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2 OpenVINO支持的TENSORFLOW模型
- Inception v1 、 Inception v2、 Inception v3 、Inception V4 、 Inception ResNet v2
- MobileNet v1 128、 MobileNet v1 160 、MobileNet v1 224
- NasNet Large 、 NasNet Mobile
- ResidualNet-50 、ResidualNet-101 、ResidualNet-152
- VGG-16 、VGG-19
3 OpenVINO支持的TENSORFLOW层与其在Intermediate Representation (IR)中的对应关系
NUMBER | OPERATION NAME IN TENSORFLOW | LAYER NAME IN THE INTERMEDIATE REPRESENTATION |
1 | Transpose | Permute |
2 | LRN | Norm |
3 | Split | Split |
4 | SplitV | Split |
5 | FusedBatchNorm | ScaleShift (can be fused into Convolution or FullyConnected) |
6 | Relu6 | Clamp |
7 | DepthwiseConv2dNative | Convolution |
8 | ExpandDims | Constant propagation |
9 | Slice | Split |
10 | ConcatV2 | Concat |
11 | MatMul | FullyConnected |
12 | Pack | Reshapes and Concat |
13 | StridedSlice | Constant propagation and several cases when StridedSlice can be expressed with Splits |
14 | Prod | Constant propagation |
15 | Const | Constant propagation |
16 | Tile | Tile |
17 | Placeholder | Input |
18 | Pad | Fused into Convolution or Pooling layers (not supported as single operation) |
19 | Conv2D | Convolution |
20 | Conv2DBackpropInput | Deconvolution |
21 | Identity | Ignored, does not appear in the IR |
22 | Add | Eltwise(operation = sum) |
23 | Mul | Eltwise(operation = mul) |
24 | Maximum | |
25 | Rsqrt | Power(power=-0.5) |
26 | Neg | Power(scale=-1) |
27 | Sub | Eltwise(operation = sum) + Power(scale=-1) |
28 | Relu | ReLU |
29 | AvgPool | Pooling (pool_method=avg) |
30 | MaxPool | Pooling (pool_method=max) |
31 | Mean | Pooling (pool_method = avg); spatial dimensions are supported only |
32 | RandomUniform | Not supported |
33 | BiasAdd | Fused or converted to ScaleShift |
34 | Reshape | Reshape |
35 | Squeeze | Reshape |
36 | Shape | Constant propagation (or layer generation if the “–keep_shape_ops” command line parameter has been specified) |
37 | Softmax | SoftMax |
38 | SpaceToBatchND | Supported in a pattern when converted to Convolution layer dilation attribute, Constant propagation |
39 | BatchToSpaceND | Supported in a pattern when converted to Convolution layer dilation attribute, Constant propagation |
40 | StopGradient | |
41 | Square Constant propagation | |
42 | Sum | Pool(pool_method = avg) + Eltwise(operation = mul) |
43 | Range | Constant propagation |
44 | CropAndResize | ROIPooling (if the the method is ‘bilinear’) |
45 | ArgMax | ArgMax |
46 | DepthToSpace | Reshape + Permute + Reshape (works for CPU only because of 6D tensors) |
47 | ExtractImagePatches | ReorgYolo |
48 | ResizeBilinear | Interp |
49 | ResizeNearestNeighbor | Resample |
50 | Unpack | Split + Reshape (removes dimension being unpacked) if the number of parts is equal to size along given axis |
51 | AddN | Several Eltwises |
52 | Concat | Concat |
53 | Minimum | Power(scale=-1) + Eltwise(operation = max) + Power(scale=-1) |
54 | Unsqueeze | Reshape |
55 | RealDiv | Power(power = -1) and Eltwise(operation = mul) |
56 | SquaredDifference | Power(scale = -1) + Eltwise(operation = sum) + Power(power = 2) |
57 | Gather | Gather |
58 | GatherV2 | Gather |
59 | ResourceGather | Gather |
60 | Sqrt | Power(power=0.5) |
61 | Square | Power(power=2) |
62 | Pad | Pad |
63 | PadV2 | Pad |
64 | MirrorPad | Pad |
65 | ReverseSequence | ReverseSequence |
66 | ZerosLike Constant | propagation |
参考资料：
1 Converting a TensorFlow* Model
2 Supported Framework Layers
