arg_scope
tf.contrib.framework.arg_scope(list_ops_or_scope, **kwargs)
#或者
tf.contrib.slim.arg_scope(list_ops_or_scope, **kwargs)
# 为给定的 list_ops_or_scope 存储默认的参数
示例:
with slim.arg_scope([slim.conv2d, slim.fully_connected],
weights_initializer=tf.truncated_normal_initializer(stddev=0.1),
weights_regularizer=slim.l2_regularizer(weight_decay),
normalizer_fn=slim.batch_norm,
normalizer_params=batch_norm_params):
就这样给slim.conv2d
和slim.fully_connected
准备了默认参数。
如何给自定义的函数也附上这种功能
from tensorflow.contrib import framework
from tensorflow.contrib.framework.python.ops.arg_scope import add_arg_scope
@add_arg_scope
def haha(name, age):
print(name, age)
with framework.arg_scope([haha], age = 15):
haha("keith")
# 输出
# keith 15
with slim.arg_scope(...) as argScope:
...
with slim.arg_scope(argScope):
...
# argScope 是一个字典。这个字典可以继续使用,下面的arg_scope配置和上面的是一样的。