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# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Tests for factory functions."""
# Import libraries
from absl.testing import parameterized
import tensorflow as tf, tf_keras
from tensorflow.python.distribute import combinations
from official.vision.configs import backbones as backbones_cfg
from official.vision.configs import backbones_3d as backbones_3d_cfg
from official.vision.configs import common as common_cfg
from official.vision.modeling import backbones
from official.vision.modeling.backbones import factory
class FactoryTest(tf.test.TestCase, parameterized.TestCase):
@combinations.generate(
combinations.combine(model_id=[18, 34, 50, 101, 152],))
def test_resnet_creation(self, model_id):
"""Test creation of ResNet models."""
network = backbones.ResNet(
model_id=model_id, se_ratio=0.0, norm_momentum=0.99, norm_epsilon=1e-5)
backbone_config = backbones_cfg.Backbone(
type='resnet',
resnet=backbones_cfg.ResNet(model_id=model_id, se_ratio=0.0))
norm_activation_config = common_cfg.NormActivation(
norm_momentum=0.99, norm_epsilon=1e-5, use_sync_bn=False)
factory_network = factory.build_backbone(
input_specs=tf_keras.layers.InputSpec(shape=[None, None, None, 3]),
backbone_config=backbone_config,
norm_activation_config=norm_activation_config)
network_config = network.get_config()
factory_network_config = factory_network.get_config()
self.assertEqual(network_config, factory_network_config)
@combinations.generate(
combinations.combine(
model_id=['b0', 'b1', 'b2', 'b3', 'b4', 'b5', 'b6', 'b7'],
se_ratio=[0.0, 0.25],
))
def test_efficientnet_creation(self, model_id, se_ratio):
"""Test creation of EfficientNet models."""
network = backbones.EfficientNet(
model_id=model_id,
se_ratio=se_ratio,
norm_momentum=0.99,
norm_epsilon=1e-5)
backbone_config = backbones_cfg.Backbone(
type='efficientnet',
efficientnet=backbones_cfg.EfficientNet(
model_id=model_id, se_ratio=se_ratio))
norm_activation_config = common_cfg.NormActivation(
norm_momentum=0.99, norm_epsilon=1e-5, use_sync_bn=False)
factory_network = factory.build_backbone(
input_specs=tf_keras.layers.InputSpec(shape=[None, None, None, 3]),
backbone_config=backbone_config,
norm_activation_config=norm_activation_config)
network_config = network.get_config()
factory_network_config = factory_network.get_config()
self.assertEqual(network_config, factory_network_config)
@combinations.generate(
combinations.combine(
model_id=['MobileNetV1', 'MobileNetV2',
'MobileNetV3Large', 'MobileNetV3Small',
'MobileNetV3EdgeTPU'],
filter_size_scale=[1.0, 0.75],
))
def test_mobilenet_creation(self, model_id, filter_size_scale):
"""Test creation of Mobilenet models."""
network = backbones.MobileNet(
model_id=model_id,
filter_size_scale=filter_size_scale,
norm_momentum=0.99,
norm_epsilon=1e-5)
backbone_config = backbones_cfg.Backbone(
type='mobilenet',
mobilenet=backbones_cfg.MobileNet(
model_id=model_id, filter_size_scale=filter_size_scale))
norm_activation_config = common_cfg.NormActivation(
norm_momentum=0.99, norm_epsilon=1e-5, use_sync_bn=False)
factory_network = factory.build_backbone(
input_specs=tf_keras.layers.InputSpec(shape=[None, None, None, 3]),
backbone_config=backbone_config,
norm_activation_config=norm_activation_config)
network_config = network.get_config()
factory_network_config = factory_network.get_config()
self.assertEqual(network_config, factory_network_config)
@combinations.generate(combinations.combine(model_id=['49'],))
def test_spinenet_creation(self, model_id):
"""Test creation of SpineNet models."""
input_size = 128
min_level = 3
max_level = 7
input_specs = tf_keras.layers.InputSpec(
shape=[None, input_size, input_size, 3])
network = backbones.SpineNet(
input_specs=input_specs,
min_level=min_level,
max_level=max_level,
norm_momentum=0.99,
norm_epsilon=1e-5)
backbone_config = backbones_cfg.Backbone(
type='spinenet',
spinenet=backbones_cfg.SpineNet(model_id=model_id))
norm_activation_config = common_cfg.NormActivation(
norm_momentum=0.99, norm_epsilon=1e-5, use_sync_bn=False)
factory_network = factory.build_backbone(
input_specs=tf_keras.layers.InputSpec(
shape=[None, input_size, input_size, 3]),
backbone_config=backbone_config,
norm_activation_config=norm_activation_config)
network_config = network.get_config()
factory_network_config = factory_network.get_config()
self.assertEqual(network_config, factory_network_config)
@combinations.generate(
combinations.combine(model_id=[38, 56, 104],))
def test_revnet_creation(self, model_id):
"""Test creation of RevNet models."""
network = backbones.RevNet(
model_id=model_id, norm_momentum=0.99, norm_epsilon=1e-5)
backbone_config = backbones_cfg.Backbone(
type='revnet',
revnet=backbones_cfg.RevNet(model_id=model_id))
norm_activation_config = common_cfg.NormActivation(
norm_momentum=0.99, norm_epsilon=1e-5, use_sync_bn=False)
factory_network = factory.build_backbone(
input_specs=tf_keras.layers.InputSpec(shape=[None, None, None, 3]),
backbone_config=backbone_config,
norm_activation_config=norm_activation_config)
network_config = network.get_config()
factory_network_config = factory_network.get_config()
self.assertEqual(network_config, factory_network_config)
@combinations.generate(combinations.combine(model_type=['resnet_3d'],))
def test_resnet_3d_creation(self, model_type):
"""Test creation of ResNet 3D models."""
backbone_cfg = backbones_3d_cfg.Backbone3D(type=model_type).get()
temporal_strides = []
temporal_kernel_sizes = []
for block_spec in backbone_cfg.block_specs:
temporal_strides.append(block_spec.temporal_strides)
temporal_kernel_sizes.append(block_spec.temporal_kernel_sizes)
_ = backbones.ResNet3D(
model_id=backbone_cfg.model_id,
temporal_strides=temporal_strides,
temporal_kernel_sizes=temporal_kernel_sizes,
norm_momentum=0.99,
norm_epsilon=1e-5)
@combinations.generate(
combinations.combine(
model_id=[
'MobileDetCPU',
'MobileDetDSP',
'MobileDetEdgeTPU',
'MobileDetGPU'],
filter_size_scale=[1.0, 0.75],
))
def test_mobiledet_creation(self, model_id, filter_size_scale):
"""Test creation of Mobiledet models."""
network = backbones.MobileDet(
model_id=model_id,
filter_size_scale=filter_size_scale,
norm_momentum=0.99,
norm_epsilon=1e-5)
backbone_config = backbones_cfg.Backbone(
type='mobiledet',
mobiledet=backbones_cfg.MobileDet(
model_id=model_id, filter_size_scale=filter_size_scale))
norm_activation_config = common_cfg.NormActivation(
norm_momentum=0.99, norm_epsilon=1e-5, use_sync_bn=False)
factory_network = factory.build_backbone(
input_specs=tf_keras.layers.InputSpec(shape=[None, None, None, 3]),
backbone_config=backbone_config,
norm_activation_config=norm_activation_config)
network_config = network.get_config()
factory_network_config = factory_network.get_config()
self.assertEqual(network_config, factory_network_config)
if __name__ == '__main__':
tf.test.main()
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