From a325b2ca800223cd0db38ebb5cf543a7f2d1dd6c Mon Sep 17 00:00:00 2001 From: Dominik Strzako Date: Sun, 9 May 2021 23:34:32 +0200 Subject: [PATCH] =?UTF-8?q?Zaj=C4=99cia=207=20z=20Sacred=20(Zadanie=202=20?= =?UTF-8?q?nie=20jest=20sko=C5=84czone=20-=20awaria=20Jenkinsa)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- Dockerfile | 1 + Zajęcia4_oraz_5/Dockerfile | 1 + Zajęcia7/Zadanie_1_Sacred.py | 76 ++ Zajęcia7/Zadanie_2_Sacred.py | 84 ++ Zajęcia7/my_runs/1/config.json | 5 + Zajęcia7/my_runs/1/cout.txt | 1216 +++++++++++++++++ Zajęcia7/my_runs/1/info.json | 4 + Zajęcia7/my_runs/1/metrics.json | 1 + Zajęcia7/my_runs/1/run.json | 82 ++ Zajęcia7/my_runs/1/saved_model.pb | Bin 0 -> 88381 bytes ...Sacred_30ef87dbd210931ef4b8384e66e7736f.py | 76 ++ Zajęcia7/saved_model/saved_model.pb | Bin 0 -> 88381 bytes .../variables/variables.data-00000-of-00001 | Bin 0 -> 35137 bytes .../saved_model/variables/variables.index | Bin 0 -> 1688 bytes .../winequality-red.csv | 0 15 files changed, 1546 insertions(+) create mode 100644 Zajęcia7/Zadanie_1_Sacred.py create mode 100644 Zajęcia7/Zadanie_2_Sacred.py create mode 100644 Zajęcia7/my_runs/1/config.json create mode 100644 Zajęcia7/my_runs/1/cout.txt create mode 100644 Zajęcia7/my_runs/1/info.json create mode 100644 Zajęcia7/my_runs/1/metrics.json create mode 100644 Zajęcia7/my_runs/1/run.json create mode 100644 Zajęcia7/my_runs/1/saved_model.pb create mode 100644 Zajęcia7/my_runs/_sources/Zadanie_1_Sacred_30ef87dbd210931ef4b8384e66e7736f.py create mode 100644 Zajęcia7/saved_model/saved_model.pb create mode 100644 Zajęcia7/saved_model/variables/variables.data-00000-of-00001 create mode 100644 Zajęcia7/saved_model/variables/variables.index rename winequality-red.csv => Zajęcia7/winequality-red.csv (100%) 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 795us/step - loss: 0.5157 +Epoch 24/600 + 1/40 [..............................] - ETA: 0s - loss: 0.8917 40/40 [==============================] - 0s 590us/step - loss: 0.5135 +Epoch 25/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4138 40/40 [==============================] - 0s 577us/step - loss: 0.4778 +Epoch 26/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5297 40/40 [==============================] - 0s 641us/step - loss: 0.4717 +Epoch 27/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3460 40/40 [==============================] - 0s 564us/step - loss: 0.4495 +Epoch 28/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2483 40/40 [==============================] - 0s 590us/step - loss: 0.4043 +Epoch 29/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3856 34/40 [========================>.....] - ETA: 0s - loss: 0.4231 40/40 [==============================] - 0s 1ms/step - loss: 0.4277 +Epoch 30/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2276 40/40 [==============================] - 0s 1ms/step - loss: 0.4307 +Epoch 31/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4349 40/40 [==============================] - 0s 577us/step - loss: 0.4183 +Epoch 32/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5284 40/40 [==============================] - 0s 590us/step - loss: 0.4388 +Epoch 33/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5634 40/40 [==============================] - 0s 590us/step - loss: 0.4383 +Epoch 34/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3060 40/40 [==============================] - 0s 616us/step - loss: 0.4365 +Epoch 35/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4404 40/40 [==============================] - 0s 692us/step - loss: 0.4381 +Epoch 36/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3532 40/40 [==============================] - 0s 769us/step - loss: 0.4242 +Epoch 37/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3077 40/40 [==============================] - 0s 782us/step - loss: 0.3895 +Epoch 38/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3548 40/40 [==============================] - 0s 795us/step - loss: 0.4140 +Epoch 39/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5062 40/40 [==============================] - 0s 667us/step - loss: 0.4071 +Epoch 40/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4113 40/40 [==============================] - 0s 564us/step - loss: 0.4292 +Epoch 41/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3990 40/40 [==============================] - 0s 564us/step - loss: 0.4097 +Epoch 42/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4642 40/40 [==============================] - 0s 577us/step - loss: 0.4204 +Epoch 43/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3446 40/40 [==============================] - 0s 589us/step - loss: 0.4065 +Epoch 44/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2910 40/40 [==============================] - 0s 577us/step - loss: 0.3976 +Epoch 45/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3881 40/40 [==============================] - 0s 603us/step - loss: 0.4256 +Epoch 46/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2790 40/40 [==============================] - 0s 564us/step - loss: 0.3590 +Epoch 47/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4332 40/40 [==============================] - 0s 538us/step - loss: 0.4113 +Epoch 48/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4933 40/40 [==============================] - 0s 705us/step - loss: 0.4073 +Epoch 49/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2643 40/40 [==============================] - 0s 732us/step - loss: 0.3958 +Epoch 50/600 + 1/40 [..............................] - ETA: 0s - loss: 0.1927 40/40 [==============================] - 0s 769us/step - loss: 0.3865 +Epoch 51/600 + 1/40 [..............................] - ETA: 0s - loss: 0.1783 40/40 [==============================] - 0s 757us/step - loss: 0.3881 +Epoch 52/600 + 1/40 [..............................] - ETA: 0s - loss: 0.1931 40/40 [==============================] - 0s 757us/step - loss: 0.3729 +Epoch 53/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3806 40/40 [==============================] - 0s 859us/step - loss: 0.3825 +Epoch 54/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3511 40/40 [==============================] - 0s 846us/step - loss: 0.4092 +Epoch 55/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3569 40/40 [==============================] - 0s 757us/step - loss: 0.3835 +Epoch 56/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4245 40/40 [==============================] - 0s 744us/step - loss: 0.4284 +Epoch 57/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2735 40/40 [==============================] - 0s 706us/step - loss: 0.3777 +Epoch 58/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4255 40/40 [==============================] - 0s 705us/step - loss: 0.3832 +Epoch 59/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3080 40/40 [==============================] - 0s 705us/step - loss: 0.3682 +Epoch 60/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3770 40/40 [==============================] - 0s 615us/step - loss: 0.3878 +Epoch 61/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5007 40/40 [==============================] - 0s 564us/step - loss: 0.4113 +Epoch 62/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4295 40/40 [==============================] - 0s 577us/step - loss: 0.4161 +Epoch 63/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5035 40/40 [==============================] - 0s 564us/step - loss: 0.4362 +Epoch 64/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3864 40/40 [==============================] - 0s 603us/step - loss: 0.3791 +Epoch 65/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2476 32/40 [=======================>......] - ETA: 0s - loss: 0.3883 40/40 [==============================] - 0s 1ms/step - loss: 0.3874 +Epoch 66/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5060 40/40 [==============================] - 0s 744us/step - loss: 0.3944 +Epoch 67/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3321 40/40 [==============================] - 0s 667us/step - loss: 0.4095 +Epoch 68/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3097 40/40 [==============================] - 0s 680us/step - loss: 0.3800 +Epoch 69/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3030 40/40 [==============================] - 0s 718us/step - loss: 0.3595 +Epoch 70/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5100 40/40 [==============================] - 0s 629us/step - loss: 0.4390 +Epoch 71/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4997 40/40 [==============================] - 0s 564us/step - loss: 0.3994 +Epoch 72/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4542 40/40 [==============================] - 0s 552us/step - loss: 0.3847 +Epoch 73/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4348 40/40 [==============================] - 0s 539us/step - loss: 0.3890 +Epoch 74/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2517 40/40 [==============================] - 0s 578us/step - loss: 0.3662 +Epoch 75/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4348 40/40 [==============================] - 0s 577us/step - loss: 0.3950 +Epoch 76/600 + 1/40 [..............................] - ETA: 0s - loss: 0.6040 40/40 [==============================] - 0s 564us/step - loss: 0.3992 +Epoch 77/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2597 40/40 [==============================] - 0s 590us/step - loss: 0.3964 +Epoch 78/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4023 40/40 [==============================] - 0s 577us/step - loss: 0.3879 +Epoch 79/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3626 40/40 [==============================] - 0s 615us/step - loss: 0.3760 +Epoch 80/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4254 40/40 [==============================] - 0s 552us/step - loss: 0.3814 +Epoch 81/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5368 40/40 [==============================] - 0s 603us/step - loss: 0.4004 +Epoch 82/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3683 40/40 [==============================] - 0s 564us/step - loss: 0.3822 +Epoch 83/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3807 40/40 [==============================] - 0s 578us/step - loss: 0.3932 +Epoch 84/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3463 40/40 [==============================] - 0s 564us/step - loss: 0.3907 +Epoch 85/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3400 40/40 [==============================] - 0s 564us/step - loss: 0.3811 +Epoch 86/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3107 40/40 [==============================] - 0s 564us/step - loss: 0.3769 +Epoch 87/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5306 40/40 [==============================] - 0s 538us/step - loss: 0.3879 +Epoch 88/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2343 40/40 [==============================] - 0s 577us/step - loss: 0.3807 +Epoch 89/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5033 40/40 [==============================] - 0s 551us/step - loss: 0.4060 +Epoch 90/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3118 40/40 [==============================] - 0s 619us/step - loss: 0.3679 +Epoch 91/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3423 40/40 [==============================] - 0s 577us/step - loss: 0.3733 +Epoch 92/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4992 40/40 [==============================] - 0s 615us/step - loss: 0.3886 +Epoch 93/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4652 40/40 [==============================] - 0s 564us/step - loss: 0.3806 +Epoch 94/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4413 40/40 [==============================] - 0s 641us/step - loss: 0.3814 +Epoch 95/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4685 40/40 [==============================] - 0s 590us/step - loss: 0.4000 +Epoch 96/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3481 40/40 [==============================] - 0s 615us/step - loss: 0.3783 +Epoch 97/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5392 40/40 [==============================] - 0s 538us/step - loss: 0.4288 +Epoch 98/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2500 40/40 [==============================] - 0s 615us/step - loss: 0.3738 +Epoch 99/600 + 1/40 [..............................] - ETA: 0s - loss: 0.6368 40/40 [==============================] - 0s 590us/step - loss: 0.3954 +Epoch 100/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4323 40/40 [==============================] - 0s 692us/step - loss: 0.3597 +Epoch 101/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4489 40/40 [==============================] - 0s 552us/step - loss: 0.3979 +Epoch 102/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4285 40/40 [==============================] - 0s 538us/step - loss: 0.4018 +Epoch 103/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3075 40/40 [==============================] - 0s 552us/step - loss: 0.3893 +Epoch 104/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2449 40/40 [==============================] - 0s 564us/step - loss: 0.3463 +Epoch 105/600 + 1/40 [..............................] - ETA: 0s - loss: 0.1954 40/40 [==============================] - 0s 564us/step - loss: 0.3939 +Epoch 106/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2881 40/40 [==============================] - 0s 577us/step - loss: 0.3886 +Epoch 107/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3066 40/40 [==============================] - 0s 590us/step - loss: 0.3698 +Epoch 108/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4139 40/40 [==============================] - 0s 641us/step - loss: 0.3654 +Epoch 109/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2654 40/40 [==============================] - 0s 615us/step - loss: 0.3575 +Epoch 110/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4450 40/40 [==============================] - 0s 692us/step - loss: 0.3750 +Epoch 111/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2633 40/40 [==============================] - 0s 577us/step - loss: 0.3671 +Epoch 112/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3204 40/40 [==============================] - 0s 577us/step - loss: 0.3691 +Epoch 113/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2011 40/40 [==============================] - 0s 552us/step - loss: 0.3693 +Epoch 114/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4676 40/40 [==============================] - 0s 641us/step - loss: 0.3965 +Epoch 115/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2450 40/40 [==============================] - 0s 795us/step - loss: 0.3820 +Epoch 116/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4224 40/40 [==============================] - 0s 731us/step - loss: 0.3896 +Epoch 117/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2768 40/40 [==============================] - 0s 705us/step - loss: 0.3711 +Epoch 118/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3560 40/40 [==============================] - 0s 577us/step - loss: 0.3963 +Epoch 119/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3189 40/40 [==============================] - 0s 590us/step - loss: 0.3798 +Epoch 120/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2827 40/40 [==============================] - 0s 603us/step - loss: 0.3619 +Epoch 121/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4919 40/40 [==============================] - 0s 654us/step - loss: 0.3857 +Epoch 122/600 + 1/40 [..............................] - ETA: 0s - loss: 0.6317 40/40 [==============================] - 0s 615us/step - loss: 0.3857 +Epoch 123/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3846 40/40 [==============================] - 0s 616us/step - loss: 0.3791 +Epoch 124/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3430 40/40 [==============================] - 0s 590us/step - loss: 0.3555 +Epoch 125/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3667 40/40 [==============================] - 0s 654us/step - loss: 0.3988 +Epoch 126/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4194 40/40 [==============================] - 0s 629us/step - loss: 0.3791 +Epoch 127/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5905 40/40 [==============================] - 0s 565us/step - loss: 0.3993 +Epoch 128/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3133 40/40 [==============================] - 0s 577us/step - loss: 0.3741 +Epoch 129/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2580 40/40 [==============================] - 0s 577us/step - loss: 0.3790 +Epoch 130/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5073 40/40 [==============================] - 0s 552us/step - loss: 0.3689 +Epoch 131/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4238 40/40 [==============================] - 0s 615us/step - loss: 0.3677 +Epoch 132/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4093 40/40 [==============================] - 0s 693us/step - loss: 0.3902 +Epoch 133/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2010 40/40 [==============================] - 0s 718us/step - loss: 0.3460 +Epoch 134/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4952 40/40 [==============================] - 0s 680us/step - loss: 0.3805 +Epoch 135/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5964 40/40 [==============================] - 0s 718us/step - loss: 0.3804 +Epoch 136/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4535 40/40 [==============================] - 0s 615us/step - loss: 0.3756 +Epoch 137/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3849 40/40 [==============================] - 0s 589us/step - loss: 0.3390 +Epoch 138/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2746 40/40 [==============================] - 0s 731us/step - loss: 0.3714 +Epoch 139/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2169 40/40 [==============================] - 0s 744us/step - loss: 0.3650 +Epoch 140/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5019 40/40 [==============================] - 0s 680us/step - loss: 0.3736 +Epoch 141/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2781 40/40 [==============================] - 0s 667us/step - loss: 0.3571 +Epoch 142/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3605 40/40 [==============================] - 0s 783us/step - loss: 0.3779 +Epoch 143/600 + 1/40 [..............................] - ETA: 0s - loss: 0.1745 40/40 [==============================] - 0s 795us/step - loss: 0.3547 +Epoch 144/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2112 40/40 [==============================] - 0s 782us/step - loss: 0.3602 +Epoch 145/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4246 40/40 [==============================] - 0s 847us/step - loss: 0.3797 +Epoch 146/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3127 40/40 [==============================] - 0s 744us/step - loss: 0.3773 +Epoch 147/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4071 40/40 [==============================] - 0s 769us/step - loss: 0.3532 +Epoch 148/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4101 40/40 [==============================] - 0s 704us/step - loss: 0.3901 +Epoch 149/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5450 40/40 [==============================] - 0s 667us/step - loss: 0.3873 +Epoch 150/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4154 40/40 [==============================] - 0s 564us/step - loss: 0.3511 +Epoch 151/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3572 40/40 [==============================] - 0s 590us/step - loss: 0.3748 +Epoch 152/600 + 1/40 [..............................] - ETA: 0s - loss: 0.1718 40/40 [==============================] - 0s 577us/step - loss: 0.3723 +Epoch 153/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4478 40/40 [==============================] - 0s 603us/step - loss: 0.3973 +Epoch 154/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4539 40/40 [==============================] - 0s 641us/step - loss: 0.3936 +Epoch 155/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3697 40/40 [==============================] - 0s 654us/step - loss: 0.3851 +Epoch 156/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2912 40/40 [==============================] - 0s 564us/step - loss: 0.3515 +Epoch 157/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5318 40/40 [==============================] - 0s 566us/step - loss: 0.3715 +Epoch 158/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3407 40/40 [==============================] - 0s 590us/step - loss: 0.3372 +Epoch 159/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3764 40/40 [==============================] - 0s 590us/step - loss: 0.3559 +Epoch 160/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4185 40/40 [==============================] - 0s 551us/step - loss: 0.3643 +Epoch 161/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2270 40/40 [==============================] - 0s 590us/step - loss: 0.3459 +Epoch 162/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3431 40/40 [==============================] - 0s 564us/step - loss: 0.3568 +Epoch 163/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2912 40/40 [==============================] - 0s 603us/step - loss: 0.3715 +Epoch 164/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2917 40/40 [==============================] - 0s 641us/step - loss: 0.3434 +Epoch 165/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4459 40/40 [==============================] - 0s 628us/step - loss: 0.3598 +Epoch 166/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4254 27/40 [===================>..........] - ETA: 0s - loss: 0.3931 40/40 [==============================] - 0s 2ms/step - loss: 0.3881 +Epoch 167/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4482 40/40 [==============================] - 0s 846us/step - loss: 0.3867 +Epoch 168/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3091 40/40 [==============================] - 0s 615us/step - loss: 0.3757 +Epoch 169/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4069 40/40 [==============================] - 0s 564us/step - loss: 0.3672 +Epoch 170/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4342 40/40 [==============================] - 0s 564us/step - loss: 0.3785 +Epoch 171/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4501 40/40 [==============================] - 0s 564us/step - loss: 0.3866 +Epoch 172/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4644 40/40 [==============================] - 0s 564us/step - loss: 0.3646 +Epoch 173/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2349 40/40 [==============================] - 0s 589us/step - loss: 0.3529 +Epoch 174/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2875 40/40 [==============================] - 0s 564us/step - loss: 0.3494 +Epoch 175/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4126 40/40 [==============================] - 0s 577us/step - loss: 0.3842 +Epoch 176/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5155 40/40 [==============================] - 0s 552us/step - loss: 0.3630 +Epoch 177/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3132 40/40 [==============================] - 0s 615us/step - loss: 0.3453 +Epoch 178/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4191 40/40 [==============================] - 0s 564us/step - loss: 0.3677 +Epoch 179/600 + 1/40 [..............................] - ETA: 0s - loss: 0.6052 40/40 [==============================] - 0s 577us/step - loss: 0.3933 +Epoch 180/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3603 40/40 [==============================] - 0s 564us/step - loss: 0.3571 +Epoch 181/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3950 40/40 [==============================] - 0s 590us/step - loss: 0.3584 +Epoch 182/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4069 40/40 [==============================] - 0s 577us/step - loss: 0.3755 +Epoch 183/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2957 40/40 [==============================] - 0s 590us/step - loss: 0.3442 +Epoch 184/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4128 40/40 [==============================] - 0s 566us/step - loss: 0.3676 +Epoch 185/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5431 40/40 [==============================] - 0s 590us/step - loss: 0.3859 +Epoch 186/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2675 40/40 [==============================] - 0s 552us/step - loss: 0.3312 +Epoch 187/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2277 40/40 [==============================] - 0s 564us/step - loss: 0.3434 +Epoch 188/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3059 40/40 [==============================] - 0s 590us/step - loss: 0.3408 +Epoch 189/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3695 40/40 [==============================] - 0s 552us/step - loss: 0.3618 +Epoch 190/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4252 40/40 [==============================] - 0s 590us/step - loss: 0.3595 +Epoch 191/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4539 40/40 [==============================] - 0s 564us/step - loss: 0.3702 +Epoch 192/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3311 40/40 [==============================] - 0s 629us/step - loss: 0.3542 +Epoch 193/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2756 40/40 [==============================] - 0s 564us/step - loss: 0.3444 +Epoch 194/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2441 40/40 [==============================] - 0s 603us/step - loss: 0.3551 +Epoch 195/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3262 40/40 [==============================] - 0s 538us/step - loss: 0.3629 +Epoch 196/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4134 40/40 [==============================] - 0s 577us/step - loss: 0.3594 +Epoch 197/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2861 40/40 [==============================] - 0s 564us/step - loss: 0.3568 +Epoch 198/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2572 40/40 [==============================] - 0s 564us/step - loss: 0.3562 +Epoch 199/600 + 1/40 [..............................] - ETA: 0s - loss: 0.1690 40/40 [==============================] - 0s 615us/step - loss: 0.3344 +Epoch 200/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2851 40/40 [==============================] - 0s 539us/step - loss: 0.3837 +Epoch 201/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3615 40/40 [==============================] - 0s 603us/step - loss: 0.3687 +Epoch 202/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3114 40/40 [==============================] - 0s 564us/step - loss: 0.3341 +Epoch 203/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3332 40/40 [==============================] - 0s 603us/step - loss: 0.3683 +Epoch 204/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3614 40/40 [==============================] - 0s 603us/step - loss: 0.3550 +Epoch 205/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3385 40/40 [==============================] - 0s 692us/step - loss: 0.3594 +Epoch 206/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4425 40/40 [==============================] - 0s 693us/step - loss: 0.3534 +Epoch 207/600 + 1/40 [..............................] - ETA: 0s - loss: 0.6033 40/40 [==============================] - 0s 641us/step - loss: 0.3482 +Epoch 208/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2440 40/40 [==============================] - 0s 577us/step - loss: 0.3669 +Epoch 209/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4160 40/40 [==============================] - 0s 538us/step - loss: 0.3776 +Epoch 210/600 + 1/40 [..............................] - ETA: 0s - loss: 0.1812 40/40 [==============================] - 0s 603us/step - loss: 0.3599 +Epoch 211/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4471 40/40 [==============================] - 0s 538us/step - loss: 0.3739 +Epoch 212/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3031 40/40 [==============================] - 0s 564us/step - loss: 0.3390 +Epoch 213/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4198 40/40 [==============================] - 0s 552us/step - loss: 0.3678 +Epoch 214/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2537 40/40 [==============================] - 0s 564us/step - loss: 0.3328 +Epoch 215/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3846 40/40 [==============================] - 0s 538us/step - loss: 0.3591 +Epoch 216/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2426 40/40 [==============================] - 0s 552us/step - loss: 0.3415 +Epoch 217/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3252 40/40 [==============================] - 0s 564us/step - loss: 0.3645 +Epoch 218/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4383 40/40 [==============================] - 0s 552us/step - loss: 0.3819 +Epoch 219/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3733 40/40 [==============================] - 0s 590us/step - loss: 0.3583 +Epoch 220/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4862 40/40 [==============================] - 0s 538us/step - loss: 0.3863 +Epoch 221/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4561 40/40 [==============================] - 0s 603us/step - loss: 0.3713 +Epoch 222/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4778 40/40 [==============================] - 0s 564us/step - loss: 0.3791 +Epoch 223/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2891 40/40 [==============================] - 0s 564us/step - loss: 0.3432 +Epoch 224/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4577 40/40 [==============================] - 0s 577us/step - loss: 0.3608 +Epoch 225/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5919 40/40 [==============================] - 0s 564us/step - loss: 0.3690 +Epoch 226/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4255 40/40 [==============================] - 0s 590us/step - loss: 0.3603 +Epoch 227/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4440 40/40 [==============================] - 0s 1ms/step - loss: 0.3553 +Epoch 228/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3701 40/40 [==============================] - 0s 590us/step - loss: 0.3403 +Epoch 229/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3204 40/40 [==============================] - 0s 577us/step - loss: 0.3582 +Epoch 230/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4527 40/40 [==============================] - 0s 564us/step - loss: 0.3447 +Epoch 231/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3954 40/40 [==============================] - 0s 538us/step - loss: 0.3550 +Epoch 232/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3021 40/40 [==============================] - 0s 603us/step - loss: 0.3689 +Epoch 233/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3692 40/40 [==============================] - 0s 744us/step - loss: 0.3620 +Epoch 