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# mypy: allow-untyped-defs
"""
This module provides Source classes that track the origins of values in PyTorch Dynamo.
Sources represent where values come from (e.g. local variables, globals, attributes) and
are used for guard generation and code reconstruction during compilation.
The module includes specialized sources for:
- Local variables and synthetic locals
- Global variables and constants
- Object attributes and method calls
- NN module specialization (specialized vs unspecialized)
- Random values and tensor properties
- Default argument handling
- FSDP (Fully Sharded Data Parallel) modules
Sources play a key role in Dynamo's guard system by tracking value origins for
guard generation, and in code reconstruction by providing methods to rebuild
the code needed to recreate values.
"""
import dataclasses
import enum
from typing import Any, Optional, Union
from torch._guards import ChainedSource, GuardSource, Source
from . import utils
from .bytecode_transformation import create_call_function, create_instruction
# It shouldn't be supported to construct an NNModuleVariable inside an FSDP module,
# so those cases are omitted intentionally
# represents nn.Modules tracked with NNModuleVariable (specialized is implicit in the variable name)
_GUARD_SOURCE_SPECIALIZED_NN_MODULE = {
GuardSource.LOCAL: GuardSource.LOCAL_SPECIALIZED_NN_MODULE,
GuardSource.GLOBAL: GuardSource.GLOBAL_SPECIALIZED_NN_MODULE,
GuardSource.LOCAL_SPECIALIZED_NN_MODULE: GuardSource.LOCAL_SPECIALIZED_NN_MODULE,
GuardSource.GLOBAL_SPECIALIZED_NN_MODULE: GuardSource.GLOBAL_SPECIALIZED_NN_MODULE,
# Just to ensure that guard_source() works
GuardSource.LOCAL_UNSPECIALIZED_NN_MODULE: GuardSource.LOCAL_UNSPECIALIZED_NN_MODULE,
GuardSource.GLOBAL_UNSPECIALIZED_NN_MODULE: GuardSource.GLOBAL_UNSPECIALIZED_NN_MODULE,
GuardSource.LOCAL_UNSPECIALIZED_BUILTIN_NN_MODULE: GuardSource.LOCAL_UNSPECIALIZED_BUILTIN_NN_MODULE,
GuardSource.GLOBAL_UNSPECIALIZED_BUILTIN_NN_MODULE: GuardSource.GLOBAL_UNSPECIALIZED_BUILTIN_NN_MODULE,
GuardSource.LOCAL_FSDP_MODULE: GuardSource.LOCAL_FSDP_MODULE,
GuardSource.GLOBAL_FSDP_MODULE: GuardSource.GLOBAL_FSDP_MODULE,
}
# represents nn.Modules tracked with UnspecializedNNModuleVariable
_GUARD_SOURCE_UNSPECIALIZED_NN_MODULE = {
GuardSource.LOCAL: GuardSource.LOCAL_UNSPECIALIZED_NN_MODULE,
GuardSource.GLOBAL: GuardSource.GLOBAL_UNSPECIALIZED_NN_MODULE,
GuardSource.LOCAL_UNSPECIALIZED_NN_MODULE: GuardSource.LOCAL_UNSPECIALIZED_NN_MODULE,
