Translating text encodings of machine learning models to executable code
Translating text encodings of machine learning models to executable code, the method comprising: receiving a text encoding of a machine learning model; generating, based on the text encoding of the machine learning model, compilable code encoding the machine learning model; and generating, based on the compilable code, executable code encoding the machine learning model.
1. A method of translating text encodings of machine learning models to executable code, the method comprising:
receiving a text encoding of a machine learning model;
generating, based on the text encoding of the machine learning model, compilable code encoding the machine learning model; and
generating, based on the compilable code, executable code encoding the machine learning model.
2. The method of claim 1 , wherein the text encoding of the machine learning model comprises a plurality of conditional statements, and wherein generating the compilable code comprises:
parsing the plurality of conditional statements; and
generating the compilable code based on the parsed plurality of conditional statements.
3. The method of claim 2 , wherein each of the plurality of conditional statements comprise one or more conditional actions, wherein the one or more conditional actions comprise a nested conditional statement or a modification to a confidence score.
4. The method of claim 2 , wherein generating the compilable code based on the parsed plurality of conditional statements comprises generating, in the compilable code, another conditional statement combining two or more of the plurality of conditional statements.
5. The method of claim 2 , wherein generating the compilable code based on the plurality of parsed conditional statements comprises generating, in the compilable code, a function corresponding to a branch of one or more nested conditional statements.
6. The method of claim 1 , wherein generating the compilable code comprises truncating one or more numerical values included in the text encoding of the machine learning model.
7. The method of claim 1 , wherein generating the executable code comprises compiling the compilable code to a target platform.
8. The method of claim 1 , wherein the machine learning model comprises a classifier.
9. An apparatus for translating text encodings of machine learning models to executable code, the apparatus comprising a computer processor and a computer memory, the computer memory including computer program instructions that, when executed by the computer processor, cause the computer processor to carry out;
receiving a text encoding of a machine learning model;
generating, based on the text encoding of the machine learning model, compilable code encoding the machine learning model; and
generating, based on the compilable code, executable code encoding the machine learning model.
10. The apparatus of claim 9 , wherein the text encoding of the machine learning model comprises a plurality of conditional statements, and wherein generating the compilable code comprises:
parsing the plurality of conditional statements; and
generating the compilable code based on the parsed plurality of conditional statements.
11. The apparatus of claim 10 , wherein each of the plurality of conditional statements comprise one or more conditional actions, wherein the one or more conditional actions comprise a nested conditional statement or a modification to a confidence score.
12. The apparatus of claim 10 , wherein generating the compilable code based on the parsed plurality of conditional statements comprises generating, in the compilable code, another conditional statement combining two or more of the plurality of conditional statements.
13. The apparatus of claim 10 , wherein generating the compilable code based on the plurality of parsed conditional statements comprises generating, in the compilable code, a function corresponding to a branch of one or more nested conditional statements.
14. The apparatus of claim 9 , wherein generating the compilable code comprises truncating one or more numerical values included in the text encoding of the machine learning model.
15. The apparatus of claim 9 , wherein generating the executable code comprises compiling the compilable code to a target platform.
16. The apparatus of claim 9 , wherein the machine learning model comprises a classifier.
17. A computer program product disposed upon a non-transitory computer readable medium, the computer program product comprising computer program instructions for translating text encodings of machine learning models to executable code that, when executed, cause a computer system to perform steps comprising:
receiving a text encoding of a machine learning model;
generating, based on the text encoding of the machine learning model, compilable code encoding the machine learning model; and
generating, based on the compilable code, executable code encoding the machine learning model.
18. The computer program product of claim 17 , wherein the text encoding of the machine learning model comprises a plurality of conditional statements, and wherein generating the compilable code comprises:
parsing the plurality of conditional statements; and
generating the compilable code based on the parsed plurality of conditional statements.
19. The computer program product of claim 18 , wherein each of the plurality of conditional statements comprise one or more conditional actions, wherein the one or more conditional actions comprise a nested conditional statement or a modification to a confidence score.
20. The computer program product of claim 18 , wherein generating the compilable code based on the parsed plurality of conditional statements comprises generating, in the compilable code, another conditional statement combining two or more of the plurality of conditional statements.