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': {