[SPARK-12016][MLlib][PySpark] Wrap Word2VecModel when loading it in pyspark #10100
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Test build #47056 has finished for PR 10100 at commit
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Test build #47061 has finished for PR 10100 at commit
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Contributor
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This is only a suggestion, but looking at the other Java loadable models which are also wrapped in python it seems the standard approach is to instead add a load[X] method to the PythonMLLibAPI instead of doing the wrapper in Python. Might be worth doing that way just for consistencies sake - what are your thoughts? |
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It makes sense. Thanks. I will update this later. |
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Test build #47122 has finished for PR 10100 at commit
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Member
Author
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ping @davies Can you take a look of this? It should be straightforward one. |
Contributor
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LGTM, merging this into master, thanks! |
asfgit
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… pyspark JIRA: https://issues.apache.org/jira/browse/SPARK-12016 We should not directly use Word2VecModel in pyspark. We need to wrap it in a Word2VecModelWrapper when loading it in pyspark. Author: Liang-Chi Hsieh <[email protected]> Closes #10100 from viirya/fix-load-py-wordvecmodel. (cherry picked from commit b51a4cd) Signed-off-by: Joseph K. Bradley <[email protected]>
asfgit
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that referenced
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Jan 7, 2016
… pyspark JIRA: https://issues.apache.org/jira/browse/SPARK-12016 We should not directly use Word2VecModel in pyspark. We need to wrap it in a Word2VecModelWrapper when loading it in pyspark. Author: Liang-Chi Hsieh <[email protected]> Closes #10100 from viirya/fix-load-py-wordvecmodel. (cherry picked from commit b51a4cd) Signed-off-by: Joseph K. Bradley <[email protected]>
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I just backported this to 1.6 and 1.5 |
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JIRA: https://issues.apache.org/jira/browse/SPARK-12016
We should not directly use Word2VecModel in pyspark. We need to wrap it in a Word2VecModelWrapper when loading it in pyspark.