pytorch/torch/_dynamo/variables/base.py

import collections
from typing import Any, Callable, Dict, List, Optional, Set

from .. import variables
from ..exc import unimplemented
from ..source import AttrSource, Source
from ..utils import dict_values, identity, istype, odict_values


class MutableLocal:
    """
    Marker used to indicate this (list, iter, etc) was constructed in
    local scope and can be mutated safely in analysis without leaking
    state.
    """

    def __hash__(self):
        return id(self)

    def __eq__(self, other):
        return self is other


# metaclass to call post_init
class HasPostInit(type):
    def __call__(cls, *args, **kwargs):
        obj = type.__call__(cls, *args, **kwargs)
        obj.__post_init__(*args, **kwargs)
        return obj


class VariableTracker(metaclass=HasPostInit):
    """
    Base class for tracked locals and stack values

    VariableTracker instances are immutable and should be copied in
    order to change them.
    """

    # fields to leave unmodified in apply()
    _nonvar_fields = ["value"]

    @staticmethod
    def propagate(*vars: List[List["VariableTracker"]]):
        """Combine the guards from many VariableTracker into **kwargs for a new instance"""
        guards = set()

        def visit(var):
            if type(var) in (list, tuple, dict_values, odict_values):
                for i in var:
                    visit(i)
            else:
                assert isinstance(var, VariableTracker), typestr(var)
                guards.update(var.guards)

        visit(vars)
        return {
            "guards": guards,
        }

    def clone(self, **kwargs):
        """Shallow copy with some (optional) changes"""
        args = dict(self.__dict__)
        args.update(kwargs)
        return self.__class__(**args)

    @classmethod
    def copy(cls, value):
        """Deeper (but not full) copy, leaving FX and user objects alone"""
        return cls.apply(identity, value)

    @classmethod
    def apply(
        cls,
        fn: Callable[["VariableTracker"], "VariableTracker"],
        value,
        cache=None,
        skip_fn=lambda _: False,  # Whether we should skip applying to this var
    ):
        """
        Walk this object and call fn on all the VariableTracker
        instances to produce a new VariableTracker with the results.
        """
        if cache is None:
            cache = dict()

        idx = id(value)
        if idx in cache:
            return cache[idx][0]

        if isinstance(value, VariableTracker):
            if not skip_fn(value):
                updated_dict = dict(value.__dict__)
                for key in updated_dict.keys():
                    if key not in value._nonvar_fields:
                        updated_dict[key] = cls.apply(
                            fn, updated_dict[key], cache, skip_fn
                        )
                result = fn(value.clone(**updated_dict))
            else:
                result = fn(value)

        elif istype(value, list):
            result = [cls.apply(fn, v, cache, skip_fn) for v in value]
        elif istype(value, tuple):
            result = tuple(cls.apply(fn, v, cache, skip_fn) for v in value)
        elif istype(value, collections.OrderedDict):
            result = collections.OrderedDict(
                cls.apply(fn, v, cache, skip_fn) for v in value.items()
            )
        elif istype(value, dict):
            result = {
                k: cls.apply(fn, v, cache, skip_fn) for k, v in list(value.items())
            }
        else:
            result = value

        # save `value` to keep it alive and ensure id() isn't reused
        cache[idx] = (result, value)
        return result

    def add_guard(self, guard):
        return self.clone(guards=set.union(self.guards, {guard}))

    def add_guards(self, guards):
        if guards is None:
            return self
        assert isinstance(guards, set)
        return self.clone(guards=set.union(self.guards, guards))

    def add_options(self, options, *more):
        if more:
            return self.add_options(options).add_options(*more)
        if isinstance(options, VariableTracker):
            return self.add_guards(options.guards)
        assert isinstance(options, dict)
        return self.add_guards(options.get("guards", set()))

    def __str__(self):
        return f"{self.__class__.__name__}()"

    def __repr__(self):
        return str(self)

    def python_type(self):
        raise NotImplementedError(f"{self} has no type")

    def as_python_constant(self):
        """For constants"""
        raise NotImplementedError(f"{self} is not a constant")

