本文整理汇总了Python中tensorflow.python.ops.nn.l2_normalize方法的典型用法代码示例。如果您正苦于以下问题：Python nn.l2_normalize方法的具体用法？Python nn.l2_normalize怎么用？Python nn.l2_normalize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类tensorflow.python.ops.nn的用法示例。
在下文中一共展示了nn.l2_normalize方法的4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: l2_normalize
# 需要导入模块: from tensorflow.python.ops import nn [as 别名]
# 或者: from tensorflow.python.ops.nn import l2_normalize [as 别名]
def l2_normalize(x, axis):
"""Normalizes a tensor wrt the L2 norm alongside the specified axis.
Arguments:
x: Tensor or variable.
axis: axis along which to perform normalization.
Returns:
A tensor.
"""
if axis < 0:
axis %= len(x.get_shape())
return nn.l2_normalize(x, dim=axis) 示例2: test_forward_lrn
# 需要导入模块: from tensorflow.python.ops import nn [as 别名]
# 或者: from tensorflow.python.ops.nn import l2_normalize [as 别名]
def test_forward_lrn():
_test_lrn((1, 3, 20, 20), 3, 1, 1.0, 1.0, 0.5)
#######################################################################
# l2_normalize
# ------------ 示例3: _test_l2_normalize
# 需要导入模块: from tensorflow.python.ops import nn [as 别名]
# 或者: from tensorflow.python.ops.nn import l2_normalize [as 别名]
def _test_l2_normalize(ishape, eps, axis):
""" testing l2 normalize (uses max, sum, square, sqrt frontend operators)"""
inp_array = np.random.uniform(size=ishape).astype(np.float32)
with tf.Graph().as_default():
in1 = tf.placeholder(shape=inp_array.shape, dtype=inp_array.dtype)
nn.l2_normalize(in1,
axis=axis,
epsilon=eps,
name=None,
dim=None)
compare_tf_with_tvm(inp_array, 'Placeholder:0', 'l2_normalize:0') 示例4: l2_normalize
# 需要导入模块: from tensorflow.python.ops import nn [as 别名]
# 或者: from tensorflow.python.ops.nn import l2_normalize [as 别名]
def l2_normalize(x, axis=None):
"""Normalizes a tensor wrt the L2 norm alongside the specified axis.
Arguments:
x: Tensor or variable.
axis: axis along which to perform normalization.
Returns:
A tensor.
"""
return nn.l2_normalize(x, dim=axis) 开发者ID:PacktPublishing，项目名称:Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda，代码行数:13，代码来源:backend.py