[Feature] add onnx simplify

docs/onnx.md

@@ -0,0 +1,40 @@
+# Introduction of `onnx` module in MMCV (Experimental)
+
+## register_extra_symbolics
+
+Some extra symbolic functions need to be registered before exporting PyTorch model to ONNX.
+
+### Example
+
+```python
+import mmcv
+from mmcv.onnx import register_extra_symbolics
+
+opset_version = 11
+register_extra_symbolics(opset_version)
+```
+
+## ONNX simplify
+
+### Intention
+
+`mmcv.onnx.simplify` is based on [onnx-simplifier](https://github.com/daquexian/onnx-simplifier), which is a useful tool to make exported ONNX models slimmer by performing a series of optimization. However, for Pytorch models with custom op from `mmcv`, it would break down. Thus, custom ops for ONNX Runtime should be registered.
+
+### Usage
+
+```python
+import onnx
+import numpy as np
+
+import mmcv
+from mmcv.onnx import simplify
+dummy_input = np.random.randn(1, 3, 224, 224).astype(np.float32)
+input = {'input':dummy_input}
+input_file = 'sample.onnx'
+output_file = 'slim.onnx'
+model = simplify(input_file, [input], output_file)
+```
+
+### FAQs
+
+- None

mmcv/onnx/__init__.py

@@ -1,3 +1,4 @@
+from .simplify import simplify
 from .symbolic import register_extra_symbolics
 
-__all__ = ['register_extra_symbolics']
+__all__ = ['register_extra_symbolics', 'simplify']

mmcv/onnx/simplify/__init__.py

@@ -0,0 +1,3 @@
+from .core import simplify
+
+__all__ = ['simplify']

mmcv/onnx/simplify/common.py

@@ -0,0 +1,43 @@
+import copy
+import warnings
+
+import onnx
+
+
+def add_suffix2name(ori_model, suffix='__', verify=False):
+    """Simplily add a suffix to the name of node, which has a numeric name."""
+    # check if has special op, which has subgraph.
+    special_ops = ('If', 'Loop')
+    for node in ori_model.graph.node:
+        if node.op_type in special_ops:
+            warnings.warn(f'This model has special op: {node.op_type}.')
+            return ori_model
+
+    model = copy.deepcopy(ori_model)
+
+    def need_update(name):
+        return name.isnumeric()
+
+    def update_name(nodes):
+        for node in nodes:
+            if need_update(node.name):
+                node.name += suffix
+
+    update_name(model.graph.initializer)
+    update_name(model.graph.input)
+    update_name(model.graph.output)
+
+    for i, node in enumerate(ori_model.graph.node):
+        # process input of node
+        for j, name in enumerate(node.input):
+            if need_update(name):
+                model.graph.node[i].input[j] = name + suffix
+
+        # process output of node
+        for j, name in enumerate(node.output):
+            if need_update(name):
+                model.graph.node[i].output[j] = name + suffix
+    if verify:
+        onnx.checker.check_model(model)
+
+    return model