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; }