GuardSource.GLOBAL_UNSPECIALIZED_NN_MODULE: GuardSource.GLOBAL_UNSPECIALIZED_NN_MODULE,
# this happens for an UnspecializedNNModule submodule on a NNModuleVariable
GuardSource.LOCAL_SPECIALIZED_NN_MODULE: GuardSource.LOCAL_UNSPECIALIZED_NN_MODULE,
GuardSource.GLOBAL_SPECIALIZED_NN_MODULE: GuardSource.GLOBAL_UNSPECIALIZED_NN_MODULE,
# Just to ensure that guard_source() works
GuardSource.LOCAL_UNSPECIALIZED_BUILTIN_NN_MODULE: GuardSource.LOCAL_UNSPECIALIZED_BUILTIN_NN_MODULE,
GuardSource.GLOBAL_UNSPECIALIZED_BUILTIN_NN_MODULE: GuardSource.GLOBAL_UNSPECIALIZED_BUILTIN_NN_MODULE,
GuardSource.LOCAL_FSDP_MODULE: GuardSource.LOCAL_FSDP_MODULE,
GuardSource.GLOBAL_FSDP_MODULE: GuardSource.GLOBAL_FSDP_MODULE,
}
# represents nn.Modules tracked with UnspecializedBuiltinNNModuleVariable
_GUARD_SOURCE_UNSPECIALIZED_BUILTIN_NN_MODULE = {
GuardSource.LOCAL: GuardSource.LOCAL_UNSPECIALIZED_BUILTIN_NN_MODULE,
GuardSource.GLOBAL: GuardSource.GLOBAL_UNSPECIALIZED_BUILTIN_NN_MODULE,
GuardSource.LOCAL_UNSPECIALIZED_NN_MODULE: GuardSource.LOCAL_UNSPECIALIZED_BUILTIN_NN_MODULE,
GuardSource.GLOBAL_UNSPECIALIZED_NN_MODULE: GuardSource.GLOBAL_UNSPECIALIZED_BUILTIN_NN_MODULE,
GuardSource.LOCAL_SPECIALIZED_NN_MODULE: GuardSource.LOCAL_UNSPECIALIZED_BUILTIN_NN_MODULE,
GuardSource.GLOBAL_SPECIALIZED_NN_MODULE: GuardSource.GLOBAL_UNSPECIALIZED_BUILTIN_NN_MODULE,
# Just to ensure that guard_source() works
GuardSource.LOCAL_UNSPECIALIZED_BUILTIN_NN_MODULE: GuardSource.LOCAL_UNSPECIALIZED_BUILTIN_NN_MODULE,
GuardSource.GLOBAL_UNSPECIALIZED_BUILTIN_NN_MODULE: GuardSource.GLOBAL_UNSPECIALIZED_BUILTIN_NN_MODULE,
GuardSource.LOCAL_FSDP_MODULE: GuardSource.LOCAL_FSDP_MODULE,
GuardSource.GLOBAL_FSDP_MODULE: GuardSource.GLOBAL_FSDP_MODULE,
}
_GUARD_SOURCE_FSDP_MODULE = {
GuardSource.LOCAL: GuardSource.LOCAL_FSDP_MODULE,
GuardSource.GLOBAL: GuardSource.GLOBAL_FSDP_MODULE,
GuardSource.LOCAL_SPECIALIZED_NN_MODULE: GuardSource.LOCAL_FSDP_MODULE,
GuardSource.GLOBAL_SPECIALIZED_NN_MODULE: GuardSource.GLOBAL_FSDP_MODULE,
GuardSource.LOCAL_FSDP_MODULE: GuardSource.LOCAL_FSDP_MODULE,
GuardSource.GLOBAL_FSDP_MODULE: GuardSource.GLOBAL_FSDP_MODULE,
GuardSource.LOCAL_UNSPECIALIZED_NN_MODULE: GuardSource.LOCAL_FSDP_MODULE,
GuardSource.GLOBAL_UNSPECIALIZED_NN_MODULE: GuardSource.GLOBAL_FSDP_MODULE,
GuardSource.LOCAL_UNSPECIALIZED_BUILTIN_NN_MODULE: GuardSource.LOCAL_FSDP_MODULE,
GuardSource.GLOBAL_UNSPECIALIZED_BUILTIN_NN_MODULE: GuardSource.GLOBAL_FSDP_MODULE,
}
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
@dataclasses.dataclass(frozen=True)
class LocalSource(Source):
