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Merge pull request #119 from sassoftware/mlflow
New Feature: Simple Mlflow Integration
2 parents e3dcd1a + 6f03d0a commit 99294a8

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+1616
-70
lines changed

‎examples/data/MLFlowModels/Test1/MLFlowTest.pickle

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‎examples/data/MLFlowModels/Test1/MLFlowTest.zip

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‎examples/data/MLFlowModels/Test1/MLFlowTestScore.py

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import math
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import pickle
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import pandas as pd
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import numpy as np
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with open('/models/resources/viya/d02aadfe-618e-44e0-af6d-1bf00c6396e3/MLFlowTest.pickle', 'rb') as _pFile:
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_thisModelFit = pickle.load(_pFile)
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def scoreMLFlowTest(fixedacidity, volatileacidity, citricacid, residualsugar, chlorides, freesulfurdioxide, totalsulfurdioxide, density, pH, sulphates, alcohol):
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"Output: tensor"
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try:
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global _thisModelFit
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except NameError:
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with open('/models/resources/viya/d02aadfe-618e-44e0-af6d-1bf00c6396e3/MLFlowTest.pickle', 'rb') as _pFile:
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_thisModelFit = pickle.load(_pFile)
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try:
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inputArray = pd.DataFrame([[fixedacidity, volatileacidity, citricacid, residualsugar, chlorides, freesulfurdioxide, totalsulfurdioxide, density, pH, sulphates, alcohol]],
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columns=['fixedacidity', 'volatileacidity', 'citricacid', 'residualsugar', 'chlorides', 'freesulfurdioxide', 'totalsulfurdioxide', 'density', 'pH', 'sulphates', 'alcohol'],
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dtype=float)
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prediction = _thisModelFit.predict(inputArray)
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except ValueError:
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# For models requiring or including an intercept value, a 'const' column is required
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# For example, many statsmodels models include an intercept value that must be included for the model prediction
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inputArray = pd.DataFrame([[1.0, fixedacidity, volatileacidity, citricacid, residualsugar, chlorides, freesulfurdioxide, totalsulfurdioxide, density, pH, sulphates, alcohol]],
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columns=['const', 'fixedacidity', 'volatileacidity', 'citricacid', 'residualsugar', 'chlorides', 'freesulfurdioxide', 'totalsulfurdioxide', 'density', 'pH', 'sulphates', 'alcohol'],
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dtype=float)
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prediction = _thisModelFit.predict(inputArray)
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tensor = prediction
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return(tensor)

‎examples/data/MLFlowModels/Test1/ModelProperties.json

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{
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"name": "MLFlowTest",
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"description": "MLFlow Model ",
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"function": "classification",
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"scoreCodeType": "python",
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"trainTable": " ",
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"trainCodeType": "Python",
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"algorithm": "",
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"targetVariable": "",
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"targetEvent": 1,
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"targetLevel": "BINARY",
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"eventProbVar": "tensor",
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"modeler": "sasdemo",
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"tool": "Python 3",
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"toolVersion": "3.8.3"
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}

