本文整理汇总了Python中tensorflow.python.ops.nn.softplus方法的典型用法代码示例。如果您正苦于以下问题：Python nn.softplus方法的具体用法？Python nn.softplus怎么用？Python nn.softplus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.softplus方法的15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: __init__
# 需要导入模块: from tensorflow.python.ops import nn [as 别名]
# 或者: from tensorflow.python.ops.nn import softplus [as 别名]
def __init__(self,
concentration,
rate,
validate_args=False,
allow_nan_stats=True,
name="GammaWithSoftplusConcentrationRate"):
parameters = locals()
with ops.name_scope(name, values=[concentration, rate]):
super(GammaWithSoftplusConcentrationRate, self).__init__(
concentration=nn.softplus(concentration,
name="softplus_concentration"),
rate=nn.softplus(rate, name="softplus_rate"),
validate_args=validate_args,
allow_nan_stats=allow_nan_stats,
name=name)
self._parameters = parameters 示例2: __init__
# 需要导入模块: from tensorflow.python.ops import nn [as 别名]
# 或者: from tensorflow.python.ops.nn import softplus [as 别名]
def __init__(self,
concentration1,
concentration0,
validate_args=False,
allow_nan_stats=True,
name="BetaWithSoftplusConcentration"):
parameters = locals()
with ops.name_scope(name, values=[concentration1,
concentration0]) as ns:
super(BetaWithSoftplusConcentration, self).__init__(
concentration1=nn.softplus(concentration1,
name="softplus_concentration1"),
concentration0=nn.softplus(concentration0,
name="softplus_concentration0"),
validate_args=validate_args,
allow_nan_stats=allow_nan_stats,
name=ns)
self._parameters = parameters 示例3: __init__
# 需要导入模块: from tensorflow.python.ops import nn [as 别名]
# 或者: from tensorflow.python.ops.nn import softplus [as 别名]
def __init__(self,
df,
loc,
scale,
validate_args=False,
allow_nan_stats=True,
name="StudentTWithAbsDfSoftplusScale"):
parameters = locals()
with ops.name_scope(name, values=[df, scale]):
super(StudentTWithAbsDfSoftplusScale, self).__init__(
df=math_ops.floor(math_ops.abs(df)),
loc=loc,
scale=nn.softplus(scale, name="softplus_scale"),
validate_args=validate_args,
allow_nan_stats=allow_nan_stats,
name=name)
self._parameters = parameters 示例4: __init__
# 需要导入模块: from tensorflow.python.ops import nn [as 别名]
# 或者: from tensorflow.python.ops.nn import softplus [as 别名]
def __init__(self,
concentration,
rate,
validate_args=False,
allow_nan_stats=True,
name="InverseGammaWithSoftplusConcentrationRate"):
parameters = locals()
with ops.name_scope(name, values=[concentration, rate]):
super(InverseGammaWithSoftplusConcentrationRate, self).__init__(
concentration=nn.softplus(concentration,
name="softplus_concentration"),
rate=nn.softplus(rate, name="softplus_rate"),
validate_args=validate_args,
allow_nan_stats=allow_nan_stats,
name=name)
self._parameters = parameters 示例5: __init__
# 需要导入模块: from tensorflow.python.ops import nn [as 别名]
# 或者: from tensorflow.python.ops.nn import softplus [as 别名]
def __init__(self,
alpha,
beta,
validate_args=False,
allow_nan_stats=True,
name="GammaWithSoftplusAlphaBeta"):
parameters = locals()
parameters.pop("self")
with ops.name_scope(name, values=[alpha, beta]) as ns:
super(GammaWithSoftplusAlphaBeta, self).__init__(
alpha=nn.softplus(alpha, name="softplus_alpha"),
beta=nn.softplus(beta, name="softplus_beta"),
validate_args=validate_args,
allow_nan_stats=allow_nan_stats,
name=ns)
self._parameters = parameters 示例6: __init__
# 需要导入模块: from tensorflow.python.ops import nn [as 别名]
# 或者: from tensorflow.python.ops.nn import softplus [as 别名]
def __init__(self,
alpha,
beta,
validate_args=False,
allow_nan_stats=True,
name="InverseGammaWithSoftplusAlphaBeta"):
parameters = locals()
parameters.pop("self")
with ops.name_scope(name, values=[alpha, beta]) as ns:
super(InverseGammaWithSoftplusAlphaBeta, self).__init__(
alpha=nn.softplus(alpha, name="softplus_alpha"),
beta=nn.softplus(beta, name="softplus_gamma"),
validate_args=validate_args,
allow_nan_stats=allow_nan_stats,
name=ns)
self._parameters = parameters 示例7: __init__
# 需要导入模块: from tensorflow.python.ops import nn [as 别名]
# 或者: from tensorflow.python.ops.nn import softplus [as 别名]
def __init__(self,
a,
b,
validate_args=False,
allow_nan_stats=True,
name="BetaWithSoftplusAB"):
parameters = locals()
parameters.pop("self")
with ops.name_scope(name, values=[a, b]) as ns:
super(BetaWithSoftplusAB, self).__init__(
a=nn.softplus(a, name="softplus_a"),
b=nn.softplus(b, name="softplus_b"),
validate_args=validate_args,
allow_nan_stats=allow_nan_stats,
name=ns)
self._parameters = parameters 示例8: __init__
# 需要导入模块: from tensorflow.python.ops import nn [as 别名]
# 或者: from tensorflow.python.ops.nn import softplus [as 别名]
def __init__(self,
mu,
diag_stdev,
validate_args=False,
allow_nan_stats=True,
name="MultivariateNormalDiagWithSoftplusStdDev"):
parameters = locals()
parameters.pop("self")
with ops.name_scope(name, values=[diag_stdev]) as ns:
super(MultivariateNormalDiagWithSoftplusStDev, self).__init__(
mu=mu,
diag_stdev=nn.softplus(diag_stdev),
validate_args=validate_args,
allow_nan_stats=allow_nan_stats,
name=ns)
self._parameters = parameters 示例9: _kl_bernoulli_bernoulli
# 需要导入模块: from tensorflow.python.ops import nn [as 别名]
# 或者: from tensorflow.python.ops.nn import softplus [as 别名]
def _kl_bernoulli_bernoulli(a, b, name=None):
"""Calculate the batched KL divergence KL(a || b) with a and b Bernoulli.