234/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4765 40/40 [==============================] - 0s 616us/step - loss: 0.3570 +Epoch 235/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4328 40/40 [==============================] - 0s 590us/step - loss: 0.3520 +Epoch 236/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4757 40/40 [==============================] - 0s 577us/step - loss: 0.3806 +Epoch 237/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2873 40/40 [==============================] - 0s 577us/step - loss: 0.3646 +Epoch 238/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2942 40/40 [==============================] - 0s 564us/step - loss: 0.3589 +Epoch 239/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2002 40/40 [==============================] - 0s 577us/step - loss: 0.3381 +Epoch 240/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3413 40/40 [==============================] - 0s 590us/step - loss: 0.3968 +Epoch 241/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4987 40/40 [==============================] - 0s 577us/step - loss: 0.3571 +Epoch 242/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2718 40/40 [==============================] - 0s 577us/step - loss: 0.3578 +Epoch 243/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3828 40/40 [==============================] - 0s 590us/step - loss: 0.3726 +Epoch 244/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2602 40/40 [==============================] - 0s 577us/step - loss: 0.3367 +Epoch 245/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5242 40/40 [==============================] - 0s 564us/step - loss: 0.3538 +Epoch 246/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3660 40/40 [==============================] - 0s 564us/step - loss: 0.3759 +Epoch 247/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4281 40/40 [==============================] - 0s 538us/step - loss: 0.3641 +Epoch 248/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5315 40/40 [==============================] - 0s 564us/step - loss: 0.3715 +Epoch 249/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4890 40/40 [==============================] - 0s 564us/step - loss: 0.3768 +Epoch 250/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3405 40/40 [==============================] - 0s 564us/step - loss: 0.3630 +Epoch 251/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2932 40/40 [==============================] - 0s 564us/step - loss: 0.3511 +Epoch 252/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3678 40/40 [==============================] - 0s 552us/step - loss: 0.3614 +Epoch 253/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4753 40/40 [==============================] - 0s 590us/step - loss: 0.3894 +Epoch 254/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4299 40/40 [==============================] - 0s 564us/step - loss: 0.3412 +Epoch 255/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5135 40/40 [==============================] - 0s 642us/step - loss: 0.3949 +Epoch 256/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3936 40/40 [==============================] - 0s 590us/step - loss: 0.3536 +Epoch 257/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2286 40/40 [==============================] - 0s 577us/step - loss: 0.3269 +Epoch 258/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4201 40/40 [==============================] - 0s 538us/step - loss: 0.4023 +Epoch 259/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3811 40/40 [==============================] - 0s 590us/step - loss: 0.3615 +Epoch 260/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3942 40/40 [==============================] - 0s 564us/step - loss: 0.3468 +Epoch 261/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3055 40/40 [==============================] - 0s 538us/step - loss: 0.3368 +Epoch 262/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5033 40/40 [==============================] - 0s 563us/step - loss: 0.3576 +Epoch 263/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2799 40/40 [==============================] - 0s 538us/step - loss: 0.3418 +Epoch 264/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4908 40/40 [==============================] - 0s 628us/step - loss: 0.3632 +Epoch 265/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3329 40/40 [==============================] - 0s 564us/step - loss: 0.3281 +Epoch 266/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3008 40/40 [==============================] - 0s 578us/step - loss: 0.3385 +Epoch 267/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3409 40/40 [==============================] - 0s 570us/step - loss: 0.3569 +Epoch 268/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3096 40/40 [==============================] - 0s 552us/step - loss: 0.3522 +Epoch 269/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4768 40/40 [==============================] - 0s 564us/step - loss: 0.3582 +Epoch 270/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3617 40/40 [==============================] - 0s 603us/step - loss: 0.3614 +Epoch 271/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3640 40/40 [==============================] - 0s 538us/step - loss: 0.3316 +Epoch 272/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4558 40/40 [==============================] - 0s 526us/step - loss: 0.3585 +Epoch 273/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3610 40/40 [==============================] - 0s 590us/step - loss: 0.3614 +Epoch 274/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2227 40/40 [==============================] - 0s 564us/step - loss: 0.3399 +Epoch 275/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2489 40/40 [==============================] - 0s 577us/step - loss: 0.3627 +Epoch 276/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3809 40/40 [==============================] - 0s 564us/step - loss: 0.3860 +Epoch 277/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3724 40/40 [==============================] - 0s 564us/step - loss: 0.3553 +Epoch 278/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5146 40/40 [==============================] - 0s 578us/step - loss: 0.3749 +Epoch 279/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2504 40/40 [==============================] - 0s 564us/step - loss: 0.3303 +Epoch 280/600 + 1/40 [..............................] - ETA: 0s - loss: 0.6082 40/40 [==============================] - 0s 552us/step - loss: 0.3687 +Epoch 281/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3400 40/40 [==============================] - 0s 538us/step - loss: 0.3276 +Epoch 282/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3414 40/40 [==============================] - 0s 564us/step - loss: 0.3617 +Epoch 283/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2631 40/40 [==============================] - 0s 577us/step - loss: 0.3381 +Epoch 284/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2420 40/40 [==============================] - 0s 615us/step - loss: 0.3445 +Epoch 285/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2642 40/40 [==============================] - 0s 564us/step - loss: 0.3534 +Epoch 286/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3413 40/40 [==============================] - 0s 552us/step - loss: 0.3576 +Epoch 287/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4473 40/40 [==============================] - 0s 564us/step - loss: 0.3703 +Epoch 288/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5375 40/40 [==============================] - 0s 539us/step - loss: 0.3727 +Epoch 289/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3783 40/40 [==============================] - 0s 577us/step - loss: 0.3597 +Epoch 290/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2937 40/40 [==============================] - 0s 564us/step - loss: 0.3480 +Epoch 291/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3501 34/40 [========================>.....] - ETA: 0s - loss: 0.3218 40/40 [==============================] - 0s 1ms/step - loss: 0.3278 +Epoch 292/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3979 40/40 [==============================] - 0s 859us/step - loss: 0.3661 +Epoch 293/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3735 40/40 [==============================] - 0s 564us/step - loss: 0.3489 +Epoch 294/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5604 40/40 [==============================] - 0s 603us/step - loss: 0.3681 +Epoch 295/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3973 40/40 [==============================] - 0s 590us/step - loss: 0.3539 +Epoch 296/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4618 40/40 [==============================] - 0s 590us/step - loss: 0.3675 +Epoch 297/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2172 40/40 [==============================] - 0s 552us/step - loss: 0.3392 +Epoch 298/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4918 40/40 [==============================] - 0s 564us/step - loss: 0.3692 +Epoch 299/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3730 40/40 [==============================] - 0s 564us/step - loss: 0.3525 +Epoch 300/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5167 40/40 [==============================] - 0s 565us/step - loss: 0.3720 +Epoch 301/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3481 40/40 [==============================] - 0s 590us/step - loss: 0.3414 +Epoch 302/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2607 40/40 [==============================] - 0s 568us/step - loss: 0.3414 +Epoch 303/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2929 40/40 [==============================] - 0s 590us/step - loss: 0.3586 +Epoch 304/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3896 40/40 [==============================] - 0s 564us/step - loss: 0.3612 +Epoch 305/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3663 40/40 [==============================] - 0s 590us/step - loss: 0.3407 +Epoch 306/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3155 40/40 [==============================] - 0s 552us/step - loss: 0.3494 +Epoch 307/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3180 40/40 [==============================] - 0s 590us/step - loss: 0.3262 +Epoch 308/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4136 40/40 [==============================] - 0s 564us/step - loss: 0.3684 +Epoch 309/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3714 40/40 [==============================] - 0s 577us/step - loss: 0.3486 +Epoch 310/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2452 40/40 [==============================] - 0s 590us/step - loss: 0.3468 +Epoch 311/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3473 40/40 [==============================] - 0s 552us/step - loss: 0.3560 +Epoch 312/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3007 40/40 [==============================] - 0s 564us/step - loss: 0.3434 +Epoch 313/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4516 40/40 [==============================] - 0s 564us/step - loss: 0.3614 +Epoch 314/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4370 40/40 [==============================] - 0s 577us/step - loss: 0.3471 +Epoch 315/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4613 40/40 [==============================] - 0s 538us/step - loss: 0.3864 +Epoch 316/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2850 40/40 [==============================] - 0s 603us/step - loss: 0.3143 +Epoch 317/600 + 1/40 [..............................] - ETA: 0s - loss: 0.1941 40/40 [==============================] - 0s 564us/step - loss: 0.3429 +Epoch 318/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2746 40/40 [==============================] - 0s 564us/step - loss: 0.3418 +Epoch 319/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2609 40/40 [==============================] - 0s 552us/step - loss: 0.3400 +Epoch 320/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2916 40/40 [==============================] - 0s 564us/step - loss: 0.3291 +Epoch 321/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2856 40/40 [==============================] - 0s 577us/step - loss: 0.3656 +Epoch 322/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3832 40/40 [==============================] - 0s 538us/step - loss: 0.3498 +Epoch 323/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3653 40/40 [==============================] - 0s 603us/step - loss: 0.3308 +Epoch 324/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3160 40/40 [==============================] - 0s 564us/step - loss: 0.3582 +Epoch 325/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4164 40/40 [==============================] - 0s 628us/step - loss: 0.3457 +Epoch 326/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2760 40/40 [==============================] - 0s 564us/step - loss: 0.3556 +Epoch 327/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2842 40/40 [==============================] - 0s 590us/step - loss: 0.3377 +Epoch 328/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3005 40/40 [==============================] - 0s 538us/step - loss: 0.3269 +Epoch 329/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3452 40/40 [==============================] - 0s 590us/step - loss: 0.3428 +Epoch 330/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3374 40/40 [==============================] - 0s 552us/step - loss: 0.3216 +Epoch 331/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3658 40/40 [==============================] - 0s 564us/step - loss: 0.3625 +Epoch 332/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2381 40/40 [==============================] - 0s 590us/step - loss: 0.3169 +Epoch 333/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4899 40/40 [==============================] - 0s 538us/step - loss: 0.3735 +Epoch 334/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3230 40/40 [==============================] - 0s 594us/step - loss: 0.3536 +Epoch 335/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4828 40/40 [==============================] - 0s 552us/step - loss: 0.3556 +Epoch 336/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2027 40/40 [==============================] - 0s 590us/step - loss: 0.3447 +Epoch 337/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2153 40/40 [==============================] - 0s 538us/step - loss: 0.3442 +Epoch 338/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2787 40/40 [==============================] - 0s 565us/step - loss: 0.3355 +Epoch 339/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4168 40/40 [==============================] - 0s 538us/step - loss: 0.3535 +Epoch 340/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2942 40/40 [==============================] - 0s 590us/step - loss: 0.3700 +Epoch 341/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4191 40/40 [==============================] - 0s 538us/step - loss: 0.3449 +Epoch 342/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4000 40/40 [==============================] - 0s 564us/step - loss: 0.3530 +Epoch 343/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3351 40/40 [==============================] - 0s 577us/step - loss: 0.3601 +Epoch 344/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3264 40/40 [==============================] - 0s 564us/step - loss: 0.3303 +Epoch 345/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3996 40/40 [==============================] - 0s 705us/step - loss: 0.3667 +Epoch 