mlflow

mlflow/MLproject

@@ -1,7 +1,7 @@
 name: MLflow_s464937
 conda_env: conda.yaml
 entry_points:
-  optimal_parameters:
+  main:
     parameters:
       epochs: { type: int, default: 20 }
     command: 'python mlflow_model.py {epochs}'

mlflow/mlflow_model.py

@@ -7,6 +7,8 @@ from sklearn.pipeline import Pipeline
 from tensorflow.keras.models import Sequential
 from tensorflow.keras.layers import Dense
 import tensorflow as tf
+from sklearn.metrics import accuracy_score, precision_recall_fscore_support, mean_squared_error
+from math import sqrt
 import mlflow
 
 
@@ -14,41 +16,63 @@ mlflow.set_tracking_uri("http://localhost:5000")
 
 
 def main():
-    data = pd.read_csv('./data/train.csv')
+    data = pd.read_csv('../openpowerlifting.csv')
-
     data = data[['Sex', 'Age', 'BodyweightKg', 'TotalKg']].dropna()
     data['Age'] = pd.to_numeric(data['Age'], errors='coerce')
     data['BodyweightKg'] = pd.to_numeric(data['BodyweightKg'], errors='coerce')
     data['TotalKg'] = pd.to_numeric(data['TotalKg'], errors='coerce')
     features = data[['Sex', 'Age', 'BodyweightKg']]
     target = data['TotalKg']
-
     X_train, X_test, y_train, y_test = train_test_split(features, target, test_size=0.2, random_state=42)
 
-    preprocessor = ColumnTransformer(
+    with mlflow.start_run() as run:
-        transformers=[
+        preprocessor = ColumnTransformer(
-            ('num', StandardScaler(), ['Age', 'BodyweightKg']),
+            transformers=[
-            ('cat', OneHotEncoder(), ['Sex'])
+                ('num', StandardScaler(), ['Age', 'BodyweightKg']),
-        ],
+                ('cat', OneHotEncoder(), ['Sex'])
-    )
+            ],
+        )
 
-    pipeline = Pipeline(steps=[
+        model = Sequential([
-        ('preprocessor', preprocessor),
-        ('model', Sequential([
             Dense(64, activation='relu', input_dim=5),
             Dense(64, activation='relu'),
             Dense(1)
-        ]))
+        ])
-    ])
 
-    pipeline['model'].compile(optimizer='adam', loss='mse', metrics=['mae'])
+        model.compile(optimizer='adam', loss='mse', metrics=['mae'])
+        pipeline = Pipeline(steps=[
+            ('preprocessor', preprocessor),
+            ('model', model)
+        ])
 
-    X_train_excluded = X_train.iloc[1:]
+        X_train_excluded = X_train.iloc[1:]
-    y_train_excluded = y_train.iloc[1:]
+        y_train_excluded = y_train.iloc[1:]
+        pipeline.fit(X_train_excluded, y_train_excluded, model__epochs=int(sys.argv[1]), model__validation_split=0.1)
+        pipeline['model'].save('powerlifting_model.h5')
+        loaded_model = tf.keras.models.load_model('powerlifting_model.h5')
 
-    pipeline.fit(X_train_excluded, y_train_excluded, model__epochs=int(sys.argv[1]), model__validation_split=0.1)
+        test_data = pd.read_csv('openpowerlifting.csv')
+        test_data = test_data[['Sex', 'Age', 'BodyweightKg', 'TotalKg']].dropna()
+        test_data['Age'] = pd.to_numeric(test_data['Age'], errors='coerce')
+        test_data['BodyweightKg'] = pd.to_numeric(test_data['BodyweightKg'], errors='coerce')
+        test_data['TotalKg'] = pd.to_numeric(test_data['TotalKg'], errors='coerce')
+        test_features = test_data[['Sex', 'Age', 'BodyweightKg']]
+        test_target = test_data['TotalKg']
 
-    pipeline['model'].save('powerlifting_model.h5')
+        X_test_transformed = preprocessor.transform(test_features)
+        predictions = loaded_model.predict(X_test_transformed)
+        predictions_df = pd.DataFrame(predictions, columns=['predicted_TotalKg'])
+        predictions_df['actual_TotalKg'] = test_target.reset_index(drop=True)
+        predictions_df.to_csv('powerlifting_test_predictions.csv', index=False)
+
+        data = pd.read_csv('powerlifting_test_predictions.csv')
+        y_pred = data['predicted_TotalKg']
+        y_test = data['actual_TotalKg']
+        rmse = sqrt(mean_squared_error(y_test, y_pred))
+
+
+        mlflow.log_param("epochs", int(sys.argv[1]))
+        mlflow.log_metric("rmse", rmse)
 
