546 lines
17 KiB
Python
546 lines
17 KiB
Python
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import collections
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import dataclasses
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import enum
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from typing import Any, Optional, Union
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from torch._guards import ChainedSource, GuardSource, Source
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from . import utils
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from .bytecode_transformation import create_call_function, create_instruction
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from .utils import enum_repr
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# It shouldn't be supported to construct an NNModuleVariable inside an FSDP module,
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# so those cases are omitted intentionally
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_GUARD_SOURCE_NN_MODULE = {
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GuardSource.LOCAL: GuardSource.LOCAL_NN_MODULE,
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GuardSource.GLOBAL: GuardSource.GLOBAL_NN_MODULE,
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GuardSource.LOCAL_NN_MODULE: GuardSource.LOCAL_NN_MODULE,
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GuardSource.GLOBAL_NN_MODULE: GuardSource.GLOBAL_NN_MODULE,
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}
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_GUARD_SOURCE_FSDP_MODULE = {
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GuardSource.LOCAL: GuardSource.LOCAL_FSDP_MODULE,
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GuardSource.GLOBAL: GuardSource.GLOBAL_FSDP_MODULE,
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GuardSource.LOCAL_NN_MODULE: GuardSource.LOCAL_FSDP_MODULE,
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GuardSource.GLOBAL_NN_MODULE: GuardSource.GLOBAL_FSDP_MODULE,
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GuardSource.LOCAL_FSDP_MODULE: GuardSource.LOCAL_FSDP_MODULE,
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GuardSource.GLOBAL_FSDP_MODULE: GuardSource.GLOBAL_FSDP_MODULE,
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}
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_GUARD_SOURCE_NOT_NN_MODULE = {
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GuardSource.LOCAL: GuardSource.LOCAL,
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GuardSource.GLOBAL: GuardSource.GLOBAL,
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GuardSource.LOCAL_NN_MODULE: GuardSource.LOCAL,
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GuardSource.GLOBAL_NN_MODULE: GuardSource.GLOBAL,
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GuardSource.LOCAL_FSDP_MODULE: GuardSource.LOCAL,
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GuardSource.GLOBAL_FSDP_MODULE: GuardSource.GLOBAL,
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}
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def is_constant_source(source):
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if isinstance(source, ConstantSource):
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return True
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try:
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if source.guard_source() == GuardSource.CONSTANT:
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return True
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except NotImplementedError:
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pass
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return False
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def reconstruct_getitem(
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source: Union["GetItemSource", "ODictGetItemSource"], codegen, index_is_slice
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):
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source.base.reconstruct(codegen)
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if isinstance(source.index, Source):
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source.index.reconstruct(codegen)
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else:
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if index_is_slice:
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assert isinstance(source, GetItemSource)
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codegen.append_output(codegen.create_load_const(source.unpack_slice()))
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else:
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codegen.append_output(codegen.create_load_const(source.index))
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@dataclasses.dataclass(frozen=True)
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class LocalSource(Source):
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local_name: str
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cell_or_freevar: bool = False
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def reconstruct(self, codegen):
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codegen.append_output(codegen.create_load(self.local_name))
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def guard_source(self):
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return GuardSource.LOCAL
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def name(self):
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return f"L[{repr(self.local_name)}]"
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@dataclasses.dataclass(frozen=True)
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class SyntheticLocalSource(Source):
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local_name: str
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def reconstruct(self, codegen):
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codegen.append_output(codegen.create_load(self.local_name))
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def guard_source(self):
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return GuardSource.SYNTHETIC_LOCAL
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def name(self):
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return f"SYNTHETIC_LOCAL[{self.local_name!r}]"
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@dataclasses.dataclass(frozen=True)
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class RandomValueSource(Source):
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random_call_index: int
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def guard_source(self):
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return GuardSource.RANDOM_VALUE
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def reconstruct(self, codegen):
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codegen.append_output(codegen.create_load(codegen.tx.output.random_values_var))
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codegen.append_output(codegen.create_load_const(self.random_call_index))
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codegen.append_output(create_instruction("BINARY_SUBSCR"))
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def name(self):
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return f"random_value_{self.random_call_index}"
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@dataclasses.dataclass(frozen=True)
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class GlobalSource(Source):
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global_name: str
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def reconstruct(self, codegen):
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codegen.append_output(
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codegen.create_load_global(self.global_name, False, add=True)
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)
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def guard_source(self):
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return GuardSource.GLOBAL
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def name(self):
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return f"G[{repr(self.global_name)}]"
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@dataclasses.dataclass(frozen=True)
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class GlobalWeakRefSource(Source):
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global_name: str
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def reconstruct(self, codegen):
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codegen.append_output(
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codegen.create_load_global(self.global_name, True, add=True)
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)
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codegen.extend_output(create_call_function(0, False))
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def guard_source(self):
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return GuardSource.GLOBAL
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def name(self):
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return f"G[{repr(self.global_name)}]()"
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@dataclasses.dataclass(frozen=True)
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class AttrSource(ChainedSource):
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member: str
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get_static: bool = False
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def __post_init__(self):
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assert self.base, "Can't construct an AttrSource without a valid base source"
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if "." in self.member:
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member_parts = self.member.split(".")
