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Support numeric, boolean, and string keyword arguments to class methods during CPU dispatching #5236

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merged 7 commits into from
Apr 3, 2023
Merged

Support numeric, boolean, and string keyword arguments to class methods during CPU dispatching #5236

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1245494
Updates the CPU dispatching logic to support keyword arguments that a…
beckernick Feb 15, 2023
42ce632
cleanup
beckernick Feb 15, 2023
6640939
fix typo
beckernick Feb 15, 2023
1cb3f58
remove original LOC
beckernick Feb 15, 2023
30fdc11
flake8
beckernick Feb 15, 2023
2ffdbf4
23.04 merge conflicts
beckernick Mar 16, 2023
f1fd094
Merge branch 'branch-23.04' into bugfix/cpu-gpu-args-checks
dantegd Apr 3, 2023
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13 changes: 11 additions & 2 deletions python/cuml/internals/base.pyx
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Original file line number Diff line number Diff line change
Expand Up @@ -18,6 +18,7 @@

import os
import inspect
import numbers
from importlib import import_module
from cuml.internals.safe_imports import cpu_only_import
np = cpu_only_import('numpy')
Expand All @@ -36,7 +37,8 @@ from cuml.internals.device_type import DeviceType
from cuml.internals.input_utils import (
determine_array_type,
input_to_cuml_array,
input_to_host_array
input_to_host_array,
is_array_like
)
from cuml.internals.memory_utils import determine_array_memtype
from cuml.internals.mem_type import MemoryType
Expand Down Expand Up @@ -626,7 +628,14 @@ class UniversalBase(Base):
# put all the kwargs on host
new_kwargs = dict()
for kw, arg in kwargs.items():
new_kwargs[kw] = input_to_host_array(arg)[0]
# if array-like, ensure array-like is on the host
if is_array_like(arg):
new_kwargs[kw] = input_to_host_array(arg)[0]
# if Real or string, pass as is
elif isinstance(arg, (numbers.Real, str)):
new_kwargs[kw] = arg
else:
raise ValueError(f"Unable to process argument {kw}")
return new_args, new_kwargs

def dispatch_func(self, func_name, gpu_func, *args, **kwargs):
Expand Down
15 changes: 11 additions & 4 deletions python/cuml/tests/test_device_selection.py
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Original file line number Diff line number Diff line change
Expand Up @@ -511,6 +511,7 @@ def tsvd_test_data(request):
"input_type": ["numpy", "dataframe", "cupy", "cudf", "numba"],
"metric": ["euclidean", "cosine"],
"n_neighbors": [3, 8],
"return_distance": [True],
}
)
)
Expand All @@ -519,6 +520,7 @@ def nn_test_data(request):
"metric": request.param["metric"],
"n_neighbors": request.param["n_neighbors"],
}
infer_func_kwargs = {"return_distance": request.param["return_distance"]}

sk_model = skNearestNeighbors(**kwargs)
sk_model.fit(X_train_blob)
Expand All @@ -529,6 +531,7 @@ def nn_test_data(request):
"cuEstimator": NearestNeighbors,
"kwargs": kwargs,
"infer_func": "kneighbors",
"infer_func_kwargs": infer_func_kwargs,
"assert_func": check_nn,
"X_train": to_output_type(X_train_blob, input_type),
"X_test": to_output_type(X_test_blob, input_type),
Expand Down Expand Up @@ -563,7 +566,8 @@ def test_train_cpu_infer_cpu(test_data):
else:
model.fit(test_data["X_train"])
infer_func = getattr(model, test_data["infer_func"])
cuml_output = infer_func(test_data["X_test"])
infer_func_kwargs = test_data.get("infer_func_kwargs", {})
cuml_output = infer_func(test_data["X_test"], **infer_func_kwargs)

assert_func = test_data["assert_func"]
assert_func(cuml_output, test_data)
Expand All @@ -582,7 +586,8 @@ def test_train_gpu_infer_cpu(test_data):
model.fit(test_data["X_train"])
with using_device_type("cpu"):
infer_func = getattr(model, test_data["infer_func"])
cuml_output = infer_func(test_data["X_test"])
infer_func_kwargs = test_data.get("infer_func_kwargs", {})
cuml_output = infer_func(test_data["X_test"], **infer_func_kwargs)

assert_func = test_data["assert_func"]
assert_func(cuml_output, test_data)
Expand All @@ -598,7 +603,8 @@ def test_train_cpu_infer_gpu(test_data):
model.fit(test_data["X_train"])
with using_device_type("gpu"):
infer_func = getattr(model, test_data["infer_func"])
cuml_output = infer_func(test_data["X_test"])
infer_func_kwargs = test_data.get("infer_func_kwargs", {})
cuml_output = infer_func(test_data["X_test"], **infer_func_kwargs)

assert_func = test_data["assert_func"]
assert_func(cuml_output, test_data)
Expand All @@ -613,7 +619,8 @@ def test_train_gpu_infer_gpu(test_data):
else:
model.fit(test_data["X_train"])
infer_func = getattr(model, test_data["infer_func"])
cuml_output = infer_func(test_data["X_test"])
infer_func_kwargs = test_data.get("infer_func_kwargs", {})
cuml_output = infer_func(test_data["X_test"], **infer_func_kwargs)

assert_func = test_data["assert_func"]
assert_func(cuml_output, test_data)
Expand Down