rocking5566

import numpy as np
import tensorflow as tf
from tensorflow.keras.datasets import mnist
from tensorflow.keras.utils import to_categorical
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Activation, Conv2D, Flatten
from tensorflow.keras.optimizers import RMSprop

# download the mnist to the path '~/.keras/datasets/' if it is the first time to be called
# X shape (60,000 28x28), y shape (10,000, )

alanwells

def custom_train(cfg, tub_names, model_name):
    '''
    use the specified data in tub_names to train an artifical neural network
    saves the output trained model as model_name
    '''
    import sklearn
    from sklearn.model_selection import train_test_split
    from sklearn.utils import shuffle
    import random
    from PIL import Image