Remove .train() mode exports (#9429)

* Remove `.train()` mode exports

No common use cases.

Signed-off-by: Glenn Jocher <[email protected]>

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Signed-off-by: Glenn Jocher <[email protected]>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Author: glenn-jocher

export.py

@@ -126,7 +126,7 @@ def export_torchscript(model, im, file, optimize, prefix=colorstr('TorchScript:'
 
 
 @try_export
-def export_onnx(model, im, file, opset, train, dynamic, simplify, prefix=colorstr('ONNX:')):
+def export_onnx(model, im, file, opset, dynamic, simplify, prefix=colorstr('ONNX:')):
     # YOLOv5 ONNX export
     check_requirements('onnx')
     import onnx
@@ -140,8 +140,7 @@ def export_onnx(model, im, file, opset, train, dynamic, simplify, prefix=colorst
         f,
         verbose=False,
         opset_version=opset,
-        training=torch.onnx.TrainingMode.TRAINING if train else torch.onnx.TrainingMode.EVAL,
-        do_constant_folding=not train,
+        do_constant_folding=True,
         input_names=['images'],
         output_names=['output'],
         dynamic_axes={
@@ -459,7 +458,6 @@ def run(
         include=('torchscript', 'onnx'),  # include formats
         half=False,  # FP16 half-precision export
         inplace=False,  # set YOLOv5 Detect() inplace=True
-        train=False,  # model.train() mode
         keras=False,  # use Keras
         optimize=False,  # TorchScript: optimize for mobile
         int8=False,  # CoreML/TF INT8 quantization
@@ -501,7 +499,7 @@ def run(
     im = torch.zeros(batch_size, 3, *imgsz).to(device)  # image size(1,3,320,192) BCHW iDetection
 
     # Update model
-    model.train() if train else model.eval()  # training mode = no Detect() layer grid construction
+    model.eval()
     for k, m in model.named_modules():
         if isinstance(m, Detect):
             m.inplace = inplace
@@ -524,7 +522,7 @@ def run(
     if engine:  # TensorRT required before ONNX
         f[1], _ = export_engine(model, im, file, half, dynamic, simplify, workspace, verbose)
     if onnx or xml:  # OpenVINO requires ONNX
-        f[2], _ = export_onnx(model, im, file, opset, train, dynamic, simplify)
+        f[2], _ = export_onnx(model, im, file, opset, dynamic, simplify)
     if xml:  # OpenVINO
         f[3], _ = export_openvino(file, metadata, half)
     if coreml:  # CoreML
@@ -578,7 +576,6 @@ def parse_opt():
     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('--keras', action='store_true', help='TF: use Keras')
     parser.add_argument('--optimize', action='store_true', help='TorchScript: optimize for mobile')
     parser.add_argument('--int8', action='store_true', help='CoreML/TF INT8 quantization')