Python object_detection.builders.hyperparams_builder.KerasLayerHyperparams() Examples
The following are 30
code examples of object_detection.builders.hyperparams_builder.KerasLayerHyperparams().
You can vote up the ones you like or vote down the ones you don't like,
and go to the original project or source file by following the links above each example.
You may also want to check out all available functions/classes of the module
object_detection.builders.hyperparams_builder
, or try the search function
.
Example #1
Source File: hyperparams_builder_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
def test_variance_in_range_with_variance_scaling_initializer_uniform_keras( self): conv_hyperparams_text_proto = """ regularizer { l2_regularizer { } } initializer { variance_scaling_initializer { factor: 2.0 mode: FAN_IN uniform: true } } """ conv_hyperparams_proto = hyperparams_pb2.Hyperparams() text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams_proto) keras_config = hyperparams_builder.KerasLayerHyperparams( conv_hyperparams_proto) initializer = keras_config.params()['kernel_initializer'] self._assert_variance_in_range(initializer, shape=[100, 40], variance=2. / 100.)
Example #2
Source File: hyperparams_builder_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
def test_do_not_use_batch_norm_if_default_keras(self): conv_hyperparams_text_proto = """ regularizer { l2_regularizer { } } initializer { truncated_normal_initializer { } } """ conv_hyperparams_proto = hyperparams_pb2.Hyperparams() text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams_proto) keras_config = hyperparams_builder.KerasLayerHyperparams( conv_hyperparams_proto) self.assertFalse(keras_config.use_batch_norm()) self.assertEqual(keras_config.batch_norm_params(), {}) # The batch norm builder should build an identity Lambda layer identity_layer = keras_config.build_batch_norm() self.assertTrue(isinstance(identity_layer, tf.keras.layers.Lambda))
Example #3
Source File: hyperparams_builder_test.py From BMW-TensorFlow-Training-GUI with Apache License 2.0 | 6 votes |
def test_variance_in_range_with_random_normal_initializer_keras(self): conv_hyperparams_text_proto = """ regularizer { l2_regularizer { } } initializer { random_normal_initializer { mean: 0.0 stddev: 0.8 } } """ conv_hyperparams_proto = hyperparams_pb2.Hyperparams() text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams_proto) keras_config = hyperparams_builder.KerasLayerHyperparams( conv_hyperparams_proto) initializer = keras_config.params()['kernel_initializer'] self._assert_variance_in_range(initializer, shape=[100, 40], variance=0.64, tol=1e-1)
Example #4
Source File: hyperparams_builder_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
def test_return_l2_regularizer_weights_keras(self): conv_hyperparams_text_proto = """ regularizer { l2_regularizer { weight: 0.42 } } initializer { truncated_normal_initializer { } } """ conv_hyperparams_proto = hyperparams_pb2.Hyperparams() text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams_proto) keras_config = hyperparams_builder.KerasLayerHyperparams( conv_hyperparams_proto) regularizer = keras_config.params()['kernel_regularizer'] weights = np.array([1., -1, 4., 2.]) with self.test_session() as sess: result = sess.run(regularizer(tf.constant(weights))) self.assertAllClose(np.power(weights, 2).sum() / 2.0 * 0.42, result)
Example #5
Source File: hyperparams_builder_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
def test_return_l1_regularized_weights_keras(self): conv_hyperparams_text_proto = """ regularizer { l1_regularizer { weight: 0.5 } } initializer { truncated_normal_initializer { } } """ conv_hyperparams_proto = hyperparams_pb2.Hyperparams() text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams_proto) keras_config = hyperparams_builder.KerasLayerHyperparams( conv_hyperparams_proto) regularizer = keras_config.params()['kernel_regularizer'] weights = np.array([1., -1, 4., 2.]) with self.test_session() as sess: result = sess.run(regularizer(tf.constant(weights))) self.assertAllClose(np.abs(weights).sum() * 0.5, result)
Example #6
Source File: hyperparams_builder_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
