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Specifications and Common Mistakes

- Specifications and Common Mistakes:

- Misspellings or punctuation mistakes,incorrect formulas, abnormal display.

- Incorrect links, empty cells, or wrong formats.

- Chinese characters in English context.

- Minor inconsistencies between the UI and descriptions.

- Low writing fluency that does not affect understanding.

- Incorrect version numbers, including software package names and version numbers on the UI.

Usability

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- Incorrect or missing key steps.

- Missing main function descriptions, keyword explanation, necessary prerequisites, or precautions.

- Ambiguous descriptions, unclear reference, or contradictory context.

- Unclear logic, such as missing classifications, items, and steps.

Correctness

- Correctness:

- Technical principles, function descriptions, supported platforms, parameter types, or exceptions inconsistent with that of software implementation.

- Incorrect schematic or architecture diagrams.

- Incorrect commands or command parameters.

- Incorrect code.

- Commands inconsistent with the functions.

- Wrong screenshots.

- Sample code running error, or running results inconsistent with the expectation.

Risk Warnings

- Risk Warnings:

- Lack of risk warnings for operations that may damage the system or important data.

Content Compliance

- Content Compliance:

- Contents that may violate applicable laws and regulations or geo-cultural context-sensitive words and expressions.

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mindspore.ops.bessel_y1

mindspore.ops.bessel_y1(x)

Computes the first order Bessel function of the second kind for each element input.

$$\begin{array}{r}\begin{array}{l}\\ Y_1(x)=\underset{n\to 1}{lim}\frac{J_n(x)\cos n\pi -J_{-n}(x)}{\sin n\pi }\end{array}\end{array}$$

Parameters

x (Tensor) – The input tensor.

Returns

Tensor

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore
>>> x = mindspore.tensor([0.5, 1., 2., 4.])
>>> output = mindspore.ops.bessel_y1(x)
>>> print(output)
[-1.47147239  -0.78121282  -0.10703243  0.39792571]