ONNX Simplifier (ultralytics#2815)

* ONNX Simplifier Add ONNX Simplifier to ONNX export pipeline in export.py. Will auto-install onnx-simplifier if onnx is installed but onnx-simplifier is not. * Update general.py
fhkiel-mlaip · Apr 16, 2021 · b82cab5 · b82cab5
1 parent e1e4245
commit b82cab5
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Showing 2 changed files with 31 additions and 16 deletions.
diff --git a/models/export.py b/models/export.py
@@ -1,7 +1,7 @@
 """Exports a YOLOv5 *.pt model to ONNX and TorchScript formats
 
 Usage:
-    $ export PYTHONPATH="$PWD" && python models/export.py --weights ./weights/yolov5s.pt --img 640 --batch 1
+    $ export PYTHONPATH="$PWD" && python models/export.py --weights yolov5s.pt --img 640 --batch 1
 """
 
 import argparse
@@ -16,7 +16,7 @@
 import models
 from models.experimental import attempt_load
 from utils.activations import Hardswish, SiLU
-from utils.general import set_logging, check_img_size
+from utils.general import colorstr, check_img_size, check_requirements, set_logging
 from utils.torch_utils import select_device
 
 if __name__ == '__main__':
@@ -59,46 +59,61 @@
     y = model(img)  # dry run
 
     # TorchScript export
+    prefix = colorstr('TorchScript:')
     try:
-        print('\nStarting TorchScript export with torch %s...' % torch.__version__)
+        print(f'\n{prefix} starting export with torch {torch.__version__}...')
         f = opt.weights.replace('.pt', '.torchscript.pt')  # filename
         ts = torch.jit.trace(model, img, strict=False)
         ts.save(f)
-        print('TorchScript export success, saved as %s' % f)
+        print(f'{prefix} export success, saved as {f}')
     except Exception as e:
-        print('TorchScript export failure: %s' % e)
+        print(f'{prefix} export failure: {e}')
 
     # ONNX export
+    prefix = colorstr('ONNX:')
     try:
         import onnx
 
-        print('\nStarting ONNX export with onnx %s...' % onnx.__version__)
+        print(f'{prefix} starting export with onnx {onnx.__version__}...')
         f = opt.weights.replace('.pt', '.onnx')  # filename
         torch.onnx.export(model, img, f, verbose=False, opset_version=12, input_names=['images'],
                           output_names=['classes', 'boxes'] if y is None else ['output'],
                           dynamic_axes={'images': {0: 'batch', 2: 'height', 3: 'width'},  # size(1,3,640,640)
                                         'output': {0: 'batch', 2: 'y', 3: 'x'}} if opt.dynamic else None)
 
         # Checks
-        onnx_model = onnx.load(f)  # load onnx model
-        onnx.checker.check_model(onnx_model)  # check onnx model
-        # print(onnx.helper.printable_graph(onnx_model.graph))  # print a human readable model
-        print('ONNX export success, saved as %s' % f)
+        model_onnx = onnx.load(f)  # load onnx model
+        onnx.checker.check_model(model_onnx)  # check onnx model
+        # print(onnx.helper.printable_graph(model_onnx.graph))  # print
+
+        # Simplify
+        try:
+            check_requirements(['onnx-simplifier'])
+            import onnxsim
+
+            print(f'{prefix} simplifying with onnx-simplifier {onnxsim.__version__}...')
+            model_onnx, check = onnxsim.simplify(model_onnx)
+            assert check, 'assert check failed'
+            onnx.save(model_onnx, f)
+        except Exception as e:
+            print(f'{prefix} simplifier failure: {e}')
+        print(f'{prefix} export success, saved as {f}')
     except Exception as e:
-        print('ONNX export failure: %s' % e)
+        print(f'{prefix} export failure: {e}')
 
     # CoreML export
+    prefix = colorstr('CoreML:')
     try:
         import coremltools as ct
 
-        print('\nStarting CoreML export with coremltools %s...' % ct.__version__)
+        print(f'{prefix} starting export with coremltools {onnx.__version__}...')
         # convert model from torchscript and apply pixel scaling as per detect.py
         model = ct.convert(ts, inputs=[ct.ImageType(name='image', shape=img.shape, scale=1 / 255.0, bias=[0, 0, 0])])
         f = opt.weights.replace('.pt', '.mlmodel')  # filename
         model.save(f)
-        print('CoreML export success, saved as %s' % f)
+        print(f'{prefix} export success, saved as {f}')
     except Exception as e:
-        print('CoreML export failure: %s' % e)
+        print(f'{prefix} export failure: {e}')
 
     # Finish
-    print('\nExport complete (%.2fs). Visualize with https://github.com/lutzroeder/netron.' % (time.time() - t))
+    print(f'\nExport complete ({time.time() - t:.2f}s). Visualize with https://github.com/lutzroeder/netron.')
diff --git a/utils/general.py b/utils/general.py
@@ -111,7 +111,7 @@ def check_requirements(requirements='requirements.txt', exclude=()):
         except Exception as e:  # DistributionNotFound or VersionConflict if requirements not met
             n += 1
             print(f"{prefix} {e.req} not found and is required by YOLOv5, attempting auto-update...")
-            print(subprocess.check_output(f"pip install '{e.req}'", shell=True).decode())
+            print(subprocess.check_output(f"pip install {e.req}", shell=True).decode())
 
     if n:  # if packages updated
         source = file.resolve() if 'file' in locals() else requirements