def test_variance_in_range_with_random_normal_initializer_keras(self): conv_hyperparams_text_proto = """ regularizer { l2_regularizer { } } initializer { random_normal_initializer { mean: 0.0 stddev: 0.8 } } """ conv_hyperparams_proto = hyperparams_pb2.Hyperparams() text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams_proto) keras_config = hyperparams_builder.KerasLayerHyperparams( conv_hyperparams_proto) initializer = keras_config.params()['kernel_initializer'] self._assert_variance_in_range(initializer, shape=[100, 40], variance=0.64, tol=1e-1)
Example #7
Source File: hyperparams_builder_test.py From MAX-Object-Detector with Apache License 2.0 | 6 votes |
def test_return_l1_regularized_weights_keras(self): conv_hyperparams_text_proto = """ regularizer { l1_regularizer { weight: 0.5 } } initializer { truncated_normal_initializer { } } """ conv_hyperparams_proto = hyperparams_pb2.Hyperparams() text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams_proto) keras_config = hyperparams_builder.KerasLayerHyperparams( conv_hyperparams_proto) regularizer = keras_config.params()['kernel_regularizer'] weights = np.array([1., -1, 4., 2.]) with self.test_session() as sess: result = sess.run(regularizer(tf.constant(weights))) self.assertAllClose(np.abs(weights).sum() * 0.5, result)
Example #8
Source File: hyperparams_builder_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
def test_use_relu_6_activation_keras(self): conv_hyperparams_text_proto = """ regularizer { l2_regularizer { } } initializer { truncated_normal_initializer { } } activation: RELU_6 """ conv_hyperparams_proto = hyperparams_pb2.Hyperparams() text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams_proto) keras_config = hyperparams_builder.KerasLayerHyperparams( conv_hyperparams_proto) self.assertEqual(keras_config.params()['activation'], None) self.assertEqual( keras_config.params(include_activation=True)['activation'], tf.nn.relu6) activation_layer = keras_config.build_activation_layer() self.assertTrue(isinstance(activation_layer, tf.keras.layers.Lambda)) self.assertEqual(activation_layer.function, tf.nn.relu6)
Example #9
Source File: hyperparams_builder_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
def test_variance_in_range_with_variance_scaling_initializer_fan_in_keras( self): conv_hyperparams_text_proto = """ regularizer { l2_regularizer { } } initializer { variance_scaling_initializer { factor: 2.0 mode: FAN_IN uniform: false } } """ conv_hyperparams_proto = hyperparams_pb2.Hyperparams() text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams_proto) keras_config = hyperparams_builder.KerasLayerHyperparams( conv_hyperparams_proto) initializer = keras_config.params()['kernel_initializer'] self._assert_variance_in_range(initializer, shape=[100, 40], variance=2. / 100.)
Example #10
Source File: hyperparams_builder_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
def test_variance_in_range_with_variance_scaling_initializer_fan_out_keras( self): conv_hyperparams_text_proto = """ regularizer { l2_regularizer { } } initializer { variance_scaling_initializer { factor: 2.0 mode: FAN_OUT uniform: false } } """ conv_hyperparams_proto = hyperparams_pb2.Hyperparams() text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams_proto) keras_config = hyperparams_builder.KerasLayerHyperparams( conv_hyperparams_proto) initializer = keras_config.params()['kernel_initializer'] self._assert_variance_in_range(initializer, shape=[100, 40], variance=2. / 40.)
Example #11
Source File: hyperparams_builder_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
def test_variance_in_range_with_variance_scaling_initializer_fan_avg_keras( self): conv_hyperparams_text_proto = """ regularizer { l2_regularizer { } } initializer { variance_scaling_initializer { factor: 2.0 mode: FAN_AVG uniform: false } } """ conv_hyperparams_proto = hyperparams_pb2.Hyperparams() text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams_proto) keras_config = hyperparams_builder.KerasLayerHyperparams( conv_hyperparams_proto) initializer = keras_config.params()['kernel_initializer'] self._assert_variance_in_range(initializer, shape=[100, 40], variance=4. / (100. + 40.))
