Files
openvino/tests/layer_tests/pytorch_tests/test_flip.py
Ekaterina Aidova fb4efe7203 [PT FE]: support flip operation (#17705)
* [PT FE]: support flip operation

* more tests
2023-05-31 12:07:24 +02:00

43 lines
1.5 KiB
Python

# Copyright (C) 2018-2023 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import pytest
from pytorch_layer_test_class import PytorchLayerTest
class TestFlip(PytorchLayerTest):
def _prepare_input(self, out=False, dtype="float32"):
import numpy as np
x = np.random.randn(2, 3, 4, 5).astype(dtype)
if not out:
return (x,)
return (x, np.zeros_like(x).astype(dtype))
def create_model(self, axis, out):
import torch
class aten_flip(torch.nn.Module):
def __init__(self, dim, out):
super(aten_flip, self).__init__()
self.dim = dim
if out:
self.forward = self.forward_out
def forward(self, x):
return torch.flip(x, self.dim)
def forward_out(self, x, y):
return torch.flip(x, self.dim, out=y), y
ref_net = None
return aten_flip(axis, out), ref_net, "aten::flip"
@pytest.mark.nightly
@pytest.mark.precommit
@pytest.mark.parametrize("axis", [[0], [1], [-1], [1, 2], [2, 3], [1, 2, 3]])
@pytest.mark.parametrize("out", [True, False])
@pytest.mark.parametrize("dtype", ["float32", "float64", "int32", "int64", "uint8"])
def test_flip(self, axis, out, dtype, ie_device, precision, ir_version):
self._test(*self.create_model(axis, out), ie_device, precision, ir_version, kwargs_to_prepare_input={"out": out, "dtype": dtype})