Equal#
Equal - 13#
Version
name: Equal (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
Returns the tensor resulted from performing the equal logical operation elementwise on the input tensors A and B (with Numpy-style broadcasting support).
This operator supports multidirectional (i.e., Numpy-style) broadcasting; for more details please check Broadcasting in ONNX.
Inputs
A (heterogeneous) - T: First input operand for the logical operator.
B (heterogeneous) - T: Second input operand for the logical operator.
Outputs
C (heterogeneous) - T1: Result tensor.
Type Constraints
T in ( tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) ): Constrains input types to all numeric tensors.
T1 in ( tensor(bool) ): Constrains output to boolean tensor.
Examples
equal_broadcast
node = onnx.helper.make_node(
'Equal',
inputs=['x', 'y'],
outputs=['z'],
)
x = (np.random.randn(3, 4, 5) * 10).astype(np.int32)
y = (np.random.randn(5) * 10).astype(np.int32)
z = np.equal(x, y)
expect(node, inputs=[x, y], outputs=[z],
name='test_equal_bcast')
Differences
0 | 0 | Returns the tensor resulted from performing the equal logical operation | Returns the tensor resulted from performing the equal logical operation |
1 | 1 | elementwise on the input tensors A and B (with Numpy-style broadcasting support). | elementwise on the input tensors A and B (with Numpy-style broadcasting support). |
2 | 2 | | |
3 | 3 | This operator supports **multidirectional (i.e., Numpy-style) broadcasting**; for more details please check Broadcasting in ONNX | This operator supports **multidirectional (i.e., Numpy-style) broadcasting**; for more details please check Broadcasting in ONNX |
4 | 4 | | |
5 | 5 | **Inputs** | **Inputs** |
6 | 6 | | |
7 | 7 | * **A** (heterogeneous) - **T**: | * **A** (heterogeneous) - **T**: |
8 | 8 | First input operand for the logical operator. | First input operand for the logical operator. |
9 | 9 | * **B** (heterogeneous) - **T**: | * **B** (heterogeneous) - **T**: |
10 | 10 | Second input operand for the logical operator. | Second input operand for the logical operator. |
11 | 11 | | |
12 | 12 | **Outputs** | **Outputs** |
13 | 13 | | |
14 | 14 | * **C** (heterogeneous) - **T1**: | * **C** (heterogeneous) - **T1**: |
15 | 15 | Result tensor. | Result tensor. |
16 | 16 | | |
17 | 17 | **Type Constraints** | **Type Constraints** |
18 | 18 | | |
19 | 19 | * **T** in ( | * **T** in ( |
20 | tensor(bfloat16), | ||
20 | 21 | tensor(bool), | tensor(bool), |
21 | 22 | tensor(double), | tensor(double), |
22 | 23 | tensor(float), | tensor(float), |
23 | 24 | tensor(float16), | tensor(float16), |
24 | 25 | tensor(int16), | tensor(int16), |
25 | 26 | tensor(int32), | tensor(int32), |
26 | 27 | tensor(int64), | tensor(int64), |
27 | 28 | tensor(int8), | tensor(int8), |
28 | 29 | tensor(uint16), | tensor(uint16), |
29 | 30 | tensor(uint32), | tensor(uint32), |
30 | 31 | tensor(uint64), | tensor(uint64), |
31 | 32 | tensor(uint8) | tensor(uint8) |
32 | 33 | ): | ): |
33 | 34 | Constrains input types to all numeric tensors. | Constrains input types to all numeric tensors. |
34 | 35 | * **T1** in ( | * **T1** in ( |
35 | 36 | tensor(bool) | tensor(bool) |
36 | 37 | ): | ): |
37 | 38 | Constrains output to boolean tensor. | Constrains output to boolean tensor. |
Equal - 11#
Version
name: Equal (GitHub)
domain: main
since_version: 11
function: False
support_level: SupportType.COMMON
shape inference: True
This version of the operator has been available since version 11.
Summary
Returns the tensor resulted from performing the equal logical operation elementwise on the input tensors A and B (with Numpy-style broadcasting support).
This operator supports multidirectional (i.e., Numpy-style) broadcasting; for more details please check Broadcasting in ONNX.
Inputs
A (heterogeneous) - T: First input operand for the logical operator.
B (heterogeneous) - T: Second input operand for the logical operator.
Outputs
C (heterogeneous) - T1: Result tensor.
Type Constraints
T in ( tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) ): Constrains input types to all numeric tensors.
T1 in ( tensor(bool) ): Constrains output to boolean tensor.