346/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3112 40/40 [==============================] - 0s 564us/step - loss: 0.3408 +Epoch 347/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3426 40/40 [==============================] - 0s 591us/step - loss: 0.3334 +Epoch 348/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3297 40/40 [==============================] - 0s 565us/step - loss: 0.3741 +Epoch 349/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3156 40/40 [==============================] - 0s 590us/step - loss: 0.3227 +Epoch 350/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4035 40/40 [==============================] - 0s 564us/step - loss: 0.3421 +Epoch 351/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2710 40/40 [==============================] - 0s 603us/step - loss: 0.3347 +Epoch 352/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3862 40/40 [==============================] - 0s 564us/step - loss: 0.3481 +Epoch 353/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2666 40/40 [==============================] - 0s 564us/step - loss: 0.3344 +Epoch 354/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2648 40/40 [==============================] - 0s 552us/step - loss: 0.3271 +Epoch 355/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4126 40/40 [==============================] - 0s 564us/step - loss: 0.3485 +Epoch 356/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3986 40/40 [==============================] - 0s 590us/step - loss: 0.3339 +Epoch 357/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2388 40/40 [==============================] - 0s 564us/step - loss: 0.3339 +Epoch 358/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2301 40/40 [==============================] - 0s 564us/step - loss: 0.3402 +Epoch 359/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3123 40/40 [==============================] - 0s 577us/step - loss: 0.3359 +Epoch 360/600 + 1/40 [..............................] - ETA: 0s - loss: 0.6193 40/40 [==============================] - 0s 590us/step - loss: 0.3774 +Epoch 361/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2585 40/40 [==============================] - 0s 577us/step - loss: 0.3265 +Epoch 362/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2853 40/40 [==============================] - 0s 590us/step - loss: 0.3654 +Epoch 363/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3644 40/40 [==============================] - 0s 590us/step - loss: 0.3640 +Epoch 364/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3158 40/40 [==============================] - 0s 577us/step - loss: 0.3208 +Epoch 365/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5520 40/40 [==============================] - 0s 615us/step - loss: 0.3600 +Epoch 366/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3256 40/40 [==============================] - 0s 603us/step - loss: 0.3371 +Epoch 367/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4059 40/40 [==============================] - 0s 590us/step - loss: 0.3330 +Epoch 368/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2327 40/40 [==============================] - 0s 590us/step - loss: 0.3488 +Epoch 369/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3649 40/40 [==============================] - 0s 551us/step - loss: 0.3410 +Epoch 370/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2836 40/40 [==============================] - 0s 577us/step - loss: 0.3110 +Epoch 371/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3031 40/40 [==============================] - 0s 577us/step - loss: 0.3305 +Epoch 372/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3349 40/40 [==============================] - 0s 564us/step - loss: 0.3260 +Epoch 373/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3213 40/40 [==============================] - 0s 590us/step - loss: 0.3635 +Epoch 374/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2606 40/40 [==============================] - 0s 551us/step - loss: 0.3262 +Epoch 375/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2240 40/40 [==============================] - 0s 564us/step - loss: 0.3498 +Epoch 376/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2921 40/40 [==============================] - 0s 552us/step - loss: 0.3471 +Epoch 377/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3368 40/40 [==============================] - 0s 564us/step - loss: 0.3449 +Epoch 378/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2951 40/40 [==============================] - 0s 590us/step - loss: 0.3457 +Epoch 379/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3035 40/40 [==============================] - 0s 552us/step - loss: 0.3274 +Epoch 380/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2338 40/40 [==============================] - 0s 590us/step - loss: 0.3202 +Epoch 381/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4649 40/40 [==============================] - 0s 552us/step - loss: 0.3346 +Epoch 382/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3015 40/40 [==============================] - 0s 577us/step - loss: 0.3345 +Epoch 383/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3726 40/40 [==============================] - 0s 538us/step - loss: 0.3430 +Epoch 384/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3436 40/40 [==============================] - 0s 578us/step - loss: 0.3458 +Epoch 385/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3610 40/40 [==============================] - 0s 538us/step - loss: 0.3429 +Epoch 386/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3223 40/40 [==============================] - 0s 615us/step - loss: 0.3422 +Epoch 387/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2472 40/40 [==============================] - 0s 589us/step - loss: 0.3466 +Epoch 388/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4908 40/40 [==============================] - 0s 641us/step - loss: 0.3641 +Epoch 389/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2277 40/40 [==============================] - 0s 552us/step - loss: 0.3384 +Epoch 390/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4867 40/40 [==============================] - 0s 590us/step - loss: 0.3534 +Epoch 391/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3896 40/40 [==============================] - 0s 590us/step - loss: 0.3463 +Epoch 392/600 + 1/40 [..............................] - ETA: 0s - loss: 0.1847 40/40 [==============================] - 0s 680us/step - loss: 0.3184 +Epoch 393/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3839 40/40 [==============================] - 0s 769us/step - loss: 0.3427 +Epoch 394/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2304 40/40 [==============================] - 0s 718us/step - loss: 0.3277 +Epoch 395/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2402 40/40 [==============================] - 0s 744us/step - loss: 0.3327 +Epoch 396/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2439 40/40 [==============================] - 0s 615us/step - loss: 0.3211 +Epoch 397/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2751 40/40 [==============================] - 0s 692us/step - loss: 0.3387 +Epoch 398/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4774 40/40 [==============================] - 0s 808us/step - loss: 0.3331 +Epoch 399/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3158 40/40 [==============================] - 0s 897us/step - loss: 0.3453 +Epoch 400/600 + 1/40 [..............................] - ETA: 0s - loss: 0.1977 40/40 [==============================] - 0s 782us/step - loss: 0.3387 +Epoch 401/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2242 40/40 [==============================] - 0s 692us/step - loss: 0.3461 +Epoch 402/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2828 40/40 [==============================] - 0s 731us/step - loss: 0.3088 +Epoch 403/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3817 40/40 [==============================] - 0s 744us/step - loss: 0.3452 +Epoch 404/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3975 40/40 [==============================] - 0s 603us/step - loss: 0.3295 +Epoch 405/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2534 40/40 [==============================] - 0s 641us/step - loss: 0.3237 +Epoch 406/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3743 40/40 [==============================] - 0s 538us/step - loss: 0.3393 +Epoch 407/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3403 40/40 [==============================] - 0s 603us/step - loss: 0.3251 +Epoch 408/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2007 40/40 [==============================] - 0s 564us/step - loss: 0.3071 +Epoch 409/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2724 40/40 [==============================] - 0s 577us/step - loss: 0.3250 +Epoch 410/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2269 40/40 [==============================] - 0s 564us/step - loss: 0.3432 +Epoch 411/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5724 40/40 [==============================] - 0s 564us/step - loss: 0.3576 +Epoch 412/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2730 40/40 [==============================] - 0s 551us/step - loss: 0.3316 +Epoch 413/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2527 40/40 [==============================] - 0s 564us/step - loss: 0.3378 +Epoch 414/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2486 40/40 [==============================] - 0s 603us/step - loss: 0.3066 +Epoch 415/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2877 40/40 [==============================] - 0s 591us/step - loss: 0.3344 +Epoch 416/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4265 40/40 [==============================] - 0s 590us/step - loss: 0.3459 +Epoch 417/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3338 40/40 [==============================] - 0s 538us/step - loss: 0.3318 +Epoch 418/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2788 40/40 [==============================] - 0s 604us/step - loss: 0.3247 +Epoch 419/600 + 1/40 [..............................] - ETA: 0s - loss: 0.1303 40/40 [==============================] - 0s 538us/step - loss: 0.3310 +Epoch 420/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3400 40/40 [==============================] - 0s 577us/step - loss: 0.3323 +Epoch 421/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2921 40/40 [==============================] - 0s 552us/step - loss: 0.3067 +Epoch 422/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5679 40/40 [==============================] - 0s 564us/step - loss: 0.3628 +Epoch 423/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3226 40/40 [==============================] - 0s 564us/step - loss: 0.3357 +Epoch 424/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3059 40/40 [==============================] - 0s 552us/step - loss: 0.3223 +Epoch 425/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3698 40/40 [==============================] - 0s 564us/step - loss: 0.3426 +Epoch 426/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2914 40/40 [==============================] - 0s 577us/step - loss: 0.3287 +Epoch 427/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3761 40/40 [==============================] - 0s 590us/step - loss: 0.3466 +Epoch 428/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4018 40/40 [==============================] - 0s 538us/step - loss: 0.3545 +Epoch 429/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2324 40/40 [==============================] - 0s 564us/step - loss: 0.3236 +Epoch 430/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4002 40/40 [==============================] - 0s 564us/step - loss: 0.3353 +Epoch 431/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2359 40/40 [==============================] - 0s 616us/step - loss: 0.3263 +Epoch 432/600 + 1/40 [..............................] - ETA: 1s - loss: 0.1568 40/40 [==============================] - 0s 872us/step - loss: 0.3241 +Epoch 433/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2291 40/40 [==============================] - 0s 615us/step - loss: 0.3360 +Epoch 434/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2725 40/40 [==============================] - 0s 552us/step - loss: 0.3418 +Epoch 435/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3328 40/40 [==============================] - 0s 564us/step - loss: 0.3390 +Epoch 436/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3294 40/40 [==============================] - 0s 590us/step - loss: 0.3263 +Epoch 437/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4121 40/40 [==============================] - 0s 552us/step - loss: 0.3318 +Epoch 438/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3038 40/40 [==============================] - 0s 564us/step - loss: 0.3101 +Epoch 439/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3000 40/40 [==============================] - 0s 565us/step - loss: 0.3325 +Epoch 440/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3481 40/40 [==============================] - 0s 577us/step - loss: 0.3308 +Epoch 441/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2573 40/40 [==============================] - 0s 577us/step - loss: 0.3279 +Epoch 442/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3419 40/40 [==============================] - 0s 578us/step - loss: 0.3452 +Epoch 443/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2489 40/40 [==============================] - 0s 564us/step - loss: 0.3198 +Epoch 444/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3112 40/40 [==============================] - 0s 577us/step - loss: 0.3325 +Epoch 445/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3686 40/40 [==============================] - 0s 577us/step - loss: 0.3352 +Epoch 446/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4347 40/40 [==============================] - 0s 615us/step - loss: 0.3188 +Epoch 447/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2023 40/40 [==============================] - 0s 564us/step - loss: 0.3315 +Epoch 448/600 + 1/40 [..............................] - ETA: 0s - loss: 0.1727 40/40 [==============================] - 0s 577us/step - loss: 0.3202 +Epoch 449/600 + 1/40 [..............................] - ETA: 0s - loss: 0.7075 40/40 [==============================] - 0s 577us/step - loss: 0.3575 +Epoch 450/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2700 40/40 [==============================] - 0s 590us/step - loss: 0.3182 +Epoch 451/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2717 40/40 [==============================] - 0s 564us/step - loss: 0.3340 +Epoch 452/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2967 40/40 [==============================] - 0s 564us/step - loss: 0.3232 +Epoch 453/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2798 40/40 [==============================] - 0s 552us/step - loss: 0.3459 +Epoch 454/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2366 40/40 [==============================] - 0s 539us/step - loss: 0.3234 +Epoch 455/600 + 1/40 [..............................] - ETA: 0s - loss: 0.1952 40/40 [==============================] - 0s 590us/step - loss: 0.3101 +Epoch 456/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3488 40/40 [==============================] - 0s 552us/step - loss: 0.3328 +Epoch 457/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4614 40/40 [==============================] - 0s 590us/step - loss: 0.3269 +Epoch 