| | |
| |
|
| | import unittest |
| | import torch |
| |
|
| | import detectron2.export.torchscript |
| | from detectron2 import model_zoo |
| | from detectron2.config import get_cfg |
| | from detectron2.layers import ShapeSpec |
| | from detectron2.modeling.backbone import build_resnet_backbone |
| | from detectron2.modeling.backbone.fpn import build_resnet_fpn_backbone |
| |
|
| |
|
| | class TestBackBone(unittest.TestCase): |
| | def test_resnet_scriptability(self): |
| | cfg = get_cfg() |
| | resnet = build_resnet_backbone(cfg, ShapeSpec(channels=3)) |
| |
|
| | scripted_resnet = torch.jit.script(resnet) |
| |
|
| | inp = torch.rand(2, 3, 100, 100) |
| | out1 = resnet(inp)["res4"] |
| | out2 = scripted_resnet(inp)["res4"] |
| | self.assertTrue(torch.allclose(out1, out2)) |
| |
|
| | def test_fpn_scriptability(self): |
| | cfg = model_zoo.get_config("Misc/scratch_mask_rcnn_R_50_FPN_3x_gn.yaml") |
| | bb = build_resnet_fpn_backbone(cfg, ShapeSpec(channels=3)) |
| | bb_s = torch.jit.script(bb) |
| |
|
| | inp = torch.rand(2, 3, 128, 128) |
| | out1 = bb(inp)["p5"] |
| | out2 = bb_s(inp)["p5"] |
| | self.assertTrue(torch.allclose(out1, out2)) |
| |
|