‎examples/data/MLFlowModels/Test1/dmcas_epscorecode.sas

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data sasep.out;
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dcl package pymas pm;
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dcl package logger logr('App.tk.MAS');
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dcl varchar(32767) character set utf8 pypgm;
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dcl double resultCode revision;
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dcl double tensor;
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method score(double fixedacidity, double volatileacidity, double citricacid, double residualsugar, double chlorides, double freesulfurdioxide, double totalsulfurdioxide, double density, double pH, double sulphates, double alcohol, in_out double resultCode, in_out double tensor);
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resultCode = revision = 0;
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if null(pm) then do;
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pm = _new_ pymas();
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resultCode = pm.useModule('model_exec_3106686d-a021-449a-9c2d-f2a6f47a4948', 1);
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if resultCode then do;
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resultCode = pm.appendSrcLine('');
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resultCode = pm.appendSrcLine('');
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resultCode = pm.appendSrcLine('import math');
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resultCode = pm.appendSrcLine('import pickle');
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resultCode = pm.appendSrcLine('import pandas as pd');
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resultCode = pm.appendSrcLine('import numpy as np');
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resultCode = pm.appendSrcLine('');
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resultCode = pm.appendSrcLine('with open("/models/resources/viya/d02aadfe-618e-44e0-af6d-1bf00c6396e3/MLFlowTest.pickle", "rb") as _pFile:');
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resultCode = pm.appendSrcLine(' _thisModelFit = pickle.load(_pFile)');
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resultCode = pm.appendSrcLine('');
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resultCode = pm.appendSrcLine('def scoreMLFlowTest(fixedacidity, volatileacidity, citricacid, residualsugar, chlorides, freesulfurdioxide, totalsulfurdioxide, density, pH, sulphates, alcohol):');
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resultCode = pm.appendSrcLine(' "Output: tensor"');
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resultCode = pm.appendSrcLine('');
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resultCode = pm.appendSrcLine(' try:');
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resultCode = pm.appendSrcLine(' global _thisModelFit');
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resultCode = pm.appendSrcLine(' except NameError:');
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resultCode = pm.appendSrcLine('');
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resultCode = pm.appendSrcLine(' with open("/models/resources/viya/d02aadfe-618e-44e0-af6d-1bf00c6396e3/MLFlowTest.pickle", "rb") as _pFile:');
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resultCode = pm.appendSrcLine(' _thisModelFit = pickle.load(_pFile)');
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resultCode = pm.appendSrcLine('');
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resultCode = pm.appendSrcLine(' try:');
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resultCode = pm.appendSrcLine(' inputArray = pd.DataFrame([[fixedacidity, volatileacidity, citricacid, residualsugar, chlorides, freesulfurdioxide, totalsulfurdioxide, density, pH, sulphates, alcohol]],');
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resultCode = pm.appendSrcLine(' columns=["fixedacidity", "volatileacidity", "citricacid", "residualsugar", "chlorides", "freesulfurdioxide", "totalsulfurdioxide", "density", "pH", "sulphates", "alcohol"],');
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resultCode = pm.appendSrcLine(' dtype=float)');
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resultCode = pm.appendSrcLine(' prediction = _thisModelFit.predict(inputArray)');
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resultCode = pm.appendSrcLine(' except ValueError:');
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resultCode = pm.appendSrcLine(' # For models requiring or including an intercept value, a "const" column is required');
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resultCode = pm.appendSrcLine(' # For example, many statsmodels models include an intercept value that must be included for the model prediction');
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resultCode = pm.appendSrcLine(' inputArray = pd.DataFrame([[1.0, fixedacidity, volatileacidity, citricacid, residualsugar, chlorides, freesulfurdioxide, totalsulfurdioxide, density, pH, sulphates, alcohol]],');
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resultCode = pm.appendSrcLine(' columns=["const", "fixedacidity", "volatileacidity", "citricacid", "residualsugar", "chlorides", "freesulfurdioxide", "totalsulfurdioxide", "density", "pH", "sulphates", "alcohol"],');
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resultCode = pm.appendSrcLine(' dtype=float)');
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resultCode = pm.appendSrcLine(' prediction = _thisModelFit.predict(inputArray)');
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resultCode = pm.appendSrcLine('');
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resultCode = pm.appendSrcLine(' tensor = prediction');
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resultCode = pm.appendSrcLine('');
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resultCode = pm.appendSrcLine(' return(tensor)');
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revision = pm.publish(pm.getSource(), 'model_exec_3106686d-a021-449a-9c2d-f2a6f47a4948');
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if ( revision < 1 ) then do;
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logr.log( 'e', 'py.publish() failed.');
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resultCode = -1;
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return;
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end;
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end;
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end;
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resultCode = pm.useMethod('scoreMLFlowTest');
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if resultCode then do;
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logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
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return;
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end;
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resultCode = pm.setDouble('fixedacidity', fixedacidity);
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if resultCode then
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logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
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resultCode = pm.setDouble('volatileacidity', volatileacidity);
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if resultCode then
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logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
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resultCode = pm.setDouble('citricacid', citricacid);
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if resultCode then
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logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
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resultCode = pm.setDouble('residualsugar', residualsugar);
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if resultCode then
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logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
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resultCode = pm.setDouble('chlorides', chlorides);
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if resultCode then
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logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
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resultCode = pm.setDouble('freesulfurdioxide', freesulfurdioxide);
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if resultCode then
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logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
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resultCode = pm.setDouble('totalsulfurdioxide', totalsulfurdioxide);
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if resultCode then
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logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
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resultCode = pm.setDouble('density', density);
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if resultCode then
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logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
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resultCode = pm.setDouble('pH', pH);
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if resultCode then
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logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
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resultCode = pm.setDouble('sulphates', sulphates);
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if resultCode then
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logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
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resultCode = pm.setDouble('alcohol', alcohol);
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if resultCode then
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logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
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resultCode = pm.execute();
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if (resultCode) then put 'Error: pm.execute failed. resultCode=' resultCode;
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else do;
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tensor = pm.getDouble('tensor');
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end;
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end;
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method run();
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set SASEP.IN;
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score(fixedacidity, volatileacidity, citricacid, residualsugar, chlorides, freesulfurdioxide, totalsulfurdioxide, density, pH, sulphates, alcohol, resultCode, tensor);
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end;
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enddata;
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‎examples/data/MLFlowModels/Test1/dmcas_packagescorecode.sas

