Operation Param Weight Table — ncnn

operation	param id	param phase	default value	weight order
AbsVal
ArgMax	0	out_max_val	0
	1	topk	1
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
	18	pad_value	0.f
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
	18	pad_value	0.f
Crop	0	woffset	0
	1	hoffset	0
	2	coffset	0
	3	outw	0
	4	outh	0
	5	outc	0
	6	woffset2	0
	7	hoffset2	0
	8	coffset2	0
	9	starts	[ ]
	10	ends	[ ]
	11	axes	[ ]
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
	18	output_pad_right	0
	19	output_pad_bottom	output_pad_right
	20	output_w	0
	21	output_h	output_w
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
	18	output_pad_right	0
	19	output_pad_bottom	output_pad_right
	20	output_w	0
	21	output_h	output_w
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
	3	axes	[ ]
Flatten
Gemm	0	alpha	1.f	A_data B_data C_data A_data_int8_scales B_data_int8_scales/B_data_quantize_scales B_data_input_scales
	1	beta	1.f
	2	transA	0
	3	transB	0
	4	constantA	0
	5	constantB	0
	6	constantC	0
	7	constantM	0
	8	constantN	0
	9	constantK	0
	10	constant_broadcast_type_C	0
	11	output_N1M	0
	12	output_elempack	0
	13	output_elemtype	0
	14	output_transpose	0
	18	quantize_term	0
	20	constant_TILE_M	0
	21	constant_TILE_N	0
	22	constant_TILE_K	0
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
LSTM	0	num_output	0
	1	weight_data_size	1
	2	direction	0
MemoryData	0	w	0
	1	h	0
	2	c	0
Mish
MVN	0	normalize_variance	0
	1	across_channels	0
	2	eps	0.0001f
Noop
Normalize	0	across_spatial	0	scale
	4	across_channel	0
	1	channel_shared	0
	2	eps	0.0001f
	9	eps_mode	0
	3	scale_data_size	0
Packing	0	out_packing	1
	1	use_padding	0
	2	cast_type_from	0
	3	cast_type_to	0
	4	storage_type_from	0
	5	storage_type_to	0
Padding	0	top	0	per_channel_pad_data
	1	bottom	0
	2	left	0
	3	right	0
	4	type	0
	5	value	0.f
	6	per_channel_pad_data_size	0
	7	front	0
	8	behind	0
Permute	0	order_type	0
PixelShuffle	0	upscale_factor	1
Pooling	0	pooling_type(0: max 1: avg)	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
	14	step_mmdetection	0
	15	center_mmdetection	0
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
	3	axes	[ ]
	4	keepdims	0
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
	3	sampling_ratio	0
	4	aligned	0
	5	version	0
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
SELU	0	alpha	1.67326324f
	1	lambda	1.050700987f
ShuffleChannel	0	group	1
Sigmoid
Slice	0	slices	[ ]
	1	axis	0
Softmax	0	axis	0
Split
SPP	0	pooling_type	0
	1	pyramid_height	1
Squeeze	0	squeeze_w	0
	1	squeeze_h	0
	2	squeeze_c	0
	3	axes	[ ]
StatisticsPooling	0	include_stddev	0
Swish
TanH
Threshold	0	threshold	0.f
Tile	0	dim	0
	1	tiles	1
UnaryOp	0	op_type	0
YoloDetectionOutput	0	num_class	20
	1	num_box	5
	2	confidence_threshold	0.01f
	3	num_threshold	0.45f
	4	biases	[]
Yolov3DetectionOutput	0	num_class	20
	1	num_box	5
	2	confidence_threshold	0.01f
	3	num_threshold	0.45f
	4	biases	[]
	5	mask	[]
	6	anchors_scale	[]
RNN	0	num_output	0
	1	weight_data_size	0
	2	direction	0
MultiHeadAttention	0	embed_dim	0	q_weight_data q_bias_data k_weight_data k_bias_data v_weight_data v_bias_data out_weight_data out_bias_data q_weight_data_int8_scales k_weight_data_int8_scales v_weight_data_int8_scales out_weight_data_int8_scales q_weight_data_quantize_scales k_weight_data_quantize_scales v_weight_data_quantize_scales out_weight_data_quantize_scales q_weight_data_input_scales k_weight_data_input_scales v_weight_data_input_scales out_weight_data_input_scales
	1	num_head	1
	2	weight_data_size	0
	3	kdim	embed_dim
	4	vdim	embed_dim
	5	attn_mask	0
	6	scale	1.f / sqrt(embed_dim / num_heads)
	7	kv_cache	0
	18	quantize_term	0

Source: docs/developer-guide/operation-param-weight-table.md