Where#

Where - 16
Where - 9

Where - 16 #

Version

name: Where (GitHub)
domain: main
since_version: 16
function: False
support_level: SupportType.COMMON
shape inference: True

This version of the operator has been available since version 16.

Summary

Return elements, either from X or Y, depending on condition. Where behaves like [numpy.where](https://docs.scipy.org/doc/numpy/reference/generated/numpy.where.html) with three parameters.

This operator supports multidirectional (i.e., Numpy-style) broadcasting; for more details please check Broadcasting in ONNX.

History - Version 16 adds bfloat16 to the types allowed (for the second and third parameter).

Inputs

condition (heterogeneous) - B: When True (nonzero), yield X, otherwise yield Y
X (heterogeneous) - T: values selected at indices where condition is True
Y (heterogeneous) - T: values selected at indices where condition is False

Outputs

output (heterogeneous) - T: Tensor of shape equal to the broadcasted shape of condition, X, and Y.

Type Constraints

B in ( tensor(bool) ): Constrain to boolean tensors.
T in ( tensor(bfloat16), tensor(bool), tensor(complex128), tensor(complex64), 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 and output types to all tensor types (including bfloat).

Examples

long

node = onnx.helper.make_node(
    'Where',
    inputs=['condition', 'x', 'y'],
    outputs=['z'],
)

condition = np.array([[1, 0], [1, 1]], dtype=bool)
x = np.array([[1, 2], [3, 4]], dtype=np.int64)
y = np.array([[9, 8], [7, 6]], dtype=np.int64)
z = np.where(condition, x, y)  # expected output [[1, 8], [3, 4]]
expect(node, inputs=[condition, x, y], outputs=[z],
       name='test_where_long_example')

Differences

`0`	`0`	`Return elements, either from X or Y, depending on condition.`	`Return elements, either from X or Y, depending on condition.`
`1`	`1`	`Where behaves like`	`Where behaves like`
`2`	`2`	`[numpy.where](https://docs.scipy.org/doc/numpy/reference/generated/numpy.where.html)`	`[numpy.where](https://docs.scipy.org/doc/numpy/reference/generated/numpy.where.html)`
`3`	`3`	`with three parameters.`	`with three parameters.`
`4`	`4`
`5`	`5`	`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 _.`
`6`	`6`
	`7`		`History`
	`8`		`- Version 16 adds bfloat16 to the types allowed (for the second and third parameter).`
	`9`
`7`	`10`	`Inputs`	`Inputs`
`8`	`11`
`9`	`12`	`* condition (heterogeneous) - B:`	`* condition (heterogeneous) - B:`
`10`	`13`	`When True (nonzero), yield X, otherwise yield Y`	`When True (nonzero), yield X, otherwise yield Y`
`11`	`14`	`* X (heterogeneous) - T:`	`* X (heterogeneous) - T:`
`12`	`15`	`values selected at indices where condition is True`	`values selected at indices where condition is True`
`13`	`16`	`* Y (heterogeneous) - T:`	`* Y (heterogeneous) - T:`
`14`	`17`	`values selected at indices where condition is False`	`values selected at indices where condition is False`
`15`	`18`
`16`	`19`	`Outputs`	`Outputs`
`17`	`20`
`18`	`21`	`* output (heterogeneous) - T:`	`* output (heterogeneous) - T:`
`19`	`22`	`Tensor of shape equal to the broadcasted shape of condition, X, and`	`Tensor of shape equal to the broadcasted shape of condition, X, and`
`20`	`23`	`Y.`	`Y.`
`21`	`24`
`22`	`25`	`Type Constraints`	`Type Constraints`
`23`	`26`
`24`	`27`	`* B in (`	`* B in (`
`25`	`28`	`tensor(bool)`	`tensor(bool)`
`26`	`29`	`):`	`):`
`27`	`30`	`Constrain to boolean tensors.`	`Constrain to boolean tensors.`
`28`	`31`	`* T in (`	`* T in (`
	`32`		`tensor(bfloat16),`
`29`	`33`	`tensor(bool),`	`tensor(bool),`
`30`	`34`	`tensor(complex128),`	`tensor(complex128),`
`31`	`35`	`tensor(complex64),`	`tensor(complex64),`
`32`	`36`	`tensor(double),`	`tensor(double),`
`33`	`37`	`tensor(float),`	`tensor(float),`
`34`	`38`	`tensor(float16),`	`tensor(float16),`
`35`	`39`	`tensor(int16),`	`tensor(int16),`
`36`	`40`	`tensor(int32),`	`tensor(int32),`
`37`	`41`	`tensor(int64),`	`tensor(int64),`
`38`	`42`	`tensor(int8),`	`tensor(int8),`
`39`	`43`	`tensor(string),`	`tensor(string),`
`40`	`44`	`tensor(uint16),`	`tensor(uint16),`
`41`	`45`	`tensor(uint32),`	`tensor(uint32),`
`42`	`46`	`tensor(uint64),`	`tensor(uint64),`
`43`	`47`	`tensor(uint8)`	`tensor(uint8)`
`44`	`48`	`):`	`):`
`45`	`49`	`Constrain input and output types to all tensor types.`	`Constrain input and output types to all tensor types (including`
	`50`		`bfloat).`

Where - 9 #