[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
| ) | ||
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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
ethanglaser
reviewed
Nov 13, 2024
| @@ -155,6 +168,14 @@ def finalize_fit(self, queue=None): | |||
| ) | |||
| options = self._get_result_options(self.options).split("|") | |||
| for opt in options: | |||
| setattr(self, opt, from_table(getattr(result, opt)).ravel()) | |||
| opt_value = self._input_xp.ravel( | |||
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When running sklearnex example incremental_basic_statistics_dpctl.py leads to AttributeError: 'NoneType' object has no attribute 'ravel'
ethanglaser
reviewed
Nov 13, 2024
| @@ -136,7 +148,12 @@ def finalize_fit(self, queue=None): | |||
| self._partial_result, | |||
| ) | |||
| if daal_check_version((2024, "P", 1)) or (not self.bias): | |||
| self.covariance_ = from_table(result.cov_matrix) | |||
| self.covariance_ = from_table( | |||
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When running sklearnex example incremental_covariance_spmd.py leads to AttributeError: 'IncrementalEmpiricalCovariance' object has no attribute '_input_sua_iface'
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/intelci: run |
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There are significant issues with private CI for certain algos here that need to be addressed. |
samir-nasibli
commented
Nov 22, 2024
Comment on lines
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| with config_context(use_raw_input=use_raw_input): | ||
| for i in range(num_blocks): | ||
| X_split_df = _convert_to_dataframe( | ||
| X_split[i], sycl_queue=queue, target_df=dataframe | ||
| ) | ||
| incpca.partial_fit(X_split_df) |
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👍 I think make sense other tests also update like this
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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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