Files
openvino/tests/layer_tests/pytorch_tests/test_sign.py
Ekaterina Aidova d41663694c [PT FE]: aten::gather (#16784)
* [PT FE]: aten::gather

* add detach and sign
2023-04-11 14:28:05 +04:00

53 lines
1.6 KiB
Python

# Copyright (C) 2018-2023 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import pytest
from pytorch_layer_test_class import PytorchLayerTest
class TestSilu(PytorchLayerTest):
def _prepare_input(self, inp_type="mixed", out=False):
import numpy as np
inp = np.arange(0, 10).astype(np.float32)
if inp_type == "negative":
inp[0] = 1
inp = -1 * inp
elif inp_type == "positive":
inp[0] = 11
elif inp_type == "zeros":
inp *= 0
else:
idx = np.random.choice(inp, 3)
inp[idx.astype(int)] *= -1
if out:
return (inp, np.zeros_like(inp))
return (inp, )
def create_model(self, out):
import torch
class aten_sign(torch.nn.Module):
def __init__(self, out):
super(aten_sign, self).__init__()
if out:
self.forward = self.forward_out
def forward(self, x):
return torch.sign(x)
def forward_out(self, x, out):
return torch.sign(x), out
ref_net = None
return aten_sign(out), ref_net, "aten::sign"
@pytest.mark.nightly
@pytest.mark.precommit
@pytest.mark.parametrize("input_type", ["zeros", "positive", "negative", "mixed"])
@pytest.mark.parametrize("out", [True, False])
def test_sign(self, input_type, out, ie_device, precision, ir_version):
self._test(*self.create_model(out), ie_device, precision, ir_version,
kwargs_to_prepare_input={"inp_type": input_type, "out": out})