Skip to content

Port test_backbone_utils.py to pytest #3991

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 2 commits into from
Jun 7, 2021
Merged

Port test_backbone_utils.py to pytest #3991

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
559de27
Port test_backbone_utils.py to pytest
NicolasHug Jun 7, 2021
e2b578d
Merge branch 'master' into backbone_util_port
NicolasHug Jun 7, 2021
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
26 changes: 6 additions & 20 deletions test/test_backbone_utils.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,25 +1,11 @@
import unittest


import torch
from torchvision.models.detection.backbone_utils import resnet_fpn_backbone

import pytest

class ResnetFPNBackboneTester(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.dtype = torch.float32

def test_resnet18_fpn_backbone(self):
device = torch.device('cpu')
x = torch.rand(1, 3, 300, 300, dtype=self.dtype, device=device)
resnet18_fpn = resnet_fpn_backbone(backbone_name='resnet18', pretrained=False)
y = resnet18_fpn(x)
self.assertEqual(list(y.keys()), ['0', '1', '2', '3', 'pool'])

def test_resnet50_fpn_backbone(self):
device = torch.device('cpu')
x = torch.rand(1, 3, 300, 300, dtype=self.dtype, device=device)
resnet50_fpn = resnet_fpn_backbone(backbone_name='resnet50', pretrained=False)
y = resnet50_fpn(x)
self.assertEqual(list(y.keys()), ['0', '1', '2', '3', 'pool'])
@pytest.mark.parametrize('backbone_name', ('resnet18', 'resnet50'))
def test_resnet_fpn_backbone(backbone_name):
x = torch.rand(1, 3, 300, 300, dtype=torch.float32, device='cpu')
y = resnet_fpn_backbone(backbone_name=backbone_name, pretrained=False)(x)
assert list(y.keys()) == ['0', '1', '2', '3', 'pool']