本文整理匯總了Python中tensorflow.python.util.deprecation._PRINT_DEPRECATION_WARNINGS屬性的典型用法代碼示例。如果您正苦於以下問題：Python deprecation._PRINT_DEPRECATION_WARNINGS屬性的具體用法？Python deprecation._PRINT_DEPRECATION_WARNINGS怎麽用？Python deprecation._PRINT_DEPRECATION_WARNINGS使用的例子？那麽, 這裏精選的屬性代碼示例或許可以為您提供幫助。您也可以進一步了解該屬性所在類tensorflow.python.util.deprecation的用法示例。
在下文中一共展示了deprecation._PRINT_DEPRECATION_WARNINGS屬性的1個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: keras_reproducible
# 需要導入模塊: from tensorflow.python.util import deprecation [as 別名]
# 或者: from tensorflow.python.util.deprecation import _PRINT_DEPRECATION_WARNINGS [as 別名]
def keras_reproducible(seed=1234, verbose=0, TF_CPP_MIN_LOG_LEVEL="3"):
"""
https://keras.io/getting-started/faq/#how-can-i-obtain-reproducible-results-using-keras-during-development
"""
import random
import pkg_resources
import os
random.seed(seed)
np.random.seed(seed)
os.environ["PYTHONHASHSEED"] = "0" # might need to do this outside the script
if verbose == 0:
os.environ[
"TF_CPP_MIN_LOG_LEVEL"
] = TF_CPP_MIN_LOG_LEVEL # 2 will print warnings
try:
import tensorflow
except ImportError:
raise ImportError("Missing required package 'tensorflow'")
# Use the TF 1.x API
if pkg_resources.get_distribution("tensorflow").version.startswith("1."):
tf = tensorflow
else:
tf = tensorflow.compat.v1
if verbose == 0:
# https://github.com/tensorflow/tensorflow/issues/27023
try:
from tensorflow.python.util import deprecation
deprecation._PRINT_DEPRECATION_WARNINGS = False
except ImportError:
try:
from tensorflow.python.util import module_wrapper as deprecation
except ImportError:
from tensorflow.python.util import deprecation_wrapper as deprecation
deprecation._PER_MODULE_WARNING_LIMIT = 0
# this was deprecated in 1.15 (maybe earlier)
tensorflow.compat.v1.logging.set_verbosity(tensorflow.compat.v1.logging.ERROR)
ConfigProto = tf.ConfigProto
session_conf = tf.ConfigProto(
intra_op_parallelism_threads=1, inter_op_parallelism_threads=1
)
with capture_all(): # doesn't have quiet option
try:
from tensorflow.python.keras import backend as K
except ImportError:
raise ImportError("Missing required module 'keras'")
tf.set_random_seed(seed)
sess = tf.Session(graph=tf.get_default_graph(), config=session_conf)
K.set_session(sess)