diff --git a/Dockerfile b/Dockerfile index 0f97d6f..03aab8c 100644 --- a/Dockerfile +++ b/Dockerfile @@ -13,6 +13,7 @@ RUN pip3 install --user pandas RUN pip3 install --user numpy RUN pip3 install --user matplotlib RUN pip3 install --user tensorflow +RUN pip3 install --user sacred # Stwórzmy w kontenerze (jeśli nie istnieje) katalog /app i przejdźmy do niego (wszystkie kolejne polecenia RUN, CMD, ENTRYPOINT, COPY i ADD będą w nim wykonywane) diff --git a/Zajęcia4_oraz_5/Dockerfile b/Zajęcia4_oraz_5/Dockerfile index 0f97d6f..03aab8c 100644 --- a/Zajęcia4_oraz_5/Dockerfile +++ b/Zajęcia4_oraz_5/Dockerfile @@ -13,6 +13,7 @@ RUN pip3 install --user pandas RUN pip3 install --user numpy RUN pip3 install --user matplotlib RUN pip3 install --user tensorflow +RUN pip3 install --user sacred # Stwórzmy w kontenerze (jeśli nie istnieje) katalog /app i przejdźmy do niego (wszystkie kolejne polecenia RUN, CMD, ENTRYPOINT, COPY i ADD będą w nim wykonywane) diff --git a/Zajęcia7/Zadanie_1_Sacred.py b/Zajęcia7/Zadanie_1_Sacred.py new file mode 100644 index 0000000..a87887e --- /dev/null +++ b/Zajęcia7/Zadanie_1_Sacred.py @@ -0,0 +1,76 @@ +from tensorflow.keras.models import Sequential, load_model +from tensorflow.keras.layers import Dense +from sklearn.metrics import accuracy_score, classification_report +import pandas as pd +from sklearn.model_selection import train_test_split +import wget +import numpy as np +from sacred.observers import FileStorageObserver +from sacred import Experiment +from datetime import datetime +import os + +ex = Experiment("file_observer", interactive=True) + +ex.observers.append(FileStorageObserver('Zajęcia7/my_runs')) + +@ex.config +def my_config(): + train_size_param = 0.8 + test_size_param = 0.2 + +@ex.capture +def prepare_model(train_size_param, test_size_param, _run): + _run.info["prepare_model_ts"] = str(datetime.now()) + + url = 'https://git.wmi.amu.edu.pl/s434788/ium_434788/raw/branch/master/winequality-red.csv' + wget.download(url, out='Zajęcia7/winequality-red.csv', bar=None) + + wine=pd.read_csv('Zajęcia7/winequality-red.csv') + wine + + y = wine.quality + y.head() + + x = wine.drop(['quality'], axis= 1) + x.head() + + x=((x-x.min())/(x.max()-x.min())) #Normalizacja + + x_train, x_test, y_train, y_test = train_test_split(x,y , test_size=test_size_param, train_size=train_size_param, random_state=21) + + def regression_model(): + model = Sequential() + model.add(Dense(32,activation = "relu", input_shape = (x_train.shape[1],))) + model.add(Dense(64,activation = "relu")) + model.add(Dense(1,activation = "relu")) + + model.compile(optimizer = "adam", loss = "mean_squared_error") + return model + + model = regression_model() + model.fit(x_train, y_train, epochs = 600, verbose = 1) + + model.save('Zajęcia7/saved_model') + + y_pred = model.predict(x_test) + + y_pred[:5] + + y_pred = np.around(y_pred, decimals=0) + + y_pred[:5] + + print(accuracy_score(y_test, y_pred)) + + _run.info["Final Results: "] = classification_report(y_test,y_pred) + + return(classification_report(y_test,y_pred)) + +@ex.main +def my_main(train_size_param, test_size_param): + print(prepare_model()) ## Nie musimy przekazywać wartości + + +r = ex.run() +ex.add_artifact("Zajęcia7/saved_model/saved_model.pb") \ No newline at end of file diff --git a/Zajęcia7/Zadanie_2_Sacred.py b/Zajęcia7/Zadanie_2_Sacred.py new file mode 100644 index 