Differences
0 | 0 | Returns the tensor resulted from performing the equal logical operation | Returns the tensor resulted from performing the equal logical operation |
1 | 1 | elementwise on the input tensors A and B (with Numpy-style broadcasting support). | elementwise on the input tensors A and B (with Numpy-style broadcasting support). |
2 | 2 | | |
3 | 3 | This operator supports **multidirectional (i.e., Numpy-style) broadcasting**; for more details please check Broadcasting in ONNX | This operator supports **multidirectional (i.e., Numpy-style) broadcasting**; for more details please check Broadcasting in ONNX |
4 | 4 | | |
5 | 5 | **Inputs** | **Inputs** |
6 | 6 | | |
7 | 7 | * **A** (heterogeneous) - **T**: | * **A** (heterogeneous) - **T**: |
8 | 8 | First input operand for the logical operator. | First input operand for the logical operator. |
9 | 9 | * **B** (heterogeneous) - **T**: | * **B** (heterogeneous) - **T**: |
10 | 10 | Second input operand for the logical operator. | Second input operand for the logical operator. |
11 | 11 | | |
12 | 12 | **Outputs** | **Outputs** |
13 | 13 | | |
14 | 14 | * **C** (heterogeneous) - **T1**: | * **C** (heterogeneous) - **T1**: |
15 | 15 | Result tensor. | Result tensor. |
16 | 16 | | |
17 | 17 | **Type Constraints** | **Type Constraints** |
18 | 18 | | |
19 | 19 | * **T** in ( | * **T** in ( |
20 | 20 | tensor(bool), | tensor(bool), |
21 | tensor(double), | ||
22 | tensor(float), | ||
23 | tensor(float16), | ||
24 | tensor(int16), | ||
21 | 25 | tensor(int32), | tensor(int32), |
22 | 26 | tensor(int64) | |
27 | tensor(int8), | ||
28 | tensor(uint16), | ||
29 | tensor(uint32), | ||
30 | tensor(uint64), | ||
31 | tensor(uint8) | ||
23 | 32 | ): | ): |
24 | 33 | Constrains input to integral tensors. | |
25 | 34 | * **T1** in ( | * **T1** in ( |
26 | 35 | tensor(bool) | tensor(bool) |
27 | 36 | ): | ): |
28 | 37 | Constrains output to boolean tensor. | Constrains output to boolean tensor. |
Equal - 7#
Version
name: Equal (GitHub)
domain: main
since_version: 7
function: False
support_level: SupportType.COMMON
shape inference: True
This version of the operator has been available since version 7.
Summary
Returns the tensor resulted from performing the equal logical operation elementwise on the input tensors A and B (with Numpy-style broadcasting support).
This operator supports multidirectional (i.e., Numpy-style) broadcasting; for more details please check Broadcasting in ONNX.
Inputs
A (heterogeneous) - T: First input operand for the logical operator.
B (heterogeneous) - T: Second input operand for the logical operator.
Outputs
C (heterogeneous) - T1: Result tensor.
Type Constraints
T in ( tensor(bool), tensor(int32), tensor(int64) ): Constrains input to integral tensors.
T1 in ( tensor(bool) ): Constrains output to boolean tensor.
Differences
0 | 0 | Returns the tensor resulted from performing the equal logical operation | Returns the tensor resulted from performing the equal logical operation |
1 | 1 | elementwise on the input tensors A and B. | |
2 | 2 | | |
3 | 3 | If broadcasting is enabled, the right-hand-side argument will be broadcasted | |
4 | to match the shape of left-hand-side argument. See the doc of Add for a | ||
5 | detailed description of the broadcasting rules. | ||
6 | 4 | | |
7 | **Attributes** | ||
8 | | ||
9 | * **axis**: | ||
10 | If set, defines the broadcast dimensions. | ||
11 | * **broadcast**: | ||
12 | Enable broadcasting Default value is 0. | ||
13 | | ||
14 | 5 | **Inputs** | **Inputs** |
15 | 6 | | |
16 | 7 | * **A** (heterogeneous) - **T**: | * **A** (heterogeneous) - **T**: |
17 | 8 | Left input tensor for the logical operator. | |
18 | 9 | * **B** (heterogeneous) - **T**: | * **B** (heterogeneous) - **T**: |
19 | 10 | Right input tensor for the logical operator. | |
20 | 11 | | |
21 | 12 | **Outputs** | **Outputs** |
22 | 13 | | |
23 | 14 | * **C** (heterogeneous) - **T1**: | * **C** (heterogeneous) - **T1**: |
24 | 15 | Result tensor. | Result tensor. |
25 | 16 | | |
26 | 17 | **Type Constraints** | **Type Constraints** |
27 | 18 | | |
28 | 19 | * **T** in ( | * **T** in ( |
29 | 20 | tensor(bool), | tensor(bool), |
30 | 21 | tensor(int32), | tensor(int32), |
31 | 22 | tensor(int64) | tensor(int64) |
32 | 23 | ): | ): |
33 | 24 | Constrains input to integral tensors. | Constrains input to integral tensors. |
34 | 25 | * **T1** in ( | * **T1** in ( |
35 | 26 | tensor(bool) | tensor(bool) |
36 | 27 | ): | ): |
37 | 28 | Constrains output to boolean tensor. | Constrains output to boolean tensor. |
Equal - 1#
Version
name: Equal (GitHub)
domain: main
since_version: 1
function: False
support_level: SupportType.COMMON
shape inference: True
This version of the operator has been available since version 1.
Summary
Returns the tensor resulted from performing the equal logical operation elementwise on the input tensors A and B.
If broadcasting is enabled, the right-hand-side argument will be broadcasted to match the shape of left-hand-side argument. See the doc of Add for a detailed description of the broadcasting rules.
Attributes
axis: If set, defines the broadcast dimensions.
broadcast: Enable broadcasting Default value is
0.
Inputs
A (heterogeneous) - T: Left input tensor for the logical operator.
B (heterogeneous) - T: Right input tensor for the logical operator.
Outputs
C (heterogeneous) - T1: Result tensor.
Type Constraints
T in ( tensor(bool), tensor(int32), tensor(int64) ): Constrains input to integral tensors.
T1 in ( tensor(bool) ): Constrains output to boolean tensor.