Function Usage

Image processing algorithm, tensor square root operation (Sqrt). The float16 and float32 data types are supported. Asynchronous calling is supported. The inplace operation is not supported.

It is supported by the Atlas inference product and Atlas 200I/500 A2 inference product.

For the Atlas 200I/500 A2 inference products, preloading is supported (see Example of the Preloading File of the Initialization Operator).

The following conditions must be met:

The input and output tensors must be on the device or DVPP side, and the parameters (stream and data memory) must be on the same device.
For synchronization, the device where the data memory is located must be the same as the initialized device.
The input and output parameters cannot exceed four dimensions, and must match the tensor shapes and types. The values cannot be negative.
For the Atlas inference product, when the tensor size is greater than 480p (640 x 480), the compute performance of Sqrt is better than that of cv::sqrt on the CPU.
For the Atlas 200I/500 A2 inference product, when the input size is greater than 720p (1280 x 720), the compute performance is better than that of cv::sqrt on the CPU.

Prototype

APP_ERROR Sqrt(const Tensor &src, Tensor &dst, AscendStream &stream = AscendStream::DefaultStream());

Parameters

Parameter	Input/Output	Description
src	Input	Tensor class, input tensor, supporting the float16 and float32 data types.
dst	Output	Tensor class, output tensor, supporting float16 and float32 data types. An empty tensor can be passed. If dst is not an empty tensor, call Tensor.Malloc() to allocate memory in advance.
stream	Input	AscendStream type. The default value is AscendStream::DefaultStream(). When the parameter value is the default value, the API calling is a synchronous operation. In other cases, the API calling is an asynchronous operation.

Response Parameters

Data Structure	Description
APP_ERROR	For details about the returned error codes, see APP_ERROR Description.