0000000..a38fc78 --- /dev/null +++ b/Zajęcia7/Zadanie_2_Sacred.py @@ -0,0 +1,84 @@ +''' +Zadanie na dzień 09.05.2021 nie jest możliwe do skończenia bez dostępu do Jenkinsa! +''' + + + + +from tensorflow.keras.models import Sequential, load_model +from tensorflow.keras.layers import Dense +from sklearn.metrics import accuracy_score, classification_report +import pandas as pd +from sklearn.model_selection import train_test_split +import wget +import numpy as np +from sacred.observers import MongoObserver +from sacred import Experiment +from datetime import datetime +import os + +ex = Experiment("sacred_scopes", interactive=True) +ex.observers.append(MongoObserver(url='mongodb://mongo_user:mongo_password_IUM_2021@localhost:27017', + db_name='sacred')) # Tutaj podajemy dane uwierzytelniające i nazwę bazy skonfigurowane w pliku .env podczas uruchamiania bazy. +# W przypadku instancji na Jenkinsie url będzie wyglądał następująco: mongodb://mongo_user:mongo_password_IUM_2021@localhost:27017 + +@ex.config +def my_config(): + train_size_param = 0.8 + test_size_param = 0.2 + +@ex.capture +def prepare_model(train_size_param, test_size_param, _run): + _run.info["prepare_model_ts"] = str(datetime.now()) + + url = 'https://git.wmi.amu.edu.pl/s434788/ium_434788/raw/branch/master/winequality-red.csv' + wget.download(url, out='Zajęcia7/winequality-red.csv', bar=None) + + wine=pd.read_csv('Zajęcia7/winequality-red.csv') + wine + + y = wine.quality + y.head() + + x = wine.drop(['quality'], axis= 1) + x.head() + + x=((x-x.min())/(x.max()-x.min())) #Normalizacja + + x_train, x_test, y_train, y_test = train_test_split(x,y , test_size=test_size_param, train_size=train_size_param, random_state=21) + + def regression_model(): + model = Sequential() + model.add(Dense(32,activation = "relu", input_shape = (x_train.shape[1],))) + model.add(Dense(64,activation = "relu")) + model.add(Dense(1,activation = "relu")) + + model.compile(optimizer = "adam", loss = "mean_squared_error") + return model + + model = regression_model() + model.fit(x_train, y_train, epochs = 600, verbose = 1) + + model.save('Zajęcia7/saved_model') + + y_pred = model.predict(x_test) + + y_pred[:5] + + y_pred = np.around(y_pred, decimals=0) + + y_pred[:5] + + print(accuracy_score(y_test, y_pred)) + + _run.info["Final Results: "] = classification_report(y_test,y_pred) + + return(classification_report(y_test,y_pred)) + +@ex.main +def my_main(train_size_param, test_size_param): + print(prepare_model()) ## Nie musimy przekazywać wartości + + +r = ex.run() +ex.add_artifact("Zajęcia7/saved_model/saved_model.pb") \ No newline at end of file diff --git a/Zajęcia7/my_runs/1/config.json b/Zajęcia7/my_runs/1/config.json new file mode 100644 index 0000000..220009f --- /dev/null +++ b/Zajęcia7/my_runs/1/config.json @@ -0,0 +1,5 @@ +{ + "seed": 93742377, + "test_size_param": 0.2, + "train_size_param": 0.8 +} \ No newline at end of file diff --git a/Zajęcia7/my_runs/1/cout.txt b/Zajęcia7/my_runs/1/cout.txt new file mode 100644 index 0000000..e66fa07 --- /dev/null +++ b/Zajęcia7/my_runs/1/cout.txt @@ -0,0 +1,1216 @@ +Epoch 1/600 + 1/40 [..............................] - ETA: 16s - loss: 30.3634 40/40 [==============================] - 0s 805us/step - loss: 25.9431 +Epoch 2/600 + 1/40 [..............................] - ETA: 0s - loss: 9.6697 40/40 [==============================] - 0s 846us/step - loss: 