Update export.py with --train mode argument (ultralytics#3066)

models/export.py

@@ -29,6 +29,7 @@
     parser.add_argument('--device', default='cpu', help='cuda device, i.e. 0 or 0,1,2,3 or cpu')
     parser.add_argument('--half', action='store_true', help='FP16 half-precision export')
     parser.add_argument('--inplace', action='store_true', help='set YOLOv5 Detect() inplace=True')
+    parser.add_argument('--train', action='store_true', help='model.train() mode')
     parser.add_argument('--dynamic', action='store_true', help='dynamic ONNX axes')  # ONNX-only
     parser.add_argument('--simplify', action='store_true', help='simplify ONNX model')  # ONNX-only
     opt = parser.parse_args()
@@ -53,6 +54,8 @@
     # Update model
     if opt.half:
         img, model = img.half(), model.half()  # to FP16
+    if opt.train:
+        model.train()  # training mode (no grid construction in Detect layer)
     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