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object.__setattr__(
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self, "base", AttrSource(self.base, ".".join(member_parts[:-1]))
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)
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object.__setattr__(self, "member", member_parts[-1])
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def reconstruct(self, codegen):
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self.base.reconstruct(codegen)
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codegen.extend_output(codegen.create_load_attrs(self.member))
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def guard_source(self):
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return self.base.guard_source()
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def name(self):
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if self.get_static:
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return f"inspect.getattr_static({self.base.name()}, {self.member!r})"
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elif not self.member.isidentifier():
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return f"getattr({self.base.name()}, {self.member!r})"
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return f"{self.base.name()}.{self.member}"
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@dataclasses.dataclass(frozen=True)
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class ParamBufferSource(AttrSource):
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def guard_source(self):
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return _GUARD_SOURCE_NN_MODULE[self.base.guard_source()]
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# This source is intended to be used in places where a source is needed but it is expected
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# that the symbol will be simplified out later on. Symbols with ephemeral sources are
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# prioritized to be simplified out when e.g. compared against a symbol without an ephemeral
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# source. Guarding on this source is an error.
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#
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# Example: During subclass view fake-ification, any close-over ViewFunc state should be
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# symbolicized / fake-ified to avoid invalid specialization during view replay. This source
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# is useful for symbols utilized in the middle of the view chain that are not expected to be
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# present within the final view shape metadata.
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@dataclasses.dataclass(frozen=True)
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class EphemeralSource(Source):
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desc: Optional[str] = None
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def guard_source(self):
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return GuardSource.EPHEMERAL
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def name(self):
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return f"<ephemeral{': ' + self.desc if self.desc is not None else ''}>"
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def make_guard(self):
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raise NotImplementedError()
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def is_ephemeral(self):
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return True
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class TensorProperty(enum.Enum):
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SIZE = 0
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STRIDE = 1
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STORAGE_OFFSET = 2
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def method_name(self):
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if self is TensorProperty.SIZE:
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return "size"
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elif self is TensorProperty.STRIDE:
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return "stride"
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elif self is TensorProperty.STORAGE_OFFSET:
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return "storage_offset"
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@dataclasses.dataclass(frozen=True)
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class TensorPropertySource(ChainedSource):
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prop: TensorProperty
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idx: Optional[int] = None # None for STORAGE_OFFSET
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def __post_init__(self):
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assert self.base is not None
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if self.prop is TensorProperty.STORAGE_OFFSET:
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assert self.idx is None
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else:
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assert self.idx is not None
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def reconstruct(self, codegen):
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self.base.reconstruct(codegen)
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codegen.append_output(codegen.create_load_attr(self.prop.method_name()))
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if self.idx is not None:
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codegen.append_output(codegen.create_load_const(self.idx))
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codegen.extend_output(
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create_call_function(1 if self.idx is not None else 0, True)
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)
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def guard_source(self):
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return self.base.guard_source()
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def name(self):
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if self.prop is TensorProperty.SIZE:
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return f"{self.base.name()}.size()[{self.idx}]"
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elif self.prop is TensorProperty.STRIDE:
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return f"{self.base.name()}.stride()[{self.idx}]"
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elif self.prop is TensorProperty.STORAGE_OFFSET:
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assert self.idx is None
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return f"{self.base.name()}.storage_offset()"
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else:
