add multipieline project

lab06/jenkinsfile-train

@@ -28,13 +28,12 @@ pipeline {
         }
       stage('Docker'){
          steps{
-            sh 'python3 "./pytorch-example.py" ${BATCH_SIZE} ${EPOCHS} > pred.txt'
+            sh 'python3 "./pytorch-example.py" ${BATCH_SIZE} ${EPOCHS} > model.txt'
          }
       }
       stage('archiveArtifacts') {
 			steps{
-                archiveArtifacts 'ium_s440058/**'
-				archiveArtifacts 'pred.txt'
+				archiveArtifacts 'model.txt'
                 archiveArtifacts 'diabetes.pkl'
 			}
 		}

pytorch-example.py

@@ -6,6 +6,7 @@ import numpy as np
 import torch.nn.functional as F
 from torch.utils.data import DataLoader, TensorDataset, random_split
 from sklearn import preprocessing
+import sys
 
 class LogisticRegressionModel(torch.nn.Module):
     def __init__(self, input_dim, output_dim):
@@ -35,9 +36,9 @@ tTrain = torch.from_numpy(y_train.values.reshape(460,1))
 fTest= torch.from_numpy(x_test.values)
 tTest = torch.from_numpy(y_test.values)
 
-batch_size = 95
+batch_size = int(sys.argv[1]) if len(sys.argv) > 1 else 20
 n_iters = 900
-num_epochs = int(n_iters / (len(x_train) / batch_size))
+num_epochs = int(sys.argv[2]) if len(sys.argv) > 2 else 10
 learning_rate = 0.005
 input_dim = 4
 output_dim = 1