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package pythonScore / overwrite=yes;
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dcl package pymas pm;
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dcl package logger logr('App.tk.MAS');
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dcl varchar(32767) character set utf8 pypgm;
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dcl int resultCode revision;
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method score(double fixedacidity, double volatileacidity, double citricacid, double residualsugar, double chlorides, double freesulfurdioxide, double totalsulfurdioxide, double density, double pH, double sulphates, double alcohol, in_out double resultCode, in_out double tensor);
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resultCode = revision = 0;
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if null(pm) then do;
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pm = _new_ pymas();
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resultCode = pm.useModule('model_exec_3106686d-a021-449a-9c2d-f2a6f47a4948', 1);
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if resultCode then do;
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resultCode = pm.appendSrcLine('');
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resultCode = pm.appendSrcLine('');
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resultCode = pm.appendSrcLine('import math');
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resultCode = pm.appendSrcLine('import pickle');
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resultCode = pm.appendSrcLine('import pandas as pd');
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resultCode = pm.appendSrcLine('import numpy as np');
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resultCode = pm.appendSrcLine('');
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resultCode = pm.appendSrcLine('with open("/models/resources/viya/d02aadfe-618e-44e0-af6d-1bf00c6396e3/MLFlowTest.pickle", "rb") as _pFile:');
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resultCode = pm.appendSrcLine(' _thisModelFit = pickle.load(_pFile)');
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resultCode = pm.appendSrcLine('');
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resultCode = pm.appendSrcLine('def scoreMLFlowTest(fixedacidity, volatileacidity, citricacid, residualsugar, chlorides, freesulfurdioxide, totalsulfurdioxide, density, pH, sulphates, alcohol):');
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resultCode = pm.appendSrcLine(' "Output: tensor"');
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resultCode = pm.appendSrcLine('');
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resultCode = pm.appendSrcLine(' try:');
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resultCode = pm.appendSrcLine(' global _thisModelFit');
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resultCode = pm.appendSrcLine(' except NameError:');
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resultCode = pm.appendSrcLine('');
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resultCode = pm.appendSrcLine(' with open("/models/resources/viya/d02aadfe-618e-44e0-af6d-1bf00c6396e3/MLFlowTest.pickle", "rb") as _pFile:');
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resultCode = pm.appendSrcLine(' _thisModelFit = pickle.load(_pFile)');
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resultCode = pm.appendSrcLine('');
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resultCode = pm.appendSrcLine(' try:');
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resultCode = pm.appendSrcLine(' inputArray = pd.DataFrame([[fixedacidity, volatileacidity, citricacid, residualsugar, chlorides, freesulfurdioxide, totalsulfurdioxide, density, pH, sulphates, alcohol]],');
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resultCode = pm.appendSrcLine(' columns=["fixedacidity", "volatileacidity", "citricacid", "residualsugar", "chlorides", "freesulfurdioxide", "totalsulfurdioxide", "density", "pH", "sulphates", "alcohol"],');
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resultCode = pm.appendSrcLine(' dtype=float)');
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resultCode = pm.appendSrcLine(' prediction = _thisModelFit.predict(inputArray)');
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resultCode = pm.appendSrcLine(' except ValueError:');
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resultCode = pm.appendSrcLine(' # For models requiring or including an intercept value, a "const" column is required');
40+
resultCode = pm.appendSrcLine(' # For example, many statsmodels models include an intercept value that must be included for the model prediction');
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resultCode = pm.appendSrcLine(' inputArray = pd.DataFrame([[1.0, fixedacidity, volatileacidity, citricacid, residualsugar, chlorides, freesulfurdioxide, totalsulfurdioxide, density, pH, sulphates, alcohol]],');
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resultCode = pm.appendSrcLine(' columns=["const", "fixedacidity", "volatileacidity", "citricacid", "residualsugar", "chlorides", "freesulfurdioxide", "totalsulfurdioxide", "density", "pH", "sulphates", "alcohol"],');
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resultCode = pm.appendSrcLine(' dtype=float)');
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resultCode = pm.appendSrcLine(' prediction = _thisModelFit.predict(inputArray)');
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resultCode = pm.appendSrcLine('');
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resultCode = pm.appendSrcLine(' tensor = prediction');
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resultCode = pm.appendSrcLine('');
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resultCode = pm.appendSrcLine(' return(tensor)');
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revision = pm.publish(pm.getSource(), 'model_exec_3106686d-a021-449a-9c2d-f2a6f47a4948');
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if ( revision < 1 ) then do;
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logr.log( 'e', 'py.publish() failed.');
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resultCode = -1;
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return;
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end;
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end;
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end;
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resultCode = pm.useMethod('scoreMLFlowTest');
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if resultCode then do;
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logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
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return;
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end;
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resultCode = pm.setDouble('fixedacidity', fixedacidity);
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if resultCode then
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logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
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resultCode = pm.setDouble('volatileacidity', volatileacidity);
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if resultCode then
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logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
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resultCode = pm.setDouble('citricacid', citricacid);
70+
if resultCode then
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logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
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resultCode = pm.setDouble('residualsugar', residualsugar);
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if resultCode then
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logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
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resultCode = pm.setDouble('chlorides', chlorides);
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if resultCode then
77+
logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
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resultCode = pm.setDouble('freesulfurdioxide', freesulfurdioxide);
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if resultCode then
80+
logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
81+
resultCode = pm.setDouble('totalsulfurdioxide', totalsulfurdioxide);
82+
if resultCode then
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logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
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resultCode = pm.setDouble('density', density);
85+
if resultCode then
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logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
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resultCode = pm.setDouble('pH', pH);
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if resultCode then
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logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
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resultCode = pm.setDouble('sulphates', sulphates);
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if resultCode then
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logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
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resultCode = pm.setDouble('alcohol', alcohol);
94+
if resultCode then
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logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
96+
resultCode = pm.execute();
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if (resultCode) then put 'Error: pm.execute failed. resultCode=' resultCode;
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else do;
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tensor = pm.getDouble('tensor');
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end;
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end;
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endpackage;
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‎examples/data/MLFlowModels/Test1/fileMetadata.json

