vrec

Description

Performs the reciprocal operation on a tensor element-wise and returns 1/x.

Prototype

vrec(raw_tensor, impl_mode="high_performance")

Parameters

• raw_tensor: a tvm.tensor for the input tensor

  Atlas training product: supports float16 and float32.

  Atlas inference product: supports float16 and float32.

  Atlas 200I/500 A2 inference product: supports float16 and float32.

  Atlas A2 training product/Atlas A2 inference product: supports float16 and float32.

  Atlas A3 training product/Atlas A3 inference product: supports float16 and float32.

• impl_mode: specifies if precision takes priority over performance.
  • high_precision: Precision takes priority. In this case, performance is compromised due to the complex compute process.
  • high_performance: Performance takes priority. In this case, the precision decreases.

  Defaults to high_performance.

Returns

res_tensor: a tvm.tensor for the result tensor

Restrictions

None

Applicability

Atlas training product

Atlas inference product

Atlas 200I/500 A2 inference product

Atlas A2 training product/Atlas A2 inference product

Atlas A3 training product/Atlas A3 inference product

Example

from tbe import tvm
from tbe import dsl
shape = (1024,1024)
input_dtype = "float16"
data = tvm.placeholder(shape, name="data", dtype=input_dtype)
res = dsl.vrec(data)