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test_cpp_models.py
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import os
import sys
import unittest
import torch
import torchvision.transforms.functional as F
from PIL import Image
from torchvision import models
try:
from torchvision import _C_tests
except ImportError:
_C_tests = None
def process_model(model, tensor, func, name):
model.eval()
traced_script_module = torch.jit.trace(model, tensor)
traced_script_module.save("model.pt")
py_output = model.forward(tensor)
cpp_output = func("model.pt", tensor)
assert torch.allclose(py_output, cpp_output), "Output mismatch of " + name + " models"
def read_image1():
image_path = os.path.join(
os.path.dirname(os.path.abspath(__file__)), "assets", "encode_jpeg", "grace_hopper_517x606.jpg"
)
image = Image.open(image_path)
image = image.resize((224, 224))
x = F.to_tensor(image)
return x.view(1, 3, 224, 224)
def read_image2():
image_path = os.path.join(
os.path.dirname(os.path.abspath(__file__)), "assets", "encode_jpeg", "grace_hopper_517x606.jpg"
)
image = Image.open(image_path)
image = image.resize((299, 299))
x = F.to_tensor(image)
x = x.view(1, 3, 299, 299)
return torch.cat([x, x], 0)
@unittest.skipIf(
sys.platform == "darwin" or True,
"C++ models are broken on OS X at the moment, and there's a BC breakage on main; "
"see https://github.com/pytorch/vision/issues/1191",
)
class Tester(unittest.TestCase):
pretrained = False
image = read_image1()
def test_alexnet(self):
process_model(models.alexnet(self.pretrained), self.image, _C_tests.forward_alexnet, "Alexnet")
def test_vgg11(self):
process_model(models.vgg11(self.pretrained), self.image, _C_tests.forward_vgg11, "VGG11")
def test_vgg13(self):
process_model(models.vgg13(self.pretrained), self.image, _C_tests.forward_vgg13, "VGG13")
def test_vgg16(self):
process_model(models.vgg16(self.pretrained), self.image, _C_tests.forward_vgg16, "VGG16")
def test_vgg19(self):
process_model(models.vgg19(self.pretrained), self.image, _C_tests.forward_vgg19, "VGG19")
def test_vgg11_bn(self):
process_model(models.vgg11_bn(self.pretrained), self.image, _C_tests.forward_vgg11bn, "VGG11BN")
def test_vgg13_bn(self):
process_model(models.vgg13_bn(self.pretrained), self.image, _C_tests.forward_vgg13bn, "VGG13BN")
def test_vgg16_bn(self):
process_model(models.vgg16_bn(self.pretrained), self.image, _C_tests.forward_vgg16bn, "VGG16BN")
def test_vgg19_bn(self):
process_model(models.vgg19_bn(self.pretrained), self.image, _C_tests.forward_vgg19bn, "VGG19BN")
def test_resnet18(self):
process_model(models.resnet18(self.pretrained), self.image, _C_tests.forward_resnet18, "Resnet18")
def test_resnet34(self):
process_model(models.resnet34(self.pretrained), self.image, _C_tests.forward_resnet34, "Resnet34")
def test_resnet50(self):
process_model(models.resnet50(self.pretrained), self.image, _C_tests.forward_resnet50, "Resnet50")
def test_resnet101(self):
process_model(models.resnet101(self.pretrained), self.image, _C_tests.forward_resnet101, "Resnet101")
def test_resnet152(self):
process_model(models.resnet152(self.pretrained), self.image, _C_tests.forward_resnet152, "Resnet152")
def test_resnext50_32x4d(self):
process_model(models.resnext50_32x4d(), self.image, _C_tests.forward_resnext50_32x4d, "ResNext50_32x4d")
def test_resnext101_32x8d(self):
process_model(models.resnext101_32x8d(), self.image, _C_tests.forward_resnext101_32x8d, "ResNext101_32x8d")
def test_wide_resnet50_2(self):
process_model(models.wide_resnet50_2(), self.image, _C_tests.forward_wide_resnet50_2, "WideResNet50_2")
def test_wide_resnet101_2(self):
process_model(models.wide_resnet101_2(), self.image, _C_tests.forward_wide_resnet101_2, "WideResNet101_2")
def test_squeezenet1_0(self):
process_model(
models.squeezenet1_0(self.pretrained), self.image, _C_tests.forward_squeezenet1_0, "Squeezenet1.0"
)
def test_squeezenet1_1(self):
process_model(
models.squeezenet1_1(self.pretrained), self.image, _C_tests.forward_squeezenet1_1, "Squeezenet1.1"
)
def test_densenet121(self):
process_model(models.densenet121(self.pretrained), self.image, _C_tests.forward_densenet121, "Densenet121")
def test_densenet169(self):
process_model(models.densenet169(self.pretrained), self.image, _C_tests.forward_densenet169, "Densenet169")
def test_densenet201(self):
process_model(models.densenet201(self.pretrained), self.image, _C_tests.forward_densenet201, "Densenet201")
def test_densenet161(self):
process_model(models.densenet161(self.pretrained), self.image, _C_tests.forward_densenet161, "Densenet161")
def test_mobilenet_v2(self):
process_model(models.mobilenet_v2(self.pretrained), self.image, _C_tests.forward_mobilenetv2, "MobileNet")
def test_googlenet(self):
process_model(models.googlenet(self.pretrained), self.image, _C_tests.forward_googlenet, "GoogLeNet")
def test_mnasnet0_5(self):
process_model(models.mnasnet0_5(self.pretrained), self.image, _C_tests.forward_mnasnet0_5, "MNASNet0_5")
def test_mnasnet0_75(self):
process_model(models.mnasnet0_75(self.pretrained), self.image, _C_tests.forward_mnasnet0_75, "MNASNet0_75")
def test_mnasnet1_0(self):
process_model(models.mnasnet1_0(self.pretrained), self.image, _C_tests.forward_mnasnet1_0, "MNASNet1_0")
def test_mnasnet1_3(self):
process_model(models.mnasnet1_3(self.pretrained), self.image, _C_tests.forward_mnasnet1_3, "MNASNet1_3")
def test_inception_v3(self):
self.image = read_image2()
process_model(models.inception_v3(self.pretrained), self.image, _C_tests.forward_inceptionv3, "Inceptionv3")
if __name__ == "__main__":
unittest.main()