本文整理汇总了Python中config.get_config方法的典型用法代码示例。如果您正苦于以下问题：Python config.get_config方法的具体用法？Python config.get_config怎么用？Python config.get_config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模块config的用法示例。

在下文中一共展示了config.get_config方法的21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，您的评价将有助于我们的系统推荐出更棒的Python代码示例。

示例1: main

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# 需要导入模块: import config [as 别名]

# 或者: from config import get_config [as 别名]

def main(_):

gpu_options = tf.GPUOptions(

per_process_gpu_memory_fraction=calc_gpu_fraction(FLAGS.gpu_fraction))

with tf.Session(config=tf.ConfigProto(gpu_options=gpu_options)) as sess:

config = get_config(FLAGS) or FLAGS

if config.env_type == 'simple':

env = SimpleGymEnvironment(config)

else:

env = GymEnvironment(config)

if not tf.test.is_gpu_available() and FLAGS.use_gpu:

raise Exception("use_gpu flag is true when no GPUs are available")

if not FLAGS.use_gpu:

config.cnn_format = 'NHWC'

agent = Agent(config, env, sess)

if FLAGS.is_train:

agent.train()

else:

agent.play()

开发者ID:devsisters，项目名称:DQN-tensorflow，代码行数:26，

示例2: init

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# 需要导入模块: import config [as 别名]

# 或者: from config import get_config [as 别名]

def init(browser_type):

""" Initialize the uwsgi worker which will read urls to archive from redis queue

and use associated web driver to connect to remote web browser

"""

logging.basicConfig(format='%(asctime)s: [%(levelname)s]: %(message)s',

level=logging.DEBUG)

logging.debug('WebDriver Worker Started')

config = get_config()

archives = config['archives']

rc = init_redis(config)

browser = get_avail_browser(config, rc, browser_type)

run(rc, browser, archives, config, browser_type)

开发者ID:ikreymer，项目名称:browsertrix，代码行数:19，

示例3: test

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# 需要导入模块: import config [as 别名]

# 或者: from config import get_config [as 别名]

def test(self):

from torch.utils.data import DataLoader

from lib.utils import Timer

from config import get_config

config = get_config()

dataset = SynthiaVoxelizationDataset(config)

timer = Timer()

data_loader = DataLoader(

dataset=dataset,

collate_fn=cfl_collate_fn_factory(limit_numpoints=False),

num_workers=0,

batch_size=4,

shuffle=True)

# Start from index 1

# for i, batch in enumerate(data_loader, 1):

iter = data_loader.__iter__()

for i in range(100):

timer.tic()

batch = iter.next()

print(batch, timer.toc())

开发者ID:chrischoy，项目名称:SpatioTemporalSegmentation，代码行数:25，

示例4: add_towel_mode

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# 需要导入模块: import config [as 别名]

# 或者: from config import get_config [as 别名]

def add_towel_mode(upd: Updater, handlers_group: int):

logger.info("registering towel-mode handlers")

dp = upd.dispatcher

# catch all new users and drop the towel

dp.add_handler(MessageHandler(Filters.status_update.new_chat_members, catch_new_user),

handlers_group)

# check for reply or remove messages

dp.add_handler(MessageHandler(

Filters.group & ~Filters.status_update, catch_reply),

handlers_group

)

# "i am a bot button"

dp.add_handler(CallbackQueryHandler(i_am_a_bot_btn), handlers_group)

# ban quarantine users, if time is gone

upd.job_queue.run_repeating(ban_user, interval=60, first=60, context={

"chat_id": get_config()["GROUP_CHAT_ID"]

})

开发者ID:egregors，项目名称:vldc-bot，代码行数:23，

示例5: destalinate_job

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# 需要导入模块: import config [as 别名]

# 或者: from config import get_config [as 别名]

def destalinate_job():

raven_client = RavenClient()

logging.info("Destalinating")

if not get_config().sb_token or not get_config().api_token:

logging.error(

"Missing at least one required Slack environment variable.\n"

"Make sure to set DESTALINATOR_SB_TOKEN and DESTALINATOR_API_TOKEN."

