update jenkinsfile_train-sacred, dllib-mlflow

Biblioteka_DL/dllib-mlflow.py

@@ -1,9 +1,12 @@
+from urllib.parse import urlparse
+
 import numpy as np
 import sys
 import os
 import torch
 import mlflow
 import pandas as pd
+from mlflow.models import infer_signature
 from torch import nn
 from torch.autograd import Variable
 from sklearn.model_selection import train_test_split
@@ -17,7 +20,6 @@ from sacred.observers import MongoObserver
 
 # EPOCHS = int(sys.argv[1])
 
-#mlflow.set_tracking_uri("http://localhost:5000/#/")
 mlflow.set_experiment("s444356")
 
 class Model(nn.Module):
@@ -298,6 +300,22 @@ def my_main(epochs):
 
     x_train, y_train = Variable(torch.from_numpy(features_train_g)).float(), Variable(
         torch.from_numpy(labels_train_g)).long()
+
+    input_example = features_train_g
+    siganture = infer_signature(features_train_g, labels_train_g)
+    # mlflow.set_tracking_uri("http://172.17.0.1:5000")
+    # mlflow.set_tracking_uri("http://172.17.0.1:5000/#/")
+    tracking_url_type_store = urlparse(mlflow.get_tracking_uri()).scheme
+    # print(tracking_url_type_store)
+
+    if tracking_url_type_store != "file":
+        mlflow.pytorch.log_model(model, "model", registered_model_name="s444356", signature=siganture,
+                                 input_example=input_example)
+    else:
+        mlflow.pytorch.log_model(model, "model", signature=siganture, input_example=input_example)
+        mlflow.pytorch.save_model(model, "my_model", signature=siganture, input_example=input_example)
+
+
     for epoch in range(1, epochs + 1):
         print("Epoch #", epoch)
         y_pred = model(x_train)
@@ -331,4 +349,4 @@ def my_main(epochs):
 
 
 with mlflow.start_run() as run:
-    my_main(epochs)
+    my_main(epochs)

Jenkinsfile_train-sacred

@@ -23,6 +23,8 @@ pipeline {
 			sh 'ls mlruns'
 			archiveArtifacts artifacts: 'mlruns/**'
 			sh 'rm -r mlruns'
+			archiveArtifacts artifacts: 'my_model/**'
+			sh 'rm -r my_model'
 		}
 	}
     }