本文整理汇总了Python中object_detection.builders.hyperparams_builder.KerasLayerHyperparams方法的典型用法代码示例。如果您正苦于以下问题：Python hyperparams_builder.KerasLayerHyperparams方法的具体用法？Python hyperparams_builder.KerasLayerHyperparams怎么用？Python hyperparams_builder.KerasLayerHyperparams使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类object_detection.builders.hyperparams_builder的用法示例。
在下文中一共展示了hyperparams_builder.KerasLayerHyperparams方法的15个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: _build_conv_hyperparams
# 需要导入模块: from object_detection.builders import hyperparams_builder [as 别名]
# 或者: from object_detection.builders.hyperparams_builder import KerasLayerHyperparams [as 别名]
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) 示例2: _build_conv_hyperparams
# 需要导入模块: from object_detection.builders import hyperparams_builder [as 别名]
# 或者: from object_detection.builders.hyperparams_builder import KerasLayerHyperparams [as 别名]
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) 示例3: test_return_l1_regularized_weights_keras
# 需要导入模块: from object_detection.builders import hyperparams_builder [as 别名]
# 或者: from object_detection.builders.hyperparams_builder import KerasLayerHyperparams [as 别名]
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) 示例4: test_return_l2_regularizer_weights_keras
# 需要导入模块: from object_detection.builders import hyperparams_builder [as 别名]
# 或者: from object_detection.builders.hyperparams_builder import KerasLayerHyperparams [as 别名]
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) 示例5: test_use_none_activation_keras
# 需要导入模块: from object_detection.builders import hyperparams_builder [as 别名]
# 或者: from object_detection.builders.hyperparams_builder import KerasLayerHyperparams [as 别名]
def test_use_none_activation_keras(self):
conv_hyperparams_text_proto = """
regularizer {
l2_regularizer {
}
}
initializer {
truncated_normal_initializer {
}
}
activation: NONE
"""
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'], None)
activation_layer = keras_config.build_activation_layer()
self.assertTrue(isinstance(activation_layer, tf.keras.layers.Lambda))
self.assertEqual(activation_layer.function, tf.identity) 示例6: test_use_relu_activation_keras
# 需要导入模块: from object_detection.builders import hyperparams_builder [as 别名]
# 或者: from object_detection.builders.hyperparams_builder import KerasLayerHyperparams [as 别名]
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) 示例7: test_use_relu_6_activation_keras
# 需要导入模块: from object_detection.builders import hyperparams_builder [as 别名]
# 或者: from object_detection.builders.hyperparams_builder import KerasLayerHyperparams [as 别名]
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) 示例8: test_override_activation_keras
# 需要导入模块: from object_detection.builders import hyperparams_builder [as 别名]
# 或者: from object_detection.builders.hyperparams_builder import KerasLayerHyperparams [as 别名]
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) 示例9: test_variance_in_range_with_variance_scaling_initializer_fan_in_keras
# 需要导入模块: from object_detection.builders import hyperparams_builder [as 别名]
# 或者: from object_detection.builders.hyperparams_builder import KerasLayerHyperparams [as 别名]
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.) 示例10: test_variance_in_range_with_variance_scaling_initializer_fan_avg_keras
# 需要导入模块: from object_detection.builders import hyperparams_builder [as 别名]
# 或者: from object_detection.builders.hyperparams_builder import KerasLayerHyperparams [as 别名]
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.)) 示例11: test_variance_in_range_with_variance_scaling_initializer_uniform_keras
# 需要导入模块: from object_detection.builders import hyperparams_builder [as 别名]
# 或者: from object_detection.builders.hyperparams_builder import KerasLayerHyperparams [as 别名]
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.) 示例12: test_variance_in_range_with_truncated_normal_initializer_keras
# 需要导入模块: from object_detection.builders import hyperparams_builder [as 别名]
# 或者: from object_detection.builders.hyperparams_builder import KerasLayerHyperparams [as 别名]
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) 示例13: test_variance_in_range_with_random_normal_initializer_keras
# 需要导入模块: from object_detection.builders import hyperparams_builder [as 别名]
# 或者: from object_detection.builders.hyperparams_builder import KerasLayerHyperparams [as 别名]
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) 示例14: test_do_not_use_batch_norm_if_default_keras
# 需要导入模块: from object_detection.builders import hyperparams_builder [as 别名]
# 或者: from object_detection.builders.hyperparams_builder import KerasLayerHyperparams [as 别名]
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)) 示例15: test_use_relu_activation_keras
# 需要导入模块: from object_detection.builders import hyperparams_builder [as 别名]
# 或者: from object_detection.builders.hyperparams_builder import KerasLayerHyperparams [as 别名]
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'], tf.nn.relu)