def test_serialize_deserialize(self, model_id):
# Create a network object that sets all of its config options.
kwargs = dict(
model_id=model_id,
filter_size_scale=1.0,
use_sync_bn=False,
kernel_initializer='VarianceScaling',
kernel_regularizer=None,
bias_regularizer=None,
norm_momentum=0.99,
norm_epsilon=0.001,
min_depth=8,
divisible_by=8,
regularize_depthwise=False,
)
network = mobiledet.MobileDet(**kwargs)
expected_config = dict(kwargs)
self.assertEqual(network.get_config(), expected_config)
# Create another network object from the first object's config.
new_network = mobiledet.MobileDet.from_config(network.get_config())
# Validate that the config can be forced to JSON.
_ = new_network.to_json()
# If the serialization was successful, the new config should match the old.
self.assertAllEqual(network.get_config(), new_network.get_config())
def test_input_specs(self, input_dim, model_id):
"""Test different input feature dimensions."""
tf.keras.backend.set_image_data_format('channels_last')
input_specs = tf.keras.layers.InputSpec(
shape=[None, None, None, input_dim])
network = mobiledet.MobileDet(model_id=model_id,
input_specs=input_specs)
inputs = tf.keras.Input(shape=(128, 128, input_dim), batch_size=1)
_ = network(inputs)
def test_mobiledet_creation(self, model_id, input_size):
"""Test creation of MobileDet family models."""
tf.keras.backend.set_image_data_format('channels_last')
mobiledet_layers = {
# The number of filters of layers having outputs been collected
# for filter_size_scale = 1.0
'MobileDetCPU': [8, 16, 32, 72, 144],
'MobileDetDSP': [24, 32, 64, 144, 240],
'MobileDetEdgeTPU': [16, 16, 40, 96, 384],
'MobileDetGPU': [16, 32, 64, 128, 384],
}
network = mobiledet.MobileDet(model_id=model_id, filter_size_scale=1.0)
inputs = tf.keras.Input(shape=(input_size, input_size, 3),
batch_size=1)
endpoints = network(inputs)
for idx, num_filter in enumerate(mobiledet_layers[model_id]):
self.assertAllEqual([
1, input_size / 2**(idx + 1), input_size / 2**(idx + 1),
num_filter
], endpoints[str(idx + 1)].shape.as_list())