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Second test example for MLFlow
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‎examples/data/MLFlowModels/Test2/MLFlowTest2.pickle

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‎examples/data/MLFlowModels/Test2/MLFlowTest2.zip

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‎examples/data/MLFlowModels/Test2/MLFlowTest2Score.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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import settings
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with open(settings.pickle_path + 'MLFlowTest2.pickle', 'rb') as _pFile:
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_thisModelFit = pickle.load(_pFile)
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def scoreMLFlowTest2(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(settings.pickle_path + 'MLFlowTest2.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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if isinstance(tensor, np.ndarray):
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tensor = prediction.item(0)
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return(tensor)

‎examples/data/MLFlowModels/Test2/ModelProperties.json

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{
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"name": "MLFlowTest2",
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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/Test2/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_8388003e-3c58-4215-93f2-4e795d124c61', 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/4beb897f-f903-4b4b-b0ea-ceaf83537ec6/MLFlowTest2.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 scoreMLFlowTest2(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/4beb897f-f903-4b4b-b0ea-ceaf83537ec6/MLFlowTest2.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(' if isinstance(tensor, np.ndarray):');
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resultCode = pm.appendSrcLine(' tensor = prediction.item(0)');
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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_8388003e-3c58-4215-93f2-4e795d124c61');
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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('scoreMLFlowTest2');
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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/Test2/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();
11+
resultCode = pm.useModule('model_exec_8388003e-3c58-4215-93f2-4e795d124c61', 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/4beb897f-f903-4b4b-b0ea-ceaf83537ec6/MLFlowTest2.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 scoreMLFlowTest2(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/4beb897f-f903-4b4b-b0ea-ceaf83537ec6/MLFlowTest2.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');
41+
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(' if isinstance(tensor, np.ndarray):');
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resultCode = pm.appendSrcLine(' tensor = prediction.item(0)');
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resultCode = pm.appendSrcLine('');
50+
resultCode = pm.appendSrcLine(' return(tensor)');
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revision = pm.publish(pm.getSource(), 'model_exec_8388003e-3c58-4215-93f2-4e795d124c61');
52+
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if ( revision < 1 ) then do;
54+
logr.log( 'e', 'py.publish() failed.');
55+
resultCode = -1;
56+
return;
57+
end;
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end;
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end;
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resultCode = pm.useMethod('scoreMLFlowTest2');
61+
if resultCode then do;
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logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
63+
return;
64+
end;
65+
resultCode = pm.setDouble('fixedacidity', fixedacidity);
66+
if resultCode then
67+
logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
68+
resultCode = pm.setDouble('volatileacidity', volatileacidity);
69+
if resultCode then
70+
logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
71+
resultCode = pm.setDouble('citricacid', citricacid);
72+
if resultCode then
73+
logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
74+
resultCode = pm.setDouble('residualsugar', residualsugar);
75+
if resultCode then
76+
logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
77+
resultCode = pm.setDouble('chlorides', chlorides);
78+
if resultCode then
79+
logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
80+
resultCode = pm.setDouble('freesulfurdioxide', freesulfurdioxide);
81+
if resultCode then
82+
logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
83+
resultCode = pm.setDouble('totalsulfurdioxide', totalsulfurdioxide);
84+
if resultCode then
85+
logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
86+
resultCode = pm.setDouble('density', density);
87+
if resultCode then
88+
logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
89+
resultCode = pm.setDouble('pH', pH);
90+
if resultCode then
91+
logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
92+
resultCode = pm.setDouble('sulphates', sulphates);
93+
if resultCode then
94+
logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
95+
resultCode = pm.setDouble('alcohol', alcohol);
96+
if resultCode then
97+
logr.log('E', 'useMethod() failed. resultCode=$s', resultCode);
98+
resultCode = pm.execute();
99+
if (resultCode) then put 'Error: pm.execute failed. resultCode=' resultCode;
100+
else do;
101+
tensor = pm.getDouble('tensor');
102+
end;
103+
end;
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endpackage;
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‎examples/data/MLFlowModels/Test2/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",
8+
"name": "outputVar.json"
9+
},
10+
{
11+
"role": "score",
12+
"name": "MLFlowTest2Score.py"
13+
},
14+
{
15+
"role": "scoreResource",
16+
"name": "MLFlowTest2.pickle"
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}
18+
]

‎examples/data/MLFlowModels/Test2/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"
7+
},
8+
{
9+
"name": "volatileacidity",
10+
"length": 8,
11+
"type": "decimal",
12+
"level": "interval"
13+
},
14+
{
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"name": "citricacid",
16+
"length": 8,
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"type": "decimal",
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"level": "interval"
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},
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{
21+
"name": "residualsugar",
22+
"length": 8,
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"type": "decimal",
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"level": "interval"
25+
},
26+
{
27+
"name": "chlorides",
28+
"length": 8,
29+
"type": "decimal",
30+
"level": "interval"
31+
},
32+
{
33+
"name": "freesulfurdioxide",
34+
"length": 8,
35+
"type": "decimal",
36+
"level": "interval"
37+
},
38+
{
39+
"name": "totalsulfurdioxide",
40+
"length": 8,
41+
"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",
58+
"length": 8,
59+
"type": "decimal",
60+
"level": "interval"
61+
},
62+
{
63+
"name": "alcohol",
64+
"length": 8,
65+
"type": "decimal",
66+
"level": "interval"
67+
}
68+
]

‎examples/data/MLFlowModels/Test2/model.pkl

627 Bytes
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‎examples/data/MLFlowModels/Test2/outputVar.json

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[
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{
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"name": "tensor",
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"length": 8,
5+
"type": "decimal",
6+
"level": "interval"
7+
}
8+
]

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