Upgrade onnxsim to at least 0.4.0 (#8383)

* Upgrade onnxsim to 0.4.0

* Update pytorch2onnx.py

* Update pytorch2onnx.py

tools/deployment/pytorch2onnx.py

@@ -101,31 +101,17 @@ def pytorch2onnx(model,
 
     model.forward = origin_forward
 
-    # get the custom op path
-    ort_custom_op_path = ''
-    try:
-        from mmcv.ops import get_onnxruntime_op_path
-        ort_custom_op_path = get_onnxruntime_op_path()
-    except (ImportError, ModuleNotFoundError):
-        warnings.warn('If input model has custom op from mmcv, \
-            you may have to build mmcv with ONNXRuntime from source.')
-
     if do_simplify:
         import onnxsim
 
         from mmdet import digit_version
 
-        min_required_version = '0.3.0'
+        min_required_version = '0.4.0'
         assert digit_version(onnxsim.__version__) >= digit_version(
             min_required_version
-        ), f'Requires to install onnx-simplify>={min_required_version}'
+        ), f'Requires to install onnxsim>={min_required_version}'
 
-        input_dic = {'input': img_list[0].detach().cpu().numpy()}
-        model_opt, check_ok = onnxsim.simplify(
-            output_file,
-            input_data=input_dic,
-            custom_lib=ort_custom_op_path,
-            dynamic_input_shape=dynamic_export)
+        model_opt, check_ok = onnxsim.simplify(output_file)
         if check_ok:
             onnx.save(model_opt, output_file)
             print(f'Successfully simplified ONNX model: {output_file}')