def default_hparams(input_shape, num_classes):
hp = {}
# [general]
kernel_size = Range("kernel_size", 3, 5, 2, group="general")
hp["kernel_size"] = (kernel_size, kernel_size)
hp["initial_strides"] = (2, 2)
hp["activation"] = Choice("activation", ["relu", "selu"], group="general")
hp["learning_rate"] = Choice("learning_rate", [.001, .0001, .00001],
group="general")
# [entry flow]
# -conv2d
hp["conv2d_num_filters"] = Choice("num_filters", [32, 64, 128],
group="conv2d")
# seprarable block > not an exact match to the paper
hp["sep_num_filters"] = Range("num_filters",
128,
768,
128,
group="entry_flow")
# [Middle Flow]
hp["num_residual_blocks"] = Range("num_residual_blocks",
2,
8,
group="middle_flow")
# [Exit Flow]
hp["dense_merge_type"] = Choice("merge_type", ["avg", "flatten", "max"],
group="exit_flow")
hp["num_dense_layers"] = Range("dense_layers", 1, 3, group="exit_flow")
hp["dropout_rate"] = Linear("dropout",
start=0.0,
stop=0.5,
num_buckets=6,
precision=1,
group="exit_flow")
hp["dense_use_bn"] = Choice("batch_normalization", [True, False],
"exit_flow")
return hp
def model_fn():
"Model with hyper-parameters"
# Hyper-parameters are defined as normal python variables
DIMS = Range('dims', 2, 4, 2, group='layers')
ACTIVATION = Choice('activation', ['relu', 'tanh'], group="layers")
EXTRA_LAYER = Boolean('extra_layer', group="layers")
LR = Choice('lr', [0.01, 0.001, 0.0001], group="optimizer")
# converting a model to a tunable model is a simple as replacing static
# values with the hyper parameters variables.
model = Sequential()
model.add(Dense(DIMS, input_shape=(1, )))
model.add(Dense(DIMS, activation=ACTIVATION))
if EXTRA_LAYER:
model.add(Dense(DIMS, activation=ACTIVATION))
model.add(Dense(1, activation='sigmoid'))
optimizer = Adam(LR)
model.compile(optimizer=optimizer,
loss="binary_crossentropy",
metrics=['acc'])
return model
def test_range_incr_larger_than_range():
with pytest.raises(ValueError):
Range('test_range_incr_larger_than_range', 1, 3, 10)
def test_range_stop_larger_than_start():
with pytest.raises(ValueError):
Range('test_range_stop_larger_than_start', 3, 1)
def test_range_invalid_increment():
with pytest.raises(ValueError):
Range('test_range_invalid_increment', 1, 3, 'a')
def test_range_invalid_stop():
with pytest.raises(ValueError):
Range('test_range_invalid_stop', 1, 'a', 4)
def test_range_invalid_start():
with pytest.raises(ValueError):
Range('test_range_invalid_start', 'a', 3, 4)
def test_range():
assert Range('test_range', 7, 20, 5) == 7