# Equal¶

## Equal - 19¶

### Version¶

• name: Equal (GitHub)

• domain: main

• since_version: 19

• function: False

• support_level: SupportType.COMMON

• shape inference: True

This version of the operator has been available since version 19.

### Summary¶

Returns the tensor resulted from performing the equal logical operation elementwise on the input tensors A and B (with Numpy-style broadcasting support).

### 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(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) ):

Constrain input types to all (non-complex) tensors.

• T1 in ( tensor(bool) ):

Constrain output to boolean tensor.

## 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).

### 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) ):

Constrain input types to all numeric tensors.

• T1 in ( tensor(bool) ):

Constrain 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).

### 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) ):

Constrain input types to all numeric tensors.

• T1 in ( tensor(bool) ):

Constrain 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).

### 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) ):

Constrain input to integral tensors.

• T1 in ( tensor(bool) ):

Constrain 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 - INT :

If set, defines the broadcast dimensions.

• broadcast - INT (default 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) ):

Constrain input to integral tensors.

• T1 in ( tensor(bool) ):

Constrain output to boolean tensor.