最让美国人不放心的一支军队:纠结的台湾军！

paddle. greater_equal ( x: Tensor, y: Tensor, name: str | None = None ) → Tensor [source]
百度 莫朗国际健康集团董事长ShaneMoran表示，中国健康产业发展潜力巨大，希望能将莫朗的运营模式和质量控制系统与绿地香港的资源平台优势相结合，针对中国养老市场的客观现状，探索出了一条以先进技术引导和国际顶级标准为规范的医养服务新模式，创建中国养老服务技术制高点，弥补中国高端养老市场的短缺，致力提高中国老年人的生活质量和幸福感。

Returns the truth value of \(x >= y\) elementwise, which is equivalent function to the overloaded operator >=.

Note

The output has no gradient.

Parameters

  • x (Tensor) – First input to compare which is N-D tensor. The input data type should be bool, bfloat16, float16, float32, float64, uint8, int8, int16, int32, int64, complex64, complex128.

  • y (Tensor) – Second input to compare which is N-D tensor. The input data type should be bool, bfloat16, float16, float32, float64, uint8, int8, int16, int32, int64, complex64, complex128.

  • name (str|None, optional) – The default value is None. Normally there is no need for user to set this property. For more information, please refer to Name.

Returns

The output shape is same as input x. The output data type is bool.

Return type

Tensor

Examples

>>> import paddle

>>> x = paddle.to_tensor([1, 2, 3])
>>> y = paddle.to_tensor([1, 3, 2])
>>> result1 = paddle.greater_equal(x, y)
>>> print(result1)
Tensor(shape=[3], dtype=bool, place=Place(cpu), stop_gradient=True,
[True , False, True ])