Files
zeekayandHanzo Dev f84fe1fd15 snapshot slice 1
Co-authored-by: Hanzo Dev <[email protected]>
2026-07-28 15:29:05 -07:00

38 lines
1.0 KiB
Python

# Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import onnx
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
class Shrink(Base):
@staticmethod
def export_hard_shrink() -> None:
node = onnx.helper.make_node(
"Shrink",
inputs=["x"],
outputs=["y"],
lambd=1.5,
)
X = np.arange(-2.0, 2.1, dtype=np.float32)
Y = np.array([-2, 0, 0, 0, 2], dtype=np.float32)
expect(node, inputs=[X], outputs=[Y], name="test_shrink_hard")
@staticmethod
def export_soft_shrink() -> None:
node = onnx.helper.make_node(
"Shrink",
inputs=["x"],
outputs=["y"],
lambd=1.5,
bias=1.5,
)
X = np.arange(-2.0, 2.1, dtype=np.float32)
Y = np.array([-0.5, 0, 0, 0, 0.5], dtype=np.float32)
expect(node, inputs=[X], outputs=[Y], name="test_shrink_soft")