Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

ENH: fallback to stock sklearn for Kmeans CSR inputs in train #2061

Closed
wants to merge 1 commit into from
Closed

ENH: fallback to stock sklearn for Kmeans CSR inputs in train #2061

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
32 changes: 23 additions & 9 deletions sklearnex/cluster/k_means.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -90,8 +90,11 @@ def _initialize_onedal_estimator(self):

self._onedal_estimator = onedal_KMeans(**onedal_params)

def _onedal_fit_supported(self, method_name, X, y=None, sample_weight=None):
def _onedal_fit_supported(
self, method_name, _is_gpu, X, y=None, sample_weight=None
):
assert method_name == "fit"
assert _is_gpu is not None

class_name = self.__class__.__name__
patching_status = PatchingConditionsChain(f"sklearn.cluster.{class_name}.fit")
Expand All @@ -105,9 +108,12 @@ def _onedal_fit_supported(self, method_name, X, y=None, sample_weight=None):
)
correct_count = self.n_clusters < sample_count

is_data_supported = (
_is_csr(X) and daal_check_version((2024, "P", 700))
) or not issparse(X)
if not _is_gpu:
is_data_supported = (
_is_csr(X) and daal_check_version((2024, "P", 700))
) or not issparse(X)
else:
is_data_supported = not (_is_csr(X) or issparse(X))

_acceptable_sample_weights = self._validate_sample_weight(sample_weight, X)

Expand All @@ -124,7 +130,7 @@ def _onedal_fit_supported(self, method_name, X, y=None, sample_weight=None):
),
(
is_data_supported,
"Supported data formats: Dense, CSR (oneDAL version >= 2024.7.0).",
"Supported data formats: Dense, CSR (oneDAL version >= 2024.7.0 on CPU).",
),
]
)
Expand Down Expand Up @@ -295,17 +301,25 @@ def _onedal_predict(self, X, sample_weight=None, queue=None):

return self._onedal_estimator.predict(X, queue=queue)

def _onedal_supported(self, method_name, *data):
def _onedal_gpu_supported(self, method_name, *data):
_is_gpu = True
if method_name == "fit":
return self._onedal_fit_supported(method_name, *data)
return self._onedal_fit_supported(method_name, _is_gpu, *data)
if method_name in ["predict", "score"]:
return self._onedal_predict_supported(method_name, *data)
raise RuntimeError(
f"Unknown method {method_name} in {self.__class__.__name__}"
)

_onedal_gpu_supported = _onedal_supported
_onedal_cpu_supported = _onedal_supported
def _onedal_cpu_supported(self, method_name, *data):
_is_gpu = False
if method_name == "fit":
return self._onedal_fit_supported(method_name, _is_gpu, *data)
if method_name in ["predict", "score"]:
return self._onedal_predict_supported(method_name, *data)
raise RuntimeError(
f"Unknown method {method_name} in {self.__class__.__name__}"
)

@wrap_output_data
def fit_transform(self, X, y=None, sample_weight=None):
Expand Down