def test_lock(self):
params = params_dict.ParamsDict({'a': 1, 'b': 2})
params.lock()
with self.assertRaises(ValueError):
params.a = 10
with self.assertRaises(ValueError):
params.override({'b': 20})
def test_init_from_an_empty_dict(self):
params = params_dict.ParamsDict()
with self.assertRaises(AttributeError):
_ = params.a
with self.assertRaises(KeyError):
params.a = 'aa'
def test_setattr(self):
params = params_dict.ParamsDict()
params.override({'a': 'aa', 'b': 2, 'c': None}, is_strict=False)
params.c = 'ccc'
self.assertEqual(params.a, 'aa')
self.assertEqual(params.b, 2)
self.assertEqual(params.c, 'ccc')
def __init__(self, params):
"""Creates the consine learning rate tensor with linear warmup."""
super(CosineLearningRateWithLinearWarmup, self).__init__()
assert isinstance(params, (dict, params_dict.ParamsDict))
if isinstance(params, dict):
params = params_dict.ParamsDict(params)
self._params = params
def config_generator(model):
"""Model function generator."""
if model == 'retinanet':
default_config = retinanet_config.RETINANET_CFG
restrictions = retinanet_config.RETINANET_RESTRICTIONS
elif model == 'mask_rcnn':
default_config = maskrcnn_config.MASKRCNN_CFG
restrictions = maskrcnn_config.MASKRCNN_RESTRICTIONS
else:
raise ValueError('Model %s is not supported.' % model)
return params_dict.ParamsDict(default_config, restrictions)
def test_validate(self):
# Raise error due to the unknown parameter.
with self.assertRaises(KeyError):
params = params_dict.ParamsDict({
'a': 1,
'b': {
'a': 11
}
}, ['a == c'])
# OK to check equality of two nested dicts.
params = params_dict.ParamsDict(
{
'a': 1,
'b': {
'a': 10
},
'c': {
'a': 10
}
}, ['b == c'])
# Raise error due to inconsistency
with self.assertRaises(KeyError):
params = params_dict.ParamsDict({
'a': 1,
'c': {
'a': 10
}
}, ['a == c.a'])
# Valid rule.
params = params_dict.ParamsDict({'a': 1, 'c': {'a': 1}}, ['a == c.a'])
# Overridding violates the existing rule, raise error upon validate.
params.override({'a': 11})
with self.assertRaises(KeyError):
params.validate()
def test_as_dict(self):
params = params_dict.ParamsDict({
'a': 'aa',
'b': 2,
'c': {
'c1': 10,
'c2': 20
}
})
params_d = params.as_dict()
self.assertEqual(params_d['a'], 'aa')
self.assertEqual(params_d['b'], 2)
self.assertEqual(params_d['c']['c1'], 10)
self.assertEqual(params_d['c']['c2'], 20)
def test_override_is_strict_false(self):
params = params_dict.ParamsDict({
'a': 'aa',
'b': 2,
'c': {
'c1': 10,
'c2': 20
}
})
params.override({'a': 2, 'c': {'c3': 3000}}, is_strict=False)
self.assertEqual(params.a, 2)
self.assertEqual(params.c.c3, 3000)
params.override({'d': 'ddd'}, is_strict=False)
self.assertEqual(params.d, 'ddd')
params.override({'c': {'c4': 4444}}, is_strict=False)
self.assertEqual(params.c.c4, 4444)
def test_override_is_strict_true(self):
params = params_dict.ParamsDict({
'a': 'aa',
'b': 2,
'c': {
'c1': 'cc',
'c2': 20
}
})
params.override({'a': 2, 'c': {'c1': 'ccc'}}, is_strict=True)
self.assertEqual(params.a, 2)
self.assertEqual(params.c.c1, 'ccc')
with self.assertRaises(KeyError):
params.override({'d': 'ddd'}, is_strict=True)
with self.assertRaises(KeyError):
params.override({'c': {'c3': 30}}, is_strict=True)
def test_override_params_dict_using_yaml_string(self):
params = params_dict.ParamsDict({
'a': 1,
'b': 2.5,
'c': [3, 4],
'd': 'hello',
'e': False
})
override_yaml_string = "'b': 5.2\n'c': [30, 40]"
params = params_dict.override_params_dict(params,
override_yaml_string,
