1
2 OpenVINO支持的MXNet模型
2-1 Classification models:
- VGG-16 VGG-19
- ResNet-152 v1
- SqueezeNet_v1.1
- Inception BN
- CaffeNet
- DenseNet-121 DenseNet-161 DenseNet-169 DenseNet-201
- MobileNet
2-2 Object detection models:
- SSD-ResNet-50
- SSD-VGG-16-300
- SSD-Inception v3
2-3 Semantic Segmentation models:
- FCN8
2-4 Face Detection models:
- MTCNN P-Net MTCNN N-Net MTCNN O-Net MTCNN R-Net
Lightened_moon
RNN-Transducer Repo
word_lm Repo
3 OpenVINO支持的MXNet层与其在Intermediate Representation (IR)中的对应关系
NUMBER | SYMBOL NAME IN MXNET* | LAYER NAME IN THE INTERMEDIATE REPRESENTATION |
1 | BatchNorm | BatchNormalization |
2 | Crop | Crop |
3 | ScaleShift | ScaleShift |
4 | Pooling | Pooling |
5 | SoftmaxOutput | SoftMax |
6 | SoftmaxActivation | SoftMax |
7 | null | Ignored, does not appear in IR |
8 | Convolution | Convolution |
9 | Deconvolution | Deconvolution |
10 | Activation(act_type = relu) | ReLU |
11 | ReLU | ReLU |
12 | LeakyReLU | ReLU (negative_slope = 0.25) |
13 | Concat | Concat |
14 | elemwise_add | Eltwise(operation = sum) |
15 | _Plus | Eltwise(operation = sum) |
16 | Flatten | Flatten |
17 | Reshape | Reshape |
18 | FullyConnected | FullyConnected |
19 | UpSampling | Resample |
20 | transpose | Permute |
21 | LRN | Norm |
22 | L2Normalization | Normalize |
23 | Dropout | Ignored, does not appear in IR |
24 | _copy | Ignored, does not appear in IR |
25 | _contrib_MultiBoxPrior | PriorBox |
26 | _contrib_MultiBoxDetection | DetectionOutput |
27 | broadcast_mul | ScaleShift |
28 | sigmoid | sigmoid |
29 | Activation (act_type = tanh) | Activation (operation = tanh) |
30 | LeakyReLU (act_type = prelu) | PReLU |
31 | LeakyReLU (act_type = elu) | Activation (operation = elu) |
32 | elemwise_mul | Eltwise (operation = mul) |
33 | add_n | Eltwise (operation = sum) |
34 | ElementWiseSum | Eltwise (operation = sum) |
35 | _mul_scalar | Power |
36 | broadcast_add | Eltwise (operation = sum) |
37 | slice_axis | Crop |
38 | Custom | Custom Layers in the Model Optimizer |
39 | _minus_scalar | Power |
40 | Pad | Pad |
41 | _contrib_Proposal | Proposal |
42 | ROIPooling | ROIPooling |
43 | stack | Concat |
44 | swapaxis | Permute |
45 | zeros | Const |
45 | rnn | TensorIterator |
46 | rnn_param_concat | Concat |
47 | slice_channel | Split |
48 | _maximum | Eltwise(operation = max) |
49 | _minimum | Power(scale=-1) + Eltwise(operation = max) + Power(scale=-1) |
50 | InstanceNorm | scale * (x - mean) / sqrt(variance + epsilon) + B |
51 | Embedding | Gather |
参考资料：
1 Converting a MXNet* Model
2 Supported Framework Layers