458/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3957 40/40 [==============================] - 0s 564us/step - loss: 0.3533 +Epoch 459/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3937 40/40 [==============================] - 0s 577us/step - loss: 0.3260 +Epoch 460/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2880 40/40 [==============================] - 0s 590us/step - loss: 0.3324 +Epoch 461/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2012 40/40 [==============================] - 0s 564us/step - loss: 0.3239 +Epoch 462/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3346 40/40 [==============================] - 0s 565us/step - loss: 0.3179 +Epoch 463/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2780 40/40 [==============================] - 0s 564us/step - loss: 0.3469 +Epoch 464/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3059 40/40 [==============================] - 0s 604us/step - loss: 0.3467 +Epoch 465/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4288 40/40 [==============================] - 0s 538us/step - loss: 0.3248 +Epoch 466/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3469 40/40 [==============================] - 0s 615us/step - loss: 0.3263 +Epoch 467/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2252 40/40 [==============================] - 0s 552us/step - loss: 0.3130 +Epoch 468/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5549 40/40 [==============================] - 0s 615us/step - loss: 0.3366 +Epoch 469/600 + 1/40 [..............................] - ETA: 0s - loss: 0.6838 40/40 [==============================] - 0s 577us/step - loss: 0.3767 +Epoch 470/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2655 40/40 [==============================] - 0s 615us/step - loss: 0.3374 +Epoch 471/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2393 40/40 [==============================] - 0s 564us/step - loss: 0.3179 +Epoch 472/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3122 40/40 [==============================] - 0s 577us/step - loss: 0.3484 +Epoch 473/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4359 40/40 [==============================] - 0s 564us/step - loss: 0.3312 +Epoch 474/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3330 40/40 [==============================] - 0s 577us/step - loss: 0.3346 +Epoch 475/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4489 40/40 [==============================] - 0s 564us/step - loss: 0.3233 +Epoch 476/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3915 40/40 [==============================] - 0s 577us/step - loss: 0.3249 +Epoch 477/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3845 40/40 [==============================] - 0s 565us/step - loss: 0.3480 +Epoch 478/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3780 40/40 [==============================] - 0s 552us/step - loss: 0.3518 +Epoch 479/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4271 40/40 [==============================] - 0s 590us/step - loss: 0.3456 +Epoch 480/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4063 40/40 [==============================] - 0s 538us/step - loss: 0.3333 +Epoch 481/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4536 40/40 [==============================] - 0s 603us/step - loss: 0.3604 +Epoch 482/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3324 40/40 [==============================] - 0s 564us/step - loss: 0.3024 +Epoch 483/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4737 40/40 [==============================] - 0s 603us/step - loss: 0.3132 +Epoch 484/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3897 40/40 [==============================] - 0s 564us/step - loss: 0.3437 +Epoch 485/600 + 1/40 [..............................] - ETA: 0s - loss: 0.1952 40/40 [==============================] - 0s 564us/step - loss: 0.3302 +Epoch 486/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3192 40/40 [==============================] - 0s 603us/step - loss: 0.3450 +Epoch 487/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3254 40/40 [==============================] - 0s 564us/step - loss: 0.3470 +Epoch 488/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3477 40/40 [==============================] - 0s 603us/step - loss: 0.3194 +Epoch 489/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3204 40/40 [==============================] - 0s 564us/step - loss: 0.3128 +Epoch 490/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3827 40/40 [==============================] - 0s 590us/step - loss: 0.3193 +Epoch 491/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2699 40/40 [==============================] - 0s 565us/step - loss: 0.3218 +Epoch 492/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3259 40/40 [==============================] - 0s 590us/step - loss: 0.3254 +Epoch 493/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4149 40/40 [==============================] - 0s 564us/step - loss: 0.3282 +Epoch 494/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3194 40/40 [==============================] - 0s 564us/step - loss: 0.3206 +Epoch 495/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2927 40/40 [==============================] - 0s 564us/step - loss: 0.3264 +Epoch 496/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3298 40/40 [==============================] - 0s 577us/step - loss: 0.3477 +Epoch 497/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3906 40/40 [==============================] - 0s 538us/step - loss: 0.3273 +Epoch 498/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3502 40/40 [==============================] - 0s 603us/step - loss: 0.3289 +Epoch 499/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5215 40/40 [==============================] - 0s 538us/step - loss: 0.3530 +Epoch 500/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3746 40/40 [==============================] - 0s 564us/step - loss: 0.3417 +Epoch 501/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2148 40/40 [==============================] - 0s 552us/step - loss: 0.3157 +Epoch 502/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3532 40/40 [==============================] - 0s 564us/step - loss: 0.3301 +Epoch 503/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3483 40/40 [==============================] - 0s 564us/step - loss: 0.3294 +Epoch 504/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3279 40/40 [==============================] - 0s 552us/step - loss: 0.3353 +Epoch 505/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3172 40/40 [==============================] - 0s 564us/step - loss: 0.3147 +Epoch 506/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2801 40/40 [==============================] - 0s 564us/step - loss: 0.3169 +Epoch 507/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2955 40/40 [==============================] - 0s 590us/step - loss: 0.3353 +Epoch 508/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2051 40/40 [==============================] - 0s 564us/step - loss: 0.3291 +Epoch 509/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2842 40/40 [==============================] - 0s 564us/step - loss: 0.3169 +Epoch 510/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3697 40/40 [==============================] - 0s 564us/step - loss: 0.3427 +Epoch 511/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2206 40/40 [==============================] - 0s 565us/step - loss: 0.3118 +Epoch 512/600 + 1/40 [..............................] - ETA: 0s - loss: 0.1985 40/40 [==============================] - 0s 577us/step - loss: 0.3112 +Epoch 513/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3648 40/40 [==============================] - 0s 538us/step - loss: 0.3283 +Epoch 514/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2989 40/40 [==============================] - 0s 577us/step - loss: 0.3241 +Epoch 515/600 + 1/40 [..............................] - ETA: 0s - loss: 0.1960 40/40 [==============================] - 0s 538us/step - loss: 0.3146 +Epoch 516/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2431 40/40 [==============================] - 0s 590us/step - loss: 0.3327 +Epoch 517/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2895 40/40 [==============================] - 0s 552us/step - loss: 0.3250 +Epoch 518/600 + 1/40 [..............................] - ETA: 0s - loss: 0.6090 40/40 [==============================] - 0s 564us/step - loss: 0.3404 +Epoch 519/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3296 40/40 [==============================] - 0s 578us/step - loss: 0.3109 +Epoch 520/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3475 40/40 [==============================] - 0s 552us/step - loss: 0.3368 +Epoch 521/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2644 40/40 [==============================] - 0s 564us/step - loss: 0.3280 +Epoch 522/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2093 40/40 [==============================] - 0s 552us/step - loss: 0.3008 +Epoch 523/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4348 40/40 [==============================] - 0s 590us/step - loss: 0.3111 +Epoch 524/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2513 40/40 [==============================] - 0s 564us/step - loss: 0.3060 +Epoch 525/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3530 40/40 [==============================] - 0s 577us/step - loss: 0.3292 +Epoch 526/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2255 40/40 [==============================] - 0s 538us/step - loss: 0.3138 +Epoch 527/600 + 1/40 [..............................] - ETA: 0s - loss: 0.1820 40/40 [==============================] - 0s 552us/step - loss: 0.3120 +Epoch 528/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3882 40/40 [==============================] - 0s 564us/step - loss: 0.3459 +Epoch 529/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2871 40/40 [==============================] - 0s 552us/step - loss: 0.3164 +Epoch 530/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3902 40/40 [==============================] - 0s 564us/step - loss: 0.3344 +Epoch 531/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4977 40/40 [==============================] - 0s 590us/step - loss: 0.3370 +Epoch 532/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3452 40/40 [==============================] - 0s 620us/step - loss: 0.3437 +Epoch 533/600 + 1/40 [..............................] - ETA: 0s - loss: 0.1611 40/40 [==============================] - 0s 552us/step - loss: 0.3137 +Epoch 534/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3184 40/40 [==============================] - 0s 577us/step - loss: 0.3050 +Epoch 535/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3581 40/40 [==============================] - 0s 552us/step - loss: 0.3159 +Epoch 536/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3620 40/40 [==============================] - 0s 564us/step - loss: 0.3076 +Epoch 537/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4282 40/40 [==============================] - 0s 577us/step - loss: 0.3158 +Epoch 538/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2706 40/40 [==============================] - 0s 564us/step - loss: 0.3243 +Epoch 539/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4429 40/40 [==============================] - 0s 590us/step - loss: 0.3067 +Epoch 540/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3584 40/40 [==============================] - 0s 577us/step - loss: 0.3251 +Epoch 541/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3631 40/40 [==============================] - 0s 590us/step - loss: 0.3029 +Epoch 542/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2830 40/40 [==============================] - 0s 538us/step - loss: 0.2961 +Epoch 543/600 + 1/40 [..............................] - ETA: 0s - loss: 0.5376 40/40 [==============================] - 0s 603us/step - loss: 0.3484 +Epoch 544/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4337 40/40 [==============================] - 0s 538us/step - loss: 0.3123 +Epoch 545/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3004 40/40 [==============================] - 0s 564us/step - loss: 0.3376 +Epoch 546/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3009 40/40 [==============================] - 0s 552us/step - loss: 0.3267 +Epoch 547/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2411 40/40 [==============================] - 0s 564us/step - loss: 0.3157 +Epoch 548/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2630 40/40 [==============================] - 0s 577us/step - loss: 0.3285 +Epoch 549/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3516 40/40 [==============================] - 0s 564us/step - loss: 0.3384 +Epoch 550/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2020 40/40 [==============================] - 0s 590us/step - loss: 0.3135 +Epoch 551/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3946 40/40 [==============================] - 0s 577us/step - loss: 0.3401 +Epoch 552/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4100 40/40 [==============================] - 0s 590us/step - loss: 0.3176 +Epoch 553/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2512 40/40 [==============================] - 0s 564us/step - loss: 0.3020 +Epoch 554/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3068 40/40 [==============================] - 0s 615us/step - loss: 0.3280 +Epoch 555/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2709 40/40 [==============================] - 0s 567us/step - loss: 0.3395 +Epoch 556/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2740 40/40 [==============================] - 0s 590us/step - loss: 0.3119 +Epoch 557/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4142 40/40 [==============================] - 0s 538us/step - loss: 0.3177 +Epoch 558/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3044 40/40 [==============================] - 0s 564us/step - loss: 0.3130 +Epoch 559/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4284 40/40 [==============================] - 0s 577us/step - loss: 0.3178 +Epoch 560/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2083 40/40 [==============================] - 0s 564us/step - loss: 0.3211 +Epoch 561/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3825 40/40 [==============================] - 0s 603us/step - loss: 0.3112 +Epoch 562/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2951 40/40 [==============================] - 0s 564us/step - loss: 0.3118 +Epoch 563/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3614 40/40 [==============================] - 0s 590us/step - loss: 0.3047 +Epoch 564/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3828 40/40 [==============================] - 0s 577us/step - loss: 0.3441 +Epoch 565/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2772 40/40 [==============================] - 0s 680us/step - loss: 0.3237 +Epoch 566/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3168 40/40 [==============================] - 0s 564us/step - loss: 0.3068 +Epoch 567/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3627 40/40 [==============================] - 0s 590us/step - loss: 0.3157 +Epoch 568/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3390 40/40 [==============================] - 0s 564us/step - loss: 0.3101 +Epoch 569/600 + 1/40 [..............................] - ETA: 0s - loss: 0.1421 40/40 [==============================] - 0s 565us/step - loss: 0.3113 +Epoch 