[i] for i in unmapped_arguments]
new_type = FunctionType(new_argument_types, new_return_type, argument_names=new_argument_names)
return new_type
def _gen_partial_overriden_call(new_type, resolved_args, call):
assert isinstance(new_type, FunctionType)
def partial_overriden_call(*new_args, **new_kwargs):
new_resolved_args = new_type.resolve_args(*new_args, **new_kwargs)
new_full_args = resolved_args.copy()
j = 0
for i in range(len(resolved_args)):
if new_full_args[i] is FunctionArgumentUnset:
new_full_args[i] = new_resolved_args[j]
j += 1
return call(*new_full_args)
return partial_overriden_call