Update export.py, yolo.py sys.path.append() (#3579)

models/export.py

@@ -9,13 +9,15 @@
 import time
 from pathlib import Path
 
-sys.path.append(Path(__file__).parent.parent.absolute().__str__())  # to run '$ python *.py' files in subdirectories
-
 import torch
 import torch.nn as nn
 from torch.utils.mobile_optimizer import optimize_for_mobile
 
-import models
+FILE = Path(__file__).absolute()
+sys.path.append(FILE.parents[1].as_posix())  # add yolov5/ to path
+
+from models.common import Conv
+from models.yolo import Detect
 from models.experimental import attempt_load
 from utils.activations import Hardswish, SiLU
 from utils.general import colorstr, check_img_size, check_requirements, file_size, set_logging
@@ -56,12 +58,12 @@ def export(weights='./yolov5s.pt',  # weights path
     model.train() if train else model.eval()  # training mode = no Detect() layer grid construction
     for k, m in model.named_modules():
         m._non_persistent_buffers_set = set()  # pytorch 1.6.0 compatibility
-        if isinstance(m, models.common.Conv):  # assign export-friendly activations
+        if isinstance(m, Conv):  # assign export-friendly activations
             if isinstance(m.act, nn.Hardswish):
                 m.act = Hardswish()
             elif isinstance(m.act, nn.SiLU):
                 m.act = SiLU()
-        elif isinstance(m, models.yolo.Detect):
+        elif isinstance(m, Detect):
             m.inplace = inplace
             m.onnx_dynamic = dynamic
             # m.forward = m.forward_export  # assign forward (optional)

models/yolo.py

@@ -10,8 +10,8 @@
 from copy import deepcopy
 from pathlib import Path
 
-sys.path.append(Path(__file__).parent.parent.absolute().__str__())  # to run '$ python *.py' files in subdirectories
-logger = logging.getLogger(__name__)
+FILE = Path(__file__).absolute()
+sys.path.append(FILE.parents[1].as_posix())  # add yolov5/ to path
 
 from models.common import *
 from models.experimental import *
@@ -25,6 +25,8 @@
 except ImportError:
     thop = None
 
+logger = logging.getLogger(__name__)
+
 
 class Detect(nn.Module):
     stride = None  # strides computed during build