Example #12
Source File: hyperparams_builder_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
def test_variance_in_range_with_variance_scaling_initializer_uniform_keras( self): conv_hyperparams_text_proto = """ regularizer { l2_regularizer { } } initializer { variance_scaling_initializer { factor: 2.0 mode: FAN_IN uniform: true } } """ conv_hyperparams_proto = hyperparams_pb2.Hyperparams() text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams_proto) keras_config = hyperparams_builder.KerasLayerHyperparams( conv_hyperparams_proto) initializer = keras_config.params()['kernel_initializer'] self._assert_variance_in_range(initializer, shape=[100, 40], variance=2. / 100.)
Example #13
Source File: hyperparams_builder_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
def test_variance_in_range_with_truncated_normal_initializer_keras(self): conv_hyperparams_text_proto = """ regularizer { l2_regularizer { } } initializer { truncated_normal_initializer { mean: 0.0 stddev: 0.8 } } """ conv_hyperparams_proto = hyperparams_pb2.Hyperparams() text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams_proto) keras_config = hyperparams_builder.KerasLayerHyperparams( conv_hyperparams_proto) initializer = keras_config.params()['kernel_initializer'] self._assert_variance_in_range(initializer, shape=[100, 40], variance=0.49, tol=1e-1)
Example #14
Source File: ssd_feature_extractor_test.py From MAX-Object-Detector with Apache License 2.0 | 6 votes |
def _build_conv_hyperparams(self): conv_hyperparams = hyperparams_pb2.Hyperparams() conv_hyperparams_text_proto = """ activation: RELU_6 regularizer { l2_regularizer { } } initializer { truncated_normal_initializer { } } batch_norm { scale: false } """ text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams) return hyperparams_builder.KerasLayerHyperparams(conv_hyperparams)
Example #15
Source File: hyperparams_builder_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
def test_use_relu_activation_keras(self): conv_hyperparams_text_proto = """ regularizer { l2_regularizer { } } initializer { truncated_normal_initializer { } } activation: RELU """ conv_hyperparams_proto = hyperparams_pb2.Hyperparams() text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams_proto) keras_config = hyperparams_builder.KerasLayerHyperparams( conv_hyperparams_proto) self.assertEqual(keras_config.params()['activation'], None) self.assertEqual( keras_config.params(include_activation=True)['activation'], tf.nn.relu) activation_layer = keras_config.build_activation_layer() self.assertTrue(isinstance(activation_layer, tf.keras.layers.Lambda)) self.assertEqual(activation_layer.function, tf.nn.relu)
Example #16
Source File: hyperparams_builder_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
def test_variance_in_range_with_truncated_normal_initializer_keras(self): conv_hyperparams_text_proto = """ regularizer { l2_regularizer { } } initializer { truncated_normal_initializer { mean: 0.0 stddev: 0.8 } } """ conv_hyperparams_proto = hyperparams_pb2.Hyperparams() text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams_proto) keras_config = hyperparams_builder.KerasLayerHyperparams( conv_hyperparams_proto) initializer = keras_config.params()['kernel_initializer'] self._assert_variance_in_range(initializer, shape=[100, 40], variance=0.49, tol=1e-1)
Example #17
Source File: hyperparams_builder_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
def test_variance_in_range_with_variance_scaling_initializer_fan_out_keras( self): conv_hyperparams_text_proto = """ regularizer { l2_regularizer { } } initializer { variance_scaling_initializer { factor: 2.0 mode: FAN_OUT uniform: false } } """ conv_hyperparams_proto = hyperparams_pb2.Hyperparams() text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams_proto) keras_config = hyperparams_builder.KerasLayerHyperparams( conv_hyperparams_proto) initializer = keras_config.params()['kernel_initializer'] self._assert_variance_in_range(initializer, shape=[100, 40], variance=2. / 40.)
