Shape - 21 vs 23

Next section compares an older to a newer version of the same operator after both definition are converted into markdown text.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.

Files changed (1) hide show
  1. Shape21 → Shape23 +1 -1
Shape21 → Shape23 RENAMED
@@ -1 +1 @@
1
1
  Takes a tensor as input and outputs an 1D int64 tensor containing the shape of the input tensor.
2
2
  Optional attributes start and end can be used to compute a slice of the input tensor's shape.
3
3
  If start axis is omitted, the slice starts from axis 0.
4
4
  The end axis, if specified, is exclusive (and the returned value will not include the size of that axis).
5
5
  If the end axis is omitted, the axes upto the last one will be included.
6
6
  Negative axes indicate counting back from the last axis.
7
7
  Note that axes will be clamped to the range [0, r-1], where r is the
8
8
  rank of the input tensor if they are out-of-range (after adding r in the case of
9
9
  negative axis). Thus, specifying any end value > r is equivalent to specifying an end
10
10
  value of r, and specifying any start value < -r is equivalent to specifying a start
11
11
  value of 0.
12
12
  Examples:
13
13
  Input tensor with shape: [2, 3, 4]
14
14
  No attributes specified.
15
15
  Output: [2, 3, 4]
16
16
  Input tensor with shape: [2, 3, 4]
17
17
  start: -1
18
18
  Output: [4]
19
19
  Input tensor with shape: [2, 3, 4]
20
20
  end: -1
21
21
  Output: [2, 3]
22
22
  Input tensor with shape: [2, 3, 4]
23
23
  start: 1
24
24
  end: 2
25
25
  Output: [3]
26
26
  ### Attributes
27
27
  * **end - INT** :
28
28
  (Optional) Ending axis for slicing the shape. Negative value means counting dimensions from the back. If omitted, sizes of all axes upto (including) the last one will be included.
29
29
  * **start - INT** (default is '0'):
30
30
  (Optional) Starting axis for slicing the shape. Default value is 0.Negative value means counting dimensions from the back.
31
31
  ### Inputs
32
32
  - **data** (heterogeneous) - **T**:
33
33
  An input tensor.
34
34
  ### Outputs
35
35
  - **shape** (heterogeneous) - **T1**:
36
36
  Shape of the input tensor
37
37
  ### Type Constraints
38
- * **T** in ( tensor(bfloat16), tensor(bool), tensor(complex128), tensor(complex64), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int4), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint4), tensor(uint64), tensor(uint8) ):
38
+ * **T** in ( tensor(bfloat16), tensor(bool), tensor(complex128), tensor(complex64), tensor(double), tensor(float), tensor(float16), tensor(float4e2m1), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int4), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint4), tensor(uint64), tensor(uint8) ):
39
39
  Input tensor can be of arbitrary type.
40
40
  * **T1** in ( tensor(int64) ):
41
41
  Constrain output to int64 tensor.