OptionalHasElement#

OptionalHasElement - 15#

Version

  • name: OptionalHasElement (GitHub)

  • domain: main

  • since_version: 15

  • function: False

  • support_level: SupportType.COMMON

  • shape inference: True

This version of the operator has been available since version 15.

Summary

Returns true if the optional-type input contains an element. If it is an empty optional-type, this op returns false.

Inputs

  • input (heterogeneous) - O: The optional input.

Outputs

  • output (heterogeneous) - B: A scalar boolean tensor. If true, it indicates that optional-type input contains an element. Otherwise, it is empty.

Type Constraints

  • O in ( optional(seq(tensor(bool))), optional(seq(tensor(complex128))), optional(seq(tensor(complex64))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bool)), optional(tensor(complex128)), optional(tensor(complex64)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)) ): Constrain input type to optional tensor and optional sequence types.

  • B in ( tensor(bool) ): Constrain output to a boolean tensor.

Examples

default

optional = np.array([1, 2, 3, 4]).astype(np.float32)
tensor_type_proto = onnx.helper.make_tensor_type_proto(elem_type=onnx.TensorProto.FLOAT, shape=[4, ])
input_type_proto = onnx.helper.make_optional_type_proto(tensor_type_proto)
node = onnx.helper.make_node(
    'OptionalHasElement',
    inputs=['optional_input'],
    outputs=['output']
)
output = optional_has_element_reference_implementation(optional)
expect(node, inputs=[optional], outputs=[output],
       input_type_protos=[input_type_proto],
       name='test_optional_has_element')

_empty

optional = None
tensor_type_proto = onnx.helper.make_tensor_type_proto(elem_type=onnx.TensorProto.INT32, shape=[])
input_type_proto = onnx.helper.make_optional_type_proto(tensor_type_proto)
node = onnx.helper.make_node(
    'OptionalHasElement',
    inputs=['optional_input'],
    outputs=['output']
)
output = optional_has_element_reference_implementation(optional)
expect(node, inputs=[optional], outputs=[output],
       input_type_protos=[input_type_proto],
       name='test_optional_has_element_empty')