diff --git a/op_list.md b/op_list.md
index caea557b9a2f432965f58e772b2fc536bcaf73a2..a8ae84811cf79eb02274331262680e64f2c7fc15 100644
--- a/op_list.md
+++ b/op_list.md
@@ -7,31 +7,31 @@
 
 | 序号 | OP | 序号 | OP |序号 | OP |序号 | OP |
 |------|------|------|------|------|------|------|------|
-| 1 | Relu | 2 | Relu6 | 3 | Shape | 4 | Abs |
-|5 | Sigmoid | 6 | Exp | 7 | Rsqrt | 8 |swish_f32 |
-|9 | Tanh | 10 | LeakyRelu | 11 | Add | 12 | RealDiv |
-| 13 | Sub | 14 | Maximum | 15 | Mul | 16 | FloorDiv |
-|17 | Placeholder | 18 | Const | 19 | Transpose | 20 |FusedBatchNorm|
-|21 | Conv2D | 22 | BiasAdd | 23 | MaxPool | 24 | DepthwiseConv2dNative |
-| 25 | Reshape | 26 | AvgPool | 27 | SplitV | 28 |  SquaredDifference|
-|29 | Tile | 30 | Pack | 31 | Pad | 32 |  ResizeBilinear|
-|33 | Mean | 34 | MatMul | 35 | ArgMax | 36 | StridedSlice |
-| 37 | Slice | 38 | Sum | 39 | Max | 40 |  Conv2DBackpropInput|
-|41 | Cast | 42 | Split | 43| Squeeze | 44 |  ResizeNearestNeighbor|
-|45 | Softmax | 46 | Range | 47 | ConcatV2 | 
+| 1  | Relu        | 2  | Relu6     | 3  | Shape     | 4  | Abs                   |
+| 5  | Sigmoid     | 6  | Exp       | 7  | Rsqrt     | 8  | swish_f32             |
+| 9  | Tanh        | 10 | LeakyRelu | 11 | Add       | 12 | RealDiv               |
+| 13 | Sub         | 14 | Maximum   | 15 | Mul       | 16 | FloorDiv              |
+| 17 | Placeholder | 18 | Const     | 19 | Transpose | 20 | FusedBatchNorm        |
+| 21 | Conv2D      | 22 | BiasAdd   | 23 | MaxPool   | 24 | DepthwiseConv2dNative |
+| 25 | Reshape     | 26 | AvgPool   | 27 | SplitV    | 28 | SquaredDifference     |
+| 29 | Tile        | 30 | Pack      | 31 | Pad       | 32 | ResizeBilinear        |
+| 33 | Mean        | 34 | MatMul    | 35 | ArgMax    | 36 | StridedSlice          |
+| 37 | Slice       | 38 | Sum       | 39 | Max       | 40 | Conv2DBackpropInput   |
+| 41 | Cast        | 42 | Split     | 43 | Squeeze   | 44 | ResizeNearestNeighbor |
+| 45 | Softmax     | 46 | Range     | 47 | ConcatV2  | 
 
 ## Caffe
 
 | 序号 | OP | 序号 | OP |序号 | OP |序号 | OP |
 |------|------|------|------|------|------|------|------|
-| 1 | Input | 2 | Convolution| 3 |Deconvolution | 4 | Pooling |
-|5  |LRN    |6  |InnerProduct|  7 | Softmax    |    8  |   Slice    |
-|9  |Concat    |10  |PReLU|  11 |    Accuracy   |    12 |   Eltwise    |
-|13  |BatchNorm    |14  |Scale|  15 |Reshape|    16  |ArgMax|
-|17  |  Crop  |18 |  Flatten |  19 |    Power   |  20  |   Reduction    |
-|21  |  Axpy  |22  | ROIPolling |  23 |    Permute   |   24 |    DetectionOutput   |
-|25  |Normalize|26  |  Select|  27 |   ShuffleChannel    |   28 |    ConvolutionDepthwise   |
-|29  |ReLU|30  |AbsVal|  31 |   Sigmoid    |   32 |    TanH   |
+| 1  | Input     | 2  | Convolution  | 3  | Deconvolution  | 4  | Pooling              |
+| 5  | LRN       | 6  | InnerProduct | 7  | Softmax        | 8  | Slice                |
+| 9  | Concat    | 10 | PReLU        | 11 | Accuracy       | 12 | Eltwise              |
+| 13 | BatchNorm | 14 | Scale        | 15 | Reshape        | 16 | ArgMax               |
+| 17 | Crop      | 18 | Flatten      | 19 | Power          | 20 | Reduction            |
+| 21 | Axpy      | 22 | ROIPolling   | 23 | Permute        | 24 | DetectionOutput      |
+| 25 | Normalize | 26 | Select       | 27 | ShuffleChannel | 28 | ConvolutionDepthwise |
+| 29 | ReLU      | 30 | AbsVal       | 31 | Sigmoid        | 32 | TanH                 |
  
 ## ONNX