    def is_python_constant(self):
        try:
            self.as_python_constant()
            return True
        except NotImplementedError:
            return False

    def as_specialized(self, tx):
        """
        For specialized variables, return itself,
        For unspecialized variables, convert to constant variable and return.
        """
        return self

    def can_make_guard(self):
        try:
            self.make_guard(None)
            return True
        except NotImplementedError:
            return False

    def make_guard(self, fn):
        if self.source:
            return self.source.make_guard(fn)
        raise NotImplementedError()

    def replace_guards(self, guards, *fns):
        name = self.source.name()
        new_guards = {g for g in (guards or []) if g.name != name}
        new_guards.update(self.source.make_guard(fn) for fn in fns)
        return new_guards

    def const_getattr(self, tx, name: str) -> Any:
        """getattr(self, name) returning a python constant"""
        raise NotImplementedError()

    def var_getattr(self, tx, name: str) -> "VariableTracker":
        """getattr(self, name) returning a new variable"""
        options = VariableTracker.propagate(self)
        value = self.const_getattr(tx, name)
        if not variables.ConstantVariable.is_literal(value):
            raise NotImplementedError()
        if self.source:
            options["source"] = AttrSource(self.source, name)
        return variables.ConstantVariable(value, **options)

    def is_proxy(self):
        try:
            self.as_proxy()
            return True
        except NotImplementedError:
            return False

    def as_proxy(self):
        raise NotImplementedError(str(self))

    def reconstruct(self, codegen):
        raise NotImplementedError()

    def unpack_var_sequence(self, tx):
        raise NotImplementedError()

    def has_unpack_var_sequence(self, tx):
        try:
            self.unpack_var_sequence(tx)
            return True
        except NotImplementedError:
            return False

    def num_parameters(self):
        unimplemented(f"num_parameters: {self}")

    def call_hasattr(self, tx, name: str) -> "VariableTracker":
        unimplemented(f"hasattr: {repr(self)}")

    def call_function(
        self, tx, args: "List[VariableTracker]", kwargs: "Dict[str, VariableTracker]"
    ) -> "VariableTracker":
        unimplemented(f"call_function {self} {args} {kwargs}")

    def call_method(
        self,
        tx,
        name,
        args: "List[VariableTracker]",
        kwargs: "Dict[str, VariableTracker]",
    ) -> "VariableTracker":
        if name == "__len__" and self.has_unpack_var_sequence(tx):
            assert not (args or kwargs)
            return variables.ConstantVariable(
                len(self.unpack_var_sequence(tx)), **VariableTracker.propagate(self)
            )
        elif (
            name == "__getattr__"
            and len(args) == 1
            and args[0].is_python_constant()
            and not kwargs
        ):
            return self.var_getattr(tx, args[0].as_python_constant()).add_options(
                self, args[0]
            )
        raise unimplemented(f"call_method {self} {name} {args} {kwargs}")

    def __init__(
        self,
        guards: Optional[Set] = None,
        source: Source = None,
        mutable_local: MutableLocal = None,
        recursively_contains: Optional[Set] = None,
    ):
        super().__init__()
        self.guards = guards or set()
        self.source = source
        self.mutable_local = mutable_local
        self.recursively_contains = (
            recursively_contains  # provides hint to replace_all when replacing vars
        )

    def __post_init__(self, *args, **kwargs):
        if self.recursively_contains is None:
            self.recursively_contains = set()

            def aggregate_mutables(var):
                self.recursively_contains.update(var.recursively_contains)
                if var.mutable_local is not None:
                    self.recursively_contains.add(var.mutable_local)

                return var

            VariableTracker.apply(
                aggregate_mutables, self, skip_fn=lambda var: var is not self
            )

        assert None not in self.recursively_contains


def typestr(*objs):
    if len(objs) == 1:
        (obj,) = objs
        if isinstance(obj, VariableTracker):
            return str(obj)
        else:
            return type(obj).__name__
    else:
        return " ".join(map(typestr, objs))