[experiment] ENH: using only raw inputs for onedal backend #2153
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samir-nasibli
commented
Nov 5, 2024
samir-nasibli
changed the title
not tested properly yet
samir-nasibli
commented
Nov 5, 2024
sklearnex/cluster/dbscan.py
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Make sense for dbscan and rf use just onedal4py API only for raw inputs.
ethanglaser
reviewed
Nov 6, 2024
onedal/cluster/kmeans.py
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| ) | ||
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| use_raw_input = _get_config().get("use_raw_input") is True | ||
| if use_raw_input and _get_sycl_namespace(X)[0] is not None: |
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Suggested change
| if use_raw_input and _get_sycl_namespace(X)[0] is not None: | |
| if use_raw_input and sua_iface is not None: |
- move line 284 above this
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/intelci: run |
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/intelci: run |
ethanglaser
reviewed
Jan 17, 2025
| X, y, dtype=[np.float64, np.float32], accept_2d_y=True, force_all_finite=False | ||
| ) | ||
| y = np.asarray(y, dtype=X.dtype) | ||
| queue = self._queue = getattr(policy, "_queue", None) |
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a little confused on this line - line 90 has policy set based on queue, then line 91 sets queue based on policy?
ethanglaser
reviewed
Jan 17, 2025
| @@ -194,6 +195,9 @@ def _onedal_finalize_fit(self, queue=None): | |||
| def _onedal_partial_fit(self, X, sample_weight=None, queue=None, check_input=True): | |||
| first_pass = not hasattr(self, "n_samples_seen_") or self.n_samples_seen_ == 0 | |||
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| use_raw_input = get_config()["use_raw_input"] | |||
| # never check input when using raw input | |||
| check_input &= use_raw_input is False | |||
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Ethan TODO: add this logic to other sklearnex incremental estimators
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- also to _onedal_fit here
ethanglaser
reviewed
Jan 18, 2025
| @@ -17,6 +17,7 @@ | |||
| import logging | |||
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| from daal4py.sklearn._utils import daal_check_version | |||
| from sklearnex._config import get_config | |||
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minor comment - let's unify these eventually
Suggested change
| from sklearnex._config import get_config | |
| from .._config import get_config |
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/intelci: run |
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/intelci: run |
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/intelci: run |
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/intelci: run |
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Description
Add a comprehensive description of proposed changes
List associated issue number(s) if exist(s): #6 (for example)
Documentation PR (if needed): #1340 (for example)
Benchmarks PR (if needed): IntelPython/scikit-learn_bench#155 (for example)
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