CNTK_MNIST_Create_CNN.py

'''
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Constructing the Convolutional Neural Network
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'''
def create_convolutional_neural_network(input_vars, out_dims, dropout_prob=0.0):

    convolutional_layer_1 = Convolution((5, 5), 32, strides=1, activation=cntk.ops.relu, pad=True)(input_vars)
    pooling_layer_1 = MaxPooling((2, 2), strides=(2, 2), pad=True)(convolutional_layer_1)

    convolutional_layer_2 = Convolution((5, 5), 64, strides=1, activation=cntk.ops.relu, pad=True)(pooling_layer_1)
    pooling_layer_2 = MaxPooling((2, 2), strides=(2, 2), pad=True)(convolutional_layer_2)

    fully_connected_layer = Dense(1024, activation=cntk.ops.relu)(pooling_layer_2)
    dropout_layer = Dropout(dropout_prob)(fully_connected_layer)
    output_layer = Dense(out_dims, activation=None)(dropout_layer)

    return output_layer

# Define the input to the neural network
input_vars = cntk.ops.input_variable(image_shape, np.float32)

# Create the convolutional neural network
output = create_convolutional_neural_network(input_vars, output_dim, dropout_prob=0.5)