Args:
a: instance of a Bernoulli distribution object.
b: instance of a Bernoulli distribution object.
name: (optional) Name to use for created operations.
default is "kl_bernoulli_bernoulli".
Returns:
Batchwise KL(a || b)
"""
with ops.name_scope(name, "kl_bernoulli_bernoulli", [a.logits, b.logits]):
return (math_ops.sigmoid(a.logits) * (-nn.softplus(-a.logits) +
nn.softplus(-b.logits)) +
math_ops.sigmoid(-a.logits) * (-nn.softplus(a.logits) +
nn.softplus(b.logits))) 示例10: __init__
# 需要导入模块: from tensorflow.python.ops import nn [as 别名]
# 或者: from tensorflow.python.ops.nn import softplus [as 别名]
def __init__(self,
loc,
scale,
validate_args=False,
allow_nan_stats=True,
name="LaplaceWithSoftplusScale"):
parameters = locals()
parameters.pop("self")
with ops.name_scope(name, values=[loc, scale]) as ns:
super(LaplaceWithSoftplusScale, self).__init__(
loc=loc,
scale=nn.softplus(scale, name="softplus_scale"),
validate_args=validate_args,
allow_nan_stats=allow_nan_stats,
name=ns)
self._parameters = parameters 示例11: __init__
# 需要导入模块: from tensorflow.python.ops import nn [as 别名]
# 或者: from tensorflow.python.ops.nn import softplus [as 别名]
def __init__(self,
mu,
sigma,
validate_args=False,
allow_nan_stats=True,
name="NormalWithSoftplusSigma"):
parameters = locals()
parameters.pop("self")
with ops.name_scope(name, values=[sigma]) as ns:
super(NormalWithSoftplusSigma, self).__init__(
mu=mu,
sigma=nn.softplus(sigma, name="softplus_sigma"),
validate_args=validate_args,
allow_nan_stats=allow_nan_stats,
name=ns)
self._parameters = parameters 示例12: __init__
# 需要导入模块: from tensorflow.python.ops import nn [as 别名]
# 或者: from tensorflow.python.ops.nn import softplus [as 别名]
def __init__(self,
alpha,
beta,
validate_args=False,
allow_nan_stats=True,
name="GammaWithSoftplusAlphaBeta"):
parameters = locals()
parameters.pop("self")
with ops.name_scope(name, values=[alpha, beta]) as ns:
super(GammaWithSoftplusAlphaBeta, self).__init__(
alpha=nn.softplus(alpha),
beta=nn.softplus(beta),
validate_args=validate_args,
allow_nan_stats=allow_nan_stats,
name=ns)
self._parameters = parameters 示例13: __init__
# 需要导入模块: from tensorflow.python.ops import nn [as 别名]
# 或者: from tensorflow.python.ops.nn import softplus [as 别名]
def __init__(self,
alpha,
beta,
validate_args=False,
allow_nan_stats=True,
name="InverseGammaWithSoftplusAlphaBeta"):
parameters = locals()
parameters.pop("self")
with ops.name_scope(name, values=[alpha, beta]) as ns:
super(InverseGammaWithSoftplusAlphaBeta, self).__init__(
alpha=nn.softplus(alpha),
beta=nn.softplus(beta),
validate_args=validate_args,
allow_nan_stats=allow_nan_stats,
name=ns)
self._parameters = parameters 示例14: __init__
# 需要导入模块: from tensorflow.python.ops import nn [as 别名]
# 或者: from tensorflow.python.ops.nn import softplus [as 别名]
def __init__(self,
a,
b,
validate_args=False,
allow_nan_stats=True,
name="BetaWithSoftplusAB"):
parameters = locals()
parameters.pop("self")
with ops.name_scope(name, values=[a, b]) as ns:
super(BetaWithSoftplusAB, self).__init__(
a=nn.softplus(a),
b=nn.softplus(b),
validate_args=validate_args,
allow_nan_stats=allow_nan_stats,
name=ns)
self._parameters = parameters 示例15: __init__
# 需要导入模块: from tensorflow.python.ops import nn [as 别名]
# 或者: from tensorflow.python.ops.nn import softplus [as 别名]
def __init__(self,
loc,
scale,
validate_args=False,
allow_nan_stats=True,
name="LaplaceWithSoftplusScale"):
parameters = locals()
parameters.pop("self")
with ops.name_scope(name, values=[loc, scale]) as ns:
super(LaplaceWithSoftplusScale, self).__init__(
loc=loc,
scale=nn.softplus(scale),
validate_args=validate_args,
allow_nan_stats=allow_nan_stats,
name=ns)
self._parameters = parameters