Erf

Erf - 13

Version

  • name: Erf (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

Computes the error function of the given input tensor element-wise.

Inputs

  • input (heterogeneous) - T:

    Input tensor

Outputs

  • output (heterogeneous) - T:

    The error function of the input tensor computed element-wise. It has the same shape and type of the input.

Type Constraints

  • T in ( tensor(bfloat16), tensor(double), tensor(float), tensor(float16) ):

    Constrain input and output types to float tensors.

Examples

default

import numpy as np
import onnx

node = onnx.helper.make_node(
    "Erf",
    inputs=["x"],
    outputs=["y"],
)

x = np.random.randn(1, 3, 32, 32).astype(np.float32)
y = np.vectorize(math.erf)(x).astype(np.float32)
expect(node, inputs=[x], outputs=[y], name="test_erf")

Erf - 9

Version

  • name: Erf (GitHub)

  • domain: main

  • since_version: 9

  • function: False

  • support_level: SupportType.COMMON

  • shape inference: True

This version of the operator has been available since version 9.

Summary

Computes the error function of the given input tensor element-wise.

Inputs

  • input (heterogeneous) - T:

    Input tensor

Outputs

  • output (heterogeneous) - T:

    The error function of the input tensor computed element-wise. It has the same shape and type of the input.

Type Constraints

  • T in ( tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) ):

    Constrain input and output types to all numeric tensors.