Example #18
Source File: hyperparams_builder_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
def test_variance_in_range_with_variance_scaling_initializer_fan_in_keras( self): conv_hyperparams_text_proto = """ regularizer { l2_regularizer { } } initializer { variance_scaling_initializer { factor: 2.0 mode: FAN_IN uniform: false } } """ conv_hyperparams_proto = hyperparams_pb2.Hyperparams() text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams_proto) keras_config = hyperparams_builder.KerasLayerHyperparams( conv_hyperparams_proto) initializer = keras_config.params()['kernel_initializer'] self._assert_variance_in_range(initializer, shape=[100, 40], variance=2. / 100.)
Example #19
Source File: hyperparams_builder_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
def test_override_activation_keras(self): conv_hyperparams_text_proto = """ regularizer { l2_regularizer { } } initializer { truncated_normal_initializer { } } activation: RELU_6 """ conv_hyperparams_proto = hyperparams_pb2.Hyperparams() text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams_proto) keras_config = hyperparams_builder.KerasLayerHyperparams( conv_hyperparams_proto) new_params = keras_config.params(activation=tf.nn.relu) self.assertEqual(new_params['activation'], tf.nn.relu)
Example #20
Source File: hyperparams_builder_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
def test_use_relu_6_activation_keras(self): conv_hyperparams_text_proto = """ regularizer { l2_regularizer { } } initializer { truncated_normal_initializer { } } activation: RELU_6 """ conv_hyperparams_proto = hyperparams_pb2.Hyperparams() text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams_proto) keras_config = hyperparams_builder.KerasLayerHyperparams( conv_hyperparams_proto) self.assertEqual(keras_config.params()['activation'], None) self.assertEqual( keras_config.params(include_activation=True)['activation'], tf.nn.relu6) activation_layer = keras_config.build_activation_layer() self.assertTrue(isinstance(activation_layer, tf.keras.layers.Lambda)) self.assertEqual(activation_layer.function, tf.nn.relu6)
Example #21
Source File: hyperparams_builder_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
def test_use_relu_activation_keras(self): conv_hyperparams_text_proto = """ regularizer { l2_regularizer { } } initializer { truncated_normal_initializer { } } activation: RELU """ conv_hyperparams_proto = hyperparams_pb2.Hyperparams() text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams_proto) keras_config = hyperparams_builder.KerasLayerHyperparams( conv_hyperparams_proto) self.assertEqual(keras_config.params()['activation'], None) self.assertEqual( keras_config.params(include_activation=True)['activation'], tf.nn.relu) activation_layer = keras_config.build_activation_layer() self.assertTrue(isinstance(activation_layer, tf.keras.layers.Lambda)) self.assertEqual(activation_layer.function, tf.nn.relu)
Example #22
Source File: hyperparams_builder_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
def test_do_not_use_batch_norm_if_default_keras(self): conv_hyperparams_text_proto = """ regularizer { l2_regularizer { } } initializer { truncated_normal_initializer { } } """ conv_hyperparams_proto = hyperparams_pb2.Hyperparams() text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams_proto) keras_config = hyperparams_builder.KerasLayerHyperparams( conv_hyperparams_proto) self.assertFalse(keras_config.use_batch_norm()) self.assertEqual(keras_config.batch_norm_params(), {}) # The batch norm builder should build an identity Lambda layer identity_layer = keras_config.build_batch_norm() self.assertTrue(isinstance(identity_layer, tf.keras.layers.Lambda))
Example #23
Source File: ssd_feature_extractor_test.py From vehicle_counting_tensorflow with MIT License | 6 votes |
def _build_conv_hyperparams(self): conv_hyperparams = hyperparams_pb2.Hyperparams() conv_hyperparams_text_proto = """ activation: RELU_6 regularizer { l2_regularizer { } } initializer { truncated_normal_initializer { } } batch_norm { scale: false } """ text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams) return hyperparams_builder.KerasLayerHyperparams(conv_hyperparams)
Example #24
Source File: hyperparams_builder_test.py From MAX-Object-Detector with Apache License 2.0 | 6 votes |