local_name: str
# Whether this local is an input to the root frame.
is_input: bool = False
# Whether we know this input is dynamic (based on example_inputs)
# For non tensors, we simply look at the first index of the tuple
dynamism: Optional[frozenset[str]] = None
# Whether the item at this source is the _content_ of a cell that is
# dereferenced from the root frame, i.e., it's a part of the `co_cellvars`
# or `co_freevars`.
is_derefed_cell_contents: bool = False
def reconstruct(self, codegen):
if self.is_derefed_cell_contents:
codegen.load_deref(self.local_name)
else:
codegen.append_output(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 SyntheticLocalSource(Source):
local_name: str
def reconstruct(self, codegen):
codegen.append_output(codegen.create_load(self.local_name))
def guard_source(self):
return GuardSource.SYNTHETIC_LOCAL
def name(self):
return f"SYNTHETIC_LOCAL[{self.local_name!r}]"
@dataclasses.dataclass(frozen=True)
class RandomValueSource(Source):
random_call_index: int
def guard_source(self):
return GuardSource.RANDOM_VALUE
def reconstruct(self, codegen):
codegen.append_output(codegen.create_load(codegen.tx.output.random_values_var))
codegen.append_output(codegen.create_load_const(self.random_call_index))
codegen.append_output(create_instruction("BINARY_SUBSCR"))
def name(self):
return f"random_value_{self.random_call_index}"
@dataclasses.dataclass(frozen=True)
class GlobalSource(Source):
global_name: str
def reconstruct(self, codegen):
codegen.append_output(codegen.create_load_global(self.global_name, 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):
codegen.add_push_null(
lambda: codegen.append_output(
codegen.create_load_global(self.global_name, add=True)
)
)
codegen.extend_output(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 WeakRefCallSource(ChainedSource):
def reconstruct(self, codegen):
codegen.add_push_null(lambda: codegen(self.base))
codegen.extend_output(create_call_function(0, False))
def guard_source(self):
return self.base.guard_source()
def name(self):
return f"{self.base.name()}()"
@dataclasses.dataclass(frozen=True)
class CallFunctionNoArgsSource(WeakRefCallSource):
pass
@dataclasses.dataclass(frozen=True)
class AttrSource(ChainedSource):
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):
codegen(self.base)
codegen.extend_output(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 GenericAttrSource(ChainedSource):
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):
codegen(self.base)
codegen.extend_output(codegen.create_load_attrs(self.member))
def guard_source(self):
return self.base.guard_source()
def name(self):
return f"object.__getattribute__({self.base.name()}, {self.member!r})"
@dataclasses.dataclass(frozen=True)
class LocalCellSource(Source):
"""
Conceptually, this class is `LocalSource` for cell objects implicitly
generated by Python (e.g., captured variables).
"""
local_name: str
def reconstruct(self, codegen):
# Although `LOAD_FAST` and `LOAD_CLOSURE` have the same semantics,
# Dynamo's bytecode transformation differentiates them slightly, so we
# always emit `LOAD_CLOSURE` here.
codegen.append_output(codegen.create_load_closure(self.local_name))
# All the other methods are intentionally unimplemented because e.g., a
# local cell object should never be used for guards.
# Represents tensor.grad source. It could be represented by AttrSource as well.
# But, we could access grad field on tensor directly in C++ without going
# through the Python bytecodes. Therefore, we use a separate source for grad
# field.
@dataclasses.dataclass(frozen=True)
class GradSource(ChainedSource):
member: str = "grad"
def reconstruct(self, codegen):
codegen(self.base)
codegen.extend_output(codegen.create_load_attrs(self.member))
def guard_source(self):
return self.base.guard_source()
def name(self):
return f"{self.base.name()}.{self.member}"
@dataclasses.dataclass(frozen=True)
class ParamBufferSource(AttrSource):
def guard_source(self):
return _GUARD_SOURCE_SPECIALIZED_NN_MODULE[self.base.guard_source()]
# Special AttrSource to differentiate module._buffers or module._parameters
@dataclasses.dataclass(frozen=True)
class UnspecializedParamBufferSource(AttrSource):
