def create_mlp():
# define the model layers
relu_layer1 = Dense(input_size=784,
output_size=1000,
activation='rectifier')
relu_layer2 = Dense(inputs_hook=(1000, relu_layer1.get_outputs()),
output_size=1000,
activation='rectifier')
class_layer3 = SoftmaxLayer(inputs_hook=(1000, relu_layer2.get_outputs()),
output_size=10,
out_as_probs=False)
# add the layers as a Prototype
mlp = Prototype(layers=[relu_layer1, relu_layer2, class_layer3])
mnist = MNIST()
optimizer = AdaDelta(model=mlp, dataset=mnist, epochs=20)
optimizer.train()
test_data, test_labels = mnist.test_inputs[:25], mnist.test_targets[:25]
# use the run function!
preds = mlp.run(test_data)
log.info('-------')
log.info("predicted: %s", str(preds))
log.info("actual: %s", str(test_labels.astype('int32')))
def add_list_layers():
# You can also add lists of layers at a time (or as initialization) to a Prototype! This lets you specify
# more complex interactions between layers!
hidden1 = Dense(input_size=28*28,
output_size=512,
activation='rectifier',
noise='dropout')
hidden2 = Dense(inputs_hook=(512, hidden1.get_outputs()),
output_size=512,
activation='rectifier',
noise='dropout')
class_layer = SoftmaxLayer(inputs_hook=(512, hidden2.get_outputs()),
output_size=10)
mlp = Prototype([hidden1, hidden2, class_layer])
return mlp
def create_mlp():
# define the model layers
relu_layer1 = Dense(input_size=784, output_size=1000, activation='rectifier')
relu_layer2 = Dense(inputs_hook=(1000, relu_layer1.get_outputs()), output_size=1000, activation='rectifier')
class_layer3 = SoftmaxLayer(inputs_hook=(1000, relu_layer2.get_outputs()), output_size=10, out_as_probs=False)
# add the layers as a Prototype
mlp = Prototype(layers=[relu_layer1, relu_layer2, class_layer3])
mnist = MNIST()
optimizer = AdaDelta(model=mlp, dataset=mnist, epochs=20)
optimizer.train()
test_data, test_labels = mnist.test_inputs[:25], mnist.test_targets[:25]
# use the run function!
preds = mlp.run(test_data)
log.info('-------')
log.info("predicted: %s",str(preds))
log.info("actual: %s",str(test_labels.astype('int32')))
