blob: ec5210aa9394c49d79f503a804e2a5f38a23dd81 [file] [log] [blame]
import collections
import dataclasses
import enum
from typing import Any, Optional, Union
from torch._guards import GuardSource, Source
from . import utils
from .bytecode_transformation import create_call_function, create_instruction
from .utils import enum_repr
# It shouldn't be supported to construct an NNModuleVariable inside an FSDP module,
# so those cases are omitted intentionally
_GUARD_SOURCE_NN_MODULE = {
GuardSource.LOCAL: GuardSource.LOCAL_NN_MODULE,
GuardSource.GLOBAL: GuardSource.GLOBAL_NN_MODULE,
GuardSource.LOCAL_NN_MODULE: GuardSource.LOCAL_NN_MODULE,
GuardSource.GLOBAL_NN_MODULE: GuardSource.GLOBAL_NN_MODULE,
}
_GUARD_SOURCE_FSDP_MODULE = {
GuardSource.LOCAL: GuardSource.LOCAL_FSDP_MODULE,
GuardSource.GLOBAL: GuardSource.GLOBAL_FSDP_MODULE,
GuardSource.LOCAL_NN_MODULE: GuardSource.LOCAL_FSDP_MODULE,
GuardSource.GLOBAL_NN_MODULE: GuardSource.GLOBAL_FSDP_MODULE,
GuardSource.LOCAL_FSDP_MODULE: GuardSource.LOCAL_FSDP_MODULE,
GuardSource.GLOBAL_FSDP_MODULE: GuardSource.GLOBAL_FSDP_MODULE,
}
_GUARD_SOURCE_NOT_NN_MODULE = {
GuardSource.LOCAL: GuardSource.LOCAL,
GuardSource.GLOBAL: GuardSource.GLOBAL,
GuardSource.LOCAL_NN_MODULE: GuardSource.LOCAL,
GuardSource.GLOBAL_NN_MODULE: GuardSource.GLOBAL,
GuardSource.LOCAL_FSDP_MODULE: GuardSource.LOCAL,
GuardSource.GLOBAL_FSDP_MODULE: GuardSource.GLOBAL,
}
def is_constant_source(source):
if isinstance(source, ConstantSource):
return True
try:
if source.guard_source() == GuardSource.CONSTANT:
return True
except NotImplementedError:
pass
return False
def is_input_source(source):
return source.guard_source() in [
GuardSource.LOCAL,
GuardSource.GLOBAL,
GuardSource.LOCAL_NN_MODULE,
GuardSource.GLOBAL_NN_MODULE,
GuardSource.LOCAL_FSDP_MODULE,
GuardSource.GLOBAL_FSDP_MODULE,
]
@dataclasses.dataclass(frozen=True)
class LocalSource(Source):
local_name: str
def reconstruct(self, codegen):
return [codegen.create_load(self.local_name)]
def guard_source(self):
return GuardSource.LOCAL
def name(self):
return f"L[{repr(self.local_name)}]"
@dataclasses.dataclass(frozen=True)
class RandomValueSource(Source):
random_call_index: int
def guard_source(self):
return GuardSource.RANDOM_VALUE
def reconstruct(self, codegen):
return [
codegen.create_load(codegen.tx.output.random_values_var),
codegen.create_load_const(self.random_call_index),
create_instruction("BINARY_SUBSCR"),
]
def name(self):
return f"random_value_{self.random_call_index}"
@dataclasses.dataclass(frozen=True)
class GeneratorStateSource(Source):
device: str
initial_seed: int
def guard_source(self):
return GuardSource.RANDOM_VALUE
def reconstruct(self, codegen):
# generator state is a torch.ByteTensor, so we reuse TensorVariable reconstruction in codegen.py
raise NotImplementedError()
def name(self):
name = f"generator_state_{self.device}_{self.initial_seed}"
return f"L[{name}]"
@dataclasses.dataclass(frozen=True)
class GlobalSource(Source):
global_name: str
def reconstruct(self, codegen):
return [codegen.create_load_global(self.global_name, False, add=True)]
def guard_source(self):
return GuardSource.GLOBAL
def name(self):
return f"G[{repr(self.global_name)}]"
@dataclasses.dataclass(frozen=True)
class GlobalWeakRefSource(Source):
global_name: str
def reconstruct(self, codegen):
return [
codegen.create_load_global(self.global_name, True, add=True),
*create_call_function(0, False),
]
def guard_source(self):
return GuardSource.GLOBAL
def name(self):
return f"G[{repr(self.global_name)}]()"
@dataclasses.dataclass(frozen=True)
class AttrSource(Source):
base: Source
member: str
def __post_init__(self):
assert self.base, "Can't construct an AttrSource without a valid base source"
if "." in self.member:
member_parts = self.member.split(".")
