def test_pickle_save_restore(self, m_cdg_setupNetwork):
# Mocking set_network so we don't have to worry about actually
# initializing any caffe things for this test.
expected_params = {
'network_prototxt': DataMemoryElement(),
'network_model': DataMemoryElement(),
'image_mean': DataMemoryElement(),
'return_layer': 'layer name',
'batch_size': 777,
'use_gpu': False,
'gpu_device_id': 8,
'network_is_bgr': False,
'data_layer': 'data-other',
'load_truncated_images': True,
'pixel_rescale': (.2, .8),
'input_scale': 1.5,
}
g = CaffeDescriptorGenerator(**expected_params)
# Initialization sets up the network on construction.
self.assertEqual(m_cdg_setupNetwork.call_count, 1)
g_pickled = pickle.dumps(g, -1)
g2 = pickle.loads(g_pickled)
# Network should be setup for second class class just like in
# initial construction.
self.assertEqual(m_cdg_setupNetwork.call_count, 2)
self.assertIsInstance(g2, CaffeDescriptorGenerator)
self.assertEqual(g.get_config(), g2.get_config())
def test_get_config(self, _m_cdg_setupNetwork):
# Mocking set_network so we don't have to worry about actually
# initializing any caffe things for this test.
expected_params = {
'network_prototxt': DataMemoryElement(),
'network_model': DataMemoryElement(),
'image_mean': DataMemoryElement(),
'return_layer': 'layer name',
'batch_size': 777,
'use_gpu': False,
'gpu_device_id': 8,
'network_is_bgr': False,
'data_layer': 'data-other',
'load_truncated_images': True,
'pixel_rescale': (.2, .8),
'input_scale': 1.5,
}
# make sure that we're considering all constructor parameter options
expected_param_keys = \
set(inspect.getargspec(CaffeDescriptorGenerator.__init__)
.args[1:])
self.assertSetEqual(set(expected_params.keys()),
expected_param_keys)
g = CaffeDescriptorGenerator(**expected_params)
for key in ('network_prototxt', 'network_model', 'image_mean'):
expected_params[key] = to_config_dict(expected_params[key])
self.assertEqual(g.get_config(), expected_params)
def test_get_config(self, _m_cdg_setupNetwork):
# Mocking set_network so we don't have to worry about actually
# initializing any caffe things for this test.
expected_params = {
'network_prototxt': DataMemoryElement(),
'network_model': DataMemoryElement(),
'image_mean': DataMemoryElement(),
'return_layer': 'layer name',
'batch_size': 777,
'use_gpu': False,
'gpu_device_id': 8,
'network_is_bgr': False,
'data_layer': 'data-other',
'load_truncated_images': True,
'pixel_rescale': (.2, .8),
'input_scale': 1.5,
'threads': 14,
}
# make sure that we're considering all constructor parameter
# options
default_params = CaffeDescriptorGenerator.get_default_config()
assert set(default_params) == set(expected_params)
g = CaffeDescriptorGenerator(**expected_params)
# Shift to expecting sub-configs for DataElement params
for key in ('network_prototxt', 'network_model', 'image_mean'):
expected_params[key] = to_config_dict(expected_params[key])
assert g.get_config() == expected_params
def test_config_cycle_imagemean_nonetyped(self, m_cdg_setup_network):
"""
Test being able to get an instances config and use that config to
construct an equivalently parameterized instance where the second
instance is configured with a None-typed 'image_mean' parameter.
"""
# Mocking ``_setup_network`` so no caffe functionality is hit during
# this test
# Only required parameters, image_mean is empty SMQTK configuration
# dict
g1 = CaffeDescriptorGenerator(self.dummy_net_topo_elem,
self.dummy_caffe_model_elem)
g1_config = g1.get_config()
# Modify config for g2 to pass None for image_mean
for_g2 = dict(g1_config)
for_g2['image_mean'] = {'type': None}
g2 = CaffeDescriptorGenerator.from_config(for_g2)
expected_config = {
'network_prototxt': to_config_dict(self.dummy_net_topo_elem),
'network_model': to_config_dict(self.dummy_caffe_model_elem),
'image_mean': None,
'return_layer': 'fc7',
'batch_size': 1,
'use_gpu': False,
'gpu_device_id': 0,
'network_is_bgr': True,
'data_layer': 'data',
'load_truncated_images': False,
'pixel_rescale': None,
'input_scale': None,
'threads': None,
}
assert g1_config == g2.get_config() == expected_config
def test_pickle_save_restore(self, m_cdg_setupNetwork):
# Mocking set_network so we don't have to worry about actually
# initializing any caffe things for this test.
expected_params = {
'network_prototxt_uri': 'some_prototxt_uri',
'network_model_uri': 'some_caffemodel_uri',
'image_mean_uri': 'some_imagemean_uri',
'return_layer': 'layer name',
'batch_size': 777,
'use_gpu': False,
'gpu_device_id': 8,
'network_is_bgr': False,
'data_layer': 'data-other',
'load_truncated_images': True,
'pixel_rescale': (.2, .8),
'input_scale': 1.5,
}
g = CaffeDescriptorGenerator(**expected_params)
# Initialization sets up the network on construction.
self.assertEqual(m_cdg_setupNetwork.call_count, 1)
g_pickled = pickle.dumps(g, -1)
g2 = pickle.loads(g_pickled)
# Network should be setup for second class class just like in
# initial construction.
self.assertEqual(m_cdg_setupNetwork.call_count, 2)
self.assertIsInstance(g2, CaffeDescriptorGenerator)
self.assertEqual(g.get_config(), g2.get_config())
def test_get_config(self, _m_cdg_setupNetwork):
# Mocking set_network so we don't have to worry about actually
# initializing any caffe things for this test.
expected_params = {
'network_prototxt_uri': 'some_prototxt_uri',
'network_model_uri': 'some_caffemodel_uri',
'image_mean_uri': 'some_imagemean_uri',
'return_layer': 'layer name',
'batch_size': 777,
'use_gpu': False,
'gpu_device_id': 8,
'network_is_bgr': False,
'data_layer': 'data-other',
'load_truncated_images': True,
'pixel_rescale': (.2, .8),
'input_scale': 1.5,
}
# make sure that we're considering all constructor parameter options
expected_param_keys = \
set(inspect.getargspec(CaffeDescriptorGenerator.__init__)
.args[1:])
self.assertSetEqual(set(expected_params.keys()),
expected_param_keys)
g = CaffeDescriptorGenerator(**expected_params)
self.assertEqual(g.get_config(), expected_params)