)

else:

try:

archiver.Archiver().archive()

warner.Warner().warn()

announcer.Announcer().announce()

flagger.Flagger().flag()

logging.info("OK: destalinated")

except Exception as e: # pylint: disable=W0703

raven_client.captureException()

if not get_config().sentry_dsn:

raise e

logging.info("END: destalinate_job")

开发者ID:randsleadershipslack，项目名称:destalinator，代码行数:23，

示例6: get_model

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# 需要导入模块: import config [as 别名]

# 或者: from config import get_config [as 别名]

def get_model(config=None):

if not None:

config, unparsed = get_config()

return get_trainer(config)

开发者ID:mkocaoglu，项目名称:CausalGAN，代码行数:6，

示例7: connect

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# 需要导入模块: import config [as 别名]

# 或者: from config import get_config [as 别名]

def connect(self):

config = get_config()

self.client = MongoClient(config['db.dsn'])

self.db = self.client[config['db.database']]

开发者ID:itspoma，项目名称:audio-fingerprint-identifying-python，代码行数:7，

示例8: connect

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# 需要导入模块: import config [as 别名]

# 或者: from config import get_config [as 别名]

def connect(self):

config = get_config()

self.conn = sqlite3.connect(config['db.file'])

self.conn.text_factory = str

self.cur = self.conn.cursor()

print(colored('sqlite - connection opened','white',attrs=['dark']))

开发者ID:itspoma，项目名称:audio-fingerprint-identifying-python，代码行数:11，

示例9: init

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# 需要导入模块: import config [as 别名]

# 或者: from config import get_config [as 别名]

def init():

""" Init the application and add routes """

logging.basicConfig(format='%(asctime)s: [%(levelname)s]: %(message)s',

level=logging.DEBUG)

global theconfig

theconfig = get_config()

global rc

rc = init_redis(theconfig)

app = default_app()

return app

开发者ID:ikreymer，项目名称:browsertrix，代码行数:17，

示例10: test_get_config

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# 需要导入模块: import config [as 别名]

# 或者: from config import get_config [as 别名]

def test_get_config(self):

c: Dict = get_config()

self.assertEqual(c["DEBUG"], self.env_debug)

self.assertEqual(c["GROUP_CHAT_ID"], self.env_chat_id)

self.assertEqual(c["TOKEN"], self.env_token)

self.assertEqual(c["MONGO_USER"], self.env_mongo_initdb_root_username)

self.assertEqual(c["MONGO_PASS"], self.env_mongo_initdb_root_password)

开发者ID:egregors，项目名称:vldc-bot，代码行数:9，

示例11: __init__

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# 需要导入模块: import config [as 别名]

# 或者: from config import get_config [as 别名]

def __init__(self, satoshis=0):

super(Amount, self).__init__()

self.satoshis = satoshis

self.config = config.get_config()

self.fmt = self.config.get_option('amount_format', 'satoshis')

开发者ID:mazaclub，项目名称:hashmal，代码行数:7，

示例12: main

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# 需要导入模块: import config [as 别名]

# 或者: from config import get_config [as 别名]

def main(_):

with tf.Session() as sess:

config = get_config(FLAGS)

env = MyEnvironment(config)

agent = Agent(config, env, sess)

if FLAGS.is_train:

agent.train()

else:

if FLAGS.dataset == 'mine':

agent.play_mine()

else:

agent.play()

开发者ID:yuke93，项目名称:RL-Restore，代码行数:15，

示例13: predictByPart

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# 需要导入模块: import config [as 别名]

# 或者: from config import get_config [as 别名]

def predictByPart(data, peaks):

classesM = ['N','Ventricular','Paced','A','F','Noise']#,'L','R','f','j','E','a','J','Q','e','S']

predicted = list()

result = ""

counter = [0]* len(classesM)

from keras.models import load_model

model = load_model('models/MLII-latest.hdf5')

config = get_config()

for i, peak in enumerate(peaks[3:-1]):

total_n =len(peaks)

start, end = peak-config.input_size//2 , peak+config.input_size//2

prob = model.predict(data[:, start:end])

prob = prob[:,0]

ann = np.argmax(prob)

counter[ann]+=1

if classesM[ann] != "N":

print("The {}/{}-record classified as {} with {:3.1f}% certainty".format(i,total_n,classesM[ann],100*prob[0,ann]))

result += "("+ classesM[ann] +":" + str(round(100*prob[0,ann],1)) + "%)"

predicted.append([classesM[ann],prob])

if classesM[ann] != 'N' and prob[0,ann] > 0.95:

import matplotlib.pyplot as plt

plt.plot(data[:, start:end][0,:,0],)

mkdir_recursive('results')

plt.savefig('results/hazard-'+classesM[ann]+'.png', format="png", dpi = 300)

plt.close()

result += "{}-N, {}-Venticular, {}-Paced, {}-A, {}-F, {}-Noise".format(counter[0], counter[1], counter[2], counter[3], counter[4], counter[5])

return predicted, result

开发者ID:physhik，项目名称:ecg-mit-bih，代码行数:29，

示例14: main

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# 需要导入模块: import config [as 别名]