7.0816 +Epoch 3/600 + 1/40 [..............................] - ETA: 0s - loss: 0.7402 40/40 [==============================] - 0s 808us/step - loss: 1.0185 +Epoch 4/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5726 40/40 [==============================] - 0s 667us/step - loss: 0.8556 +Epoch 5/600 + 1/40 [..............................] - ETA: 0s - loss: 0.7778 40/40 [==============================] - 0s 641us/step - loss: 0.8666 +Epoch 6/600 + 1/40 [..............................] - ETA: 0s - loss: 1.4392 40/40 [==============================] - 0s 1ms/step - loss: 0.8366 +Epoch 7/600 + 1/40 [..............................] - ETA: 0s - loss: 0.8974 40/40 [==============================] - 0s 846us/step - loss: 0.7454 +Epoch 8/600 + 1/40 [..............................] - ETA: 0s - loss: 0.8933 40/40 [==============================] - 0s 692us/step - loss: 0.7057 +Epoch 9/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4836 40/40 [==============================] - 0s 769us/step - loss: 0.6121 +Epoch 10/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4916 40/40 [==============================] - 0s 834us/step - loss: 0.6070 +Epoch 11/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3314 40/40 [==============================] - 0s 846us/step - loss: 0.5664 +Epoch 12/600 + 1/40 [..............................] - ETA: 0s - loss: 0.7434 40/40 [==============================] - 0s 641us/step - loss: 0.5961 +Epoch 13/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2910 40/40 [==============================] - 0s 846us/step - loss: 0.5071 +Epoch 14/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5955 40/40 [==============================] - 0s 808us/step - loss: 0.5755 +Epoch 15/600 + 1/40 [..............................] - ETA: 0s - loss: 0.7243 40/40 [==============================] - 0s 705us/step - loss: 0.5382 +Epoch 16/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4032 40/40 [==============================] - 0s 692us/step - loss: 0.5214 +Epoch 17/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4972 40/40 [==============================] - 0s 731us/step - loss: 0.4850 +Epoch 18/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4014 40/40 [==============================] - 0s 718us/step - loss: 0.4633 +Epoch 19/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3637 40/40 [==============================] - 0s 846us/step - loss: 0.4795 +Epoch 20/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5728 40/40 [==============================] - 0s 911us/step - loss: 0.5188 +Epoch 21/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5218 40/40 [==============================] - 0s 873us/step - loss: 0.5114 +Epoch 22/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5180 40/40 [==============================] - 0s 846us/step - loss: 0.5059 +Epoch 23/600 + 1/40 [..............................] - ETA: 0s - loss: 0.7872 40/40 [==============================] - 0s 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[==============================] - 0s 564us/step - loss: 0.3249 +Epoch 598/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3995 40/40 [==============================] - 0s 564us/step - loss: 0.3503 +Epoch 599/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3211 40/40 [==============================] - 0s 564us/step - loss: 0.2985 +Epoch 