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 ## TensorFlow
-| 序号 | OP | 序号 | OP |序号 | OP |
+| 序号 | OP | 序号 | OP |序号 | OP |序号 | OP |
-|------|------|------|------|------|------|
+|------|------|------|------|------|------|------|------|
-| 1 | Relu | 2 | Relu6 | 3 | Shape | 4 | Abs | 5 | Sigmoid | 6 | Exp |
+| 1 | Relu | 2 | Relu6 | 3 | Shape | 4 | Abs | 
-| 7 | Rsqrt | 8 | swish_f32 | 9 | Tanh | 10 | LeakyRelu | 11 | Add | 12 | RealDiv |
+|5 | Sigmoid | 6 | Exp || 7 | Rsqrt | 8 |swish_f32 |
-| 13 | Sub | 14 | Maximum | 15 | Mul | 16 | FloorDiv | 17 | Placeholder | 18 | Const |
+|9 | Tanh | 10 | LeakyRelu | 11 | Add | 12 | RealDiv |
-| 19 | Transpose | 20 | MaxPool | 21 | Conv2D | 22 | BiasAdd | 23 | FusedBatchNorm | 24 | DepthwiseConv2dNative |
+| 13 | Sub | 14 | Maximum | 15 | Mul | 16 | FloorDiv |
-| 25 | Reshape | 26 | AvgPool | 27 | SplitV | 28 | ConcatV2 | 29 | Tile | 30 | Pack |
+|17 | Placeholder | 18 | Const | 19 | Transpose | 20 |FusedBatchNorm|
-| 31 | Pad | 32 | Range | 33 | Mean | 34 | MatMul | 35 | ArgMax | 36 | StridedSlice |
+|21 | Conv2D | 22 | BiasAdd | 23 | MaxPool | 24 | DepthwiseConv2dNative |
-| 37 | Slice | 38 | Conv2DBackpropInput | 39 | Max | 40 | Sum | 41 | Cast | 42 | Split |
+| 25 | Reshape | 26 | AvgPool | 27 | SplitV | 28 |  SquaredDifference|
-| 43| Squeeze | 44 | Softmax | 45 | ResizeNearestNeighbor | 46 | ResizeBilinear | 47 | SquaredDifference | 48 | * |
+|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 | 48 | * |