# 或者: from config import get_config [as 别名]

def main():

testing_file = "./new_data/test.ann.json"

trained_model = "./checkpoints/model.ckpt"

embedding_file = "D:/DataMining/QASystem/wiki/wiki.zh.text.vector"

# embedding_file = "./wiki.zh.text.vector"

embedding_size = 60 # Word embedding dimension

batch_size = 64 # Batch data size

sequence_length = 150 # Sentence length

learning_rate = 0.01

gpu_mem_usage = 0.75

gpu_device = "/gpu:0"

cpu_device = "/cpu:0"

config = get_config() # Not used yet

embeddings, word2idx = load_embedding(embedding_file)

questions, evidences, y1, y2 = load_data(testing_file, word2idx, sequence_length)

with tf.Graph().as_default(), tf.device(gpu_device):

gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=gpu_mem_usage)

session_conf = tf.ConfigProto(allow_soft_placement=True, gpu_options=gpu_options)

with tf.variable_scope('Model'):

model = DGCNN(config, embeddings, sequence_length, embedding_size)

with tf.Session(config=session_conf).as_default() as sess:

saver = tf.train.Saver()

print("Start loading the model")

saver.restore(sess, trained_model)

print("The model is loaded")

acc1, acc2 = [], []

for batch_questions, batch_evidences, batch_y1, batch_y2 in next_batch(questions, evidences, y1, y2, batch_size):

feed_dict = {

model.e: batch_evidences,

model.q: batch_questions,

model.y1: batch_y1,

model.y2: batch_y2,

model.is_train: False

}

acc1_, acc2_ = sess.run([model.acc1, model.acc2], feed_dict)

acc1.append(acc1_)

acc2.append(acc2_)

print('Acc1 %2.3f\tAcc2 %2.3f' % (acc1_, acc2_))

print('Average: Acc1 %2.3f\tAcc2 %2.3f' % (np.mean(acc1), np.mean(acc2)))

开发者ID:Chiang97912，项目名称:DGCNN，代码行数:42，

示例15: main

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# 需要导入模块: import config [as 别名]

# 或者: from config import get_config [as 别名]

def main ():

# parse configuration

config, _ = get_config()

# set visible GPUs

os.environ['CUDA_VISIBLE_DEVICES'] = config.gpu

if config.test:

run_test (config)

else:

run_train (config)

# end of main

开发者ID:TAMU-VITA，项目名称:ALISTA，代码行数:13，

示例16: schedule_job

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# 需要导入模块: import config [as 别名]

# 或者: from config import get_config [as 别名]

def schedule_job():

# When testing changes, set the "TEST_SCHEDULE" envvar to run more often

if get_config().test_schedule:

schedule_kwargs = {"hour": "*", "minute": "*/10"}

else:

schedule_kwargs = {"hour": get_config().schedule_hour}

sched = BlockingScheduler()

sched.add_job(destalinate_job, "cron", **schedule_kwargs)

sched.start()

开发者ID:randsleadershipslack，项目名称:destalinator，代码行数:12，

示例17: main

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# 需要导入模块: import config [as 别名]

# 或者: from config import get_config [as 别名]

def main():

# Use RUN_ONCE to only run the destalinate job once immediately

if get_config().run_once:

destalinate_job()

else:

schedule_job()

开发者ID:randsleadershipslack，项目名称:destalinator，代码行数:8，

示例18: set_up_slack_logger

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# 需要导入模块: import config [as 别名]

# 或者: from config import get_config [as 别名]

def set_up_slack_logger(slackbot=None):

"""

Sets up a handler and formatter on a given `logging.Logger` object.

* `log_level_env_var` - Grabs logging level from this ENV var. Possible values are standard: "debug", "error", etc.

* `log_to_slack_env_var` - Points to an ENV var that indicates whether to log to a Slack channel.

* `log_channel` - Indicates the name of the Slack channel to which we'll send logs.

