Acosh

English | 简体中文

Inverse hyperbolic cosine operator, which corresponds to PyTorch torch.acosh / torch.acosh_. Online aclnn API documentation: docs/aclnnAcosh&aclnnInplaceAcosh_en.md

Product Support Status

Product	Supported
Ascend 950PR&950DT products	√
Atlas A3 products	√
Atlas A2 products	√
Atlas 200I/500 A2 inference products	√
Atlas inference products	√
Atlas training products	√

Function Description

• API function: computes the inverse hyperbolic cosine of each element in the input Tensor and outputs the result.

• Computation formula:

  $$out=cos{h}^{-1}(self)$$

Parameter Description

Parameter Name	Input/Output/Attribute	Description	Data Type	Data Format
x	Input	The input x in the formula, whose dtype is the same as that of y and whose shape is arbitrary (0 to 8 dimensions). Empty tensors are supported. A non-contiguous tensor input is automatically converted to a contiguous tensor by the framework before execution.	FLOAT, FLOAT16, BFLOAT16	ND
y	Output	The output y in the formula, whose shape is exactly the same as that of x. A non-contiguous tensor output is automatically converted to a contiguous tensor by the framework before execution.	FLOAT, FLOAT16, BFLOAT16	ND
selfRef	Input/Output	A parameter specific to the aclnn in-place API (corresponding to the input x and output y in the operator definition). It is a tensor that serves as both input and output, and the computation result is written back in place. A non-contiguous tensor is automatically converted to a contiguous tensor by the framework before execution.	FLOAT, FLOAT16, BFLOAT16	ND

Constraint Description

• The value range of the real input is [1, +∞). When x is less than 1, NaN is output.
• The number of shape dimensions ∈ [0, 8], and the shape of y is exactly the same as that of x.

Invocation Description

Invocation Method	Invocation Sample	Description
aclnn invocation (non-in-place)	examples/test_aclnn_acosh.cpp	Refer to build.sh in the root directory of the ops-math repository to complete operator compilation and operator package installation, and then use the examples for verification (on a real NPU).
aclnn invocation (in-place)	examples/test_aclnn_inplace_acosh.cpp