pass
# This source is intended to be used in places where a source is needed but it is expected
# that the symbol will be simplified out later on. Symbols with ephemeral sources are
# prioritized to be simplified out when e.g. compared against a symbol without an ephemeral
# source. Guarding on this source is an error.
#
# Example: During subclass view fake-ification, any close-over ViewFunc state should be
# symbolicized / fake-ified to avoid invalid specialization during view replay. This source
# is useful for symbols utilized in the middle of the view chain that are not expected to be
# present within the final view shape metadata.
@dataclasses.dataclass(frozen=True)
class EphemeralSource(Source):
desc: Optional[str] = None
def guard_source(self):
return GuardSource.EPHEMERAL
def name(self):
return f"<ephemeral{': ' + self.desc if self.desc is not None else ''}>"
def make_guard(self, fn):
raise NotImplementedError
def is_ephemeral(self):
return True
class TensorProperty(enum.Enum):
SIZE = 0
STRIDE = 1
STORAGE_OFFSET = 2
def method_name(self):
if self is TensorProperty.SIZE:
return "size"
elif self is TensorProperty.STRIDE:
return "stride"
elif self is TensorProperty.STORAGE_OFFSET:
return "storage_offset"
@dataclasses.dataclass(frozen=True)
class TensorPropertySource(ChainedSource):
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):
codegen.add_push_null(
lambda: codegen.load_import_from(
utils.__name__, f"call_{self.prop.method_name()}"
)
)
codegen(self.base)
if self.idx is not None:
codegen.append_output(codegen.create_load_const(self.idx))
codegen.extend_output(
create_call_function(2 if self.idx is not None else 1, False)
)
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 IndexedSource(ChainedSource):
idx: int
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):
return f"({self.idx}, {self.base.name()})"
@dataclasses.dataclass(frozen=True)
class NegateSource(ChainedSource):
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 ConvertIntSource(ChainedSource):
def __post_init__(self):
assert self.base is not None
def reconstruct(self, codegen):
codegen(self.base)
def guard_source(self):
return self.base.guard_source()
def name(self):
return f"cast_symbool_to_symint_guardless({self.base.name()})"
@dataclasses.dataclass(frozen=True)
class FlattenScriptObjectSource(ChainedSource):
def __post_init__(self):
assert self.base is not None
def reconstruct(self, codegen):
codegen(self.base)
def guard_source(self):
return self.base.guard_source()
def name(self):
return f"{self.base.name()}.__obj_flatten__()"
@dataclasses.dataclass(frozen=True)
class ScriptObjectQualifiedNameSource(ChainedSource):
def __post_init__(self):
assert self.base is not None
def reconstruct(self, codegen):
codegen(self.base)
def guard_source(self):
return self.base.guard_source()
def name(self):
return f"{self.base.name()}._type().qualified_name()"
class AttrProxySource(ChainedSource):
def reconstruct(self, codegen):
codegen(self.base)
def guard_source(self):
return self.base.guard_source()
def name(self):
return f"{self.base.name()}.get_base()"
@dataclasses.dataclass(frozen=True)
class DefaultsSource(ChainedSource):
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):
codegen(self.base)
codegen.extend_output(codegen.create_load_attrs(self.field))
codegen.append_output(codegen.create_load_const(self.idx_key))
codegen.append_output(create_instruction("BINARY_SUBSCR"))
def guard_source(self):
return self.base.guard_source()
def name(self):
return self._name
@dataclasses.dataclass(frozen=True)
class GetItemSource(ChainedSource):
index: Any
index_is_slice: bool = False
def __post_init__(self):
assert self.base is not None
if isinstance(self.index, slice):
# store the hashable version of the slice so the whole GetItemSource is hashable
super().__setattr__("index", self.index.__reduce__())
super().__setattr__("index_is_slice", True)
def reconstruct(self, codegen):
codegen(self.base)
if self.index_is_slice:
codegen.append_output(codegen.create_load_const(self.unpack_slice()))
else:
codegen.append_output(codegen.create_load_const(self.index))
codegen.append_output(create_instruction("BINARY_SUBSCR"))
def guard_source(self):
return self.base.guard_source()
def unpack_slice(self):
assert self.index_is_slice
slice_class, slice_args = self.index
return slice_class(*slice_args)
def name(self):