is_strict=True)
self.assertEqual(1, params.a)
self.assertEqual(5.2, params.b)
self.assertEqual([30, 40], params.c)
self.assertEqual('hello', params.d)
self.assertEqual(False, params.e)
def test_save_params_dict_to_yaml(self):
params = params_dict.ParamsDict({
'a': 'aa',
'b': 2,
'c': {
'c1': 10,
'c2': 20
}
})
output_yaml_file = os.path.join(self.get_temp_dir(), 'params.yaml')
params_dict.save_params_dict_to_yaml(params, output_yaml_file)
with tf.io.gfile.GFile(output_yaml_file, 'r') as f:
params_d = yaml.load(f)
self.assertEqual(params.a, params_d['a'])
self.assertEqual(params.b, params_d['b'])
self.assertEqual(params.c.c1, params_d['c']['c1'])
self.assertEqual(params.c.c2, params_d['c']['c2'])
def test_override_params_dict_using_yaml_file(self):
params = params_dict.ParamsDict({
'a': 1,
'b': 2.5,
'c': [3, 4],
'd': 'hello',
'e': False
})
override_yaml_file = self.write_temp_file(
'params.yaml', r"""
b: 5.2
c: [30, 40]
""")
params = params_dict.override_params_dict(params,
override_yaml_file,
is_strict=True)
self.assertEqual(1, params.a)
self.assertEqual(5.2, params.b)
self.assertEqual([30, 40], params.c)
self.assertEqual('hello', params.d)
self.assertEqual(False, params.e)
def test_override_params_dict_using_csv_string(self):
params = params_dict.ParamsDict({
'a': 1,
'b': {
'b1': 2,
'b2': [2, 3],
},
'd': {
'd1': {
'd2': 'hello'
}
},
'e': False
})
override_csv_string = "b.b2=[3,4], d.d1.d2='hi, world', e=gs://test"
params = params_dict.override_params_dict(params,
override_csv_string,
is_strict=True)
self.assertEqual(1, params.a)
self.assertEqual(2, params.b.b1)
self.assertEqual([3, 4], params.b.b2)
self.assertEqual('hi, world', params.d.d1.d2)
self.assertEqual('gs://test', params.e)
def test_override_params_dict_using_json_string(self):
params = params_dict.ParamsDict({
'a': 1,
'b': {
'b1': 2,
'b2': [2, 3],
},
'd': {
'd1': {
'd2': 'hello'
}
},
'e': False
})
override_json_string = "{ b: { b2: [3, 4] }, d: { d1: { d2: 'hi' } } }"
params = params_dict.override_params_dict(params,
override_json_string,
is_strict=True)
self.assertEqual(1, params.a)
self.assertEqual(2, params.b.b1)
self.assertEqual([3, 4], params.b.b2)
self.assertEqual('hi', params.d.d1.d2)
self.assertEqual(False, params.e)
def test_get(self):
params = params_dict.ParamsDict()
params.override({'a': 'aa'}, is_strict=False)
self.assertEqual(params.get('a'), 'aa')
self.assertEqual(params.get('b', 2), 2)
self.assertEqual(params.get('b'), None)
def test_contains(self):
params = params_dict.ParamsDict()
params.override({'a': 'aa'}, is_strict=False)
self.assertIn('a', params)
self.assertNotIn('b', params)
def test_init_from_a_param_dict(self):
params_init = params_dict.ParamsDict({'a': 'aa', 'b': 2})
params = params_dict.ParamsDict(params_init)
self.assertEqual(params.a, 'aa')
self.assertEqual(params.b, 2)
# 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.
# ==============================================================================
"""Config template to train Mask R-CNN."""
from modeling.hyperparams import params_dict
from configs import base_config
# pylint: disable=line-too-long
MASKRCNN_CFG = params_dict.ParamsDict(base_config.BASE_CFG)
MASKRCNN_CFG.override(
{
'type': 'mask_rcnn',
'eval': {
'type': 'box_and_mask',
'num_images_to_visualize': 0,
},
'architecture': {
'parser': 'maskrcnn_parser',
'backbone': 'resnet',
'multilevel_features': 'fpn',
'use_bfloat16': True,
'include_mask': True,
},
'maskrcnn_parser': {
