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Debugging mode: compare against NumPy after each operation #1047

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86 changes: 82 additions & 4 deletions cunumeric/coverage.py
Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,7 @@
import warnings
from dataclasses import dataclass
from functools import WRAPPER_ASSIGNMENTS, wraps
from itertools import islice
from types import (
BuiltinFunctionType,
FunctionType,
Expand Down Expand Up @@ -70,6 +71,46 @@ def filter_namespace(
}


def allclose(
a: Any, # numpy or cunumeric array-like
b: Any, # numpy or cunumeric array-like
rtol: float = 1e-5,
atol: float = 1e-8,
equal_nan: bool = False,
*,
diff_limit: Union[int, None] = 5, # None means no limit at all
check_dtype: bool = True,
) -> bool:
import numpy as np

if np.shape(a) != np.shape(b):
print(f"allclose: different shape: {np.shape(a)} vs {np.shape(b)}")
return False

# simplify handling of scalar values
a, b = np.atleast_1d(a), np.atleast_1d(b)

if check_dtype and a.dtype != b.dtype:
print(f"allclose: different dtype: {a.dtype} vs {b.dtype}")
return False

close = np.isclose(a, b, rtol=rtol, atol=atol, equal_nan=equal_nan)

all_close = np.all(close)

if (diff_limit is None or diff_limit > 0) and not all_close:
a += np.zeros(b.shape, dtype=a.dtype)
b += np.zeros(a.shape, dtype=b.dtype)
inds = islice(zip(*np.where(~close)), diff_limit)
diffs = [f" index {i}: {a[i]} {b[i]}" for i in inds]
N = len(diffs)
print(f"First {N} difference{'s' if N>1 else ''} for allclose:\n")
print("\n".join(diffs))
print(f"\nWith diff_limit={diff_limit}\n")

return bool(all_close)


class AnyCallable(Protocol):
def __call__(self, *args: Any, **kwargs: Any) -> Any:
...
Expand All @@ -90,7 +131,12 @@ class CuWrapped(AnyCallable, Protocol):


def implemented(
func: AnyCallable, prefix: str, name: str, reporting: bool = True
func: AnyCallable,
orig_func: AnyCallable,
prefix: str,
name: str,
reporting: bool = True,
fallback: Union[Callable[[Any], Any], None] = None,
) -> CuWrapped:
name = f"{prefix}.{name}"

Expand All @@ -112,11 +158,34 @@ def wrapper(*args: Any, **kwargs: Any) -> Any:
return func(*args, **kwargs)

else:

# TODO: unify with "reporting" branch
@wraps(func)
@track_provenance()
def wrapper(*args: Any, **kwargs: Any) -> Any:
return func(*args, **kwargs)
import cunumeric

res = func(*args, **kwargs)
# TODO: Handle functions that return results in other ways, e.g.
# np.add(out=) and np.put.
# TODO: parameterize on the classes to check equality on
# TODO: more disciplined way to filter non-deterministic functions
if (
res is not None
and isinstance(res, cunumeric.ndarray)
and not name.startswith("numpy.random")
and fallback
):
args = deep_apply(args, fallback)
kwargs = deep_apply(kwargs, fallback)
try:
orig_res = orig_func(*args, **kwargs)
except Exception as e:
print(f"SKIP {name}: {e}")
else:
# TODO: parameterize on the function used to check equality
# TODO: skipping type checks for now
assert allclose(fallback(res), orig_res, check_dtype=False)
return res

# This is incredibly ugly and unpleasant, but @wraps(func) doesn't handle
# ufuncs the way we need it to. The alternative would be to vendor and
Expand Down Expand Up @@ -261,17 +330,24 @@ def clone_module(
and isinstance(value, BuiltinFunctionType)
):
wrapped = implemented(
cast(AnyCallable, value), mod_name, attr, reporting=reporting
cast(AnyCallable, value),
getattr(origin_module, attr),
mod_name,
attr,
reporting=reporting,
fallback=fallback,
)
new_globals[attr] = wrapped
if isinstance(value, lgufunc):
for method in UFUNC_METHODS:
wrapped_method = (
implemented(
getattr(value, method),
getattr(getattr(origin_module, attr), method),
f"{mod_name}.{attr}",
method,
reporting=reporting,
fallback=fallback,
)
if hasattr(value, method)
else unimplemented(
Expand Down Expand Up @@ -347,9 +423,11 @@ def _clone_class(cls: type) -> type:
if should_wrap(value):
wrapped = implemented(
value,
getattr(origin_class, attr),
class_name,
attr,
reporting=reporting,
fallback=fallback,
)
setattr(cls, attr, wrapped)

Expand Down