object.__setattr__(
self, "base", AttrSource(self.base, ".".join(member_parts[:-1]))
)
object.__setattr__(self, "member", member_parts[-1])
def reconstruct(self, codegen):
return self.base.reconstruct(codegen) + codegen.create_load_attrs(self.member)
def guard_source(self):
return self.base.guard_source()
def name(self):
if not self.member.isidentifier():
return f"getattr({self.base.name()}, {self.member!r})"
return f"{self.base.name()}.{self.member}"
@dataclasses.dataclass(frozen=True)
class ParamBufferSource(AttrSource):
def guard_source(self):
return _GUARD_SOURCE_NN_MODULE[self.base.guard_source()]
class TensorProperty(enum.Enum):
SIZE = 0
STRIDE = 1
STORAGE_OFFSET = 2
@dataclasses.dataclass(frozen=True)
class TensorPropertySource(Source):
base: Source
prop: TensorProperty
idx: Optional[int] = None # None for STORAGE_OFFSET
def __post_init__(self):
assert self.base is not None
if self.prop is TensorProperty.STORAGE_OFFSET:
assert self.idx is None
else:
assert self.idx is not None
def reconstruct(self, codegen):
raise NotImplementedError()
def guard_source(self):
return self.base.guard_source()
def name(self):
if self.prop is TensorProperty.SIZE:
return f"{self.base.name()}.size()[{self.idx}]"
elif self.prop is TensorProperty.STRIDE:
return f"{self.base.name()}.stride()[{self.idx}]"
elif self.prop is TensorProperty.STORAGE_OFFSET:
assert self.idx is None
return f"{self.base.name()}.storage_offset()"
else:
raise AssertionError(f"unhandled {self.prop}")
@dataclasses.dataclass(frozen=True)
class NegateSource(Source):
base: Source
def __post_init__(self):
assert self.base is not None
def reconstruct(self, codegen):
raise NotImplementedError()
def guard_source(self):
return self.base.guard_source()
def name(self):
# NB: use method call so that function stripping regexes work
return f"{self.base.name()}.__neg__()"
@dataclasses.dataclass(frozen=True)
class DefaultsSource(Source):
base: Source
idx_key: Union[int, str]
is_kw: bool = False
field: str = dataclasses.field(init=False, repr=False, compare=False)
_name: str = dataclasses.field(init=False, repr=False, compare=False)
def __post_init__(self):
assert (
self.base
), "Base must be a valid source in order to properly track and guard this Defaults to its origin."