570/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3426 40/40 [==============================] - 0s 564us/step - loss: 0.3247 +Epoch 571/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4788 40/40 [==============================] - 0s 564us/step - loss: 0.3412 +Epoch 572/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2055 40/40 [==============================] - 0s 590us/step - loss: 0.2967 +Epoch 573/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2277 40/40 [==============================] - 0s 577us/step - loss: 0.3120 +Epoch 574/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2641 40/40 [==============================] - 0s 590us/step - loss: 0.3102 +Epoch 575/600 + 1/40 [..............................] - ETA: 0s - loss: 0.1898 40/40 [==============================] - 0s 577us/step - loss: 0.3040 +Epoch 576/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2764 40/40 [==============================] - 0s 590us/step - loss: 0.3139 +Epoch 577/600 + 1/40 [..............................] - ETA: 0s - loss: 0.1110 40/40 [==============================] - 0s 552us/step - loss: 0.3178 +Epoch 578/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3087 35/40 [=========================>....] - ETA: 0s - loss: 0.3172 40/40 [==============================] - 0s 1ms/step - loss: 0.3169 +Epoch 579/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3673 40/40 [==============================] - 0s 949us/step - loss: 0.3227 +Epoch 580/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2385 40/40 [==============================] - 0s 564us/step - loss: 0.2871 +Epoch 581/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2050 40/40 [==============================] - 0s 552us/step - loss: 0.3079 +Epoch 582/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2056 40/40 [==============================] - 0s 564us/step - loss: 0.2965 +Epoch 583/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3313 40/40 [==============================] - 0s 590us/step - loss: 0.3034 +Epoch 584/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2285 40/40 [==============================] - 0s 564us/step - loss: 0.3018 +Epoch 585/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2746 40/40 [==============================] - 0s 590us/step - loss: 0.3289 +Epoch 586/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2929 40/40 [==============================] - 0s 564us/step - loss: 0.3206 +Epoch 587/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3201 40/40 [==============================] - 0s 590us/step - loss: 0.3099 +Epoch 588/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4183 40/40 [==============================] - 0s 538us/step - loss: 0.3228 +Epoch 589/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3856 40/40 [==============================] - 0s 590us/step - loss: 0.3157 +Epoch 590/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4816 40/40 [==============================] - 0s 564us/step - loss: 0.3322 +Epoch 591/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4392 40/40 [==============================] - 0s 577us/step - loss: 0.3501 +Epoch 592/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2773 40/40 [==============================] - 0s 538us/step - loss: 0.3158 +Epoch 593/600 + 1/40 [..............................] - ETA: 0s - loss: 0.2645 40/40 [==============================] - 0s 565us/step - loss: 0.3278 +Epoch 594/600 + 1/40 [..............................] - ETA: 0s - loss: 0.4382 40/40 [==============================] - 0s 577us/step - loss: 0.3361 +Epoch 595/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3165 40/40 [==============================] - 0s 538us/step - loss: 0.3170 +Epoch 596/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3251 40/40 [==============================] - 0s 590us/step - loss: 0.3398 +Epoch 597/600 + 1/40 [..............................] - ETA: 0s - loss: 0.3275 40/40 [==============================] - 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 0000000000000000000000000000000000000000..ddbee7eb5e8a0aca350fd233d12621261d2479ab GIT binary patch literal 88381 zcmeHwZEzgPbr=Q6Mn1R5l08ID}GVkwbaWmPO!>~d9H6)SNP$5l=$Ka}#1 zBv!c`S5lQ!@+W!S^VKu+W_EV5q;R@Dm5AAy*RQ+Zd;R+L>-V~23jOxCM#(oO>EDYL|8Euy;ds zpHmd_84_J9mzr0%wkR=yl?^&hM()AugtEaV$XI=^wY%4XABhD5A4TE9aWbpUD8rGF z(XrV0#F5FV89IAnE^(PmY?WH2;JEw$)av(+fqcGwslx%tY+uN9`q5&a4Nz4pq- zNuG>etJj(>cGRlIXzNjiXgrZ>^q-f^qFy@qIR=Lr%DpxoU$H>Ud`mJ5^IvKfL+I#?9 z9}`^X>`N*)ofJ7jl$$gH4Y{bKl!Q&6#8EO*dQ@(TZ)`X|M6QvE+m+I$b{}fh8eRrD zg(-22j5hC=b~UR1VIzg%xI$LR)VfyM@{>^3SwgRqk#()IM<+>aTPwBpK)gBArpZKU zvsG>jTJblDQx>laGvuf`smtd0)C`E_1gVqpbs%oN0o(w28Pn+wRG%hCbO9^YN>#y! zV`N(Nq*$tL6`PgvCV$IjNK}Vws$*g_H4|}SJW*09H(M9^pt{8A%DGY@V|PmJ9&4lB z*7gyo4P<1q1#}wUtk<^6T!!L=3pp2S{#WC4a|~yj{p1yL^v?ZKV@un5sa(-GDY!1V zS89r9pwqbEZ(}PS0Rbbmy=oDN)YxjqBQSts+eV>yl>Bpr%-v~~TH5wr<#wq70~A`K zZCxu>Ds%#btg+KnBOB!!@ZQiY>c|GDn8YmMubs36u@WC$Z=vDabYy$4wg~`Z(BJLy zj-_jc=}>}^Bl=qyM)g+R@ok<=YLB$dJrIT>XPNwwb8eL!JOplme%GYfF2PduB-D)Y?urIsS=}2tnLIcv6(6k>EZHUa-%NS=0fa*8@?Ayu*<*Sg5Hk@!baNiG$|92k;kJWT^F zFEv1JB8+;XSI4K%9=Zs#p3aD|!iebJyt8{psDvLTm@{^5p}HoOPBKr&V#KW0(Wysd zN>o!!_lMO{RV5&@iCb&MclaZ>FYCs%=!iZ3V4dTdUbZ$fp`;G|h5fRlPNa89ay;-uos zNxcS}llt#aT{JkUmk8jb;^gEu8Na$!sxFpc;^|t?jB{MNp5aQCIfvl{wNaBIIc?Pw zsy}wwFiL%#yhSEN1@|;qHKe=liXe;Kl~c~HOi~#+*(7JBxLh|KTxai+(N?`x>c!S_D2Nlz{za*dmVBI?6!=5+LN61# z;hXinTI-;U@ittbe3kVU{Q8Xy9Q&FvHc z!wl|&2q?iKU{>T30rPdJ?#m)z77P#pmpzUv{`S*U{B2zEx4Z4VsleI+tPiL7d+EMw z>@OrcEB-d7_``MEqxjnaEDx#pd+GH76o1<_>a7VV90lZ2Zx;<l!2l5msrY;8yGsPRQT%QZu(WqL8ptAG7Yz`Bu!_GIGPpz_oZ@$j zfT6#`bzc?%vtWP-xD@{pefJIaGx;9ee@hq}npEG{OiV874)nsc+iw(7VHOe5BY}f=#16TwFQvobuf~jOOHbTeiyRCAy{I=F0bFoo63tObHPYHX@#kR5e+$1Ms zWAu1K+u5tYtGD${%u2o4)S7?-Hjr${$ykhzgPB}v7E8NjG8G%Agl}Z)+j|5Y4l&rd z((Pyx14qBujfR?!_|-h=U-Oi+=A&}WyryZXrWvay>Q~dOe@(}nH63@?bV90W&Z;Ty zSJO%VnwYbudAX+FP=I8o=m_@=LibM7G2OKW&u5Hhm5j&E(ox~iAv3WBI_YqSuqcpU zsm2TNFu@-_1P{~v;luDS!ykSG9!~Iw7vW)!KYRoppj11)3J*}K9lr_>P^ukYg9j+p zj$eZZDAkUC6ds^dJAR!c$tW+Efc$2HTaZ8yo94*525-erM5%g>2Au4`yjE zh-Fc{V)Y(?6}Al>yc;6!H-ZN~qjo;_To4Z~NIbac<-sMH2gy!62&*4HNk8GClWRK( z<$+~61yJivy5Yg?*vCP+U>GF=EubVY6WmXpZrlS77wEcW6 z6~u+K#0AyMg^bLFY$q;+omXC=FL~tE-rZrBER#TNLIu(MHTtRtlf1FQp0{!7lhpyR zsUB=<5Vlw8E1tGVy9z96H%-i!LAWrvMV$9cwQ)Ko-XPpV4q9r&&-BllekdM8bPMKv+nWJEEI(qaDeeCIiWcHgAXqBy_^Pp~tE?&8Hd*jCI zH$HiNy?E!fTN{fu7pp;>dr0>@m3#aSRR+O!Ub|lGT=!b>yYwAT#qwIunzZnKTc3OE z_hb6dQ@uoV%g>7T+?@7$BYCHuTN4G|bL;aH>bWtS;5;{{n%;UIQqtSKN_zXilHNx7 zo$4g%ffaY+wq@?3L?QG+!tTL2*fyet^SU*qB6#?6}*3fF3 zTG4VD6(2TAySvb0HJ8fd$SpF}gwX3o(TqxV3PXrk)2Jgriu~Jga?&TH8A6tPneA!? z>llg3I)rnw5YdoEE#~Zs#JieUtg(;5=xsG*2-`to!Es@%Q>2v)fJQE{4zWNiWH=4; zk5OU%Q6MaA2n7ola=^mx&C6ArY^mXqv^S8{OM)987MbHP7Op zavROPnDG7XjMJQqP@KBIKKY!kEzgqE>U>lY|BdT^rdU@QvI_HAA4$cnA<1M|d-%y!Swl^JY1ZHN*57vEw1|38FETxQQZna{ynT>o#bMDe*GMI1`}&AGJb$MQ?cuqLah@!;ubfzeLXd?iRFj>WvacN1 zlNMd?+2YueeBdb5~8Hg+0qW=>1+b?pG)KNw8cEHd6C}P3vtf7#XI86gz{n`T!Iex9Vk| zFtQ~@&Lo>Qsw(KIRXvd#vP*gXCHo?5D_RM+))S-rV?j#AgdWb_#kpv(^dKZ)s!EDsgJO!SA0eV#fNC&R&0oV zjD!^URkA>i758ANTWs!Xo8|4Yna>xa#uy|2XPW%hFu5+PyQcQ(J+5K6J`;Y$FdA=Z zWhLv-ct;_dTdb+orIqD8s5kjVJ_Rpk$fORDE&@zG<9)RxzfuJh$7B^0uT}sTq83jJ z+>1VIuYKjLQFliO)enMwHbR1H@i&G{6(`e(*+25BwY)%DhI*^g$nQnDsEs&>1Gf z41Mu*7{iQ`gd5H_~>d2!nd*~ zYX!XMwgN7b=e<_IglPr1|Ee!`P+>G!!>MZ>M-}a)0c{+num&ap99?1jD00(6`k8kARGmM$(IEk6QB%U# zOZ)4+`0>rD-)udzTW&w5?MKyq%-E0F9}4IEO+NeFSbw=s2B><{cVC5l0oP*-K1#>d zU-7#>ActG)sJ^7|onQMu!v8W#elPS0hjl{6UM1+~r6_Rji#br7L-i>RbFf+bRDdrn zO=DhkgPC2h$8XAh9E|nu7n@7@!B`hQ2jO?0%d%)h-aLoe?9BuT!E`i+Ei4zA~?WMx(>` z6+J5wV$1xB>%LR~2u7fGLZIRZ*e@w0sD++vgHS>cka>a3BoMS7KqK}y74vo#odnd( zkuU?5&IOe2IrU&ch5Ni@#OxOp63A)~slttdfb{N{t za!;g$4V{}Nyekvu0JMWsN*qmPZ<&|Jhzqauv?32CuF5`B~B{TBXJ6|QJ= zwTDSJ???l{YTSW`z^bLKpsTJy;G_9HyfX;WX~GN`1m3e#?Lpwv3O@f>XFRwD0W+z{ zJA@AdAFMqO1H~Q&CTeLI_)W4NQX0dcqdgHY44g-?+QY!F4bm{MKs>|1?2~sGSY`S( z2PpP1uyEVMfS-y07a!{LfH4d#u-<0^#U2KF4eaZ~b~c@~R53(L2XcwlX=4N5XO=x> zd`9gtc2@stt0EUY&F}zABe}nu2rO#20gU(pNWVr~(Dm#I$E?{T>XdMJ&{TsD2b(Z7 z(7;g(frcUtvLe;hPV)%uFwaN-uS5MqH<*Kztl<1jAR&4%;2`At2zBHLG<^FX2+Wna1E2J}^L`^rTG zHZ)p4$;Z(82swjz{*WE>OxxYcWPmAzEORf0Z5R8;aJsXbjE1(i7Qc>wmMcEcuDPRU zvuJ?_v-{M+epex3WzIwKt_O60#pGHoUkcqS_AlV{c~9?*QDfUs&v-y|xt5G6Nq_>! z-T@fF{F};t7EaFaG*U9Oyge{F*}KKHz&Ab7I@up6B(yT{2uAlhJ76#(i}Pgowy}Sy zkdy8%TC==0AkVo$VDNdCEt0(J0%GCm*HB$m=L1^HMLoPW_i&|$DKTKcx>ownchNHT zuNA`F1h;1;d(e8gVi8;#wvw<}T)`*Jo(Jx#dMc>F>~A9~ADSu+UaThv9=@xXVmIo= z2e8ky>k$=+rpDQoovfgM0gN~numSATHuha?0Gq(p06ve%Q>YD-8hi*l939>vY?bbP z23F7^Y`8!EFYf;EiaP2Exp>z-Bz)Eq?1C2(HTqf7188e)7o*rE3^p`ci?kuongZnl zJ>0&O_0R?`4QrpPx5KVcXvj5|`eqliIt_1{s2kx8I2zgvMO*79NJwk_K+)Fv2p!T| zAIQR!i4E<`0fYSX7DxEN2P`@iu~-HN3?9CKDdkBE)vDu2LH(8EqyUjkli`@0S$P@2g#;%Br(*WySb)A~A+0V zKHLZYt#%Uw6mCthU>-B7_Hy`FSI3AiggDC6*QwF%8NwfArv|c*`h$0BtUmRWSJ%Gf zp}RF<^+`H4Ru839Jd*15b2|;E68> z!rUs3;+Y3o(nbBMH}kGD zxGWDllw*)3P05(wkdqZs4cDbSz zcN^Mv`B6MdpCPA9&1QM0CSAy_ZwWup8a1r~QD7KI+Q_)M2g%U@a-KZn!J--<>7s=R zuJ`tUWh}4&Tv;o@ClJ??1!mw{Ag4SP=8C1QQngraX$@#O1Pyy2mUW1GTB}s#K4=Uk zFTwB_JB&yxI?R@~S$Yg0a1xoPs&q<+sc5A}tz6qFHcBm6-O|(Kq!%__Y}H#O&Jy&q z3iq(@)mrcw&N1_r&X}#?=h*0EELH&+&QkLNXJuecOaXeCT=If0$)F~)1vuIagZyUL zK`?HE6FRUew;IK5FvSG7aHGH$cO-hWedwVYY|=3cyc`sxhnhy|!NIX+sHzh@7`KCm z7Cn4%JGiJPVHE+Gffgu3S6XnmBHSt&kA6;3_Lb?YLJ!!M_r5~iuZrn?W!C#Lg}%jM zRTMUZzRjXK~Ym$t%OO-v1{@Uc)S0`gpIs(QcTg&NZgg-2|?iU|w<(>Pj=H=9) zuCo@eT;14Mzp?hl#`QakZ(d!$adqvr>%}*(zV^oTwJchW52>J1SZ(PZYfCToQk&Xi zZEDBbF4cEiZ-eSHUpK&N5OC7QEat)>Sk;Dg%!xr|vLG2SLzQ;R zi&d@FC~r0wQ;TA%?7EbgL4!)IqatRC=B?WsH(tN-$?NOIJFnf^ShV|64Z?XF#iPOO!txc7z;Yo$FDdc%pe(i|qeVZ>T#D zSqsEr5Lh|p?3@kYCWHm#wi|woOu05--XizSAkQcLH+hka33q9e!v2oR6!G7<{zv{d zs!m80VmtQHcGBs8vsU*Dy1~>eq}<(&5@mz?W|MJGzv0dY5zH=~o5%ivLOdoq^}J!h z%Xv0)!!Z1Pxp2(Wnqe{|+ii+Uy)9u62r*F?)4`NT_dp5QwzSc+eT8@})pRIo$es%} zYvVi!J&s|maZp4Jrigk#im2>YF^Z@NMLIibB&w+Wri$vIN+y^pnFCTK!w**V%1H*H zN+-XRM3YRvX_9f!BpXbV>;Y+##U&++(8Mb#Za17nm2AJMl66pJDVQot2c*gpE-6b0 zRlJho^g2p3S?V`UmK-$61=A$wLzD4<`9{{VIlhzS9X&aOCV@^?i6FV&2{Nu?N;c;p z$Z{}2mVF2kGy%&5S!Tb25o8%5NC%&?M3Uv+Nur=6S$2>lA54<`0ZEd_Ns?Gw1vgGs5R!OJHOnUrI|dR(R{Bkm6;>k?w(XOWNOH_;xu$zD zT_+tCux}^?a~va73Astaj!Er52z?-w3Grw<2_ze|7=e1RXdMJfb7hOP1G8!UcZOt| zr29^jw38;XNsG~>7n{~W6V-<%m{p6=#Mlm#X>uTQ7L^m#NfX(i#c0xtMeCqRhW!&% zPB5D`>>i*@p#vGWD1|ak3d!azMxkEpTL*=*?CU6nFbg-_#-~i51DUxfeX>sa$c8RP zpI$6o2Yr^{UYSM*GJ8=PEjei<8@?Eg{4C!fL(f5@oX;r3Y+q!QpM$@uMer5%yD~lK(=Lt#Zdc=*(TW?|{vEUKP{q81gcOzQtix6gGpt&7yCY z(6>4C?K1i{kG@^OI*c|KCI^HJpboLOI0m%Cz-WZ#8SEtrxr9OHu$Rl&%RKgSg^k|j za^w~|W6w95JmJ}89U;SoAyu}I;OxWyJtB*tW8q`Dzf^m{#Rl>?kVjM=&2*HIl9x-I zbHoT!+uN$ztJmaXGO3>;VrIvDGMTY7ppGYC~38PF>FPGq0pVkZ1+TAN+IMOp7uya2k;8T;%`Q`B!m;=j1qm zMOFw73OOhaP%8rm2X{9kUF-t4m2nadw~=vz1H&;UM!T(aEI|i1F~%w6P05gYa5@UB zps=bBtW9Lm0uh?-1DYn6TF|xo z+UA4Zdb!qWvY%JTu{*6&tGv0c?P!l)+N)IHN~O*F6n*Q6D|RlIl76eCIuAJwn_9vB{W~jzZOTX(g`#CdU9<7!mo$cMz8Fa8Z9+y;ARyP z71>Y_{febUg{)@YtcI>li)u)*rB!zqMP1`o75pO3u{&Bt+iX$eFFTD9-SY6VDbYIn z_q5Sk>y4ZE9oMRGJdWN3)*|E%B;M3^UIh`L(zAoR?5GYNRO3xL93S@My9(i0c0KHq zgw*z`eCg5HGQ;cripl}Zkt8*#JiZoqO&dDQiVx?iwan;I5T*%?a+`tZ*h-T`HfBqttiD;+C_?N@-9?cXO|5Ah8K>tKiFcCZ%g@fEcUwUCVSf;r9 zX2=ERMD~~|7KjsTr8!Lc*UCX|pf4>0v+jE2cp%Q6I39>GI5!Yt29T+c{SI8cY`kys zQy33pRvfVnc-W zldy0;5*FS+!kkt6`$k+itpyn3>Tu!o_ldAj{ty<@7lOc{eh`a@!9Ebyo&SS%^nF+m zzJ3qZrO$(POCi*6fVDr^r-8L6$e)4L zU{MHf6Cx8qehlXDVYnALXaqnPdBA-AtE*T+Psrk?1=Gs~G!eO1Xb-C;WclQS+KhJ6M zR>B%+mbHu>c0Il2+*NjTX~+rJRXOEY%8>D>M;hdTd#A9-5 zCJ+zj6b-~!OLbvzIc@7IYyJZ8V<0`c&E#RKt}{W=+lhf5&y=O+2f zDEU2wB;~!)ruOMQe$-s4;<;ilm0CHJcLRN6a5qpN?gqNa?*_WD{xZ4VSseH&ISs9~ z*Qmi6mbI;Nt6Z;ffvGo}8o%FgWhFbfK8(fAe$3d9S=il;Y```&9Mh#nm1E++yGPL_Lbuh-1GWg#r2+jULp7wI_1Q`Iy5=y zzl;})A33r^;qerBdzxfS|3Hnu%v3k0(EW;I`m( zt+L0ysGv?l%0CuLT+u^J8pN`}7S-HcT$8H$~HmDwQ`GtoChuF^NAPEcwvPxeQ$NU zQh&H;)V&B-dTf<9TZKRQ35EQf1c`$S^cZ%qG?{=eQSs$+3c!X@urz=Tn_y`Gi=bdC zfJIC&l}v&sblf`in#_UQa~5Lb%Qb#0TG5=3n&c#SI*&KBoxKX&nD(|9md0WqP(v2f@@ma_PXl?TgCm;;Sc45(xm;&tl&9m<$HY=rOQyhbzC@duISYEEg3kwOp z5zgP*1^HWx5b&wh*wf&Z_GlL@&?e6x0MP^~D>ZiPui`jbjtBT$YGqW8uE-tlRp5Q`?1_)&KcZ`5}8TCbHJ zYYpBE2@%#Jcj02OwYLirP~>IdAo{APLT`6E{i%21E!Np4M7=gSCC&CXN;^B+mh{4; zv@{+Q?*ck^13n737HF=9JIeBJ2!ozr=k`DsaWZ67sM?;M;7y_dGZt?UWTS}m40vY< z3>WzBqjaqrT-l)1d-P8pAIO#c^5+WlY7~LneM!o4o zBZ?Yrv4*i|iy?~wE&4_DlwUl8el>7{cr^t#TF^ZirRPIW%r2&V*o_IH$){X)z$c3t zPl-=Lx6nGdnLuYdJh6Ov>Km%61MrpKj`MCM2R5V zKms!-Ag7ryn1Z>nXftFm1urB9Q?M|V22(IM_YD0yn1cDr<{emM{jgcIpAvJOwI-Bi z489@G=bx%psui1`-YdbHzo<1Db+ITjF2AxxM87+YJ4p0vvFtA#k$JV6{nlE!+bc)+ z?0OaM&UDTD<}_x0a%4vX^3;`7DxK2*%PwbEma|Lg3{0CM;adOBXIF9Crudm(5&tcN zdpn=bs@$LxUsdrHzHwY>HNTwAr7|3ow%aUM#B80`E~l2^O{v<1`Q2J6g7xq&`Cbg7 z`v@J=2M&qFCg=!Xr+}N{h@YEc(%(%n<#baVmE9CaVmBO~hgU;;9)3GYj@q6FVG9^e zhp$B4ys#FvCI`eSm~#g)nSERh=E~YM-a7dj+-(T4vTqvxJ>Z^MTW_w4pzaN64Bz7m$6`8@`RkG~dAIW4PvJpI-L{=OG;O8MR-Ygp3My8u{;h$e)mg{G2u9 z<98M!XkeS#5oph{;SQM5a zN;O`9hY9}hA$XYP4?f6xAfKu)F8azO$ zcKjMVK&f{8qwoNw+VSg&8Dek9>MIHIDjDUdQt$^5rQr{tQQ;3D$-o~#k%d2iU@38i zoPfo|<^!>TTPed1<3sS9?rIGK*Fr~#e%AJf5bx`^r#v5fhR)UMHGMPHwc$)+2|A{G zR)HbsfFXP*(_9zBCib&5YAlk;+1PnHuYb4ps2p3=;dif{JJ5lf)yeSN)8sjTO}MwR z!A;-_oKKvBUF;pLrooli`pI_ndvEa*gTyX2d4bHvZc%rDL*h7@w6@S8rUFh+=6l}c z45WT25YaIVGBX@oh{J(7Vm)SDT~6YK6Y!ni-_E}g{hL@`UjbQ?#I2*ibQY;@F~Xg; zzH9vX*mFT*b3qcDi(aw0B#TY5lh}myCiLt+0Lgf@50bG^IAicyMA!j8rvyKX=8e*X z6?l9J=k}^43Gmh8Hz*XYUO=Iw`^4{VFbaPAthnZ5&j<1Q1&QC6z5Ko+^Lw!qzr(KW zj>LLg%mKe&>np!S8ko&*^Y9^w--^v|{p=LNMX}c&)nd6077}EUZgm`IK zHRx-V94k-*nh0p!);U#R##<`hI?Nu@S+OsH3@N%O4eORk1T2$oH3$!bbD1d@0Pzwa z?iN)~7EkAXx*(7SyC9xUJ380$fp00K<&4L2bW|Mb3XjWlRGeS}af^B9+I>Y@yC;4M zE^oKp`nsj58&>Qsx6|!)*xcbxeABBhHhthXwrZ93hB|`7+GVD2l#kDa$VEjpy5M-F zcZDnToIVPd!zlF2uFiL`JI@uKfks%Cq&jOT5Qxw-jLF3+IbE0sAYo3bGZFx|FyQm~ z!Z`znuu#luT#aF=IPi#>&w=Bt9&c+(+Zj3XT4r+?C{_q zNWU6^Xx1i;d^s{iXGj!cdd2UtxAgaLx+=VS@Q^25(J2x$0<1*>7QmAS4|z_NjRKAf z(O)?LDVZqMYIT0xEW`}b$k!r6$>e_I0y+QQaKag@6b*pOCj==B6_LS}ipn z&`FyyoDUAB%t=g{_;MshhIfYuheEh>+`}Et3W~62T1f&9@@EnCdyzimhUZebbYIZq zbA3Rww31%#3z|&shk?oeMp6Hj5;i}4Um;%tq5gX=p+0R0_3Ey|~U3L3t%RrzT;Mkc0bPRz0F zek4u0vFW(wkw||nas^!6R+8N_?+u@^e|c;{aBJ}a-4DI+*XZ!{3|rifyg<(HM-pV= zz2Vcuu)(OOV(^v|(O>~P|K4z%C@C)(xLJv?q~8v&k8kzXkobGU$I%A(5UA@>2LuAP zh9!{bIp=6Ffq;Pl1ah=dKamEs9T2FOhTsI^67-dRmdl2Yfw}^Q# z@x_N4*F)hOl;iG%12sq@mw$u61POa8AV1CMM=c8VEN=a23)~ObYg6Mn1R5l08ID}GVkwbaWmPO!>~d9H6)SNP$5l=$Ka}#1 zBv!c`S5lQ!@+W!S^VKu+W_EV5q;R@Dm5AAy*RQ+Zd;R+L>-V~23jOxCM#(oO>EDYL|8Euy;ds zpHmd_84_J9mzr0%wkR=yl?^&hM()AugtEaV$XI=^wY%4XABhD5A4TE9aWbpUD8rGF z(XrV0#F5FV89IAnE^(PmY?WH2;JEw$)av(+fqcGwslx%tY+uN9`q5&a4Nz4pq- zNuG>etJj(>cGRlIXzNjiXgrZ>^q-f^qFy@qIR=Lr%DpxoU$H>Ud`mJ5^IvKfL+I#?9 z9}`^X>`N*)ofJ7jl$$gH4Y{bKl!Q&6#8EO*dQ@(TZ)`X|M6QvE+m+I$b{}fh8eRrD zg(-22j5hC=b~UR1VIzg%xI$LR)VfyM@{>^3SwgRqk#()IM<+>aTPwBpK)gBArpZKU zvsG>jTJblDQx>laGvuf`smtd0)C`E_1gVqpbs%oN0o(w28Pn+wRG%hCbO9^YN>#y! zV`N(Nq*$tL6`PgvCV$IjNK}Vws$*g_H4|}SJW*09H(M9^pt{8A%DGY@V|PmJ9&4lB z*7gyo4P<1q1#}wUtk<^6T!!L=3pp2S{#WC4a|~yj{p1yL^v?ZKV@un5sa(-GDY!1V zS89r9pwqbEZ(}PS0Rbbmy=oDN)YxjqBQSts+eV>yl>Bpr%-v~~TH5wr<#wq70~A`K zZCxu>Ds%#btg+KnBOB!!@ZQiY>c|GDn8YmMubs36u@WC$Z=vDabYy$4wg~`Z(BJLy zj-_jc=}>}^Bl=qyM)g+R@ok<=YLB$dJrIT>XPNwwb8eL!JOplme%GYfF2PduB-D)Y?urIsS=}2tnLIcv6(6k>EZHUa-%NS=0fa*8@?Ayu*<*Sg5Hk@!baNiG$|92k;kJWT^F zFEv1JB8+;XSI4K%9=Zs#p3aD|!iebJyt8{psDvLTm@{^5p}HoOPBKr&V#KW0(Wysd zN>o!!_lMO{RV5&@iCb&MclaZ>FYCs%=!iZ3V4dTdUbZ$fp`;G|h5fRlPNa89ay;-uos zNxcS}llt#aT{JkUmk8jb;^gEu8Na$!sxFpc;^|t?jB{MNp5aQCIfvl{wNaBIIc?Pw zsy}wwFiL%#yhSEN1@|;qHKe=liXe;Kl~c~HOi~#+*(7JBxLh|KTxai+(N?`x>c!S_D2Nlz{za*dmVBI?6!=5+LN61# z;hXinTI-;U@ittbe3kVU{Q8Xy9Q&FvHc z!wl|&2q?iKU{>T30rPdJ?#m)z77P#pmpzUv{`S*U{B2zEx4Z4VsleI+tPiL7d+EMw z>@OrcEB-d7_``MEqxjnaEDx#pd+GH76o1<_>a7VV90lZ2Zx;<l!2l5msrY;8yGsPRQT%QZu(WqL8ptAG7Yz`Bu!_GIGPpz_oZ@$j zfT6#`bzc?%vtWP-xD@{pefJIaGx;9ee@hq}npEG{OiV874)nsc+iw(7VHOe5BY}f=#16TwFQvobuf~jOOHbTeiyRCAy{I=F0bFoo63tObHPYHX@#kR5e+$1Ms zWAu1K+u5tYtGD${%u2o4)S7?-Hjr${$ykhzgPB}v7E8NjG8G%Agl}Z)+j|5Y4l&rd z((Pyx14qBujfR?!