ONNX emitter support op Relu6 and DepthwiseConv

mmdnn/conversion/onnx/onnx_emitter.py

@@ -139,6 +139,9 @@ def KitModel(weight_file = None):
         kernel_shape = list(IR_node.get_attr('kernel_shape'))[:-2]
         dilations = list(IR_node.get_attr('dilations', [1] * (len(kernel_shape) + 2)))[1:-1]
         group = IR_node.get_attr('group', 1)
+        if IR_node.type == 'DepthwiseConv':
+            group = IR_node.IR_layer.attr["kernel_shape"].list.i[-2]
+            self.weights_dict[IR_node.name]['weights'] = np.swapaxes(self.weights_dict[IR_node.name]['weights'], -1, -2)
         pads = IR_node.get_attr('pads')
         pad_length = len(pads)
         pads = pads[1:pad_length // 2 - 1] + pads[pad_length // 2 + 1:pad_length - 1]
@@ -462,5 +465,15 @@ def KitModel(weight_file = None):
                           size))
         self.nodes.append(IR_node.variable_name)
 
+    def emit_Relu6(self, IR_node):
+        self.add_body(1, "{:15} = helper.make_node('Clip', inputs=['{}'], outputs=['{}'], min=0.0, max=6.0)".format(
+            IR_node.variable_name,
+            self.parent_variable_name(IR_node),
+            IR_node.variable_name))
+        self.nodes.append(IR_node.variable_name)
+
+    def emit_DepthwiseConv(self, IR_node):
+        self.emit_Conv(IR_node)
+
     def emit_UNKNOWN(self, IR_node):
         print(IR_node.IR_layer.name)