HardSwish

HardSwish - 14

Version

• name: HardSwish (GitHub)

• domain: main

• since_version: 14

• function:

• support_level: SupportType.COMMON

• shape inference: True

This version of the operator has been available since version 14.

Summary

Inputs

• X (heterogeneous) - T:

Outputs

• Y (heterogeneous) - T:

Type Constraints

• T in ( 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(
    "HardSwish",
    inputs=["x"],
    outputs=["y"],
)
x = np.random.randn(3, 4, 5).astype(np.float32)
y = hardswish(x)

expect(node, inputs=[x], outputs=[y], name="test_hardswish")