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Use _compile_or_get in JIT groupby apply #13350

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merged 2 commits into from
May 17, 2023
Merged

Use _compile_or_get in JIT groupby apply #13350

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de9d280
use _compile_or_get in groupby
brandon-b-miller May 15, 2023
2341d40
Merge branch 'branch-23.06' into groupby-apply-compile-or-get
brandon-b-miller May 16, 2023
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21 changes: 9 additions & 12 deletions python/cudf/cudf/core/udf/groupby_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,13 +19,12 @@
)
from cudf.core.udf.utils import (
Row,
_generate_cache_key,
_compile_or_get,
_get_extensionty_size,
_get_kernel,
_get_udf_return_type,
_supported_cols_from_frame,
_supported_dtypes_from_frame,
precompiled,
)
from cudf.utils.utils import _cudf_nvtx_annotate

Expand Down Expand Up @@ -145,20 +144,18 @@ def jit_groupby_apply(offsets, grouped_values, function, *args):
function : callable
The user-defined function to execute
"""
offsets = cp.asarray(offsets)
ngroups = len(offsets) - 1

cache_key = _generate_cache_key(
grouped_values, function, args, suffix="__GROUPBY_APPLY_UDF"
kernel, return_type = _compile_or_get(
grouped_values,
function,
args,
kernel_getter=_get_groupby_apply_kernel,
suffix="__GROUPBY_APPLY_UDF",
)

if cache_key not in precompiled:
precompiled[cache_key] = _get_groupby_apply_kernel(
grouped_values, function, args
)
kernel, return_type = precompiled[cache_key]
offsets = cp.asarray(offsets)
ngroups = len(offsets) - 1

return_type = numpy_support.as_dtype(return_type)
output = cudf.core.column.column_empty(ngroups, dtype=return_type)

launch_args = [
Expand Down
6 changes: 4 additions & 2 deletions python/cudf/cudf/core/udf/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -283,7 +283,9 @@ def _generate_cache_key(frame, func: Callable, args, suffix="__APPLY_UDF"):


@_cudf_nvtx_annotate
def _compile_or_get(frame, func, args, kernel_getter=None):
def _compile_or_get(
frame, func, args, kernel_getter=None, suffix="__APPLY_UDF"
):
"""
Return a compiled kernel in terms of MaskedTypes that launches a
kernel equivalent of `f` for the dtypes of `df`. The kernel uses
Expand All @@ -308,7 +310,7 @@ def _compile_or_get(frame, func, args, kernel_getter=None):
raise TypeError("only scalar valued args are supported by apply")

# check to see if we already compiled this function
cache_key = _generate_cache_key(frame, func, args)
cache_key = _generate_cache_key(frame, func, args, suffix=suffix)
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if precompiled.get(cache_key) is not None:
kernel, masked_or_scalar = precompiled[cache_key]
return kernel, masked_or_scalar
Expand Down