本文整理汇总了Python中object_detection.utils.variables_helper.get_variables_available_in_checkpoint方法的典型用法代码示例。如果您正苦于以下问题：Python variables_helper.get_variables_available_in_checkpoint方法的具体用法？Python variables_helper.get_variables_available_in_checkpoint怎么用？Python variables_helper.get_variables_available_in_checkpoint使用的例子？那么, 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.utils.variables_helper的用法示例。
在下文中一共展示了variables_helper.get_variables_available_in_checkpoint方法的6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: test_return_variables_available_an_checkpoint_with_dict_inputs
# 需要导入模块: from object_detection.utils import variables_helper [as 别名]
# 或者: from object_detection.utils.variables_helper import get_variables_available_in_checkpoint [as 别名]
def test_return_variables_available_an_checkpoint_with_dict_inputs(self):
checkpoint_path = os.path.join(self.get_temp_dir(), 'graph.pb')
graph1_variables = [
tf.Variable(1.0, name='ckpt_weights'),
]
init_op = tf.global_variables_initializer()
saver = tf.train.Saver(graph1_variables)
with self.test_session() as sess:
sess.run(init_op)
saver.save(sess, checkpoint_path)
graph2_variables_dict = {
'ckpt_weights': tf.Variable(1.0, name='weights'),
'ckpt_biases': tf.Variable(1.0, name='biases')
}
out_variables = variables_helper.get_variables_available_in_checkpoint(
graph2_variables_dict, checkpoint_path)
self.assertTrue(isinstance(out_variables, dict))
self.assertItemsEqual(out_variables.keys(), ['ckpt_weights'])
self.assertTrue(out_variables['ckpt_weights'].op.name == 'weights') 示例2: test_return_variables_available_in_checkpoint
# 需要导入模块: from object_detection.utils import variables_helper [as 别名]
# 或者: from object_detection.utils.variables_helper import get_variables_available_in_checkpoint [as 别名]
def test_return_variables_available_in_checkpoint(self):
checkpoint_path = os.path.join(self.get_temp_dir(), 'model.ckpt')
with tf.Graph().as_default():
weight_variable = tf.Variable(1.0, name='weights')
global_step = tf.train.get_or_create_global_step()
graph1_variables = [
weight_variable,
global_step
]
init_op = tf.global_variables_initializer()
saver = tf.train.Saver(graph1_variables)
with self.test_session() as sess:
sess.run(init_op)
saver.save(sess, checkpoint_path)
with tf.Graph().as_default():
graph2_variables = graph1_variables + [tf.Variable(1.0, name='biases')]
out_variables = variables_helper.get_variables_available_in_checkpoint(
graph2_variables, checkpoint_path, include_global_step=False)
self.assertItemsEqual(out_variables, [weight_variable]) 示例3: test_return_variables_available_an_checkpoint_with_dict_inputs
# 需要导入模块: from object_detection.utils import variables_helper [as 别名]
# 或者: from object_detection.utils.variables_helper import get_variables_available_in_checkpoint [as 别名]
def test_return_variables_available_an_checkpoint_with_dict_inputs(self):
checkpoint_path = os.path.join(self.get_temp_dir(), 'model.ckpt')
with tf.Graph().as_default():
graph1_variables = [
tf.Variable(1.0, name='ckpt_weights'),
]
init_op = tf.global_variables_initializer()
saver = tf.train.Saver(graph1_variables)
with self.test_session() as sess:
sess.run(init_op)
saver.save(sess, checkpoint_path)
with tf.Graph().as_default():
graph2_variables_dict = {
'ckpt_weights': tf.Variable(1.0, name='weights'),
'ckpt_biases': tf.Variable(1.0, name='biases')
}
out_variables = variables_helper.get_variables_available_in_checkpoint(
graph2_variables_dict, checkpoint_path)
self.assertTrue(isinstance(out_variables, dict))
self.assertItemsEqual(out_variables.keys(), ['ckpt_weights'])
self.assertTrue(out_variables['ckpt_weights'].op.name == 'weights') 示例4: test_return_variables_available_in_checkpoint
# 需要导入模块: from object_detection.utils import variables_helper [as 别名]
# 或者: from object_detection.utils.variables_helper import get_variables_available_in_checkpoint [as 别名]
def test_return_variables_available_in_checkpoint(self):
checkpoint_path = os.path.join(self.get_temp_dir(), 'graph.pb')
weight_variable = tf.Variable(1.0, name='weights')
global_step = tf.train.get_or_create_global_step()
graph1_variables = [
weight_variable,
global_step
]
init_op = tf.global_variables_initializer()
saver = tf.train.Saver(graph1_variables)
with self.test_session() as sess:
sess.run(init_op)
saver.save(sess, checkpoint_path)
graph2_variables = graph1_variables + [tf.Variable(1.0, name='biases')]
out_variables = variables_helper.get_variables_available_in_checkpoint(
graph2_variables, checkpoint_path, include_global_step=False)
self.assertItemsEqual(out_variables, [weight_variable]) 示例5: test_return_variables_with_correct_sizes
# 需要导入模块: from object_detection.utils import variables_helper [as 别名]
# 或者: from object_detection.utils.variables_helper import get_variables_available_in_checkpoint [as 别名]
def test_return_variables_with_correct_sizes(self):
checkpoint_path = os.path.join(self.get_temp_dir(), 'graph.pb')
bias_variable = tf.Variable(3.0, name='biases')
global_step = tf.train.get_or_create_global_step()
graph1_variables = [
tf.Variable([[1.0, 2.0], [3.0, 4.0]], name='weights'),
bias_variable,
global_step
]
init_op = tf.global_variables_initializer()
saver = tf.train.Saver(graph1_variables)
with self.test_session() as sess:
sess.run(init_op)
saver.save(sess, checkpoint_path)
graph2_variables = [
tf.Variable([1.0, 2.0], name='weights'), # Note the new variable shape.
bias_variable,
global_step
]
out_variables = variables_helper.get_variables_available_in_checkpoint(
graph2_variables, checkpoint_path, include_global_step=True)
self.assertItemsEqual(out_variables, [bias_variable, global_step]) 示例6: test_return_all_variables_from_checkpoint_with_partition
# 需要导入模块: from object_detection.utils import variables_helper [as 别名]
# 或者: from object_detection.utils.variables_helper import get_variables_available_in_checkpoint [as 别名]
def test_return_all_variables_from_checkpoint_with_partition(self):
with tf.Graph().as_default():
partitioner = tf.fixed_size_partitioner(2)
variables = [
tf.get_variable(
name='weights', shape=(2, 2), partitioner=partitioner),
tf.Variable([1.0, 2.0], name='biases')
]
checkpoint_path = os.path.join(self.get_temp_dir(), 'model.ckpt')
init_op = tf.global_variables_initializer()
saver = tf.train.Saver(variables)
with self.test_session() as sess:
sess.run(init_op)
saver.save(sess, checkpoint_path)
out_variables = variables_helper.get_variables_available_in_checkpoint(
variables, checkpoint_path)
self.assertItemsEqual(out_variables, variables) 开发者ID:ShivangShekhar，项目名称:Live-feed-object-device-identification-using-Tensorflow-and-OpenCV，代码行数:19，代码来源:variables_helper_test.py