if self.is_kw:
assert isinstance(self.idx_key, str)
object.__setattr__(self, "field", "__kwdefaults__")
object.__setattr__(
self, "_name", f"{self.base.name()}.{self.field}['{self.idx_key}']"
)
else:
assert isinstance(self.idx_key, int)
object.__setattr__(self, "field", "__defaults__")
object.__setattr__(
self, "_name", f"{self.base.name()}.{self.field}[{self.idx_key}]"
)
def reconstruct(self, codegen):
instrs = self.base.reconstruct(codegen)
instrs.extend(codegen.create_load_attrs(self.field))
instrs.extend(
[
codegen.create_load_const(self.idx_key),
create_instruction("BINARY_SUBSCR"),
]
)
return instrs
def guard_source(self):
return self.base.guard_source()
def name(self):
return self._name
@dataclasses.dataclass(frozen=True)
class GetItemSource(Source):
base: Source
index: Any
def __post_init__(self):
assert self.base is not None
def reconstruct(self, codegen):
instrs = self.base.reconstruct(codegen)
if isinstance(self.index, Source):
instrs.extend(self.index.reconstruct(codegen))
else:
instrs.append(codegen.create_load_const(self.index))
instrs.append(create_instruction("BINARY_SUBSCR"))
return instrs
def guard_source(self):
return self.base.guard_source()
def name(self):
if isinstance(self.index, Source):
return f"{self.base.name()}[{self.index.name()}]"
else:
if isinstance(self.index, enum.Enum):
return f"{self.base.name()}[{enum_repr(self.index)}]"
else:
return f"{self.base.name()}[{self.index!r}]"
@dataclasses.dataclass(frozen=True)
class TupleIteratorGetItemSource(GetItemSource):
def reconstruct(self, codegen):
codegen.load_import_from(utils.__name__, "tuple_iterator_getitem")
return [
*self.base.reconstruct(codegen),
codegen.create_load_const(self.index),
*create_call_function(2, True),
]
def name(self):
return f"___tuple_iterator_getitem({self.base.name()}, {self.index!r})"
@dataclasses.dataclass(frozen=True)
class TypeSource(Source):
base: Source
def __post_init__(self):
assert self.base is not None
def reconstruct(self, codegen):
codegen.load_import_from("builtins", "type")
return self.base.reconstruct(codegen) + create_call_function(1, True)
def guard_source(self):
return self.base.guard_source()
def name(self):
return f"type({self.base.name()})"
@dataclasses.dataclass(frozen=True)
class SuperSource(Source):
type: Source
obj: Source
def __post_init__(self):
assert self.type is not None
assert self.obj is not None
def reconstruct(self, codegen):
codegen.load_import_from("builtins", "super")
return (
self.type.reconstruct(codegen)
+ self.obj.reconstruct(codegen)
+ create_call_function(2, True)
)
def guard_source(self):
return self.obj.guard_source()
def name(self):
return f"super({self.type.name()}, {self.obj.name()})"
@dataclasses.dataclass(frozen=True)
class ODictGetItemSource(Source):
base: Source
index: Any
def __post_init__(self):
assert self.base is not None
def reconstruct(self, codegen):
return [
codegen._create_load_const(collections.OrderedDict.__getitem__),
*self.base.reconstruct(codegen),
codegen.create_load_const(self.index),
*create_call_function(2, True),
]
def guard_source(self):
return self.base.guard_source()
def name(self):
if isinstance(self.index, type):
rep = f'__load_module("{self.index.__module__}").{self.index.__qualname__}'
return f"___odict_getitem({self.base.name()}, {rep})"
else:
return f"___odict_getitem({self.base.name()}, {self.index!r})"
@dataclasses.dataclass(frozen=True)
class NNModuleSource(Source):
inner: Source
def reconstruct(self, codegen):
return self.inner.reconstruct(codegen)
def guard_source(self):
return _GUARD_SOURCE_NN_MODULE[self.inner.guard_source()]
def name(self):
return self.inner.name()
@dataclasses.dataclass(frozen=True)
class NotNNModuleSource(NNModuleSource):
def guard_source(self):
return _GUARD_SOURCE_NOT_NN_MODULE[self.inner.guard_source()]
@dataclasses.dataclass(frozen=True)
class FSDPNNModuleSource(NNModuleSource):
def guard_source(self):
return _GUARD_SOURCE_FSDP_MODULE[self.inner.guard_source()]
@dataclasses.dataclass(frozen=True)
class DeterministicAlgorithmsSource(Source):
def name(self):
return ""
def guard_source(self):
return GuardSource.GLOBAL
@dataclasses.dataclass(frozen=True)
class ConstantSource(Source):
source_name: str
def reconstruct(self, codegen):
return [codegen.create_load_global(self.source_name, False, add=False)]
def guard_source(self):
return GuardSource.CONSTANT
def name(self):
return self.source_name
def make_guard(self, fn, is_volatile=False):
raise NotImplementedError()
# This is a synthetic source that is associated with the singleton
# shape env guard we always register for all frames. We get the actual
# guard contents from the ambient ShapeEnv
@dataclasses.dataclass(frozen=True)
class ShapeEnvSource(Source):
def name(self):
return ""
def guard_source(self):
return GuardSource.SHAPE_ENV