 
 if __name__ == '__main__':

mlflow/mlruns/0/meta.yaml

@@ -0,0 +1,6 @@
+artifact_location: mlflow-artifacts:/0
+creation_time: 1716052613528
+experiment_id: '0'
+last_update_time: 1716052613528
+lifecycle_stage: active
+name: Default

mlruns/0/852a00be19a04756b19b2a0fdb0c6a83/meta.yaml

@@ -0,0 +1,15 @@
+artifact_uri: mlflow-artifacts:/0/852a00be19a04756b19b2a0fdb0c6a83/artifacts
+end_time: null
+entry_point_name: ''
+experiment_id: '0'
+lifecycle_stage: active
+run_id: 852a00be19a04756b19b2a0fdb0c6a83
+run_name: skillful-worm-708
+run_uuid: 852a00be19a04756b19b2a0fdb0c6a83
+source_name: ''
+source_type: 4
+source_version: ''
+start_time: 1716053034879
+status: 1
+tags: []
+user_id: szymonbartanowicz

mlruns/0/852a00be19a04756b19b2a0fdb0c6a83/params/epoches

@@ -0,0 +1 @@
+12

mlruns/0/852a00be19a04756b19b2a0fdb0c6a83/params/epochs

@@ -0,0 +1 @@
+20

mlruns/0/852a00be19a04756b19b2a0fdb0c6a83/tags/mlflow.gitRepoURL

@@ -0,0 +1 @@
+https://git.wmi.amu.edu.pl/s464937/ium_464937.git

mlruns/0/852a00be19a04756b19b2a0fdb0c6a83/tags/mlflow.project.entryPoint

@@ -0,0 +1 @@
+main

mlruns/0/852a00be19a04756b19b2a0fdb0c6a83/tags/mlflow.project.env

@@ -0,0 +1 @@
+conda

mlruns/0/852a00be19a04756b19b2a0fdb0c6a83/tags/mlflow.runName

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mlruns/0/852a00be19a04756b19b2a0fdb0c6a83/tags/mlflow.source.git.commit

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mlruns/0/852a00be19a04756b19b2a0fdb0c6a83/tags/mlflow.source.git.repoURL

@@ -0,0 +1 @@
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mlruns/0/852a00be19a04756b19b2a0fdb0c6a83/tags/mlflow.source.name

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mlruns/0/852a00be19a04756b19b2a0fdb0c6a83/tags/mlflow.source.type

@@ -0,0 +1 @@
+PROJECT

mlruns/0/852a00be19a04756b19b2a0fdb0c6a83/tags/mlflow.user

@@ -0,0 +1 @@
+szymonbartanowicz

mlruns/0/a7bad8d56b5a476193134123f3175c00/meta.yaml

@@ -0,0 +1,15 @@
+artifact_uri: mlflow-artifacts:/0/a7bad8d56b5a476193134123f3175c00/artifacts
+end_time: 1716053941729
+entry_point_name: ''
+experiment_id: '0'
+lifecycle_stage: active
+run_id: a7bad8d56b5a476193134123f3175c00
+run_name: brawny-stag-513
+run_uuid: a7bad8d56b5a476193134123f3175c00
+source_name: ''
+source_type: 4
+source_version: ''
+start_time: 1716053939145
+status: 4
+tags: []
+user_id: szymonbartanowicz

mlruns/0/a7bad8d56b5a476193134123f3175c00/params/epoches

@@ -0,0 +1 @@
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mlruns/0/a7bad8d56b5a476193134123f3175c00/params/epochs

@@ -0,0 +1 @@
+20

mlruns/0/a7bad8d56b5a476193134123f3175c00/tags/mlflow.gitRepoURL

@@ -0,0 +1 @@
+https://git.wmi.amu.edu.pl/s464937/ium_464937.git

mlruns/0/a7bad8d56b5a476193134123f3175c00/tags/mlflow.project.backend

@@ -0,0 +1 @@
+local

mlruns/0/a7bad8d56b5a476193134123f3175c00/tags/mlflow.project.entryPoint

@@ -0,0 +1 @@
+main

mlruns/0/a7bad8d56b5a476193134123f3175c00/tags/mlflow.project.env

@@ -0,0 +1 @@
+conda

mlruns/0/a7bad8d56b5a476193134123f3175c00/tags/mlflow.runName

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mlruns/0/a7bad8d56b5a476193134123f3175c00/tags/mlflow.source.git.commit

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mlruns/0/a7bad8d56b5a476193134123f3175c00/tags/mlflow.source.git.repoURL