_|-h=U-Oi+=A&}WyryZXrWvay>Q~dOe@(}nH63@?bV90W&Z;Ty zSJO%VnwYbudAX+FP=I8o=m_@=LibM7G2OKW&u5Hhm5j&E(ox~iAv3WBI_YqSuqcpU zsm2TNFu@-_1P{~v;luDS!ykSG9!~Iw7vW)!KYRoppj11)3J*}K9lr_>P^ukYg9j+p zj$eZZDAkUC6ds^dJAR!c$tW+Efc$2HTaZ8yo94*525-erM5%g>2Au4`yjE zh-Fc{V)Y(?6}Al>yc;6!H-ZN~qjo;_To4Z~NIbac<-sMH2gy!62&*4HNk8GClWRK( z<$+~61yJivy5Yg?*vCP+U>GF=EubVY6WmXpZrlS77wEcW6 z6~u+K#0AyMg^bLFY$q;+omXC=FL~tE-rZrBER#TNLIu(MHTtRtlf1FQp0{!7lhpyR zsUB=<5Vlw8E1tGVy9z96H%-i!LAWrvMV$9cwQ)Ko-XPpV4q9r&&-BllekdM8bPMKv+nWJEEI(qaDeeCIiWcHgAXqBy_^Pp~tE?&8Hd*jCI zH$HiNy?E!fTN{fu7pp;>dr0>@m3#aSRR+O!Ub|lGT=!b>yYwAT#qwIunzZnKTc3OE z_hb6dQ@uoV%g>7T+?@7$BYCHuTN4G|bL;aH>bWtS;5;{{n%;UIQqtSKN_zXilHNx7 zo$4g%ffaY+wq@?3L?QG+!tTL2*fyet^SU*qB6#?6}*3fF3 zTG4VD6(2TAySvb0HJ8fd$SpF}gwX3o(TqxV3PXrk)2Jgriu~Jga?&TH8A6tPneA!? z>llg3I)rnw5YdoEE#~Zs#JieUtg(;5=xsG*2-`to!Es@%Q>2v)fJQE{4zWNiWH=4; zk5OU%Q6MaA2n7ola=^mx&C6ArY^mXqv^S8{OM)987MbHP7Op zavROPnDG7XjMJQqP@KBIKKY!kEzgqE>U>lY|BdT^rdU@QvI_HAA4$cnA<1M|d-%y!Swl^JY1ZHN*57vEw1|38FETxQQZna{ynT>o#bMDe*GMI1`}&AGJb$MQ?cuqLah@!;ubfzeLXd?iRFj>WvacN1 zlNMd?+2YueeBdb5~8Hg+0qW=>1+b?pG)KNw8cEHd6C}P3vtf7#XI86gz{n`T!Iex9Vk| zFtQ~@&Lo>Qsw(KIRXvd#vP*gXCHo?5D_RM+))S-rV?j#AgdWb_#kpv(^dKZ)s!EDsgJO!SA0eV#fNC&R&0oV zjD!^URkA>i758ANTWs!Xo8|4Yna>xa#uy|2XPW%hFu5+PyQcQ(J+5K6J`;Y$FdA=Z zWhLv-ct;_dTdb+orIqD8s5kjVJ_Rpk$fORDE&@zG<9)RxzfuJh$7B^0uT}sTq83jJ z+>1VIuYKjLQFliO)enMwHbR1H@i&G{6(`e(*+25BwY)%DhI*^g$nQnDsEs&>1Gf z41Mu*7{iQ`gd5H_~>d2!nd*~ zYX!XMwgN7b=e<_IglPr1|Ee!`P+>G!!>MZ>M-}a)0c{+num&ap99?1jD00(6`k8kARGmM$(IEk6QB%U# zOZ)4+`0>rD-)udzTW&w5?MKyq%-E0F9}4IEO+NeFSbw=s2B><{cVC5l0oP*-K1#>d zU-7#>ActG)sJ^7|onQMu!v8W#elPS0hjl{6UM1+~r6_Rji#br7L-i>RbFf+bRDdrn zO=DhkgPC2h$8XAh9E|nu7n@7@!B`hQ2jO?0%d%)h-aLoe?9BuT!E`i+Ei4zA~?WMx(>` z6+J5wV$1xB>%LR~2u7fGLZIRZ*e@w0sD++vgHS>cka>a3BoMS7KqK}y74vo#odnd( zkuU?5&IOe2IrU&ch5Ni@#OxOp63A)~slttdfb{N{t za!;g$4V{}Nyekvu0JMWsN*qmPZ<&|Jhzqauv?32CuF5`B~B{TBXJ6|QJ= zwTDSJ???l{YTSW`z^bLKpsTJy;G_9HyfX;WX~GN`1m3e#?Lpwv3O@f>XFRwD0W+z{ zJA@AdAFMqO1H~Q&CTeLI_)W4NQX0dcqdgHY44g-?+QY!F4bm{MKs>|1?2~sGSY`S( z2PpP1uyEVMfS-y07a!{LfH4d#u-<0^#U2KF4eaZ~b~c@~R53(L2XcwlX=4N5XO=x> zd`9gtc2@stt0EUY&F}zABe}nu2rO#20gU(pNWVr~(Dm#I$E?{T>XdMJ&{TsD2b(Z7 z(7;g(frcUtvLe;hPV)%uFwaN-uS5MqH<*Kztl<1jAR&4%;2`At2zBHLG<^FX2+Wna1E2J}^L`^rTG zHZ)p4$;Z(82swjz{*WE>OxxYcWPmAzEORf0Z5R8;aJsXbjE1(i7Qc>wmMcEcuDPRU zvuJ?_v-{M+epex3WzIwKt_O60#pGHoUkcqS_AlV{c~9?*QDfUs&v-y|xt5G6Nq_>! z-T@fF{F};t7EaFaG*U9Oyge{F*}KKHz&Ab7I@up6B(yT{2uAlhJ76#(i}Pgowy}Sy zkdy8%TC==0AkVo$VDNdCEt0(J0%GCm*HB$m=L1^HMLoPW_i&|$DKTKcx>ownchNHT zuNA`F1h;1;d(e8gVi8;#wvw<}T)`*Jo(Jx#dMc>F>~A9~ADSu+UaThv9=@xXVmIo= z2e8ky>k$=+rpDQoovfgM0gN~numSATHuha?0Gq(p06ve%Q>YD-8hi*l939>vY?bbP z23F7^Y`8!EFYf;EiaP2Exp>z-Bz)Eq?1C2(HTqf7188e)7o*rE3^p`ci?kuongZnl zJ>0&O_0R?`4QrpPx5KVcXvj5|`eqliIt_1{s2kx8I2zgvMO*79NJwk_K+)Fv2p!T| zAIQR!i4E<`0fYSX7DxEN2P`@iu~-HN3?9CKDdkBE)vDu2LH(8EqyUjkli`@0S$P@2g#;%Br(*WySb)A~A+0V zKHLZYt#%Uw6mCthU>-B7_Hy`FSI3AiggDC6*QwF%8NwfArv|c*`h$0BtUmRWSJ%Gf zp}RF<^+`H4Ru839Jd*15b2|;E68> z!rUs3;+Y3o(nbBMH}kGD zxGWDllw*)3P05(wkdqZs4cDbSz zcN^Mv`B6MdpCPA9&1QM0CSAy_ZwWup8a1r~QD7KI+Q_)M2g%U@a-KZn!J--<>7s=R zuJ`tUWh}4&Tv;o@ClJ??1!mw{Ag4SP=8C1QQngraX$@#O1Pyy2mUW1GTB}s#K4=Uk zFTwB_JB&yxI?R@~S$Yg0a1xoPs&q<+sc5A}tz6qFHcBm6-O|(Kq!%__Y}H#O&Jy&q z3iq(@)mrcw&N1_r&X}#?=h*0EELH&+&QkLNXJuecOaXeCT=If0$)F~)1vuIagZyUL zK`?HE6FRUew;IK5FvSG7aHGH$cO-hWedwVYY|=3cyc`sxhnhy|!NIX+sHzh@7`KCm z7Cn4%JGiJPVHE+Gffgu3S6XnmBHSt&kA6;3_Lb?YLJ!!M_r5~iuZrn?W!C#Lg}%jM zRTMUZzRjXK~Ym$t%OO-v1{@Uc)S0`gpIs(QcTg&NZgg-2|?iU|w<(>Pj=H=9) zuCo@eT;14Mzp?hl#`QakZ(d!$adqvr>%}*(zV^oTwJchW52>J1SZ(PZYfCToQk&Xi zZEDBbF4cEiZ-eSHUpK&N5OC7QEat)>Sk;Dg%!xr|vLG2SLzQ;R zi&d@FC~r0wQ;TA%?7EbgL4!)IqatRC=B?WsH(tN-$?NOIJFnf^ShV|64Z?XF#iPOO!txc7z;Yo$FDdc%pe(i|qeVZ>T#D zSqsEr5Lh|p?3@kYCWHm#wi|woOu05--XizSAkQcLH+hka33q9e!v2oR6!G7<{zv{d zs!m80VmtQHcGBs8vsU*Dy1~>eq}<(&5@mz?W|MJGzv0dY5zH=~o5%ivLOdoq^}J!h z%Xv0)!!Z1Pxp2(Wnqe{|+ii+Uy)9u62r*F?)4`NT_dp5QwzSc+eT8@})pRIo$es%} zYvVi!J&s|maZp4Jrigk#im2>YF^Z@NMLIibB&w+Wri$vIN+y^pnFCTK!w**V%1H*H zN+-XRM3YRvX_9f!BpXbV>;Y+##U&++(8Mb#Za17nm2AJMl66pJDVQot2c*gpE-6b0 zRlJho^g2p3S?V`UmK-$61=A$wLzD4<`9{{VIlhzS9X&aOCV@^?i6FV&2{Nu?N;c;p z$Z{}2mVF2kGy%&5S!Tb25o8%5NC%&?M3Uv+Nur=6S$2>lA54<`0ZEd_Ns?Gw1vgGs5R!OJHOnUrI|dR(R{Bkm6;>k?w(XOWNOH_;xu$zD zT_+tCux}^?a~va73Astaj!Er52z?-w3Grw<2_ze|7=e1RXdMJfb7hOP1G8!UcZOt| zr29^jw38;XNsG~>7n{~W6V-<%m{p6=#Mlm#X>uTQ7L^m#NfX(i#c0xtMeCqRhW!&% zPB5D`>>i*@p#vGWD1|ak3d!azMxkEpTL*=*?CU6nFbg-_#-~i51DUxfeX>sa$c8RP zpI$6o2Yr^{UYSM*GJ8=PEjei<8@?Eg{4C!fL(f5@oX;r3Y+q!QpM$@uMer5%yD~lK(=Lt#Zdc=*(TW?|{vEUKP{q81gcOzQtix6gGpt&7yCY z(6>4C?K1i{kG@^OI*c|KCI^HJpboLOI0m%Cz-WZ#8SEtrxr9OHu$Rl&%RKgSg^k|j za^w~|W6w95JmJ}89U;SoAyu}I;OxWyJtB*tW8q`Dzf^m{#Rl>?kVjM=&2*HIl9x-I zbHoT!+uN$ztJmaXGO3>;VrIvDGMTY7ppGYC~38PF>FPGq0pVkZ1+TAN+IMOp7uya2k;8T;%`Q`B!m;=j1qm zMOFw73OOhaP%8rm2X{9kUF-t4m2nadw~=vz1H&;UM!T(aEI|i1F~%w6P05gYa5@UB zps=bBtW9Lm0uh?-1DYn6TF|xo z+UA4Zdb!qWvY%JTu{*6&tGv0c?P!l)+N)IHN~O*F6n*Q6D|RlIl76eCIuAJwn_9vB{W~jzZOTX(g`#CdU9<7!mo$cMz8Fa8Z9+y;ARyP z71>Y_{febUg{)@YtcI>li)u)*rB!zqMP1`o75pO3u{&Bt+iX$eFFTD9-SY6VDbYIn z_q5Sk>y4ZE9oMRGJdWN3)*|E%B;M3^UIh`L(zAoR?5GYNRO3xL93S@My9(i0c0KHq zgw*z`eCg5HGQ;cripl}Zkt8*#JiZoqO&dDQiVx?iwan;I5T*%?a+`tZ*h-T`HfBqttiD;+C_?N@-9?cXO|5Ah8K>tKiFcCZ%g@fEcUwUCVSf;r9 zX2=ERMD~~|7KjsTr8!Lc*UCX|pf4>0v+jE2cp%Q6I39>GI5!Yt29T+c{SI8cY`kys zQy33pRvfVnc-W zldy0;5*FS+!kkt6`$k+itpyn3>Tu!o_ldAj{ty<@7lOc{eh`a@!9Ebyo&SS%^nF+m zzJ3qZrO$(POCi*6fVDr^r-8L6$e)4L zU{MHf6Cx8qehlXDVYnALXaqnPdBA-AtE*T+Psrk?1=Gs~G!eO1Xb-C;WclQS+KhJ6M zR>B%+mbHu>c0Il2+*NjTX~+rJRXOEY%8>D>M;hdTd#A9-5 zCJ+zj6b-~!OLbvzIc@7IYyJZ8V<0`c&E#RKt}{W=+lhf5&y=O+2f zDEU2wB;~!)ruOMQe$-s4;<;ilm0CHJcLRN6a5qpN?gqNa?*_WD{xZ4VSseH&ISs9~ z*Qmi6mbI;Nt6Z;ffvGo}8o%FgWhFbfK8(fAe$3d9S=il;Y```&9Mh#nm1E++yGPL_Lbuh-1GWg#r2+jULp7wI_1Q`Iy5=y zzl;})A33r^;qerBdzxfS|3Hnu%v3k0(EW;I`m( zt+L0ysGv?l%0CuLT+u^J8pN`}7S-HcT$8H$~HmDwQ`GtoChuF^NAPEcwvPxeQ$NU zQh&H;)V&B-dTf<9TZKRQ35EQf1c`$S^cZ%qG?{=eQSs$+3c!X@urz=Tn_y`Gi=bdC zfJIC&l}v&sblf`in#_UQa~5Lb%Qb#0TG5=3n&c#SI*&KBoxKX&nD(|9md0WqP(v2f@@ma_PXl?TgCm;;Sc45(xm;&tl&9m<$HY=rOQyhbzC@duISYEEg3kwOp z5zgP*1^HWx5b&wh*wf&Z_GlL@&?e6x0MP^~D>ZiPui`jbjtBT$YGqW8uE-tlRp5Q`?1_)&KcZ`5}8TCbHJ zYYpBE2@%#Jcj02OwYLirP~>IdAo{APLT`6E{i%21E!Np4M7=gSCC&CXN;^B+mh{4; zv@{+Q?*ck^13n737HF=9JIeBJ2!ozr=k`DsaWZ67sM?;M;7y_dGZt?UWTS}m40vY< z3>WzBqjaqrT-l)1d-P8pAIO#c^5+WlY7~LneM!o4o zBZ?Yrv4*i|iy?~wE&4_DlwUl8el>7{cr^t#TF^ZirRPIW%r2&V*o_IH$){X)z$c3t zPl-=Lx6nGdnLuYdJh6Ov>Km%61MrpKj`MCM2R5V zKms!-Ag7ryn1Z>nXftFm1urB9Q?M|V22(IM_YD0yn1cDr<{emM{jgcIpAvJOwI-Bi z489@G=bx%psui1`-YdbHzo<1Db+ITjF2AxxM87+YJ4p0vvFtA#k$JV6{nlE!+bc)+ z?0OaM&UDTD<}_x0a%4vX^3;`7DxK2*%PwbEma|Lg3{0CM;adOBXIF9Crudm(5&tcN zdpn=bs@$LxUsdrHzHwY>HNTwAr7|3ow%aUM#B80`E~l2^O{v<1`Q2J6g7xq&`Cbg7 z`v@J=2M&qFCg=!Xr+}N{h@YEc(%(%n<#baVmE9CaVmBO~hgU;;9)3GYj@q6FVG9^e zhp$B4ys#FvCI`eSm~#g)nSERh=E~YM-a7dj+-(T4vTqvxJ>Z^MTW_w4pzaN64Bz7m$6`8@`RkG~dAIW4PvJpI-L{=OG;O8MR-Ygp3My8u{;h$e)mg{G2u9 z<98M!XkeS#5oph{;SQM5a zN;O`9hY9}hA$XYP4?f6xAfKu)F8azO$ zcKjMVK&f{8qwoNw+VSg&8Dek9>MIHIDjDUdQt$^5rQr{tQQ;3D$-o~#k%d2iU@38i zoPfo|<^!>TTPed1<3sS9?rIGK*Fr~#e%AJf5bx`^r#v5fhR)UMHGMPHwc$)+2|A{G zR)HbsfFXP*(_9zBCib&5YAlk;+1PnHuYb4ps2p3=;dif{JJ5lf)yeSN)8sjTO}MwR z!A;-_oKKvBUF;pLrooli`pI_ndvEa*gTyX2d4bHvZc%rDL*h7@w6@S8rUFh+=6l}c z45WT25YaIVGBX@oh{J(7Vm)SDT~6YK6Y!ni-_E}g{hL@`UjbQ?#I2*ibQY;@F~Xg; zzH9vX*mFT*b3qcDi(aw0B#TY5lh}myCiLt+0Lgf@50bG^IAicyMA!j8rvyKX=8e*X z6?l9J=k}^43Gmh8Hz*XYUO=Iw`^4{VFbaPAthnZ5&j<1Q1&QC6z5Ko+^Lw!qzr(KW zj>LLg%mKe&>np!S8ko&*^Y9^w--^v|{p=LNMX}c&)nd6077}EUZgm`IK zHRx-V94k-*nh0p!);U#R##<`hI?Nu@S+OsH3@N%O4eORk1T2$oH3$!bbD1d@0Pzwa z?iN)~7EkAXx*(7SyC9xUJ380$fp00K<&4L2bW|Mb3XjWlRGeS}af^B9+I>Y@yC;4M zE^oKp`nsj58&>Qsx6|!)*xcbxeABBhHhthXwrZ93hB|`7+GVD2l#kDa$VEjpy5M-F zcZDnToIVPd!zlF2uFiL`JI@uKfks%Cq&jOT5Qxw-jLF3+IbE0sAYo3bGZFx|FyQm~ z!Z`znuu#luT#aF=IPi#>&w=Bt9&c+(+Zj3XT4r+?C{_q zNWU6^Xx1i;d^s{iXGj!cdd2UtxAgaLx+=VS@Q^25(J2x$0<1*>7QmAS4|z_NjRKAf z(O)?LDVZqMYIT0xEW`}b$k!r6$>e_I0y+QQaKag@6b*pOCj==B6_LS}ipn z&`FyyoDUAB%t=g{_;MshhIfYuheEh>+`}Et3W~62T1f&9@@EnCdyzimhUZebbYIZq zbA3Rww31%#3z|&shk?oeMp6Hj5;i}4Um;%tq5gX=p+0R0_3Ey|~U3L3t%RrzT;Mkc0bPRz0F zek4u0vFW(wkw||nas^!6R+8N_?+u@^e|c;{aBJ}a-4DI+*XZ!{3|rifyg<(HM-pV= zz2Vcuu)(OOV(^v|(O>~P|K4z%C@C)(xLJv?q~8v&k8kzXkobGU$I%A(5UA@>2LuAP zh9!{bIp=6Ffq;Pl1ah=dKamEs9T2FOhTsI^67-dRmdl2Yfw}^Q# z@x_N4*F)hOl;iG%12sq@mw$u61POa8AV1CMM=c8VEN=a23)~ObYgl`9n-^^#63*H|_hXND(DebLT#%MJQ5RBw&-e5FBfj^i=05j1=XGA^-1D4sW;*|6D0zC^grsFH0nxq=$f^Od zd#;MtfA)*vb(0xnjZ^k|(xOCEZ8VACY9~w?Sw@QNM#F#=b-2~wD%SqAkTi6iB>l`O z>BHqm$!%pv((vCva;RlKanU;r0rx-hmtO23nVtySE_X(C>B9+gay&CSu9#%?F()U7 zc7Sm~3EW&>O#Zw0f$v)M1bH3N#Q!DmXjk(GaLWBm9;9A{O(Y!)HFq+NKaP{)`=z4F z(0ugS=o!qqsVY78Wjt})W8(FAehM_V@uVhUGhE)0L~3uGCT|UE!O_$X=8WHq!+*Qr zdl&A(p{pDzySNKREk8ugY2{<}k~_=^TG{L1`OUmdkOA3ls|KA;?TlFS2XtOKL58es z2DOzOvIw)~FGT5(;eJ7|e_tMc*6$Dun5Bq!%@V;O&n;xy<-TxN*A>lLwVJHbt0UA8 zYba8lg0inBVUHpWuh~Veu&4etS#hRKq+7p~XbSd1*K;K=mCXm?{s$hu;sKy`Ef>6J z2$7AlJy<4jbwt+@<05M&#>4 zQ?Gfu{UCpUqLeq*0^w9w2-;6bft#w=`eHZONjnn14h1mVso~Xq#Q+`cK1He(f{4r8 z@90JOCw$5L5DsEIpsW2l$!@4e8^)i7tfOb~iPb%PjzbO>EOEsjkDSG8ug-v)H=bVo zHsqtW-W8-;t%Vu!!X6R>)JW#UW_Wk*ESmWuhk%j-@pl+Yws^K;=ZzJ}tW^Ulk9qKe z_KQ&_9Kw)T&I}liq(3_moH|+!Q|!v%a)Sg0YuqGry|tiK_!~IK!*I&*6+|-}KA~tr zMvuHfzBm$~^7oO0$1j5SE~yCZ>reJA7$E(kC53@~I-&0iWv>^H7UHk%smOHbAk-%L z3O4gU;T!%EQj!0F1dNq(hB+LRT$%x4Htx_=`y0vyDPTJC48Ad-1y1@<()u+(%nMDR zc`K%cs|KSV{S%36RU!Pmw~=IO78745SIEp(#%E@40=-QaiR6hZp1gM{EFJ$G(eXx5 z6QxI(U7Mj)dlrnW{)Y2E5KwsG2J1IoW>VcHIQ-KAQjoq9T(A2g=20^_cjGwRL8){UljYoC~8G2a&Z~RK1}80IV|&d zkJZ{;;lJcyB#>QumNug~f1WXRF~Ov1j5oiacijl6T_^);Ef>^e>Z~> z3nn6M=`bk$wH7|dD8X@o5%TeA;Je`@H=*DsieMgdfA{QsW(wB>b>Q3f81RUfezVtAenscJs?$}lkfuYPWP+`m*N0hq zN$twMWUo=1$jW{p9P}BE#tb%--YW2cK=*#2RJj5hKAsJgpCa)VkEz6?B?oox*+cI4 z42Q90>L8qP1;dFWWbkcgZujg&vT?&k63Z%(_*pu*Uu-aps+)0TvE7MEw2#8d8~Si> zx&kQ^9b;JCK+@8s@VcExZ-OjI`}7p%Ny$<&BBP2S!%xHW=bw0u*>!01 zQExIn*$`bBr;m%0r{O^Z({QpyK9X8*f%o-MqFeYp$_%I^btg~o+#m%Aoc9_TYzc$? z+fwkR&jNUpu?r>|CPGZrAv|zO5d^Bw;?GTUlTNr~FDkv)feL1+L+Sdp((wPp=*HDzoe45ndaad^aH(iJb-M*M3Zq>_cIw=ZDHf2RA#i39^CW} zB}T(yfS#5I_3u>3+kRGfTuvial1zZ}L8hc^gC718nnMyhSCiVeFHl5k5;&gii{7&y z5aHg4wtTXH0d)mj+EqoH&Z4!?HkgT_HJr;Vp{2Y)HaxdP~D>ckzBF3t_{vaCmcfCse-=BgTTU zP^dH$2JTZO9kd@*EF42}^KRj_D-RO?rYc-zxf!mVtU+T|Nl16l5uA1_0g@dq;men- z;0I$(5*jT@TvH9cd%OWJ`Zb=YuG;~E5$#woN=tN30+2a39d*w&A!-c-g?m=wo;CI) zQxTwYbtR4~kHp?82bkQN1;~4eF~qv-gMV`|a{Z$WJKrw`LAVaeU6hN$=}XAla3#~Z zZUZ#fokjxN7U7HL_jvB+IB0Us#Z{l(!BsO7sfASFR;5~;_%#tS!*Ws7;5yzpEEb}s z+JLDNk8Sr`l4>Iz$oy{5k2i)dUV?pJZ zF?c0Va5BLYwHHgU*{CKwx-tM+bdH9{pE4nSZxNXt-o)J7C$Rc+sG!)H*VPbo-I$#>s3E0dRS2v;1Qz2wT;}`OvHyvuVCcyk-<*@L!9<$O$ z7dl?jfDdItPslFP8}|xzzE41F)ChO}!yo2_cmbK5I1ddw&<~Ep_l0i<$AHbO99Y$- z0^hw-1v>Lp$Op~$nBH`RDfn+8NuHESj%lPqVXqz8ciMwIJ30f~T$qm^#O~*>R*eSh zFAHQf$}JR{CIGG0X+$}13bK9r9e3N`M#H9PqHgs?kU&!Tq%BX`^ycAYTVoWyou)x@ z-iyeCMdsjhGgLase>C<Tz4sOR_dKEugJd(V9 zwi2F%r=!gDAo6O_C#>)*4a7BtaLmDgJkn8tRnA!?^FjgW_%9^S(k7E}0n137-5fIZ z<5)1*^O}hd4<<(r+e=+O?8ZMI3#5XEhbZv4l63u>ZDjK6ZMe7QJuw~aOh}6s5-d|7 z5%(=gHuH)JIItU`!8=IL@h-wY*Ccncv(U+Psi?HqP->+8fYfH4CFwyYA*y~h%o2AH zenTeF4P1^6gxC?aj3APGL078Z@{TBaX-Hr0d4i0!R+9nMmT<)(nladW36f9T!g>qR z$hsSEi4%92I48}5*BS|=>&!(mv!9-*sjQIv2=i*L{StR~^EV13Dg6qbtCM`8<;7w2i-kKUfM!(L1 zpFc;F(&R~G#*!2gba4bZ-ghp1T31EPYCqs@6@f4;#|_2*q{;Wd1k`_z8ya|~8<{y9 zk=Gt)P{qY;l78e8^f)K+7XxMywf73}C&XE5U8RniAJ@RVgf{&At_}{oyoTf)q9JST zd^oo~0yM%D!0l2P>31v}zMWahH2AnPNjgsO>DFP8afH`>ON4KUo1pcM2Rag!iF?Zi zlP%iasOdxml0G&j`*vBumXYz$zHm7N%!ovda0icMuV8nJ>ExDG5;XfyM7IadM!E*F zc)H_3yk_qtt*6K0@zF=Q`1YN+q^AA0u&N{8;?=0%Vo^#B=dSN;Qq;AF+<`_fSpChOxAqGActC6qFA*8Dn ziguk3AReU;P)@K5NFQk-MZI0{dEYpgn;i(glNJ!P=OgMfvjquy9r3H3Lu5VVR%l)y z#+xkI0`4C@@NthIh@GMZ9qk9uI(%HS zmtQud5-u*x1NGVkWX?HHGOu7PbUaIgnN?NT*SZ@xuW7jFcq?8Ve-3iB*W#TUcampe zZHQGW2ln9x_!bt3Mbc|%k+v4hcwugw;Zws5&&w!9~sifFZ45p`Nk~OjIptx)v zX{f{KTJ2WQ9j}K!#ht>vrGv=?vutw3@+eyI`#Fi|a|-fKt^=hl&3J`N7Abw2MUD;H zi!;9zN`A(gdsW}mBf71&#P?1!bj0dF&#;O77599|&OZ!VWyerx$2@5Jc?+gbx(uHe zjDQ7?4AE!%=jg=R7x3HkJQ$p2!J)khSj8z={5v17nm7kf9$Jm|Mi@zNMVEuwlW?M! zZUBx7JD8B$lhETur`dGx8MwQ_AKTt?2PYp#*gAPU7~gq|REL|u^MV~|B zp`*yBezNo5>@+SvCOa1wj+33an&5BNfJ~Q$k?tBJ(pu|9k{(;47;P1js1i?-z=mmP zScZ}&>Ei0Q!;trxHl}sJSrmTl4DMYPM?!v?;3i914825VAF{2SUln|{v0s|x`zJX1;m<5I4S}`SP5sl;x`gE zi->KLH#G1+c+W&BY8}g=@>kCwJyum4*1}#~FdwHn^AIxr8z1dw zg%HvuP`17PlwM{15f#x{k!v7g6r2-mBFCn|Q*zDR)x z#C!QSpRb}*2Ai;kjz41dZQ`pvQXsk|1=}wj2Fv|+k)yE%(tdkgnE}?OIP8NZu^jV` zeEB4SB*qdL`ak4Rz7KL0jM1*u2Vi)kCe+4HBt(BEtSs$Mgw5%UXxdY>n_2{qUgh&C zy5-yhu{O*}|0S)RR|c!UPscq%9x7U#@w>s9($6V-k?oIzyg}D7{DldHojX*$&i=Uy zF?K0fr~DWc2WyiZw4PUG$~%0ZZ-1|z`sXlrsv%S+u7fg%9$vL^D^eI|+K_sNmbNUu z09CIE-2Qk0jV*QKZZA2Fj>W!3{a#;yac{?XDc`&+ZGGnryNR0Dmd*;sNyrd;-L)Xv z{1Q&7D|oG2@&aJULpbuGSgLk#7ha2|N{dV{p`k9@A>2mU%j@PhIJT1VYP`roSiKbqu=|&A@$Di{)#aU39uJ6UZYm)ko4U%?QodQ9{ zJ2ZPsB&c}xGK@>8%o4(h#$!z~Jz*qhXA$)0wJyx) zuT9?G^M&qAI|#RJMHBN85j+n@dutmIz4sfL^7;V!nx93!+o_;K0TvK$Jse)T($JhX zpO5^K2&v^i@w2DHz4cZ*@K)K7JYA3ums@=y^Gy+6wp$U3@`m9PmL0IqZ3Ud$r2*%E zUBp%Im*TS7dr?5lD7?A8FVWqYL%!cIVM3^h%*5Fapf~gfYAINlnn6lO4Y&>(M4sfV!jFC?p;uvX%>9f)@?^n7Y=1Kv&~w@e*13{Uh^A;7rw_ei!5M)`%EUsQWvXC+{TUxmP{x_Sj$6Z;j_tC-U4ZXco7p;}eH&@|+yXNq1Mn2QfVT^y}jf17?LqSjQ z6hG87lkQ~q@iQDvNax@q$Z5i0czDfEy7EIRj?K~m#l}>k6F3&sU%qDk+h-0g8O3JiwM#nq5v^%Ui-m5nRZ z$3c;05oC`#Lk1-u=jS|#V6U6eScn*o^0JGZFCZ#+etaNsV5pT{etoM zn%!h-C@*q5lp? zOPAg(#qEkF@H0P((0_*DewoY3F(a#$?AKixeqIx{mVma~Xnnild z$D=(hrx@K}4Kk{CG-)%;c)ei*_vppYjG0 zJGL9WmhnG&Cy-AaO0aqqk0NFVkS*$k%q>|RyP>NE^%e{xBNdILYKM%-yQT^lH5<>WQ|1*aVF~0etBPSTb(w(c-M1ce;}Qx9d`Fh&D#WJZ4zQ&+YfGjyFpg2T}d{N zy$ml_?#3JSYtXVj9L|flO?LHLBXK>g0s`OF{A2bp7Uyoql-+Q`Z}f&CM|5!h)&Pha z(jQfyo`GF`FCzi-33qwjLV0s+LD4%J3I6NB+uzk8=R@;B-1HOqe-DBD-dON_y91Y= z#LV215cnj%j>E6EqI9z={KhgJEaDuI>+>~m`Smx9)+v+9u5f5LH-o>{=ROjQ2;v*Q z{oy|z^n&$|?a83fXISrcGS-^7o~(#VM(6fVf~G?qc=pV29Ii7GZjZHMT9?>>bJGGS znQ;i~UKjzHj-eoEcV?P9mU6bI{qer|R5pD@Tp89Avq61(`P14O|nBpFeqo-2TS~L>g-tr-h|?|HCZ0nKm-mGS)%&DwP6wcM`V2U$RSbE~!$HvU z8qKpk04}pLAbF?k`<0A(rd~~hOy24P^!OZ-HZ_v0KYAWT)>^@W@$JxjaU!0T9EY{d zMxj4vfAE?IlS%N=Fl0$ZlY<2%+^2yca=n%gvm(1thHW*9>GuJv=6WH|r9ouK(?t+B zDuF26P$on3(wHQ_HAwTrC#Gmi4_>0&frnPxL6mm`QaJbn9SF`7{W{+doLcHowt_QR zLr+Gs!6XcS7)5@Jpn?CW0kIbP$UI^KU0sRfDDi}n-lfF2+z+aMQ{e4e z&2*{1M?GarV0Gv!G91T(wOayQToFrjUuw!`O=F?4WF+wE*{E1OkVpp_LX_@3zHHh; zyv`*8-lUBnZu7lhr{_~%FgAnpele5pE)`a0Xqd918b@)ySnyeo zG*cW-I_)B>GlOwRjv^#YPelDfY(QXJCkmV|AOh&%a|fxCp5k>RW;+Ehp3Wq$R1^t$ zFq4!8M-%UwC6M&!0~2#81Ml2n2q7J5sCz^x>9^6DL@nS^RO=H&f`nxshf zC1e`A0KD%{LyrCtvUfrc=Ng;i+{tfH>j7_Eq@RZdXM4b+pMm7Vv<%cd*B`2WpTsAH z(eOpIjuGf;Q?ng?eO-lKnw~}7 zffLBtrMKbm)jCibGDdovSxXWpSrGJY5!|0fP~eu8D5LWV(p>qCF&NZ>T)o1Hz#&R||zR29r+-GhkxhQ>eJ>1iGqVfacG4hKNr|P&R!Bw(H%G z)Z*sB&@c8RaOP6TvOIvhZw-K}x>~&7g(U=8tRjBH+{xaUnQ*^0AJ#aW!+eSWsx_|i zYc=YzO3_v#8P7m-6UOEDhJt%VB&^35xW<)5u(WD3+)uiJB$u|MczP&d)SBUH!DdW< zxy}2W*a8tc`H-~K9rR|GLr7y5Dl2@!-!@zfLA917qc$7$F7?6QkB{R0Iy&$;EeE@a z>|p*5H&XLc9eRAepb_&2fzkGIJcdz(x1Nje>5cKQIyM2{ZEL|3>w3Yfy^q(n0a<9= z0Yk5KsUJj#EFVJqFEzv)Jdw=|)V#|70Qq?A1XF%_FzLT93<(A+HK>K;;SyU5FXh}* zpej9$K5iLLf&yG&NB&ndWOeW=Y!g5O^E zk;R$kV7s#y?3$X%hqV8&#kg}s$KM+c1l@sy=P$zI9~2y;Sjb#t<>hVF##i1w1fd$(j?N12#I8_@vb&rPy$}C(^wwLw{ z!gx*v4^IPf&`+fwL=^l1sdVH+iH0k28E*nrE&RR?T86#XLFFiM+JB9 z9Erj&A3{$?Sb*ad4pn_cBA+5W{l4rs8)sA@xWEmo1^kEB z@)xjY)qOPU$ZrnQp(XW6D z=?*RiVB+AC&}O#M1R?kontJHh(@2LF*1MEAFMiyk)hxB-%%` zXh%JqI&%~n2AlJzWoJxL))r7z(D6z?c!y*L6F8hQnSg#Het9pAyq!B2zg~6@tDXOW zd{2ZC2e0Qi_ooI7m#l!SA%*-U1q*nhA;dv7dQh&p6E}LQ!hEbH|E)m!xeVE?P9SiP z72+SqhT_jl9^#FM*8?q^<&C@Vj=jBF_`2~!@#94?FwIUK6bJ0UcYf*<{~p8_>gd9j zJHxR`@N%puumHOi6T$DUB4B?zs7>Dhq0g6-Jx#v2^Vm9U@NP99W-G*MKhDy%Sj$c=nw3)fwp<=AFAI)j3}DlFG@#+hHs@rD{z zhJi#W_pb!)k|06=k@B)RlJ?NGqxk$Q|F<_Wk(?