# Index can be of following types
# 1) index is a slice - example 1:4
# 2) index is a constant - example string, integer
assert not isinstance(self.index, Source)
if self.index_is_slice:
return f"{self.base.name()}[{self.unpack_slice()!r}]"
else:
return f"{self.base.name()}[{self.index!r}]"
@dataclasses.dataclass(frozen=True)
class ConstDictKeySource(ChainedSource):
index: Any
def guard_source(self):
return self.base.guard_source()
def reconstruct(self, codegen):
codegen.add_push_null(
lambda: codegen.load_import_from(utils.__name__, "dict_keys_getitem")
)
codegen(self.base)
codegen.append_output(codegen.create_load_const(self.index))
codegen.extend_output(create_call_function(2, False))
def name(self):
# The list creation will be CSE'd by PyExprCSEPass
return f"list(dict.keys({self.base.name()}))[{self.index!r}]"
def is_dict_key(self):
return True
# Used to access an item from the dictionary
@dataclasses.dataclass(frozen=True)
class DictGetItemSource(ChainedSource):
# Key to access in the dictionary. It can be one of the the following types
# 1) ConstDictKeySource
# 2) constant - like string, integer
index: Any
def __post_init__(self):
from .variables import ConstantVariable
assert isinstance(
self.index, ConstDictKeySource
) or ConstantVariable.is_literal(self.index)
def guard_source(self):
return self.base.guard_source()
def reconstruct(self, codegen):
# reconstruct dict.__getitem__(dct, key)
# Load dict.__getitem__
codegen.add_push_null(
lambda: codegen.load_import_from(utils.__name__, "dict_getitem")
)
# Load dict
codegen(self.base)
# Load key
if isinstance(self.index, Source):
codegen(self.index)
else:
codegen.append_output(codegen.create_load_const(self.index))
codegen.extend_output(create_call_function(2, False))
def name(self):
if isinstance(self.index, ConstDictKeySource):
return f"dict.__getitem__({self.base.name()}, {self.index.name()})"
else:
return f"{self.base.name()}[{self.index!r}]"
@dataclasses.dataclass(frozen=True)
class ListGetItemSource(GetItemSource):
"""
Same as GetItemSource with reconstruct and name overridden to be list specific.
"""
def reconstruct(self, codegen):
# Reconstruct list.__getitem__(lst, index) to avoid any side effects
# from possibly overridden __getitem__.
# Load list.__getitem__
codegen.add_push_null(
lambda: codegen.load_import_from(utils.__name__, "list_getitem")
)
# Load the list
codegen(self.base)
# Load the index
if self.index_is_slice:
raise RuntimeError(
"List[slice] is a temporary object and should not have a source"
)
else:
codegen.append_output(codegen.create_load_const(self.index))
codegen.extend_output(create_call_function(2, False))
def name(self):
# Index can be of following types
# 1) index is a slice - example 1:4
# 2) index is a constant - example string, integer
assert not isinstance(self.index, Source)
if self.index_is_slice:
raise RuntimeError(
"List[slice] is a temporary object and should not have a source"
)
else:
return f"list.__getitem__({self.base.name()}, {self.index!r})"
@dataclasses.dataclass(frozen=True)
class TupleIteratorGetItemSource(GetItemSource):
def reconstruct(self, codegen):
codegen.add_push_null(
lambda: codegen.load_import_from(utils.__name__, "tuple_iterator_getitem")
)
codegen(self.base)
codegen.append_output(codegen.create_load_const(self.index))
codegen.extend_output(create_call_function(2, False))
def name(self):
return f"___tuple_iterator_getitem({self.base.name()}, {self.index!r})"
@dataclasses.dataclass(frozen=True)
class TypeSource(ChainedSource):
def __post_init__(self):
assert self.base is not None
def reconstruct(self, codegen):
codegen.add_push_null(lambda: codegen.load_import_from("builtins", "type"))
codegen(self.base)
codegen.extend_output(create_call_function(1, False))
def guard_source(self):
return self.base.guard_source()
def name(self):
return f"type({self.base.name()})"
@dataclasses.dataclass(frozen=True)
class OptimizerSource(ChainedSource):
def reconstruct(self, codegen):
codegen(self.base)
def guard_source(self):
return self.base.guard_source()
def name(self):
return self.base.name()
@dataclasses.dataclass(frozen=True)
class NNModuleSource(ChainedSource):
def reconstruct(self, codegen):
codegen(self.base)
def guard_source(self):
return _GUARD_SOURCE_SPECIALIZED_NN_MODULE[self.base.guard_source()]
def name(self):
return self.base.name()
@dataclasses.dataclass(frozen=True)
class UnspecializedNNModuleSource(NNModuleSource):
def guard_source(self):
return _GUARD_SOURCE_UNSPECIALIZED_NN_MODULE[self.base.guard_source()]
