Esempio n. 1
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    def _func_fit(sessionId, objs, datatype, **kwargs):
        from cuml.cluster.kmeans_mg import KMeansMG as cumlKMeans
        handle = worker_state(sessionId)["handle"]

        inp_data = concatenate(objs)

        return cumlKMeans(handle=handle, output_type=datatype,
                          **kwargs).fit(inp_data)
Esempio n. 2
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    def _func_create_model(sessionId, **kwargs):
        try:
            from cuml.neighbors.kneighbors_classifier_mg import \
                KNeighborsClassifierMG as cumlKNN
        except ImportError:
            raise_mg_import_exception()

        handle = worker_state(sessionId)["handle"]
        return cumlKNN(handle=handle, **kwargs)
Esempio n. 3
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    def _func_create_model(sessionId, **kwargs):
        try:
            from cuml.neighbors.nearest_neighbors_mg import \
                NearestNeighborsMG as cumlNN
        except ImportError:
            raise_mg_import_exception()

        handle = worker_state(sessionId)["handle"]
        return cumlNN(handle=handle, **kwargs)
Esempio n. 4
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 def _create_model(sessionId, datatype, **kwargs):
     from cuml.linear_model.linear_regression_mg import LinearRegressionMG
     handle = worker_state(sessionId)["handle"]
     return LinearRegressionMG(handle=handle,
                               output_type=datatype,
                               **kwargs)
Esempio n. 5
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 def _create_model(sessionId, model_func, datatype, **kwargs):
     handle = worker_state(sessionId)["handle"]
     return model_func(handle, datatype, **kwargs)
Esempio n. 6
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 def _create_model(sessionId, datatype, **kwargs):
     from cuml.linear_model.ridge_mg import RidgeMG
     handle = worker_state(sessionId)["handle"]
     return RidgeMG(handle=handle, output_type=datatype, **kwargs)
Esempio n. 7
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 def _create_model(sessionId, datatype, **kwargs):
     from cuml.solvers.cd_mg import CDMG
     handle = worker_state(sessionId)["handle"]
     return CDMG(handle=handle, output_type=datatype, **kwargs)