本文整理匯總了Python中tensorflow.python.ops.standard_ops.reduce_mean方法的典型用法代碼示例。如果您正苦於以下問題:Python standard_ops.reduce_mean方法的具體用法?Python standard_ops.reduce_mean怎麽用?Python standard_ops.reduce_mean使用的例子?那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類tensorflow.python.ops.standard_ops
的用法示例。
在下文中一共展示了standard_ops.reduce_mean方法的2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: summarize_activation
# 需要導入模塊: from tensorflow.python.ops import standard_ops [as 別名]
# 或者: from tensorflow.python.ops.standard_ops import reduce_mean [as 別名]
def summarize_activation(op):
"""Summarize an activation.
This applies the given activation and adds useful summaries specific to the
activation.
Args:
op: The tensor to summarize (assumed to be a layer activation).
Returns:
The summary op created to summarize `op`.
"""
if op.op.type in ('Relu', 'Softplus', 'Relu6'):
# Using inputs to avoid floating point equality and/or epsilons.
_add_scalar_summary(
standard_ops.reduce_mean(standard_ops.to_float(standard_ops.less(
op.op.inputs[0], standard_ops.cast(0.0, op.op.inputs[0].dtype)))),
'%s/zeros' % op.op.name)
if op.op.type == 'Relu6':
_add_scalar_summary(
standard_ops.reduce_mean(standard_ops.to_float(standard_ops.greater(
op.op.inputs[0], standard_ops.cast(6.0, op.op.inputs[0].dtype)))),
'%s/sixes' % op.op.name)
return _add_histogram_summary(op, '%s/activation' % op.op.name)
示例2: summarize_activation
# 需要導入模塊: from tensorflow.python.ops import standard_ops [as 別名]
# 或者: from tensorflow.python.ops.standard_ops import reduce_mean [as 別名]
def summarize_activation(op):
"""Summarize an activation.
This applies the given activation and adds useful summaries specific to the
activation.
Args:
op: The tensor to summarize (assumed to be a layer activation).
Returns:
The summary op created to summarize `op`.
"""
if op.op.type in ('Relu', 'Softplus', 'Relu6'):
# Using inputs to avoid floating point equality and/or epsilons.
_add_scalar_summary(
standard_ops.reduce_mean(
standard_ops.to_float(
standard_ops.less(op.op.inputs[
0], standard_ops.cast(0.0, op.op.inputs[0].dtype)))),
'%s/zeros' % op.op.name)
if op.op.type == 'Relu6':
_add_scalar_summary(
standard_ops.reduce_mean(
standard_ops.to_float(
standard_ops.greater(op.op.inputs[
0], standard_ops.cast(6.0, op.op.inputs[0].dtype)))),
'%s/sixes' % op.op.name)
return _add_histogram_summary(op, '%s/activation' % op.op.name)