本文整理汇总了Python中tensorflow.python.keras.backend.epsilon函数的典型用法代码示例。如果您正苦于以下问题：Python epsilon函数的具体用法？Python epsilon怎么用？Python epsilon使用的例子？那么恭喜您, 这里精选的函数代码示例或许可以为您提供帮助。
在下文中一共展示了epsilon函数的12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: logloss
def logloss(y_true, y_pred):
y_pred = ops.convert_to_tensor(y_pred)
y_true = math_ops.cast(y_true, y_pred.dtype)
losses = math_ops.multiply(y_true, math_ops.log(y_pred + K.epsilon()))
losses += math_ops.multiply((1 - y_true),
math_ops.log(1 - y_pred + K.epsilon()))
return K.mean(-losses, axis=-1)示例2: __call__
def __call__(self, w):
norms = K.sqrt(
math_ops.reduce_sum(math_ops.square(w), axis=self.axis, keepdims=True))
desired = (
self.rate * K.clip(norms, self.min_value, self.max_value) +
(1 - self.rate) * norms)
return w * (desired / (K.epsilon() + norms))示例3: __init__
def __init__(self, lr=0.01, epsilon=None, decay=0., **kwargs):
super(Adagrad, self).__init__(**kwargs)
with K.name_scope(self.__class__.__name__):
self.lr = K.variable(lr, name='lr')
self.decay = K.variable(decay, name='decay')
self.iterations = K.variable(0, dtype='int64', name='iterations')
if epsilon is None:
epsilon = K.epsilon()
self.epsilon = epsilon
self.initial_decay = decay示例4: poisson
def poisson(y_true, y_pred):
return K.mean(y_pred - y_true * math_ops.log(y_pred + K.epsilon()), axis=-1)示例5: kullback_leibler_divergence
def kullback_leibler_divergence(y_true, y_pred):
y_true = K.clip(y_true, K.epsilon(), 1)
y_pred = K.clip(y_pred, K.epsilon(), 1)
return math_ops.reduce_sum(y_true * math_ops.log(y_true / y_pred), axis=-1)示例6: mean_squared_logarithmic_error
def mean_squared_logarithmic_error(y_true, y_pred):
first_log = math_ops.log(K.clip(y_pred, K.epsilon(), None) + 1.)
second_log = math_ops.log(K.clip(y_true, K.epsilon(), None) + 1.)
return K.mean(math_ops.square(first_log - second_log), axis=-1)示例7: mean_absolute_percentage_error
def mean_absolute_percentage_error(y_true, y_pred):
diff = math_ops.abs(
(y_true - y_pred) / K.clip(math_ops.abs(y_true), K.epsilon(), None))
return 100. * K.mean(diff, axis=-1)示例8: poisson
def poisson(y_true, y_pred):
y_pred = ops.convert_to_tensor(y_pred)
y_true = math_ops.cast(y_true, y_pred.dtype)
return K.mean(y_pred - y_true * math_ops.log(y_pred + K.epsilon()), axis=-1)示例9: kullback_leibler_divergence
def kullback_leibler_divergence(y_true, y_pred): # pylint: disable=missing-docstring
y_pred = ops.convert_to_tensor(y_pred)
y_true = math_ops.cast(y_true, y_pred.dtype)
y_true = K.clip(y_true, K.epsilon(), 1)
y_pred = K.clip(y_pred, K.epsilon(), 1)
return math_ops.reduce_sum(y_true * math_ops.log(y_true / y_pred), axis=-1)示例10: mean_squared_logarithmic_error
def mean_squared_logarithmic_error(y_true, y_pred): # pylint: disable=missing-docstring
y_pred = ops.convert_to_tensor(y_pred)
y_true = math_ops.cast(y_true, y_pred.dtype)
first_log = math_ops.log(K.clip(y_pred, K.epsilon(), None) + 1.)
second_log = math_ops.log(K.clip(y_true, K.epsilon(), None) + 1.)
return K.mean(math_ops.squared_difference(first_log, second_log), axis=-1)示例11: mean_absolute_percentage_error
def mean_absolute_percentage_error(y_true, y_pred): # pylint: disable=missing-docstring
y_pred = ops.convert_to_tensor(y_pred)
y_true = math_ops.cast(y_true, y_pred.dtype)
diff = math_ops.abs(
(y_true - y_pred) / K.clip(math_ops.abs(y_true), K.epsilon(), None))
return 100. * K.mean(diff, axis=-1)示例12: logloss
def logloss(y_true, y_pred):
losses = math_ops.multiply(y_true, math_ops.log(y_pred + K.epsilon()))
losses += math_ops.multiply((1 - y_true),
math_ops.log(1 - y_pred + K.epsilon()))
return K.mean(-losses, axis=-1)