Sum#
Sum - 13#
Version#
name: Sum (GitHub)
domain:
main
since_version:
13
function:
False
support_level:
SupportType.COMMON
shape inference:
True
This version of the operator has been available since version 13.
Summary#
Element-wise sum of each of the input tensors (with Numpy-style broadcasting support). All inputs and outputs must have the same data type. This operator supports multidirectional (i.e., Numpy-style) broadcasting; for more details please check Broadcasting in ONNX.
Inputs#
Between 1 and 2147483647 inputs.
data_0 (variadic, heterogeneous) - T:
List of tensors for sum.
Outputs#
sum (heterogeneous) - T:
Output tensor.
Type Constraints#
T in (
tensor(bfloat16)
,tensor(double)
,tensor(float)
,tensor(float16)
):Constrain input and output types to float tensors.
Sum - 8#
Version#
name: Sum (GitHub)
domain:
main
since_version:
8
function:
False
support_level:
SupportType.COMMON
shape inference:
True
This version of the operator has been available since version 8.
Summary#
Element-wise sum of each of the input tensors (with Numpy-style broadcasting support). All inputs and outputs must have the same data type. This operator supports multidirectional (i.e., Numpy-style) broadcasting; for more details please check Broadcasting in ONNX.
Inputs#
Between 1 and 2147483647 inputs.
data_0 (variadic, heterogeneous) - T:
List of tensors for sum.
Outputs#
sum (heterogeneous) - T:
Output tensor.
Type Constraints#
T in (
tensor(double)
,tensor(float)
,tensor(float16)
):Constrain input and output types to float tensors.
Sum - 6#
Version#
name: Sum (GitHub)
domain:
main
since_version:
6
function:
False
support_level:
SupportType.COMMON
shape inference:
True
This version of the operator has been available since version 6.
Summary#
Element-wise sum of each of the input tensors. All inputs and outputs must have the same shape and data type.
Inputs#
Between 1 and 2147483647 inputs.
data_0 (variadic, heterogeneous) - T:
List of tensors for Sum.
Outputs#
sum (heterogeneous) - T:
Output tensor. Same dimension as inputs.
Type Constraints#
T in (
tensor(double)
,tensor(float)
,tensor(float16)
):Constrain input and output types to float tensors.
Sum - 1#
Version#
name: Sum (GitHub)
domain:
main
since_version:
1
function:
False
support_level:
SupportType.COMMON
shape inference:
False
This version of the operator has been available since version 1.
Summary#
Element-wise sum of each of the input tensors. All inputs and outputs must have the same shape and data type.
Attributes#
consumed_inputs - INTS :
legacy optimization attribute.
Inputs#
Between 1 and 2147483647 inputs.
data_0 (variadic, heterogeneous) - T:
List of tensors for Sum.
Outputs#
sum (heterogeneous) - T:
Output tensor. Same dimension as inputs.
Type Constraints#
T in (
tensor(double)
,tensor(float)
,tensor(float16)
):Constrain input and output types to float tensors.