<@GKg1*8)Z_+y>?Q z^&0g2KjZM$*I3=HkZ&Aj*ASKD14C>ZVfBusP@q%~FTc2xc-MK*+;I`O-g0S#!Z5g) z4Y0^)C}g*MmFE5#jx!ctL#Ku$LcgeX>9T_c4M%qsz}iQX3B7Q;EGhLRPUAO83kuib z$G6h4!Gt#6Pt*+Q5A>j6`d`lq1oP(2^IA!1++ zvywaCIWSiAcYSWR68E)yh^Wg~4L6mt^zu71MN|D}GoEc@ zRTmBBrzmMM@stb0m?ViFeRpEcotPq$g#8lD%UaEvc_uTTHH|3;Q)|APSjqMCJ_AMH z?i0>HGA`V^0ChR8m>tFRP{o0wla9u?Abzq)Yr2*w zbH{2XZSnSh{M==ji?0SF6HgVisL_le-_jYA0&n#0T|9HR{2}M8bCbInZcJJBEtEh1 z7xQs12d0a5VL~TGFfB`F%JpQ9>C05E=%JmgmT|1KgiBtOO#gj$b_>P+I>FL?10`Hp z#d&dqevqW24%0VJJe1=eu2M+f|F(*`IBb`wg0`VIwv~w-*9I|z-fR*jK3mIPVeiv1 zVdhk3Ulp1S(3ji)Y^0xP&9@;U@7@0F{rVQUo_yVEIzmHCcZROw=u1W1B)4gDyzAS| z*w|DB(Y(AqyalB$@(Z#N-hbgM@{UWD>-P-Gr*BSL&)gb*h%xeZ7xDR=Xkd91^Luf= zXj0%tNl14W*FMOC(#;K%TAbRxqH{DAL>5mIi<$5X{>P0Jq=8LrEFd{W& zUq1hnNG{(r-;x3cbVF&d0q|H_jZ{P}nlj%d$ie!iZ`1#^Miitujka&MY^-!bndF8iZ` zNNZlQXkfxrdY@{DC~)xtQIY0(_T6MGTwaqU8f0QgRSa(9T3jvU`rR)|xCQNZII&_C zuk!4RTu<4VKyHJsIiopX0oPi1nK%5X$^P~K?Kh+N^POAShKotOn&(KiVYI36$+VB6 zRqGq&`gt7%E?Ub5mHpSn%zie8>GP<8vD;;WqGoSphCGtRwsDm34rNVQ-u%jqy7*83 z?;Spj;8=y2B<1l*Kg;F(D~;JJg64Nz$dhEIWY}H4?~}!HT+2=!=c{@Qcz1k}(Mp!E z=Lf0taW9m32Z5zL7e{Se#b<82&N)aO7{RJ9qE4v?<2)stG5zi#YWQ}6GoP!=G|jf8 zvivchfA63F`z=4lDI3n=SB>((MVrsd_1Mpy&RcG75U00ia~EE2Vq3Jg%5g#RYVO^$ z@$B+@vAk03GrH`ehp^+yDbbH7XXN`nC1%cC5{rnb z4Y%JhiytxCm@+ry*!4gD*`K-YiHJG;gSH)QM>Cms<$A)^PSg3_%KU-IY0MF{mrp$U zN6!C_x2yOc>?5w)tAf!DuM!@fq{P2Dcb8L~eOu1|;C+t#neuy_UCe%w_m>Qj$o zi{s%;oa0j(a=N&&A2%_MJB=t$g{^#Xv8CMqt*_G9RyTeASX>)#BIEL}pC`Y2#2w1a z5~;1EM7hHpaQJ>(Ij(!s8~nN8Hm)n%iSO#KMOSTa=X5tr7g1No%K7i<_2BKUk3_c@ z`l1Twrz85*nwf*ywKYbR{Y_JDc3%T(vhgzZ*d#qU=hjO9{3v{>OYMH} zP*U-|TUaT`W`CI;Wt%khs0?d8YW4*qN-T)w9<;n>&qT!zSi0|v(0io;^~@@SJu$?L zdO5_HQmd(yWTY!`dTaFAWp@{`)l0fqx0L0c*RAy_(>ML;2^-9)#M){$ttXEiUSiAz z1=g|YCpG05x{Z&sk4y=;%c1+QV4Yg`u+c!?<9_DS~ z92%aojnl0uXYL-`wb+b0zi+VXkx>S6e_UE+N#(6I=Twj8u;c9PxKGc`s7Xn-EPYUy zT9~WN?LTWm8QRZeZ|_!->wcJQE#Ft(Y)!RaR26Ph{wj>GNM>d7kw@<;}jW*P|Y+v!>3UDUsaC_`;TMQf2!tn9BBjc8k4p zVKhA_$e4OG%#a@EU_@14Y-gMLX0qebG&$e4N;Yktf*ixlzWZ7BY9DU$TV3X3@H+Ox zTXU*)NCF!-DnoAn4R1ZR=hF#U4F9PszWI(DcD> z=UGq_%yc*v?Z9Ip8w&5S9UpY5)x9Nj z?E?eK`hh-WcukpJLVQK+`x*3=0o8QC@%|#}Low|=%Yd2^y^FP(Hd(pWs`qa%WrR;T2UCL0ZPknW;pf*&`76}esmxQ>V5EeL_QAPE$ zC3@d=sqUa~mi=u*nI79GDXSPS<5M7*^!}g!C;Tv=25&sb#kH&!7Oj^`!pFRqY}2u% zj#^q$P0NfZ$JT*d(TD!*wap!3!R*6g*H{C}f7TYsGc6Np>?S>`C{7{{i4(CQPP9Z! zN+q_@FC}AYwM1%tjj5zR!-P-om{HD;4@;V?E=hV0g|ROzen}DnN69gSEc+;&eX_G{(MbvOL`lw1$m%hYq}eL$@?#EsTTv0;!1ZMlr|VIzk1bfO1Pf~9 zq(1C5MSUu}uMw5<$$$#!Gfgh{uYLc&UVU0h>Aq%#qR?6sip>+!ANQM5QNdQCm?0(< zq->yH?J<&bTPiS?zyCHZ`qakeuUz7KT}k`yJi6cLleF6nD@xJYiVFW~LM2_!6Mx+D zi7vh|M9fy*WPMf5skqokdUTQnwfV9U^`gB&sI^^9loV-AZ`z+gryxDi(V6YE!dy#g z^sI39*kDuY*_I1z+_GJC)*W-v^#n`{-s{LQe0Hp(e-v7aOqI4WDf70{>Ct+Wv0Dy3 zq|Y1qdQr6#U2JxN7U|FB2fc6PRp2e{z0Qn^bbU%!4K<|Bu3f_3VDzaAM24x_l)Bkz zEhxH9Dsj{3#@qt7Os-gN~y&#Jd|Ba1ZNA=|PuWi?-4rLc| zJ%VmeZ-J&*;K_*X)hwtBrwk}Pi8YnIpn~oCwOy<_h^ouJWx)>4l;zvS74;Y5Z7686 zpu8VEa4$i>rX6gVU|a~vofMaSr}4_Tg<3H zg+7w0e&^}$x|{0HkoEHSOFV2St*l@`nNQH8s+IGFetYlJnfy=T%Gv(3N%Tefd&@~- z&JSH`!YCWIpsyaK9h1ri?MR^eAL*r4xLtJou2*slP``t&30DxgR~;2~eTt^LDvYRs zE9THisk7wvYdlt==U?APhhs}_QB?%*HsCa!8)-$Y-o(;4)QD<3zm#43_1`(ZXRI~# zq)Es{tq2tL8VlV z;X)2y5XTPuExc@DNpH=wp{DgUr=s?nQE|UF3H{fH(i47KiOUCsv&GjeDc4M?u(rU2 zvL0_uB@7)XT={AdO?zhv8yas3b2aDDt&43$CezF)!PCPM3l|&etQEzcf1yN&o=B&6 zezT|j45m7_an=fR zcr}&r^kN5VYNzpN`t(~}s#Bjx>iZZ`D=bZ@_&vr{htp;{>2|0`c*P`o*EfC2c0#7d zidq>zMNRH`r%fsEsuT}_ca!^H|C@K{%I)`bGNl|2Z{v=QA1M?(j_?o|1$bP)CVTdm z0p;RnO#L`v$_bV#dmM5LuCsln!0MIhQw{f5c@&Scq?Wuirn=r8^$?uD>E4jI%|mc= zsYho04k7OrENr-ILFIn>DgJs-#*tDDn`G?gAz<^|1=DE{!Lv>|2Elc24?*Nn_s^Ac z7=c-gNAws|D(O_Z$0q-$a{C3UyF8LqEj(^^Ir5_3^}JwfuY1-N6H0JZ-9!D033aeQ zoo!6{=f~J5=9Hkk%sqM%MOW^*PLIg3qO>Lz2>;qT<$MyoB}P{N9lIhd`?XTe{r%_v z`lyz*CRAJ4B=*Iy0&&ITcfv=e26QPlprY+`sroz<%5{9A(9mZLU0q})-mq6s9{;P< zYUOgrc9>BEb*)CaCWJ4V;rP+^3KZK9= zucyx)GN=3PTqMV^=71rcbSs(8UAR|7y?!pdH&~ylN_Z;F?HwdvuYQ{;WO+M!*4#rJ zBkO0EnETSrUo9wVm5BbKZ%D27J1ki^=-)izubn51Q|M2z+iAmbvqiIHu^FW_fNtq$ zNL5(qiXO>)IcNSndWM#|oLisBf9L-~RYNKVQn{0hhDz*4rPFoZ<#eBO#?+2tbE@c$ zIc2%cjGowdpSEpUBG#X`j9s|RoT`o(LxmoXx%g4 z=)#R&^!rpRDtWX!`)QR8<-d+&2i9((P2OvZJ~vm<%bFGC7@E~8=(JEhQPD}M$aj1) zo#C!aML*t1?;Q0n{yRRJ(06a2qF47T;`Ziw@(OBq==rwZu}liTQvVM?_0vjL@X-G+U_8BzTg zw;!FfFq%#YenCfE%b_Fh+>&GHnvhAGzI;o6(0nd>c6t)MZoMHjsWX)J`MOr_M{CDk zVYNv35f4lhvZTHfevaUZuZ}2pxOxItP{B^U-4pYkKv;`Fs`i}l$SRoYl z+e7QS%j*AfZ=u=}3ut08ti%Mkva_)C}|%CXzKK92pXZ=Ghe(9FPyI0;1_ zKCa(SsE(3_`%e852DwB??x*Ne=8@YaGwqG3wCM2?#l59M8~whtQ};PxXO)p0L$^N` z?)cD;HamG&wBh*$EUOQG zcw2Lougxg;zyy|AXUzS5e#Fv$_6?mX>tXv0q{nu(2^I2kS^v%&c7v?$spkzT&1V+W zqgjbujQMAFWY|`5>+xXPq}rUSDw)hq%`>I~X<5wG9F};GQs-2hj9JU173`m0ZSHcD zsi+`PmkN30M0?!Rr&P*Ld5r#D$Zn-9xx{5WTVARw$I$uwB)hlLhVwakLbOUPn~j`i zNG0iIv3p+G$k&rPZP~ik^XzWj$=vfj=DfJ$ExWLvOkVa=Hfy30)$zz(vSFA76)Ee1 z;=Wo_AOFZ?-8jH5GYjUHj5VY*8inj?1w$$`&z`$uY)F~^N@6{?Sjc5xg#Vc%EjOXe zvkucwuig_zzRG9Ej+e0ga`Y+38Ag=yRx|3AUNm=ObuXLZmnPPkmQTllDdng!ll7FH zL*-kns8m_MMnBc&$}U*4PtGT@)wMs^%ma<|pX+*5go7u2_KrTK6me3byI~J|%DpdV zI^Zl@pJpV-U?0t~i>dycZNwDO?6KR~EAwPC)_L1lM^{z(dj5|A><7}qY6NI;>pa`p z(Y;^TI&WR-+S0eI&jMM0vqaCO>!T4>5NAORZZ)LNNA%}@ew)rYRB7?OVY<|+A-$}j zy%ps@;~wYjVnkVf8N$6vxh|LeDehnWuh`d&3TWKsQ8s5UeZg)VXRWx7TROv(in(S; z9SoJt42C%ImJbedcb7JZwO$SuO)Qn^6`FA3jaJm(S#agfRcw|@12^5|23tE}5I3m( z2Eh?Y?QLe1 zzG(pK6rx8BnrJ~yE!!(uYOKIj#cQ!|hR8b-G?7*SJau40o) zx3Y&W>vOK=C)fuDYH|!iR1UNLUdG(b{kxezOH$dteP^HYWOnYo9?{=-^mMv0YkiYt zM~!#m--jLLvj2O)9xBqO%C6pG&F`2{J1)O*Zu0t<|Jv`Grs(C$-tFr5;>?aKk}Pi% zs;M_syr)A?*8i=LT;3_Gt@T-PS@e8)&UkhIU)}W4!kmil$fg_WK6~8m>=0+Fs!6Vd znovsnW%cwtU24+GT(;U@Br&ghQ!lt}duo-133Xd-pLjQ?PtEFMNp*40>;0`KN?J>& ziNj~ri^DH=N@9I`X_RY5?T$AQhVHVY)H78*y5Bq#cW;Q3+^*4)h$CjmF(g%}O9Wrz zC8>K|L@~lP@#8txRJi3;@wWVOIX{A>3&oXArV{cgk?Y*0!8vBSOBPuhQ6UztvVX-l zrB>K?NZwsGqd-=}eNd70x%sOk#t}aBV4r{UlNCEUg|w_)oPd&BMcG7$LoH}*IWIU@f z#hALNszlqVT2NV=Y$(TwslqvTD(GLOtnfpk5&gX@ou0g;L0;cq`S4hheb0zuk9f0z zSA_JLWtcAe9!)R2dR&e{@+y*k^8PeE!(yq#y>bxkC_AH%mpIWaJ3Zv~kNkZ>xXx!e zZK{2DghJM0PUS={J#dN4FEv|eh1(X?9P23dFUHBi*3_j~eablW483Ti5oK!e&oZYa)1w~!HmCe2$?D1fxn}Q^_4(2NYK0fI zdMSTz`&|0hbDuD=Oj&x`ikh~@kP1PjRC=R6mAdTzap$o{U;g~xJ(nG9D0IS_${nst zX>It|d!z>GQ}bj!#NYLVE&t}YGxGnf{k`X5WJziKk1c;c_YD4L$DNh`>^c!){=f2d z&X}k8?w8g4%~FZ?ix-k3lVm;IwP49cS^pU_$&bC)s!J7R?vS+pN6R@Y2>ge$wcC)& zXma43mDUQ?a*j#7Z{Cr_+%uu_&2_0^&a&_P?gw)I7mQi0p0i?aQHJNCXGT=_gAI}f zH8bj*tBmW%RpKs>fvmsTAW2B;cFAxfLpCHyRkYxkHDxg4$=9tI0=J~p_ zdkvZH*?XUJ3nes(6pe-`3JGbR5K&2kQlvqnkka7Zi&UCZiDs1sr9o-dr0?G2d3t)^ zdV1dP{eItH@9p>Nth?7<^V)0ebI!(X0TurxI4-V=eJk#~z^a~1Bvt3XrAh3@7-NQe zbR;Ka`S&nWSCVwk3QL)0h^-@WA=xjsuhSa)AbV~qAAhl|MjL9zEsrjdOe8TlGEq%EuD!{iRELQV$RL z`2XtX$=f9;P-PrpHqR9E*0Mq;(~Pi{&1!^dqU@PwO$d7Bq)7Fa8rl00xsSr*46yZ* zC6Xhz)5KFA&PK+EHlWiE`dF!gImXv9$0Aml5Kq4}qH$~LIZ9(zN)Ck@VKHk7wC{xl z7W0sXU5eWX7o2>Cb_!KcrA-hT-RCh1Z~cO@Uz%bw*Rv$1M~$%*r$}(JC=K;LuR>Ix z+={LwbW!z>h$=*7pVbL#Ei0m7dJ+m)WQ=X8OF*yi6_k!QPwS${@q18fNx5`+7dgo0^bP zETyEnnIz8YSQU9m3fHeQ$5Ppg#ceP2vDPvptpBTXRUTgUlIO`ltR1pWte|Bn8NA7p z$c-?=j)@n-6=8Z=Li_oGjHoaYkxyZ6rA@yEol`zn7%9Jq^>~J`}S|^{}Sr z`dFWxde|DwPqL=*kwiK@|C$v_!TKIIMk0lHD?z;w_%kQ$xqg z^5RqDZQQNW9nJJ;lIShQq*peYV_#laVTyQk01fjS5Mn;x=f&M#&o; zQ!LTf2K%r{L6TMIBW2tlCmChCU(&~pFMZ;E7%6ERVA(C{s9v^TKN#XDEje*pQd%D& z-5aYR6;BMLbeOE5EbYyXmge~zk!x?9mz+;G#&ToMN)ndrq2z4487HBi)srsWJWF!? z<28wp<{+JYNcJ3Cmn+SmZj7}Y2ocjS_w=fwr!spAqoupegKH{u2 z3oOjRNitP-Z!tG4LmZpIp?u$UucxMUO{8J1=7z9koh{_;+b9nEa9rGBXoe}dn_;Q* zjIjacMp96xD%rB+YE_sb2cB~_$Ml%d;^!yzvAMDwKfR))s`a*sgnVZ$j`d3yM_PMI z+=lg|@>jul7<^c2iA~|{78lOgA@;p#FQK``7PKwnp_Lig=l@Rt*^Tp|1 zM%d>6osDXqFHKuI!kG7ak*_f>2cVS#;K+w(jwIa2oC zz|RV+@NlO1{;$?Px!qv_6U3XvkHz0g^stK6T~$z4%fb#n78@CxVHMAu#J!0YYVYZB zvuB_2Y?dCDd%RR^*mV>n4DlBm(iVw9j3u`7sv*X1F~UCWEtKTa_KTN%9D2A;VkmYN zT4KYVn}}x*w#NDx>SLWsBde;;o)-J+U#O}h9K;FR1H{eTC+OiiW9)zf3%aswFkNY< z*tcV}n11u2*f(s6xOZj~r9)>)s`$F{Q*nWTF6m+8E9TBH#qzcKi+Kras5pAeYpH6U zmn(j&;!r(u9$h+YX_@##oH3R#dZ)Ob?D^sbi%(T21{q=Uy>Q23U>YWp_3_BHC&ZCQ z?WJK}Ldn&#wGyxoleWztOI&QDVfh1i=wp`+Ho7fU+CINV5?Rt;np^cu5~eGpbf{+B zmn?MkljcWvla?>bBwcxWn5F6-38|t)ooAqj$j-{Rf0Vol+gt7Z`fYW7ijlN1T6PYE zttSQg1{km!D!G5h06VQ{jCJ(0#B$60q^F(UOM}k&R&N|>mHJlnRT}b+mdfC0RNvfe znmTM2yE>(UOP$pivZ-h9STWf&^^wLjG|c}pGHjnO&5xKNb#F09{W91pwOqC*-h7OX z64Iii*(as~``8bXnavid*EitO1Fa^h#xi)z2dioi-(0EQ7A2|ahyzmZDFdsyjr$~O z8OEs!6PZ=bm=RWL(GRHyaHU~dxsoMUuS#S0Xj3|DUfU%ds>H5dw=halL9dh+M4Di3 zIi1p5+7GDsH&4DGt-IEUR@9~vWVtQTdTyuWh5;?LE9{VTh>3aXi^wzZ#&Dxl!9LT} zEp-N|%B?Zd{6S4odLS1a~O#>4I;G$sS#^#u7u?r32Axj z4L!Si3R$eQh%J|2+>}F%je1J7?+FyGos&e#zw}C*h!E@}P9%Dekw=5bmDP(W`R}LH z6Bjn^M1fi`yd;=I(G)7V;3|D;zFfYYC5t?$UQZ}>2t-MRGpX@;Uq%wgMm9kDQC&j0&rm|E zt{;-mO}JQtLbNu+=V!D?@^A>8x3m;)l)cC6mN-!Q8MPLolQZTJO63{IbyF{xPqxF) zC-}s=H;3VQPlLrN*i1IU z{nh#eO=UPSZAb(qKex34d3;(6wWk`8FH09dcIIBVQoRMSmJX!o_BPg{ScfcPQt$*K zS_#2bIbHDE)@b6J=q-Fv^cr*=JW6zU_oL6S(I)K9xKi<-Gb$G~4B3e$ytgCu?3ffE zv!TxD`R8%S?0x~!3~Pu-PmfXZH9w^g=URp%t9vI%)*v2oTAPDb9w{QOnDwmnt%?Ce zAD5FvheZQ%f;$(^`MMH?rJf+1v1N#Plm;yfR+2?YCCmr!HWL}U0x0`8H+v9iyJHF8 zkUDaQxRwv4M;{|ShB~o$GmVn}X5U$~$fE+bI`GNt%WI+Xg_qDqTbU?I z9Zu069?YZkt%l`MRHza3|5mWA#S1}=TDFil*5SR=6A%_c3aUg_aj8qix2341rm+b zZ)Gf(JSL6m-%|cp#8#89wk;vE%s+^p`dd(ZZjZl1Y~DVM04dMNw$z~_&SjjEpL1X* z`6)Y?c$``<;(ReChMPqbcVkwN1Di>TZmmu>nf&<{S-YA}diN?o9r?b5%GnoXlp^7EfIqL*TUM|fdlkR;MfjAn)=b2h95j$)-3Uk~*d^T?- z9A)n}ru-lF&YyUj|C$JXE+!0%I^eFR zOr&=1GBN698d^857*?4@kmh6KncB7mL_e!`x}4{lDsN(H!Z6~ATNP>3*g)~|8-Ed< z;T96BZ)KA0=p?Bi-A9cVdG#f|@9GlKX;VeRGb+&@^`%mM<1% zzbvHqI7Frp+wRDI-p}omXfoZuPj+^Xe^Wn{h*ZbKl2_V4^cnlwn+!79LFN=mMQ_!- zsPpo}4(5wkZKi#~uT_YAhZ&G%o)zTUa@{@`a`ute9rhDn*17f>G{u|s30LUzXZ@RW zK0~zHI8XGjOs(&oLMw{Tu^TVQ*J{2H|F{xeoW|hRm8XJitr**lRs>tpGur@mElp zTnfYRxA2Ob+ z1w)q0&fpb<(q{}80{V*(K^9vRZL(U=uPdkkW1704e7@q=QI!3D$3Anjed6IX#{fJt ztOJ~!;|yEx`!bBGiUwIcH4OB2$0h{`lf>ZJ6`eox?X2H>>GgJ zxz`AT_Ns&CX*B9vtTI{vLcEV|rA>5wOO zgQ=R@$T;1GXl-f*FDKQobn>r(K{qTY`-_hl0T10#u>7qp64Q!d&Y2BxVNs*4_NJ8( zUuMs1u8R`x7!S5S-n8z!W+od^9Vd_=fMddbr>2&2U2+b zdtbr3Y=910H4zWrCJ_(Tr6HeNc3ibBGmySR6|ZmLW882;1>@*H09YcLCeI`yy*4c9OlpSA=0jwA?ZUeywB{r@Nk+Q+bVo1TxH+ezI}!XSAjkf zu+m#m{yrL1H>rdMWlPYy&0fTVmZSC`z*M-k-I_(aQ6#KS(nNhTdl7yGfr!}njH?Ia@3cEZw-TkL=pkKp1LqpA2$9ZrYGo=!r``jrq?wl;+Egze~N?Q=Vq zeFey5!7knu)r-PM^W3<5Jhw5%Xoz@E&5bEKd0hWjKZjdf(Lm$*#3N;UI}O(uU5-TIH(UjYU!r+} z%qNcX<|YyrhZ+%z{OG=Tz6v5EBUtmacfrmGf#9Z*9Y?o%AviNyjbQKU4U^wogD%^P zQNX+bgjrjggH`lO_;3lC!Sm_ZFho^a1@5F(IE0X``FDh`U=jL?Bs`L96_CD6zxqtrb9_wDV2Lq?Pgl}v(TK1{J&Gy(*SZ{8{ zx^}@0hH{VcCHz3n0;mPvZ(4~=rq_btLD3MHIU(Ncap+0&dk3rDmhe2;%47}>##gVa zgahp)$aj@G`slTZ(qV7HCwSHJnCzF)6cKu4Av}3~FuOA?4_10_q3k!}UjkRg7^90% zVu@9QQ_#`mktpi*6uYA@{m_Mu44w*E?fz9`99M3~eCKbRfIY|1d97;DYkW5hsD4bJ zbM_ss>~dVd7fE2|w=KN0w(-ERYA02D{au$)b@SSlo9xq%`y)I{4=>W(44(CU2{hWS zusj1QnS8sKj(c7_gfMsv6ml-RZR@q1s{gMyIf2vRlLVt4E@U6nRmD%uT@LNWR^bLU z;lMS6376L%fdi**7gP^61J$ictOxHi@$2);!P2e+F!{7HT=aMYrNf|2Z-C%bHFSOY z2x{f61K-ej_Qw$`!DE996uupt#w7!3uz^vAZjBB?72Aiwt){XcTOZmV?uuaYlvA>B zmz@I2jv;#|a=!%Dz`KDH;AG_@^dWDsotJbC2&*gM7xoHA%Eg3Whm9T#E*ePr{_eJ& zRQ?~yH4yYSP$s73?8o~a^n@q#a-pU35W%G0DZB@+9HO+&TnK1e>xhxCwoJ&U{kuP`wgU9iST;5|| zL#+kO3%O)h)bDU%`mcTN27m2T6{5HdfCU%M!oyi6$TLq% z;5T?F@72CyC-*7_aphq)^4}QiUOB%U7VlihJexZn4hvS|R~=w;n4|ch*sBu7+cH zny_Zq!M)*3j*CSV{7gGb<^N*^1$e~=BDd2kh_cv?$d{guZVz#{n^G|o5qs--A0J&1 zc8oBl@_)udlGD`i5*aG50z)gVz#LrN`g}_*E?*lN`MFSCDVbM(3jiG=mC7w!RoQRd zk$nm*!#O;~M=)9amhf@nOyGD<407HMVKzSWus!lL+#&SqS@?7`9~R_#xVL^DN9BJ& zggSL4TrHSM=PwGgc8`HU$}8~4zD}S(SqqMW%4ooiWDEOTQgT^CZYhHJ{)*f? z#jg z!`Cncq?$DevVHctD~w$QhKE0=cQ1z^|up8eDE_bK0 zU(8z%9DO?|eEg>-d}o3=bbMKh2Hg)p8U4q?+UNf48$i)24T0M8~+&D&%hPLg*{Lx7ECla7Zv64_}|9cRr z9Bnl~EgwV$t>X{Q-oo-<9E~eKcni6QZ9sDPaZqla2S3$jBSQ;@{hr8l;Lje+Z26|_ zepJ;2w&h!*@fV}u9#vIJ2i*&S&}JkP>D9QQ7laZt^tsBiTK*ZFFIAxM)(0IyId2}k zzMM&<&s~XzWgL(_j}Y08ySp0>+IEPYRx*$}YtSo`X=!|}fOFsi6G_ZBgC`mf;NCPF z_GcN(H*q^MPDI_0 z`z~0=hF}Z)yyCI@_9`o??hT4GabKSsEV%F6M)}FRWR?5zSr>ZFU;nW@OdD6(yn1c# zZmRy;HOS_K`}=_g!pw#!+byr!sr>L5lp`!v$`tC(IP5-%8SE}6I~*3`zO~{B|G0%R z>(x}Yn~UrYW~t8uH&eBx?$;wig_p~^-Q@H9M+w}&y^LU74L5Qh*m2c;+{HUW=^~~u z`amtEgX3o-Vcn#5;p&OU-QI{L?uHiUnOg7nyMLUui=wZu=x~!-xe1?NTIuG&=)@0A zT}aV&OQs3aoYvXs)Y^Tw#X|2U=b7OX;lt%#@VrhYx;?XlccWoG_;_=&z550a6k*{k zQ2h2D)Q;*oA34#!j_QB6&(`xb2V8-N1{L7%-?AY&dj<>`+e?sfd?fEcg_hlzjz#Ef z_I)^85yNSgMldHOnN^^82%Jo56HIHj;QCBkjxSh6LySaO><>Nx+j{MWwGte?_sC=1 zR^14)?x!*LHEFsv*SJAzF9PL^&Vr3rbSl4fYUaSN4*k&HSZ(4~iWQvYoWmAPHilhu zqAC2z837>QWF4F%%|f$h`yh{{*I>ARkzFeN9DER}Z>Lo0;6B`76X(Llp^O(HkGX5B z`=KwoQJ|}=1j1RDST)D;@TRCDe#7MmDB0n}TdA!Nmh~S@PRRBjLvE^ARj4|HUDrQR`1t)Pc%j>VFxhP`9>y|@*ZhhlVQR+w_zge{ctNZT-=F1?ETF4Zfgc+$_oW& z0=6J-)+4?rdng@j+@ss;0{S18c5T?cLJ3eiN`Bly}agVMpzvI!E)ic$Q&`-H?k4f;zK zv6_y|f$51g)cT*t*bC0A{tC@}j)2pPPXotBHxxJhBKN5_AKh5pz*###S~%Hy5X-51 zqper3Tbz2;ZRnWkC%D=hCmOmNc}G*3(8X1krC#y@C4@8xwoNL6+m-K9vMVhXQ}(Oo zm-7b%X%OinL}1I~W;ol-1|=5U;Y((w@WT7IJ1v{*LYOzNM2Ra7yWZyQhr#~Fth(JX z(024B&a`7YStHK7fEJf(ba&1>@X>ZH)OZ_%ZnQKai#-b+6C=Ff6D*IhH`Wl$v}%Vh zD>~7${NBj!p;u=2}v-spqF zaQo}^JX5+g?6-XwpR0cskB!%*aw|$@2UY*8-}3o|0Z#bK^V5Zo&Z~j(&VxYs!!&+W z%}wsh0R_AVodK{{hy>hJEq50zRt4KRCM;dcJbeAQg?8HxWpZrtB7_Iooj}#e5-%z} zf)AdU2PWL5Lmyun<6w9ko^8;FSwAMjz0TGUj4n2Vth8|OY`GGp!|T^W!JVOWXfQ_= zIpr#Vk{J`(+85sAEX&0dzV!(ox6YjjK7aLuZ)T)|J$?3pM@xI#DU|I1?;ot;ZoDiK zUc7C@A%nCS^;?WMnJ4LR$TL&?W(=L`CBAQcghy@_*(yvi0rr(lX6MeM!tC)qdsidX zIO_S=)7KlAyG*SdpSz53Kf=WD?JK=-g;gEY-cVk{kB2$nievZV8@^0&;au+&+E0t1 z^RMR!RlL=h*?E0g{+!Y7Uko1MYrYu?@8lg8uD`hoPhYynMNV5NnI+8LZNoA=S1erj zLK*xva**H*Ui3R=l^>KNU{#i8h`?-(Z()t@gqUgdJhnD60;j?g=B# zSX#^V81LakmtOADfsJTUuy1xu!rC2W7&M`R&nBY9_!}SQ7|L>3U$3OO7Z*N zKXGG!v(~-d^fA^|aNI0qV(~OBp2ek3u+`;*AY$ktu zaomSyD`3c_XdR_PM)C{DIa7tQ9}Xq%ty%+<+Tz#;hUUQF*iH(6@%#zk=gW%BG692a)C(b!7MM=*@@3c2$F#OTbfS2m-jKBxTi`HCua zRo?Z4K9JRIxnc26o3_C>DSzt^+)nvUOWnvSaQ$9$c|2Z9j#x!<4CqMeV&&5?+EPAN zcmFc|>*FeV6!GE-KOXHVIqkzpbNZMyFX=-Dw%TMq(xb-w<0@>fTOwI2bIswSuaxx#i(h{de4$!Na&|sHj~5pEMy0^z&)}FPL9>8T(GLFRO_h zO6?!REfypsk3Mm^raKpuR5#cr9XAF}#?E#}W|Hi!{T>Sq?k2+dIYs!UL!RKsTOG*U zYJt%BF8gT{l)yw)1NxPl>F(E$=YjSC1+eDo12EujI;Dg5n@ga!a|^`CxoDnCDu`sA zVYo%i0)ZVqRQ`wUE5oNh`2=hXU!YmcJ@Ec37ntJK#&MX&gZoUfcwURGT@MK+Q~Q5w zbu)H)^j7%Jp%=tj0?@MXN9>ph1PHY^5=7PMAWI#{JFwy)_=>(!vX!6Bq1OMqUVV9$ z@wXu3MKJEH`W9Sg3Smd2qFrEg6Km&FL&u6i{n3)<9WXq&7oO038+0t|$IQ5~7`V)+ z=Z{r#=e!FWiWjfD21gj{fU>SVK({Uve%rJRX~rM1Td-*i@O9Y8s~9vVP`bZ zH~v6K)I6hfa2f;Qn37&-Y5F779{d>4vjf?=<8A}Vfu6H=`)ka=e%Z68UD}h;vgtQq zepL|^cf8{Ir{uwz(=KvdtI~xu<8h3j@k1F;^%^)!4fK%olr;=~5Qh}XzOhsm`hziU zHq2;GE0p_6MR2n7G`Lr+)8kt`J5=bXdV?kMnNpApmPKo%I_ZvY21n4tbm-86`bqGx5M0J+MLAMPu%Cf9Yn=H za>ZQ+t<46lxvdK~Sr0-}P8u`Sjv^p=_Dle0>7eL0=eW|_2f&_d-IVV;i_59!Um8V~ z9L;+zP;t*F+`{+`Xg}i)hjcY^2VOtO;JMymfJq{>wrmGH7|X(?R*%4fac+$A_{HGZ z!exS6N+UTtJqO|8Pp`txPA#x};U3^soDOq__v~-Y;>G~!&RphY{$=-3E0p2FnHq?7 z!Vk_1>xsXQErcH?_d>0vyU`cdN8lrSD0^*l3%HZnO6lmzGXqQ7BGeicTym zf)P($IPYxpVBl3}-nj1l)cs%Y7*$3`*)s06E4?Vc{%=;k9;*`bJ=Nlu>t`s=-*b=wZt|cJhxjQQ%$s4TbQsQ>+Si`CvYlP#fo1k~x1$@QT zdEkr6Ah_ckh9(60+ec*Bf(OTjF`TZZ2z?yu!QJe0FnNLz91~bh=|H#EfQKhH!`Hl1 zh|4Ph{FZ&J#<*f|*r(^*%+?tX@UBW0oOo*&Dorwk25pn!H|x*5?#8k3_4G*Q<+Bgn zCacfn2&0GC8Z2MLO47Un-E|lQW8D;T32f${ZW@kW6-C;=omqP`9rySFFcDTZzah?CwnnDe$B^T}wM0qUed6*no|Bu#e6)Y@ zMONl@Ti6t8OnAPvAieHJ5`OblsQa7z_W?xxUIuw9LRaKmh!J0JFW`Ji{)AdCVIsM1 zI-ZW`wqP#tsc1EM=ukPa_i`oSl4CCrJM1QuJ)G=zyiUV&d{6Ln@m6N(DFN>=k4cu_ zRu|b$XOR5pO}uxjPLayPO*v_&l|_zw9PG{dDT~Y$R#3c8mMx~vk!i227n~lu0++Dv zBA=@g(%e%;lQ|E*;&h`AAXIR9%r~ z7#lt-Dlv3MOmcMSjHsAN(aA{;y*0ID7&Qtb`(mn&{c@VKY#R3GG-uf~rC&~Skxf(j zbDE2$j=C~UV`@TjOkB+Ds65`|l*{{Jmt|f0f+pN6B(YdOt|g|1OF4cajYL zUXtOzN;3L)Nya}&GWjma^zS5@{ksb(NrU%lEXut zWw7-hu#2XKx(!VwGHOEjEKPlNI!z}wDm*bhCVo*-Op!x43R1E%R)mo@?eisAo4>92V90R)_ zW5EBX82qR8VKgn|CqL;@ehPK|T@3z2{?1z?X+b~n?uo99_uodL2lYF?a-YlAjC=*j z){L`kmHhh%6@|a4Xcp>%-$lXxhbTDw90kW8qu}&UQTR`5=Wn9m^1CSfiTs_neiH?k zzmGx>>UVtQK9|)hc@$)|>dz?rI6_6?Z>qh8dhg#w!TEjWpG+|LBglVsSEo4h zz+d*kp62W1=szsTZ;0P$@4(REgZ+b?{)%GU@3fmioBoq<{U3x=T{g~q*e^x*wBY|v z@I2a_p9CBICHQ+s`y0Fe>S_O-_*t|WKZ*ar>3=jmnebm({%70!??nHT<=-2{uOt2) z{a;4>pDh2QoBZ1HKU>XzXZe4a=_&thrlr6sM9PACVbhcMTy1ni3OSZxv3>ZnaRca2KveQrFkX#dX6C>L7q;bA+EvtVU9tb zVAH}JeL`J17=gwt2+&|Ly`Gb3Euz3zl3$XTLrB9MkcPwS_jEIu2spDel9UaEr|vh)!3Y*Y9b?2MvRUXs~JIBM2lXn5mgichF)GO0iSaK9nB4L zxJCoFY2nT@g0iOKA-Yzq0eZl}^pK>0AcKhzmc(yFWK1wB zG=OrE(BnjZ3e!HL!V+LwU@;YmRC#D3BTOI#fufF4VFj?{U@^U9{;7k6Xm9{)ZSVs{ zdOyF$GFejzauX0J9Yc&;G7p?0e476LBQ72w+E%;+Yg5pT)nL%(LzERssU?Z=hWN8T zgF+7|=>NVxexF~4&xnxX2_VJ0-~PJErNEbxnw(fkNW&D6hGo@)R$TIYnI*si3{UyX z2`qnG0yH>G-&IJg=hEQINlh%u%gjrUFG?&)#itQeaL)i)lzBSThye&zGczzSff#35 vS)PMvMi6n})4~l5jLZcLhj`#(83C*xkMnR`;o%1f;RoTr8@g3W-ERW`