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from typing import Any, Callable, Optional
from torch.utils._pytree import Context, TreeSpec
def reorder_kwargs(user_kwargs: dict[str, Any], spec: TreeSpec) -> dict[str, Any]:
"""Reorder user-provided kwargs to match the order in `spec`. `spec` is
expected to be the in_spec of an exported program, i.e. the spec that
results from flattening `(args, kwargs)`.
We need this to provide consistent input ordering, such so that users can
pass in foo(a=a, b=b) OR foo(b=b, a=a) and receive the same result.
"""
# Make sure that the spec is actually shaped like (args, kwargs)
assert spec.type is tuple
assert spec.num_children == 2
kwargs_spec = spec.children_specs[1]
assert kwargs_spec.type is dict
if set(user_kwargs) != set(kwargs_spec.context):
raise ValueError(
f"Ran into a kwarg keyword mismatch: "
f"Got the following keywords {list(user_kwargs)} but expected {kwargs_spec.context}"
)
reordered_kwargs = {}
for kw in kwargs_spec.context:
reordered_kwargs[kw] = user_kwargs[kw]
return reordered_kwargs
def is_equivalent(
spec1: TreeSpec,
spec2: TreeSpec,
equivalence_fn: Callable[[Optional[type], Context, Optional[type], Context], bool],
) -> bool:
"""Customizable equivalence check for two TreeSpecs.
Arguments:
spec1: The first TreeSpec to compare
spec2: The second TreeSpec to compare
equivalence_fn: A function to determine the equivalence of two
TreeSpecs by examining their types and contexts. It will be called like:
equivalence_fn(spec1.type, spec1.context, spec2.type, spec2.context)
This function will be applied recursively to all children.
Returns:
True if the two TreeSpecs are equivalent, False otherwise.
"""
if not equivalence_fn(spec1.type, spec1.context, spec2.type, spec2.context):
return False
# Recurse on children
if len(spec1.children_specs) != len(spec2.children_specs):
return False
for child_spec1, child_spec2 in zip(spec1.children_specs, spec2.children_specs):
if not is_equivalent(child_spec1, child_spec2, equivalence_fn):
return False
return True
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