600/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3498 40/40 [==============================] - 0s 590us/step - loss: 0.3268 +0.6125 +C:\Users\domstr2\anaconda3\lib\site-packages\sklearn\metrics\_classification.py:1221: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior. + _warn_prf(average, modifier, msg_start, len(result)) + precision recall f1-score support + + 3 0.00 0.00 0.00 1 + 4 0.00 0.00 0.00 16 + 5 0.69 0.65 0.67 127 + 6 0.58 0.69 0.63 131 + 7 0.56 0.52 0.54 42 + 8 0.00 0.00 0.00 3 + + accuracy 0.61 320 + macro avg 0.30 0.31 0.31 320 +weighted avg 0.58 0.61 0.60 320 + diff --git a/Zajęcia7/my_runs/1/info.json b/Zajęcia7/my_runs/1/info.json new file mode 100644 index 0000000..d16079c --- /dev/null +++ b/Zajęcia7/my_runs/1/info.json @@ -0,0 +1,4 @@ +{ + "Final Results: ": " precision recall f1-score support\n\n 3 0.00 0.00 0.00 1\n 4 0.00 0.00 0.00 16\n 5 0.69 0.65 0.67 127\n 6 0.58 0.69 0.63 131\n 7 0.56 0.52 0.54 42\n 8 0.00 0.00 0.00 3\n\n accuracy 0.61 320\n macro avg 0.30 0.31 0.31 320\nweighted avg 0.58 0.61 0.60 320\n", + "prepare_model_ts": "2021-05-09 23:25:48.528529" +} \ No newline at end of file diff --git a/Zajęcia7/my_runs/1/metrics.json b/Zajęcia7/my_runs/1/metrics.json new file mode 100644 index 0000000..9e26dfe --- /dev/null +++ b/Zajęcia7/my_runs/1/metrics.json @@ -0,0 +1 @@ +{} \ No newline at end of file diff --git a/Zajęcia7/my_runs/1/run.json b/Zajęcia7/my_runs/1/run.json new file mode 100644 index 0000000..8ff56b5 --- /dev/null +++ b/Zajęcia7/my_runs/1/run.json @@ -0,0 +1,82 @@ +{ + "artifacts": [ + "saved_model.pb" + ], + "command": "my_main", + "experiment": { + "base_dir": "c:\\Users\\domstr2\\Desktop\\Git Repositories\\ium_434788\\Zaj\u0119cia7", + "dependencies": [ + "numpy==1.19.2", + "pandas==1.1.3", + "sacred==0.8.2", + "scikit-learn==0.23.2", + "tensorflow==2.4.1", + "wget==3.2" + ], + "mainfile": "Zadanie_1_Sacred.py", + "name": "file_observer", + "repositories": [ + { + "commit": "fcc6e77ef0297c583ccde2a4eb5924839a8f2f09", + "dirty": true, + "url": "https://git.wmi.amu.edu.pl/s434788/ium_434788.git" + } + ], + "sources": [ + [ + "Zadanie_1_Sacred.py", + "_sources\\Zadanie_1_Sacred_30ef87dbd210931ef4b8384e66e7736f.py" + ] + ] + }, + "heartbeat": "2021-05-09T21:26:06.005402", + "host": { + "ENV": {}, + "cpu": "Unknown", + "gpus": { + "driver_version": "465.89", + "gpus": [ + { + "model": "NVIDIA GeForce GTX 970", + "persistence_mode": false, + "total_memory": 4096 + } + ] + }, + "hostname": "DESKTOP-1NBQAAH", + "os": [ + "Windows", + "Windows-10-10.0.19041-SP0" + ], + "python_version": "3.8.5" + }, + "meta": { + "command": "my_main", + "options": { + "--beat-interval": null, + "--capture": null, + "--comment": null, + "--debug": false, + "--enforce_clean": false, + "--file_storage": null, + "--force": false, + "--help": false, + "--loglevel": null, + "--mongo_db": null, + "--name": null, + "--pdb": false, + "--print-config": false, + "--priority": null, + "--queue": false, + "--s3": null, + "--sql": null, + "--tiny_db": null, + "--unobserved": false + } + }, + "resources": [], + "result": null, + "start_time": "2021-05-09T21:25:48.516529", + "status": "COMPLETED", + "stop_time": "2021-05-09T21:26:06.004401" +} \ No newline at end of file diff --git a/Zajęcia7/my_runs/1/saved_model.pb b/Zajęcia7/my_runs/1/saved_model.pb new file mode 100644 index 0000000..ddbee7e Binary files /dev/null and