44 lines
1.5 KiB
Python
44 lines
1.5 KiB
Python
# Copyright (C) 2018-2023 Intel Corporation
|
|
# SPDX-License-Identifier: Apache-2.0
|
|
|
|
import numpy as np
|
|
import pytest
|
|
import torch
|
|
|
|
from pytorch_layer_test_class import PytorchLayerTest
|
|
|
|
|
|
@pytest.mark.parametrize('dimension', (0, 1, 2))
|
|
@pytest.mark.parametrize('size', (1, 2))
|
|
@pytest.mark.parametrize('step', (1, 2, 3, 4))
|
|
@pytest.mark.parametrize('input_tensor', (np.random.randn(2, 2, 5).astype(np.float32),
|
|
np.random.randn(3, 3, 3, 3).astype(np.float32),
|
|
np.random.randn(2, 3, 4, 5).astype(np.float32)))
|
|
class TestUnfold(PytorchLayerTest):
|
|
|
|
def _prepare_input(self):
|
|
return (self.input_tensor, )
|
|
|
|
def create_model(self, dimension, size, step):
|
|
class aten_unfold(torch.nn.Module):
|
|
|
|
def __init__(self, dimension, size, step) -> None:
|
|
super().__init__()
|
|
self.dimension = dimension
|
|
self.size = size
|
|
self.step = step
|
|
|
|
def forward(self, input_tensor):
|
|
return input_tensor.unfold(dimension=self.dimension, size=self.size, step=self.step)
|
|
|
|
ref_net = None
|
|
|
|
return aten_unfold(dimension, size, step), ref_net, "aten::unfold"
|
|
|
|
@pytest.mark.nightly
|
|
@pytest.mark.precommit
|
|
def test_unfold(self, ie_device, precision, ir_version, dimension, size, step, input_tensor):
|
|
self.input_tensor = input_tensor
|
|
self._test(*self.create_model(dimension, size, step),
|
|
ie_device, precision, ir_version)
|