Common Compute APIs

Description

Rounds data towards the range of [min_value, max_value] and compares data with min_value and max_value element-wise. If the element value is between min_value and max_value, use the value of the data element. If the element value is less than min_value or greater than max_value, these min_value and max_value will be preferred.

The API is defined in python/site-packages/te/lang/cce/te_compute/common.py in the ATC installation path.

Restrictions

In case of data type inconsistency, max_value and min_value will be converted into the same data type as data during computation.

The supported data types are float16, float32, int8, uint8, and int32. However, int8, uint8, and int32 will be converted to float16.

Prototype

te.lang.cce.round_to(data, max_value, min_value)

Parameters

• data: a tvm.tensor for the input
• max_value: a scalar for the maximum value of the target range
• min_value: a scalar for the minimum value of the target range

Returns

res_tensor: a tvm.tensor for the result

Example

shape = (1024,1024)
input_dtype = "float16"
data = tvm.placeholder(shape, name="data", dtype=input_dtype)
max_value = tvm.const(2, dtype =input_dtype)
min_value = tvm.const(3, dtype =input_dtype)
res = te.lang.cce.round_to(data, max_value, min_value)

Description

Converts the data type of a tensor, specifically, from data to dtype.

The API is defined in python/site-packages/te/lang/cce/te_compute/common.py in the ATC installation path.

Restrictions

Prototype

te.lang.cce.cast_to(data, dtype, f1628IntegerFlag=True)

Parameters

• data: a tvm.tensor for the input tensor
• dtype: destination data type, string type
• f1628IntegerFlag: Defaults to True. If the decimal part of the data before conversion is 0, set f1628IntegerFlag to True. If the decimal part of the data before conversion is not 0, set f1628IntegerFlag to False.

Returns

res_tensor: a tvm.tensor for the result tensor

Example

shape = (1024,1024)
input_dtype = "float16"
data = tvm.placeholder(shape, name="data", dtype=input_dtype)
res = te.lang.cce.cast_to(data,"float32")