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有偿求助-3559a-mobilenet-ssd模型转换问题-有谁成功过么
请问有谁在3559a上转换mobile net ssd 成功的吗?我转后在nnie上推理结果不对, 感觉prototxt没写对。
求prototxt配置,非常感谢!!可有偿!!
下面是我的depthwise卷积层的写法:
layer {
name: "conv2_1/dw"
type: "DepthwiseConv"
bottom: "conv1"
top: "conv2_1/dw"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2_1/dw/bn"
type: "BatchNorm"
bottom: "conv2_1/dw"
top: "conv2_1/dw"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
use_global_stats: true
eps: 1e-5
}
}
layer {
name: "conv2_1/dw/scale"
type: "Scale"
bottom: "conv2_1/dw"
top: "conv2_1/dw"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "relu2_1/dw"
type: "ReLU"
bottom: "conv2_1/dw"
top: "conv2_1/dw"
}
layer {
name: "conv2_1/sep"
type: "Convolution"
bottom: "conv2_1/dw"
top: "conv2_1/sep"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
求prototxt配置,非常感谢!!可有偿!!
下面是我的depthwise卷积层的写法:
layer {
name: "conv2_1/dw"
type: "DepthwiseConv"
bottom: "conv1"
top: "conv2_1/dw"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2_1/dw/bn"
type: "BatchNorm"
bottom: "conv2_1/dw"
top: "conv2_1/dw"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
use_global_stats: true
eps: 1e-5
}
}
layer {
name: "conv2_1/dw/scale"
type: "Scale"
bottom: "conv2_1/dw"
top: "conv2_1/dw"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "relu2_1/dw"
type: "ReLU"
bottom: "conv2_1/dw"
top: "conv2_1/dw"
}
layer {
name: "conv2_1/sep"
type: "Convolution"
bottom: "conv2_1/dw"
top: "conv2_1/sep"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
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