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## input image dimensions
img_x, img_y = 28, 28

## load Fashion-MNIST data set directly
(x_train, y_train), (x_test, y_test) = fashion_mnist.load_data()

## reshape the data into a 4D tensor (sample_number, x_img, y_img, num_channels)
## there is only 1 channel in Fashion-MNIST
x_train = x_train.reshape(x_train.shape[0], img_x, img_y, 1)
x_test = x_test.reshape(x_test.shape[0], img_x, img_y, 1)

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## normalize data
x_train = x_train.astype('float32')
x_test = x_test.astype('float32')
x_train /= 255
x_test /= 255

# convert class vectors to binary class matrices
y_train = keras.utils.to_categorical(y_train, num_classes)
y_test = keras.utils.to_categorical(y_test, num_classes)

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# define CNN (LeNet)
model = Sequential()

## layer 1
model.add(Conv2D(32, kernel_size = (5, 5), strides = (1, 1),
    activation = 'relu', input_shape = input_shape))
model.add(MaxPooling2D(pool_size = (2, 2), strides = (2, 2)))

## layer 2
model.add(Conv2D(64, (5, 5), activation = 'relu'))

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model.compile(loss = keras.losses.categorical_crossentropy, 
              optimizer = keras.optimizers.Adam(), metrics = ['accuracy'])

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# training model
model.fit(x_train, y_train, batch_size = batch_size,
          epochs = epochs,
          verbose = 1,
          validation_data = (x_test, y_test),
          callbacks = [history])

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# logging metrics
class AccuracyHistory(keras.callbacks.Callback):
    def on_train_begin(self, logs = {}):
        self.acc = []

    def on_epoch_end(self, batch, logs = {}):
        self.acc.append(logs.get('acc'))

history = AccuracyHistory()

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import json
import hashlib
import datetime

class Blockchain(object):
    def __init__(self):
        self.chain = []

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class Blockchain(object):
    def __init__(self):
        """
        Initializes the Blockchain
        """
        self.chain = []
        genesis_block = self.new_block(previous_hash='0', nonce=0)

        # Mining first block (genesis block)
        self.chain.append(self.proof_of_work(genesis_block))

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@staticmethod
def hash(block):
    """
    Creates a SHA-256 hash of a Block
    :param block: block data
    :return:
    """
    block_string = json.dumps(block, sort_keys=True).encode()
    return hashlib.sha256(block_string).hexdigest()

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def proof_of_work(self, last_nonce):
    """
    Simple Proof of Work Algorithm:
    :param last_nonce: the last nonce
    :return:
    """
    nonce = 0
    while self.check_valid_nonce(last_nonce, nonce) is False:
        nonce += 1