[wip] [v1.x] Onnx export support for slicechannel and box_nms (#19846)

* slicechannel

* add warning to box_nms an unblock when id_idex!=-1

* Update _op_translations.py

* add 0,1

python/mxnet/contrib/onnx/mx2onnx/_op_translations.py

@@ -1778,44 +1778,39 @@ def convert_slice_axis(node, **kwargs):
     return nodes
 
 
-@mx_op.register("SliceChannel")
+@mx_op.register('SliceChannel')
 def convert_slice_channel(node, **kwargs):
     """Map MXNet's SliceChannel operator attributes to onnx's Squeeze or Split
     operator based on squeeze_axis attribute
     and return the created node.
     """
+    from onnx.helper import make_node
     name, input_nodes, attrs = get_inputs(node, kwargs)
 
-    opset_version = kwargs['opset_version']
-    if opset_version < 11:
-        raise AttributeError('ONNX opset 11 or greater is required to export this operator')
+    num_outputs = int(attrs.get('num_outputs'))
+    axis = int(attrs.get('axis', 1))
+    squeeze_axis = attrs.get('squeeze_axis', 'False')
 
-    num_outputs = int(attrs.get("num_outputs"))
-    axis = int(attrs.get("axis", 1))
-    squeeze_axis = int(attrs.get("squeeze_axis", 0) in [1, 'True'])
+    create_tensor([axis], name+'_axis', kwargs['initializer'])
+    create_tensor([axis+1], name+'axis_p1', kwargs['initializer'])
 
-    if squeeze_axis == 1 and num_outputs == 1:
-        node = onnx.helper.make_node(
-            "Squeeze",
-            input_nodes,
-            [name],
-            axes=[axis],
-            name=name,
-        )
-        return [node]
-    elif squeeze_axis == 0 and num_outputs > 1:
-        node = onnx.helper.make_node(
-            "Split",
-            input_nodes,
-            [name+str(i) for i in range(num_outputs)],
-            axis=axis,
-            name=name
-        )
-        return [node]
+    nodes = []
+    if squeeze_axis in ['True', '1']:
+        nodes += [
+            make_node('Split', [input_nodes[0]], [name+str(i)+'_' for i in range(num_outputs)],
+                      axis=axis)
+        ]
+        for i in range(num_outputs):
+            nodes += [
+                make_node('Squeeze', [name+str(i)+'_'], [name+str(i)], axes=[axis])
+            ]
     else:
-        raise NotImplementedError("SliceChannel operator with num_outputs>1 and"
-                                  "squeeze_axis true is not implemented.")
+        nodes += [
+            make_node('Split', [input_nodes[0]], [name+str(i) for i in range(num_outputs)],
+                      axis=axis)
+        ]
 
+    return nodes
 
 @mx_op.register("expand_dims")
 def convert_expand_dims(node, **kwargs):
@@ -3089,6 +3084,7 @@ def convert_contrib_box_nms(node, **kwargs):
     coord_start = int(attrs.get('coord_start', '2'))
     score_index = int(attrs.get('score_index', '1'))
     id_index = int(attrs.get('id_index', '-1'))
+    force_suppress = attrs.get('force_suppress', 'True')
     background_id = int(attrs.get('background_id', '-1'))
     in_format = attrs.get('in_format', 'corner')
     out_format = attrs.get('out_format', 'corner')
@@ -3101,8 +3097,11 @@ def convert_contrib_box_nms(node, **kwargs):
     if background_id != -1:
         raise NotImplementedError('box_nms does not currently support background_id != -1')
 
-    if id_index != -1:
-        raise NotImplementedError('box_nms does not currently support id_index != -1')
+    if id_index != -1 or force_suppress == 'False':
+        logging.warning('box_nms: id_idex != -1 or/and force_suppress == False detected. '
+                        'However, due to ONNX limitations, boxes of different categories will NOT '
+                        'be exempted from suppression. This might lead to different behavior than '
+                        'native MXNet')
 
     nodes = [
         create_tensor([coord_start], name+'_cs', kwargs['initializer']),

tests/python-pytest/onnx/test_operators.py

@@ -929,6 +929,19 @@ def test_onnx_export_convolution(tmp_path, dtype, shape, num_filter, num_group,
     op_export_test('convolution', M, inputs, tmp_path)
 
 
+@pytest.mark.parametrize('dtype', ['float16', 'float32'])
+@pytest.mark.parametrize('num_outputs', [1, 3, 9])
+@pytest.mark.parametrize('axis', [1, 2, -1, -2])
+@pytest.mark.parametrize('squeeze_axis', [True, False, 0, 1])
+def test_onnx_export_slice_channel(tmp_path, dtype, num_outputs, axis, squeeze_axis):
+    shape = (3, 9, 18)
+    if squeeze_axis and shape[axis] != num_outputs:
+        return
+    M = def_model('SliceChannel', num_outputs=num_outputs, axis=axis, squeeze_axis=squeeze_axis)
+    x = mx.random.uniform(0, 1, shape, dtype=dtype)
+    op_export_test('slice_channel', M, [x], tmp_path)
+
+
 @pytest.mark.parametrize('dtype', ['float32', 'float64'])
 @pytest.mark.parametrize('momentum', [0.9, 0.5, 0.1])
 def test_onnx_export_batchnorm(tmp_path, dtype, momentum):