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raise AssertionError(f"unhandled {self.prop}")
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@dataclasses.dataclass(frozen=True)
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class NegateSource(ChainedSource):
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def __post_init__(self):
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assert self.base is not None
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def reconstruct(self, codegen):
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raise NotImplementedError()
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def guard_source(self):
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return self.base.guard_source()
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def name(self):
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# NB: use method call so that function stripping regexes work
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return f"{self.base.name()}.__neg__()"
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@dataclasses.dataclass(frozen=True)
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class ConvertIntSource(ChainedSource):
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def __post_init__(self):
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assert self.base is not None
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def reconstruct(self, codegen):
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self.base.reconstruct(codegen)
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def guard_source(self):
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return self.base.guard_source()
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def name(self):
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return f"cast_symbool_to_symint_guardless({self.base.name()})"
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@dataclasses.dataclass(frozen=True)
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class DefaultsSource(ChainedSource):
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idx_key: Union[int, str]
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is_kw: bool = False
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field: str = dataclasses.field(init=False, repr=False, compare=False)
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_name: str = dataclasses.field(init=False, repr=False, compare=False)
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def __post_init__(self):
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assert (
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self.base
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), "Base must be a valid source in order to properly track and guard this Defaults to its origin."
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if self.is_kw:
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assert isinstance(self.idx_key, str)
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object.__setattr__(self, "field", "__kwdefaults__")
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object.__setattr__(
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self, "_name", f"{self.base.name()}.{self.field}['{self.idx_key}']"
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)
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else:
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assert isinstance(self.idx_key, int)
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object.__setattr__(self, "field", "__defaults__")
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object.__setattr__(
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self, "_name", f"{self.base.name()}.{self.field}[{self.idx_key}]"
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)
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def reconstruct(self, codegen):
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self.base.reconstruct(codegen)
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codegen.extend_output(codegen.create_load_attrs(self.field))
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codegen.append_output(codegen.create_load_const(self.idx_key))
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codegen.append_output(create_instruction("BINARY_SUBSCR"))
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def guard_source(self):
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return self.base.guard_source()
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def name(self):
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return self._name
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@dataclasses.dataclass(frozen=True)
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class GetItemSource(ChainedSource):
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index: Any
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index_is_slice: bool = False
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def __post_init__(self):
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assert self.base is not None
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if isinstance(self.index, slice):
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# store the hashable version of the slice so the whole GetItemSource is hashable
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super().__setattr__("index", self.index.__reduce__())
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super().__setattr__("index_is_slice", True)
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def reconstruct(self, codegen):
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reconstruct_getitem(self, codegen, index_is_slice=self.index_is_slice)
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codegen.append_output(create_instruction("BINARY_SUBSCR"))
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def guard_source(self):
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return self.base.guard_source()
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def unpack_slice(self):
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assert self.index_is_slice
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slice_class, slice_args = self.index
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return slice_class(*slice_args)
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def name(self):
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# Index can be of following types
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# 1) ConstDictKeySource
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# 2) enum.Enum
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# 3) index is a slice - example 1:4
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# 4) index is a constant - example string, integer
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if isinstance(self.index, Source):
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if not isinstance(self.index, ConstDictKeySource):
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raise ValueError(