@dataclasses.dataclass(frozen=True)
class UnspecializedBuiltinNNModuleSource(UnspecializedNNModuleSource):
def guard_source(self):
return _GUARD_SOURCE_UNSPECIALIZED_BUILTIN_NN_MODULE[self.base.guard_source()]
@dataclasses.dataclass(frozen=True)
class FSDPNNModuleSource(NNModuleSource):
def guard_source(self):
return _GUARD_SOURCE_FSDP_MODULE[self.base.guard_source()]
@dataclasses.dataclass(frozen=True)
class GlobalStateSource(Source):
def name(self):
return ""
def guard_source(self):
return GuardSource.GLOBAL
@dataclasses.dataclass(frozen=True)
class TorchFunctionModeStackSource(Source):
ind: int
def name(self):
return f"___get_torch_function_mode_stack_at({self._get_index()})"
def _get_index(self):
from .variables.torch_function import TorchFunctionModeStackVariable
return TorchFunctionModeStackVariable.get_mode_index(self.ind)
def reconstruct(self, codegen):
codegen.add_push_null(
lambda: codegen.load_import_from(
utils.__name__, "get_torch_function_mode_stack_at"
)
)
codegen.extend_output([codegen.create_load_const(self._get_index())])
codegen.extend_output(create_call_function(1, False))
def guard_source(self):
return GuardSource.GLOBAL
@dataclasses.dataclass(frozen=True)
class ConstantSource(Source):
source_name: str
def reconstruct(self, codegen):
codegen.append_output(codegen.create_load_global(self.source_name, add=False))
def guard_source(self):
return GuardSource.CONSTANT
def name(self):
return self.source_name
def make_guard(self, fn):
raise NotImplementedError
@dataclasses.dataclass(frozen=True)
class NumpyTensorSource(ChainedSource):
def name(self) -> str:
return f"___from_numpy({self.base.name()})"
def guard_source(self):
return self.base.guard_source()
def reconstruct(self, codegen):
codegen.add_push_null(lambda: codegen.load_import_from("torch", "as_tensor"))
codegen(self.base)
codegen.extend_output(create_call_function(1, False))
@dataclasses.dataclass(frozen=True)
class SubclassAttrListSource(ChainedSource):
def name(self) -> str:
return f"{self.base.name()}.__tensor_flatten__()[0]"
def guard_source(self):
return self.base.guard_source()
# NB: We don't expect you to actually ever generate guards against this
# source, it is ephemeral
@dataclasses.dataclass(frozen=True)
class FloatTensorSource(ChainedSource):
def name(self) -> str:
return f"___as_tensor({self.base.name()})"
def guard_source(self):
return self.base.guard_source()
@dataclasses.dataclass(frozen=True)
class CallMethodItemSource(ChainedSource):
def name(self) -> str:
return f"{self.base.name()}.item()"
def guard_source(self):
return self.base.guard_source()
# 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
@dataclasses.dataclass(frozen=True)
class BackwardStateSource(Source):
def name(self):
return ""
def guard_source(self):
return GuardSource.BACKWARD_STATE
def is_from_local_source(source: Source, *, only_allow_input=False):
if isinstance(source, ChainedSource):
return is_from_local_source(source.base, only_allow_input=only_allow_input)
if not isinstance(source, LocalSource):
return False
if only_allow_input and not source.is_input:
return False
return True
def is_from_unspecialized_param_buffer_source(source: Source):
if isinstance(source, UnspecializedParamBufferSource):
return True
if isinstance(source, ChainedSource):
return is_from_unspecialized_param_buffer_source(source.base)
return False
def is_from_flatten_script_object_source(source: Source):
if isinstance(source, FlattenScriptObjectSource):
return True
elif isinstance(source, ChainedSource):
return is_from_flatten_script_object_source(source.base)
return False
def is_from_optimizer_source(source: Source):
if isinstance(source, OptimizerSource):
return True
if isinstance(source, ChainedSource):
return is_from_optimizer_source(source.base)
return False
# TODO: can probably write a generic "test this on everything in the chain"
# helper
def is_from_defaults(source: Source):
if isinstance(source, DefaultsSource):
return True
# Accessed with func.__kwdefaults__["foo"]
if (
isinstance(source, DictGetItemSource)
and isinstance(source.base, AttrSource)
and source.base.member == "__kwdefaults__"
):
return True
# Accessed with func.__defaults__[0]
if (
isinstance(source, GetItemSource)
and isinstance(source.base, AttrSource)
and source.base.member == "__defaults__"
):
return True
if isinstance(source, ChainedSource):
return is_from_defaults(source.base)
return False