operation param weight table - nihui/ncnn GitHub Wiki

operation param id param phase default value weight order
AbsVal
ArgMax TODO
BatchNorm 0 channels 0 slope mean variance bias
1 eps 0.f
Bias 0 bias_data_size 0
BinaryOp 0 op_type 0
1 with_scalar 0
2 b 0.f
BNLL
Cast 0 type_from 0
1 type_to 0
Clip 0 min -FLT_MAX
1 max FLT_MAX
Concat 0 axis 0
Convolution 0 num_output 0 weight bias
1 kernel_w 0
2 dilation_w 1
3 stride_w 1
4 pad_left 0
5 bias_term 0
6 weight_data_size 0
8 int8_scale_term 0
9 activation_type 0
10 activation_params [ ]
11 kernel_h kernel_w
12 dilation_h dilation_w
13 stride_h stride_w
15 pad_right pad_left
14 pad_top pad_left
16 pad_bottom pad_top
17 impl_type 0
ConvolutionDepthWise 0 num_output 0 weight bias
1 kernel_w 0
2 dilation_w 1
3 stride_w 1
4 pad_left 0
5 bias_term 0
6 weight_data_size 0
7 group 1
8 int8_scale_term 0
9 activation_type 0
10 activation_params [ ]
11 kernel_h kernel_w
12 dilation_h dilation_w
13 stride_h stride_w
15 pad_right pad_left
14 pad_top pad_left
16 pad_bottom pad_top
Crop 0 woffset 0
1 hoffset 0
2 coffset 0
3 outw 0
4 outh 0
5 outc 0
Deconvolution 0 num_output 0 weight bias
1 kernel_w 0
2 dilation_w 1
3 stride_w 1
4 pad_left 0
5 bias_term 0
6 weight_data_size 0
9 activation_type 0
10 activation_params [ ]
11 kernel_h kernel_w
12 dilation_h dilation_w
13 stride_h stride_w
15 pad_right pad_left
14 pad_top pad_left
16 pad_bottom pad_top
DeconvolutionDepthWise 0 num_output 0 weight bias
1 kernel_w 0
2 dilation_w 1
3 stride_w 1
4 pad_left 0
5 bias_term 0
6 weight_data_size 0
7 group 1
9 activation_type 0
10 activation_params [ ]
11 kernel_h kernel_w
12 dilation_h dilation_w
13 stride_h stride_w
15 pad_right pad_left
14 pad_top pad_left
16 pad_bottom pad_top
Dequantize 0 scale 1.f bias
1 bias_term 0
2 bias_data_size 0
DetectionOutput 0 num_class 0
1 nms_threshold 0.05f
2 nms_top_k 300
3 keep_top_k 100
4 confidence_threshold 0.5f
5 variances[0] 0.1f
6 variances[1] 0.1f
7 variances[2] 0.2f
8 variances[3] 0.2f
Dropout 0 scale 1.f
Eltwise 0 op_type 0
1 coeffs [ ]
ELU 0 alpha 0.1f
Embed 0 num_output 0 weight bias
1 input_dim 0
2 bias_term 0
3 weight_data_size 0
Exp 0 base -1.f
1 scale 1.f
2 shift 0.f
ExpandDims 0 expand_w 0
1 expand_h 0
2 expand_c 0
Flatten
HardSigmoid 0 alpha 0.2f
1 beta 0.5f
HardSwish 0 alpha 0.2f
1 beta 0.5f
InnerProduct 0 num_output 0 weight bias
1 bias_term 0
2 weight_data_size 0
8 int8_scale_term 0
9 activation_type 0
10 activation_params [ ]
Input 0 w 0
1 h 0
2 c 0
InstanceNorm 0 channels 0 gamma bias
1 eps 0.001f
Interp 0 resize_type 0
1 height_scale 1.f
2 width_scale 1.f
3 output_height 0
4 output_width 0
Log 0 base -1.f
1 scale 1.f
2 shift 0.f
LRN 0 region_type 0
1 local_size 5
2 alpha 1.f
3 beta 0.75f
4 bias 1.f
MemoryData 0 w 0
1 h 0
2 c 0
MVN 0 normalize_variance 0
1 across_channels 0
2 eps 0.0001f
Normalize 0 across_spatial 0 scale
4 across_channel 0
1 channel_shared 0
2 eps 0.0001f
3 scale_data_size 0
Packing 0 out_packing 1
1 use_padding 0
Padding 0 top 0
1 bottom 0
2 left 0
3 right 0
4 type 0
5 value 0.f
Permute 0 order_type 0
Pooling 0 pooling_type 0
1 kernel_w 0
11 kernel_h kernel_w
2 stride_w 1
12 stride_h stride_w
3 pad_left 0
14 pad_right pad_left
13 pad_top pad_left
15 pad_bottom pad_top
4 global_pooling 0
5 pad_mode 0
Power 0 power 1.f
1 scale 1.f
2 shift 0.f
PReLU 0 num_slope 0 slope
PriorBox 0 min_sizes [ ]
1 max_sizes [ ]
2 aspect_ratios [ ]
3 varainces[0] 0.f
4 varainces[1] 0.f
5 varainces[2] 0.f
6 varainces[3] 0.f
7 flip 1
8 clip 0
9 image_width 0
10 image_height 0
11 step_width -233.f
12 step_height -233.f
13 offset 0.f
Proposal 0 feat_stride 16
1 base_size 16
2 pre_nms_topN 6000
3 after_nms_topN 300
4 num_thresh 0.7f
5 min_size 16
PSROIPooling 0 pooled_width 7
1 pooled_height 7
2 spatial_scale 0.0625f
3 output_dim 0
Quantize 0 scale 1.f
Reduction 0 operation 0
1 dim 0
2 coeff 1.f
ReLU 0 slope 0.f
Reorg 0 stride 0
Requantize 0 scale_in 1.f bias
1 scale_out 1.f
2 bias_term 0
3 bias_data_size 0
4 fusion_relu 0
Reshape 0 w -233
1 h -233
2 c -233
3 permute 0
ROIAlign 0 pooled_width 0
1 pooled_height 0
2 spatial_scale 1.f
ROIPooling 0 pooled_width 0
1 pooled_height 0
2 spatial_scale 1.f
Scale 0 scale_data_size 0 scale bias
1 bias_term 0
ShuffleChannel 0 group 1
Sigmoid
Slice 0 slices [ ]
1 axis 0
Softmax 0 axis 0
Split
SPP TODO
Squeeze 0 squeeze_w 0
1 squeeze_h 0
2 squeeze_c 0
TanH
Threshold 0 threshold 0.f
Tile TODO
UnaryOp 0 op_type 0
RNN TODO
LSTM TODO
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