Reshape - 1 vs 5

Files changed (1) hide show
  1. Reshape1 → Reshape5 +17 -10
Reshape1 → Reshape5 RENAMED
@@ -1 +1 @@
1
1
  Reshape the input tensor similar to numpy.reshape.
2
- It takes a tensor as input and an argument shape. It outputs the reshaped tensor.
2
+ First input is the data tensor, second input is a shape tensor which specifies the output shape. It outputs the reshaped tensor.
3
3
  At most one dimension of the new shape can be -1. In this case, the value is
4
4
  inferred from the size of the tensor and the remaining dimensions. A dimension
5
5
  could also be 0, in which case the actual dimension value is unchanged (i.e. taken
6
6
  from the input tensor). Shape (second input) could be an empty shape, which means converting to a scalar.
7
7
  The input tensor's shape and the output tensor's shape are required to have the same number of elements.
8
- **Attributes**
9
-
10
- * **consumed_inputs**:
11
- legacy optimization attribute.
12
- * **shape**:
13
- New shape
14
-
15
8
  **Inputs**
16
9
  * **data** (heterogeneous) - **T**:
17
10
  An input tensor.
11
+ * **shape** (heterogeneous) - **tensor(int64)**:
12
+ Specified shape for output.
18
13
  **Outputs**
19
14
  * **reshaped** (heterogeneous) - **T**:
20
15
  Reshaped data.
21
16
  **Type Constraints**
22
17
  * **T** in (
18
+ tensor(bool),
19
+ tensor(complex128),
20
+ tensor(complex64),
23
21
  tensor(double),
24
22
  tensor(float),
25
- tensor(float16)
23
+ tensor(float16),
24
+ tensor(int16),
25
+ tensor(int32),
26
+ tensor(int64),
27
+ tensor(int8),
28
+ tensor(string),
29
+ tensor(uint16),
30
+ tensor(uint32),
31
+ tensor(uint64),
32
+ tensor(uint8)
26
33
  ):
27
- Constrain input and output types to float tensors.? ^ ^^^
34
+ Constrain input and output types to all tensor types.? ^ ^ +++++