int SPP::load_param(const ParamDict& pd)
{
pooling_type = pd.get(0, 0);
pyramid_height = pd.get(1, 1);
return 0;
}
int MemoryData::load_param(const ParamDict& pd)
{
w = pd.get(0, 0);
h = pd.get(1, 0);
c = pd.get(2, 0);
return 0;
}
int Log::load_param(const ParamDict& pd)
{
base = pd.get(0, -1.f);
scale = pd.get(1, 1.f);
shift = pd.get(2, 0.f);
return 0;
}
int LRN::load_param(const ParamDict& pd)
{
region_type = pd.get(0, 0);
local_size = pd.get(1, 5);
alpha = pd.get(2, 1.f);
beta = pd.get(3, 0.75f);
return 0;
}
int Embed::load_param(const ParamDict& pd)
{
num_output = pd.get(0, 0);
input_dim = pd.get(1, 0);
bias_term = pd.get(2, 0);
weight_data_size = pd.get(3, 0);
return 0;
}
int Normalize::load_param(const ParamDict& pd)
{
across_spatial = pd.get(0, 0);
across_channel = pd.get(4, 1);
channel_shared = pd.get(1, 0);
eps = pd.get(2, 0.0001f);
scale_data_size = pd.get(3, 0);
return 0;
}
int DetectionOutput::load_param(const ParamDict& pd)
{
num_class = pd.get(0, 0);
nms_threshold = pd.get(1, 0.05f);
nms_top_k = pd.get(2, 300);
keep_top_k = pd.get(3, 100);
confidence_threshold = pd.get(4, 0.5f);
return 0;
}
int PriorBox::load_param(const ParamDict& pd)
{
min_sizes = pd.get(0, Mat());
max_sizes = pd.get(1, Mat());
aspect_ratios = pd.get(2, Mat());
variances[0] = pd.get(3, 0.f);
variances[1] = pd.get(4, 0.f);
variances[2] = pd.get(5, 0.f);
variances[3] = pd.get(6, 0.f);
flip = pd.get(7, 1);
clip = pd.get(8, 0);
image_width = pd.get(9, 0);
image_height = pd.get(10, 0);
step_width = pd.get(11, -233.f);
step_height = pd.get(12, -233.f);
offset = pd.get(13, 0.f);
return 0;
}
int Slice::load_param(const ParamDict& pd)
{
slices = pd.get(0, Mat());
return 0;
}
int DeconvolutionDepthWise::load_param(const ParamDict& pd)
{
num_output = pd.get(0, 0);
kernel_w = pd.get(1, 0);
kernel_h = pd.get(11, kernel_w);
dilation_w = pd.get(2, 1);
dilation_h = pd.get(12, dilation_w);
stride_w = pd.get(3, 1);
stride_h = pd.get(13, stride_w);
pad_w = pd.get(4, 0);
pad_h = pd.get(14, pad_w);
bias_term = pd.get(5, 0);
weight_data_size = pd.get(6, 0);
group = pd.get(7, 1);
return 0;
}
int Permute::load_param(const ParamDict& pd)
{
order_type = pd.get(0, 0);
return 0;
}
int Dropout::load_param(const ParamDict& pd)
{
scale = pd.get(0, 1.f);
return 0;
}
int UnaryOp::load_param(const ParamDict& pd)
{
op_type = pd.get(0, 0);
return 0;
}