本文整理汇总了Python中tensorflow.python.ops.array_ops.broadcast_dynamic_shape方法的典型用法代码示例。如果您正苦于以下问题：Python array_ops.broadcast_dynamic_shape方法的具体用法？Python array_ops.broadcast_dynamic_shape怎么用？Python array_ops.broadcast_dynamic_shape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.array_ops的用法示例。
在下文中一共展示了array_ops.broadcast_dynamic_shape方法的14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: prefer_static_broadcast_shape
# 需要导入模块: from tensorflow.python.ops import array_ops [as 别名]
# 或者: from tensorflow.python.ops.array_ops import broadcast_dynamic_shape [as 别名]
def prefer_static_broadcast_shape(
shape1, shape2, name="prefer_static_broadcast_shape"):
"""Convenience function which statically broadcasts shape when possible.
Args:
shape1: `1-D` integer `Tensor`. Already converted to tensor!
shape2: `1-D` integer `Tensor`. Already converted to tensor!
name: A string name to prepend to created ops.
Returns:
The broadcast shape, either as `TensorShape` (if broadcast can be done
statically), or as a `Tensor`.
"""
with ops.name_scope(name, values=[shape1, shape2]):
if (tensor_util.constant_value(shape1) is not None and
tensor_util.constant_value(shape2) is not None):
return array_ops.broadcast_static_shape(
tensor_shape.TensorShape(tensor_util.constant_value(shape1)),
tensor_shape.TensorShape(tensor_util.constant_value(shape2)))
return array_ops.broadcast_dynamic_shape(shape1, shape2) 示例2: _batch_shape_tensor
# 需要导入模块: from tensorflow.python.ops import array_ops [as 别名]
# 或者: from tensorflow.python.ops.array_ops import broadcast_dynamic_shape [as 别名]
def _batch_shape_tensor(self):
return array_ops.broadcast_dynamic_shape(
array_ops.shape(self.concentration),
array_ops.shape(self.rate)) 示例3: _batch_shape_tensor
# 需要导入模块: from tensorflow.python.ops import array_ops [as 别名]
# 或者: from tensorflow.python.ops.array_ops import broadcast_dynamic_shape [as 别名]
def _batch_shape_tensor(self):
return array_ops.broadcast_dynamic_shape(
array_ops.shape(self.df),
array_ops.broadcast_dynamic_shape(
array_ops.shape(self.loc), array_ops.shape(self.scale))) 示例4: _batch_shape_tensor
# 需要导入模块: from tensorflow.python.ops import array_ops [as 别名]
# 或者: from tensorflow.python.ops.array_ops import broadcast_dynamic_shape [as 别名]
def _batch_shape_tensor(self):
return array_ops.broadcast_dynamic_shape(
array_ops.shape(self.low),
array_ops.shape(self.high)) 示例5: _cdf
# 需要导入模块: from tensorflow.python.ops import array_ops [as 别名]
# 或者: from tensorflow.python.ops.array_ops import broadcast_dynamic_shape [as 别名]
def _cdf(self, x):
broadcast_shape = array_ops.broadcast_dynamic_shape(
array_ops.shape(x), self.batch_shape_tensor())
zeros = array_ops.zeros(broadcast_shape, dtype=self.dtype)
ones = array_ops.ones(broadcast_shape, dtype=self.dtype)
broadcasted_x = x * ones
result_if_not_big = array_ops.where(
x < self.low, zeros, (broadcasted_x - self.low) / self.range())
return array_ops.where(x >= self.high, ones, result_if_not_big) 示例6: _batch_shape_tensor
# 需要导入模块: from tensorflow.python.ops import array_ops [as 别名]
# 或者: from tensorflow.python.ops.array_ops import broadcast_dynamic_shape [as 别名]
def _batch_shape_tensor(self):
return array_ops.broadcast_dynamic_shape(
array_ops.shape(self.loc), array_ops.shape(self.scale)) 示例7: _batch_shape_tensor
# 需要导入模块: from tensorflow.python.ops import array_ops [as 别名]
# 或者: from tensorflow.python.ops.array_ops import broadcast_dynamic_shape [as 别名]
def _batch_shape_tensor(self):
return array_ops.broadcast_dynamic_shape(
array_ops.shape(self.total_count),
array_ops.shape(self.probs)) 示例8: _shape_tensor
# 需要导入模块: from tensorflow.python.ops import array_ops [as 别名]
# 或者: from tensorflow.python.ops.array_ops import broadcast_dynamic_shape [as 别名]
def _shape_tensor(self):
batch_shape = array_ops.broadcast_dynamic_shape(
self.base_operator.batch_shape_tensor(),
array_ops.shape(self.u)[:-2])
return array_ops.concat(
[batch_shape, self.base_operator.shape_tensor()[-2:]], axis=0) 示例9: _batch_shape
# 需要导入模块: from tensorflow.python.ops import array_ops [as 别名]
# 或者: from tensorflow.python.ops.array_ops import broadcast_dynamic_shape [as 别名]
def _batch_shape(self):
return array_ops.broadcast_dynamic_shape(
array_ops.shape(self.alpha), array_ops.shape(self.beta)) 示例10: _batch_shape
# 需要导入模块: from tensorflow.python.ops import array_ops [as 别名]
# 或者: from tensorflow.python.ops.array_ops import broadcast_dynamic_shape [as 别名]
def _batch_shape(self):
return array_ops.broadcast_dynamic_shape(
array_ops.shape(self.loc), array_ops.shape(self.scale)) 示例11: _batch_shape
# 需要导入模块: from tensorflow.python.ops import array_ops [as 别名]
# 或者: from tensorflow.python.ops.array_ops import broadcast_dynamic_shape [as 别名]
def _batch_shape(self):
return array_ops.broadcast_dynamic_shape(
array_ops.shape(self.df),
array_ops.broadcast_dynamic_shape(
array_ops.shape(self.mu), array_ops.shape(self.sigma))) 示例12: _batch_shape
# 需要导入模块: from tensorflow.python.ops import array_ops [as 别名]
# 或者: from tensorflow.python.ops.array_ops import broadcast_dynamic_shape [as 别名]
def _batch_shape(self):
return array_ops.broadcast_dynamic_shape(
array_ops.shape(self.n), array_ops.shape(self.p)) 示例13: _batch_shape
# 需要导入模块: from tensorflow.python.ops import array_ops [as 别名]
# 或者: from tensorflow.python.ops.array_ops import broadcast_dynamic_shape [as 别名]
def _batch_shape(self):
return array_ops.broadcast_dynamic_shape(
array_ops.shape(self.mu), array_ops.shape(self.sigma)) 示例14: _batch_shape_tensor
# 需要导入模块: from tensorflow.python.ops import array_ops [as 别名]
# 或者: from tensorflow.python.ops.array_ops import broadcast_dynamic_shape [as 别名]
def _batch_shape_tensor(self):
return array_ops.broadcast_dynamic_shape(
array_ops.shape(self._loc),
array_ops.shape(self._scale))