ReduceSumSquare - 1 vs 13

Next section compares an older to a newer version of the same operator after both definition are converted into markdown text. Green means an addition to the newer version, red means a deletion. Anything else is unchanged.

ReduceSumSquare1 → ReduceSumSquare13 RENAMED
@@ -1 +1 @@
1
- Computes the sum square of the input tensor's element along the provided axes. The resulting
1
+ Computes the sum square of the input tensor's elements along the provided axes. The resulting
2
- tensor has the same rank as the input if keepdims equals 1. If keepdims equal 0, then
2
+ tensor has the same rank as the input if keepdims equals 1. If keepdims equals 0, then
3
- the resulted tensor have the reduced dimension pruned. Input tensors of rank zero are
3
+ the resulting tensor has the reduced dimension pruned. Input tensors of rank zero are
4
4
  valid. Reduction over an empty set of values yields 0.
5
- The above behavior is similar to numpy, with the exception that numpy defaults keepdims to
5
+ The above behavior is similar to numpy, with the exception that numpy defaults keepdims
6
- False instead of True.
6
+ to False instead of True.
7
7
  ### Attributes
8
8
  * **axes - INTS** :
9
- A list of integers, along which to reduce. The default is to reduce over all the dimensions of the input tensor.
9
+ A list of integers, along which to reduce. The default is to reduce over all the dimensions of the input tensor. Accepted range is [-r, r-1] where r = rank(data).
10
10
  * **keepdims - INT** (default is '1'):
11
11
  Keep the reduced dimension or not, default 1 means keep reduced dimension.
12
12
  ### Inputs
13
13
  - **data** (heterogeneous) - **T**:
14
14
  An input tensor.
15
15
  ### Outputs
16
16
  - **reduced** (heterogeneous) - **T**:
17
17
  Reduced output tensor.
18
18
  ### Type Constraints
19
- * **T** in ( tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64) ):
19
+ * **T** in ( tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64) ):
20
- Constrain input and output types to high-precision numeric tensors.? ---------------
20
+ Constrain input and output types to numeric tensors.