@@ -0,0 +1 @@
+https://git.wmi.amu.edu.pl/s464937/ium_464937.git

mlruns/0/a7bad8d56b5a476193134123f3175c00/tags/mlflow.source.name

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+file:///Users/szymonbartanowicz/studia/mag_1/inzynieria_uczenia_maszynowego/ium_464937#mlflow

mlruns/0/a7bad8d56b5a476193134123f3175c00/tags/mlflow.source.type

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+PROJECT

mlruns/0/a7bad8d56b5a476193134123f3175c00/tags/mlflow.user

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+szymonbartanowicz

mlruns/0/b7c7e490ed0f4a6d98293d275b5f67a9/meta.yaml

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+artifact_uri: mlflow-artifacts:/0/b7c7e490ed0f4a6d98293d275b5f67a9/artifacts
+end_time: 1716053969998
+entry_point_name: ''
+experiment_id: '0'
+lifecycle_stage: active
+run_id: b7c7e490ed0f4a6d98293d275b5f67a9
+run_name: zealous-crow-502
+run_uuid: b7c7e490ed0f4a6d98293d275b5f67a9
+source_name: ''
+source_type: 4
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+start_time: 1716053967858
+status: 4
+tags: []
+user_id: szymonbartanowicz

mlruns/0/b7c7e490ed0f4a6d98293d275b5f67a9/params/epochs

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+12

mlruns/0/b7c7e490ed0f4a6d98293d275b5f67a9/tags/mlflow.gitRepoURL

@@ -0,0 +1 @@
+https://git.wmi.amu.edu.pl/s464937/ium_464937.git

mlruns/0/b7c7e490ed0f4a6d98293d275b5f67a9/tags/mlflow.project.backend

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mlruns/0/b7c7e490ed0f4a6d98293d275b5f67a9/tags/mlflow.project.entryPoint

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+main

mlruns/0/b7c7e490ed0f4a6d98293d275b5f67a9/tags/mlflow.project.env

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+conda

mlruns/0/b7c7e490ed0f4a6d98293d275b5f67a9/tags/mlflow.runName

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+zealous-crow-502

mlruns/0/b7c7e490ed0f4a6d98293d275b5f67a9/tags/mlflow.source.git.commit

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mlruns/0/b7c7e490ed0f4a6d98293d275b5f67a9/tags/mlflow.source.git.repoURL

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+https://git.wmi.amu.edu.pl/s464937/ium_464937.git

mlruns/0/b7c7e490ed0f4a6d98293d275b5f67a9/tags/mlflow.source.name

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mlruns/0/b7c7e490ed0f4a6d98293d275b5f67a9/tags/mlflow.source.type

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+PROJECT

mlruns/0/b7c7e490ed0f4a6d98293d275b5f67a9/tags/mlflow.user

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+szymonbartanowicz

mlruns/0/dd9e039328564f8bb20449bd7bea8ab1/meta.yaml

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+artifact_uri: mlflow-artifacts:/0/dd9e039328564f8bb20449bd7bea8ab1/artifacts
+end_time: 1716053927316
+entry_point_name: ''
+experiment_id: '0'
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+run_uuid: dd9e039328564f8bb20449bd7bea8ab1
+source_name: ''
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+status: 4
+tags: []
+user_id: szymonbartanowicz

mlruns/0/dd9e039328564f8bb20449bd7bea8ab1/params/epoches

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mlruns/0/dd9e039328564f8bb20449bd7bea8ab1/params/epochs

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+20

mlruns/0/dd9e039328564f8bb20449bd7bea8ab1/tags/mlflow.gitRepoURL

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mlruns/0/dd9e039328564f8bb20449bd7bea8ab1/tags/mlflow.project.backend

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mlruns/0/dd9e039328564f8bb20449bd7bea8ab1/tags/mlflow.project.entryPoint

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mlruns/0/dd9e039328564f8bb20449bd7bea8ab1/tags/mlflow.project.env

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mlruns/0/dd9e039328564f8bb20449bd7bea8ab1/tags/mlflow.runName

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mlruns/0/dd9e039328564f8bb20449bd7bea8ab1/tags/mlflow.source.git.commit

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mlruns/0/dd9e039328564f8bb20449bd7bea8ab1/tags/mlflow.source.git.repoURL

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mlruns/0/dd9e039328564f8bb20449bd7bea8ab1/tags/mlflow.source.name

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mlruns/0/dd9e039328564f8bb20449bd7bea8ab1/tags/mlflow.source.type

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mlruns/0/dd9e039328564f8bb20449bd7bea8ab1/tags/mlflow.user

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