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[
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{
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"role": "inputVariables",
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"name": "inputVar.json"
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},
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{
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"role": "outputVariables",
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"name": "outputVar.json"
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},
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{
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"role": "score",
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"name": "MLFlowTestScore.py"
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},
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{
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"role": "scoreResource",
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"name": "MLFlowTest.pickle"
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}
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]

‎examples/data/MLFlowModels/Test1/inputVar.json

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[
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{
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"name": "fixedacidity",
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"length": 8,
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"type": "decimal",
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"level": "interval"
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},
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{
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"name": "volatileacidity",
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"length": 8,
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"type": "decimal",
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"level": "interval"
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},
14+
{
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"name": "citricacid",
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"length": 8,
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"type": "decimal",
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"level": "interval"
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},
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{
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"name": "residualsugar",
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"length": 8,
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"type": "decimal",
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"level": "interval"
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},
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{
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"name": "chlorides",
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"length": 8,
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"type": "decimal",
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"level": "interval"
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},
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{
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"name": "freesulfurdioxide",
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"length": 8,
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"type": "decimal",
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"level": "interval"
37+
},
38+
{
39+
"name": "totalsulfurdioxide",
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"length": 8,
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"type": "decimal",
42+
"level": "interval"
43+
},
44+
{
45+
"name": "density",
46+
"length": 8,
47+
"type": "decimal",
48+
"level": "interval"
49+
},
50+
{
51+
"name": "pH",
52+
"length": 8,
53+
"type": "decimal",
54+
"level": "interval"
55+
},
56+
{
57+
"name": "sulphates",
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"length": 8,
59+
"type": "decimal",
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"level": "interval"
61+
},
62+
{
63+
"name": "alcohol",
64+
"length": 8,
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"type": "decimal",
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"level": "interval"
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}
68+
]

‎examples/data/MLFlowModels/Test1/outputVar.json

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[
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{
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"name": "tensor",
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"length": 8,
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"type": "decimal",
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"level": "interval"
7+
}
8+
]

‎examples/data/MLFlowModels/Test2/MLFlowTest2.pickle

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