Implement apply() in FIL #5358
Implement apply() in FIL #5358
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hcho3
added
non-breaking
| fm = ForestInference.load( | ||
| model_path, output_class=True, model_type="xgboost" | ||
| ) |
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Does it matter in which using_device_type context this is instantiated? If not, should we maybe test expected behavior if this is done wrongly?
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It should not matter, and yes, we should definitely test that.
| model_path, output_class=True, model_type="xgboost" | ||
| ) | ||
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| with using_device_type(infer_device): |
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Is there a way to ensure/test that the inference is actually performed on the correct device?
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| with using_device_type(infer_device): | ||
| pred_leaf = fm.apply(X).astype(np.int32) | ||
| expected_pred_leaf = bst.predict(xgb.DMatrix(X), pred_leaf=True) |
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Unless this is affected by using_device_type(), I'd suggest to move it outside of the context. That goes for all other code where the same principle applies.
| classification=True, | ||
| ) | ||
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| model_path = os.path.join(tmp_path, "xgb_class.model") |
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The tmp_path fixture should be a pathlib.Path object, so this should be equivalent:
| model_path = os.path.join(tmp_path, "xgb_class.model") | |
| model_path = tmp_path / "xgb_class.model" |
| preds | ||
| If non-None, outputs will be written in-place to this array. | ||
| Therefore, if given, this should be a C-major array of shape | ||
| n_rows * n_trees. |
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You use a X symbol in row 1254, maybe use the same here to be consistent?
| n_rows * n_trees. | |
| n_rows X n_trees. |
cpp/include/cuml/experimental/fil/detail/decision_forest_builder.hpp
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cpp/include/cuml/experimental/fil/detail/decision_forest_builder.hpp
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cpp/include/cuml/experimental/fil/detail/decision_forest_builder.hpp
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cpp/include/cuml/experimental/fil/detail/decision_forest_builder.hpp
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cpp/include/cuml/experimental/fil/detail/decision_forest_builder.hpp
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cpp/include/cuml/experimental/fil/detail/decision_forest_builder.hpp
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| categorical_data, | ||
| infer_type); | ||
| if (infer_type == infer_kind::leaf_id) { | ||
| infer_kernel_cpu<has_categorical_nodes, true>( |
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I'm only adding predict_leaf template parameter to the CPU kernel. Adding it to the GPU kernel adds too much boilerplate.
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/merge |
Replaces #5307
Depends on #5365