b/Zajęcia7/my_runs/1/saved_model.pb differ diff --git a/Zajęcia7/my_runs/_sources/Zadanie_1_Sacred_30ef87dbd210931ef4b8384e66e7736f.py b/Zajęcia7/my_runs/_sources/Zadanie_1_Sacred_30ef87dbd210931ef4b8384e66e7736f.py new file mode 100644 index 0000000..a87887e --- /dev/null +++ b/Zajęcia7/my_runs/_sources/Zadanie_1_Sacred_30ef87dbd210931ef4b8384e66e7736f.py @@ -0,0 +1,76 @@ +from tensorflow.keras.models import Sequential, load_model +from tensorflow.keras.layers import Dense +from sklearn.metrics import accuracy_score, classification_report +import pandas as pd +from sklearn.model_selection import train_test_split +import wget +import numpy as np +from sacred.observers import FileStorageObserver +from sacred import Experiment +from datetime import datetime +import os + +ex = Experiment("file_observer", interactive=True) + +ex.observers.append(FileStorageObserver('Zajęcia7/my_runs')) + +@ex.config +def my_config(): + train_size_param = 0.8 + test_size_param = 0.2 + +@ex.capture +def prepare_model(train_size_param, test_size_param, _run): + _run.info["prepare_model_ts"] = str(datetime.now()) + + url = 'https://git.wmi.amu.edu.pl/s434788/ium_434788/raw/branch/master/winequality-red.csv' + wget.download(url, out='Zajęcia7/winequality-red.csv', bar=None) + + wine=pd.read_csv('Zajęcia7/winequality-red.csv') + wine + + y = wine.quality + y.head() + + x = wine.drop(['quality'], axis= 1) + x.head() + + x=((x-x.min())/(x.max()-x.min())) #Normalizacja + + x_train, x_test, y_train, y_test = train_test_split(x,y , test_size=test_size_param, train_size=train_size_param, random_state=21) + + def regression_model(): + model = Sequential() + model.add(Dense(32,activation = "relu", input_shape = (x_train.shape[1],))) + model.add(Dense(64,activation = "relu")) + model.add(Dense(1,activation = "relu")) + + model.compile(optimizer = "adam", loss = "mean_squared_error") + return model + + model = regression_model() + model.fit(x_train, y_train, epochs = 600, verbose = 1) + + model.save('Zajęcia7/saved_model') + + y_pred = model.predict(x_test) + + y_pred[:5] + + y_pred = np.around(y_pred, decimals=0) + + y_pred[:5] + + print(accuracy_score(y_test, y_pred)) + + _run.info["Final Results: "] = classification_report(y_test,y_pred) + + return(classification_report(y_test,y_pred)) + +@ex.main +def my_main(train_size_param, test_size_param): + print(prepare_model()) ## Nie musimy przekazywać wartości + + +r = ex.run() +ex.add_artifact("Zajęcia7/saved_model/saved_model.pb") \ No newline at end of file diff --git a/Zajęcia7/saved_model/saved_model.pb b/Zajęcia7/saved_model/saved_model.pb new file mode 100644 index 0000000..ddbee7e Binary files /dev/null and b/Zajęcia7/saved_model/saved_model.pb differ diff --git a/Zajęcia7/saved_model/variables/variables.data-00000-of-00001 b/Zajęcia7/saved_model/variables/variables.data-00000-of-00001 new file mode 100644 index 0000000..ce04475 Binary files /dev/null and b/Zajęcia7/saved_model/variables/variables.data-00000-of-00001 differ diff --git a/Zajęcia7/saved_model/variables/variables.index b/Zajęcia7/saved_model/variables/variables.index new file mode 100644 index 0000000..655acc3 Binary files /dev/null and b/Zajęcia7/saved_model/variables/variables.index differ diff --git a/winequality-red.csv b/Zajęcia7/winequality-red.csv similarity index 100% rename from winequality-red.csv rename to Zajęcia7/winequality-red.csv