* `default_level` - The default log level if one is not set in the environment.

* `slackbot` - A slackbot.Slackbot() object ready to send messages to a Slack channel.

"""

logger = logging.getLogger()

if logger.handlers:

# We've likely already ran through the rest of this method:

return

_config = get_config()

slack_log_level = getattr(logging, _config.log_level.upper(), logging.INFO)

formatter = logging.Formatter('%(asctime)s [%(levelname)s]: %(message)s')

logger.setLevel(logging.DEBUG)

stream_handler = logging.StreamHandler()

stream_handler.setFormatter(formatter)

logger.addHandler(stream_handler)

if _config.log_to_channel and _config.log_channel and slackbot:

logger.debug("Logging to slack channel: %s", _config.log_channel)

slack_handler = SlackHandler(slackbot=slackbot, level=slack_log_level)

slack_handler.setFormatter(formatter)

logger.addHandler(slack_handler)

开发者ID:randsleadershipslack，项目名称:destalinator，代码行数:36，

示例19: test_environment_variable_configs

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# 需要导入模块: import config [as 别名]

# 或者: from config import get_config [as 别名]

def test_environment_variable_configs(self):

self.assertEqual(get_config().string_variable, 'test')

self.assertListEqual(get_config().list_variable, ['test'])

开发者ID:randsleadershipslack，项目名称:destalinator，代码行数:5，

示例20: mocked_slacker_object

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# 需要导入模块: import config [as 别名]

# 或者: from config import get_config [as 别名]

def mocked_slacker_object(channels_list=None, users_list=None, messages_list=None, emoji_list=None):

slacker_obj = slacker.Slacker(get_config().slack_name, token='token', init=False)

slacker_obj.get_all_channel_objects = mock.MagicMock(return_value=channels_list or [])

slacker_obj.get_channels()

slacker_obj.get_all_user_objects = mock.MagicMock(return_value=users_list or [])

slacker_obj.get_users()

slacker_obj.get_messages_in_time_range = mock.MagicMock(return_value=messages_list or [])

slacker_obj.get_emojis = mock.MagicMock(return_value=emoji_list or [])

return slacker_obj

开发者ID:randsleadershipslack，项目名称:destalinator，代码行数:15，

示例21: get_trainer

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# 需要导入模块: import config [as 别名]

# 或者: from config import get_config [as 别名]

def get_trainer():

print('tf: resetting default graph!')

tf.reset_default_graph()#for repeated calls in ipython

####GET CONFIGURATION####

#TODO:load configurations from previous model when loading previous model

##if load_path:

#load config files from dir

#except if pt_load_path, get cc_config from before

#overwrite is_train, is_pretrain with current args--sort of a mess

##else:

config,_=get_config()

cc_config,_=get_cc_config()

dcgan_config,_=get_dcgan_config()

began_config,_=get_began_config()

###SEEDS###

np.random.seed(config.seed)

#tf.set_random_seed(config.seed) # Not working right now.

prepare_dirs_and_logger(config)

if not config.load_path:

print('saving config because load path not given')

save_configs(config,cc_config,dcgan_config,began_config)

#Resolve model differences and batch_size

if config.model_type:

if config.model_type=='dcgan':

config.batch_size=dcgan_config.batch_size

cc_config.batch_size=dcgan_config.batch_size # make sure the batch size of cc is the same as the image model

config.Model=CausalGAN.CausalGAN

model_config=dcgan_config

if config.model_type=='began':

config.batch_size=began_config.batch_size

cc_config.batch_size=began_config.batch_size # make sure the batch size of cc is the same as the image model

config.Model=CausalBEGAN.CausalBEGAN

model_config=began_config

else:#no image model

model_config=None

config.batch_size=cc_config.batch_size

if began_config.is_train or dcgan_config.is_train:

raise ValueError('need to specify model_type for is_train=True')

#Interpret causal_model keyword

cc_config.graph=get_causal_graph(config.causal_model)

#Builds and loads specified models:

trainer=Trainer(config,cc_config,model_config)

return trainer

开发者ID:mkocaoglu，项目名称:CausalGAN，代码行数:55，

注：本文中的config.get_config方法示例整理自Github/MSDocs等源码及文档管理平台，相关代码片段筛选自各路编程大神贡献的开源项目，源码版权归原作者所有，传播和使用请参考对应项目的License；未经允许，请勿转载。