def test_return_l2_regularizer_weights_keras(self): conv_hyperparams_text_proto = """ regularizer { l2_regularizer { weight: 0.42 } } initializer { truncated_normal_initializer { } } """ conv_hyperparams_proto = hyperparams_pb2.Hyperparams() text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams_proto) keras_config = hyperparams_builder.KerasLayerHyperparams( conv_hyperparams_proto) regularizer = keras_config.params()['kernel_regularizer'] weights = np.array([1., -1, 4., 2.]) with self.test_session() as sess: result = sess.run(regularizer(tf.constant(weights))) self.assertAllClose(np.power(weights, 2).sum() / 2.0 * 0.42, result)
Example #25
Source File: hyperparams_builder_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
def test_return_l2_regularizer_weights_keras(self): conv_hyperparams_text_proto = """ regularizer { l2_regularizer { weight: 0.42 } } initializer { truncated_normal_initializer { } } """ conv_hyperparams_proto = hyperparams_pb2.Hyperparams() text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams_proto) keras_config = hyperparams_builder.KerasLayerHyperparams( conv_hyperparams_proto) regularizer = keras_config.params()['kernel_regularizer'] weights = np.array([1., -1, 4., 2.]) with self.test_session() as sess: result = sess.run(regularizer(tf.constant(weights))) self.assertAllClose(np.power(weights, 2).sum() / 2.0 * 0.42, result)
Example #26
Source File: hyperparams_builder_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
def test_return_l1_regularized_weights_keras(self): conv_hyperparams_text_proto = """ regularizer { l1_regularizer { weight: 0.5 } } initializer { truncated_normal_initializer { } } """ conv_hyperparams_proto = hyperparams_pb2.Hyperparams() text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams_proto) keras_config = hyperparams_builder.KerasLayerHyperparams( conv_hyperparams_proto) regularizer = keras_config.params()['kernel_regularizer'] weights = np.array([1., -1, 4., 2.]) with self.test_session() as sess: result = sess.run(regularizer(tf.constant(weights))) self.assertAllClose(np.abs(weights).sum() * 0.5, result)
Example #27
Source File: mobilenet_v2_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
def _build_conv_hyperparams(self): conv_hyperparams = hyperparams_pb2.Hyperparams() conv_hyperparams_text_proto = """ activation: RELU_6 regularizer { l2_regularizer { } } initializer { truncated_normal_initializer { } } batch_norm { train: true, scale: false, center: true, decay: 0.2, epsilon: 0.1, } """ text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams) return hyperparams_builder.KerasLayerHyperparams(conv_hyperparams)
Example #28
Source File: resnet_v1_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
def _build_conv_hyperparams(self): conv_hyperparams = hyperparams_pb2.Hyperparams() conv_hyperparams_text_proto = """ activation: RELU_6, regularizer { l2_regularizer { weight: 0.0004 } } initializer { truncated_normal_initializer { stddev: 0.03 mean: 0.0 } } batch_norm { scale: true, decay: 0.997, epsilon: 0.001, } """ text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams) return hyperparams_builder.KerasLayerHyperparams(conv_hyperparams)
Example #29
Source File: mobilenet_v2_test.py From MAX-Object-Detector with Apache License 2.0 | 6 votes |
def _build_conv_hyperparams(self): conv_hyperparams = hyperparams_pb2.Hyperparams() conv_hyperparams_text_proto = """ activation: RELU_6 regularizer { l2_regularizer { } } initializer { truncated_normal_initializer { } } batch_norm { train: true, scale: false, center: true, decay: 0.2, epsilon: 0.1, } """ text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams) return hyperparams_builder.KerasLayerHyperparams(conv_hyperparams)
Example #30
Source File: ssd_feature_extractor_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
def _build_conv_hyperparams(self, add_batch_norm=True): conv_hyperparams = hyperparams_pb2.Hyperparams() conv_hyperparams_text_proto = """ activation: RELU_6 regularizer { l2_regularizer { } } initializer { truncated_normal_initializer { } } """ if add_batch_norm: batch_norm_proto = """ batch_norm { scale: false } """ conv_hyperparams_text_proto += batch_norm_proto text_format.Merge(conv_hyperparams_text_proto, conv_hyperparams) return hyperparams_builder.KerasLayerHyperparams(conv_hyperparams)