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"GetItemSource index must be a constant, enum or ConstDictKeySource"
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)
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return f"{self.base.name()}[{self.index.name()}]"
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elif self.index_is_slice:
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return f"{self.base.name()}[{self.unpack_slice()!r}]"
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elif isinstance(self.index, enum.Enum):
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return f"{self.base.name()}[{enum_repr(self.index, self.guard_source().is_local())}]"
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else:
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return f"{self.base.name()}[{self.index!r}]"
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@dataclasses.dataclass(frozen=True)
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class ConstDictKeySource(GetItemSource):
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def is_dict_key(self):
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return True
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def reconstruct(self, codegen):
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codegen.load_import_from(utils.__name__, "dict_keys_getitem")
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self.base.reconstruct(codegen)
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codegen.append_output(codegen.create_load_const(self.index))
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codegen.extend_output(create_call_function(2, True))
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def name(self):
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# The list creation will be CSE'd by PyExprCSEPass
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return f"list({self.base.name()}.keys())[{self.index!r}]"
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@dataclasses.dataclass(frozen=True)
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class TupleIteratorGetItemSource(GetItemSource):
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def reconstruct(self, codegen):
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codegen.load_import_from(utils.__name__, "tuple_iterator_getitem")
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self.base.reconstruct(codegen)
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codegen.append_output(codegen.create_load_const(self.index))
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codegen.extend_output(create_call_function(2, True))
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def name(self):
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return f"___tuple_iterator_getitem({self.base.name()}, {self.index!r})"
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@dataclasses.dataclass(frozen=True)
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class TypeSource(ChainedSource):
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def __post_init__(self):
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assert self.base is not None
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def reconstruct(self, codegen):
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codegen.load_import_from("builtins", "type")
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self.base.reconstruct(codegen)
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codegen.extend_output(create_call_function(1, True))
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def guard_source(self):
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return self.base.guard_source()
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def name(self):
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return f"type({self.base.name()})"
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@dataclasses.dataclass(frozen=True)
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class ODictGetItemSource(ChainedSource):
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index: Any
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def __post_init__(self):
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assert self.base is not None
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def reconstruct(self, codegen):
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codegen.append_output(
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codegen._create_load_const(collections.OrderedDict.__getitem__)
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)
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reconstruct_getitem(self, codegen, index_is_slice=False)
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codegen.extend_output(create_call_function(2, True))
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def guard_source(self):
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return self.base.guard_source()
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def name(self):
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if isinstance(self.index, type):
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rep = f'__load_module("{self.index.__module__}").{self.index.__qualname__}'
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|
return f"___odict_getitem({self.base.name()}, {rep})"
|
||
|
elif isinstance(self.index, Source):
|
||
|
return f"___odict_getitem({self.base.name()}, {self.index.name()})"
|
||
|
else:
|
||
|
return f"___odict_getitem({self.base.name()}, {self.index!r})"
|
||
|
|
||
|
|
||
|
@dataclasses.dataclass(frozen=True)
|
||
|
class NNModuleSource(ChainedSource):
|
||
|
def reconstruct(self, codegen):
|
||
|
self.base.reconstruct(codegen)
|
||
|
|
||
|
def guard_source(self):
|
||
|
return _GUARD_SOURCE_NN_MODULE[self.base.guard_source()]
|
||
|
|
||
|
def name(self):
|
||
|
return self.base.name()
|
||
|
|
||
|
|
||
|
@dataclasses.dataclass(frozen=True)
|
||
|
class NotNNModuleSource(NNModuleSource):
|
||
|
def guard_source(self):
|
||
|
return _GUARD_SOURCE_NOT_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 ConstantSource(Source):
|
||
|
source_name: str
|
||
|
|
||
|
def reconstruct(self, codegen):
|
||
|
codegen.append_output(
|
||
|
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):
|
||
|
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.load_import_from("torch", "as_tensor")
|
||
|
self.base.reconstruct(codegen)
|
||
|
codegen.extend_output(create_call_function(1, True))
|
||
|
|
||
|
|
||
|
# 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, *, allow_cell_or_freevar=True):
|
||
|
if isinstance(source, ChainedSource):
|
||
|
return is_from_local_source(
|
||
|
source.base, allow_cell_or_freevar=allow_cell_or_freevar
|
||
|
)
|
||
|
if not isinstance(source, LocalSource):
|
||
|
return False
|
||
|
if not allow_cell_or_freevar and source.cell_or_freevar:
|
||
|
return False
|
||
|
return True
|
||
|
|
||
|
|
||
|
# 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
|
||
|
if isinstance(source, ChainedSource):
|
||
|
return is_from_defaults(source.base)
|
||
|
return False
|