models/QCS6490/cutoff_yolov5s_int8_snpe2/cutoff_yolov5s_int8_snpe2.csv

DLC info for: /data0/ai-transform-data/data/6cdbbbe9-4694-4093-8527-b8fc6a5b1e3a/yolov5s_save_path/cutoff_yolov5s_int8_snpe2.dlc
Model Version: N/A
Model Copyright:N/A
Id,Name,Type,Inputs,Outputs,Out Dims,Runtimes,Parameters
0,/model.0/conv/Conv,Conv2d,"images (data type: uFxp_8; tensor dimension: [1, 640, 640, 3]; tensor type: APP_WRITE) [NW Input]","/model.0/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 320, 320, 32]; tensor type: NATIVE)",1x320x320x32,A D G C,"images encoding : bitwidth 8, min 0.000000000000, max 1.000000000000, scale 0.003921568859, offset 0.000000000000"
,,,"model.0.conv.weight (data type: uFxp_8; tensor dimension: [6, 6, 3, 32]; tensor type: STATIC)",,,,"model.0.conv.weight encoding : bitwidth 8, min -11.740019798279, max 14.292198181152, scale 0.102087132633, offset -115.000000000000"
,,,model.0.conv.bias (data type: uFxp_8; tensor dimension: [32]; tensor type: STATIC),,,,"model.0.conv.bias encoding : bitwidth 8, min -10.863437652588, max 4.357312679291, scale 0.059689216316, offset -182.000000000000"
,,,,,,,"/model.0/conv/Conv_output_0 encoding : bitwidth 8, min -47.470592498779, max 50.150386810303, scale 0.382827371359, offset -124.000000000000"
,,,,,,,bias_op_name: model.0.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[2, 2], [2, 2]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [2, 2]"
,,,,,,,param count: 3k (0.0483%)
,,,,,,,MACs per inference: 353M (4.31%)
1,/model.0/act/Sigmoid,Neuron,"/model.0/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 320, 320, 32]; tensor type: NATIVE)","/model.0/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 320, 320, 32]; tensor type: NATIVE)",1x320x320x32,A D G C,"/model.0/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 1.000000000000, scale 0.003921568859, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
2,/model.0/act/Mul,Eltwise_Binary,"/model.0/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 320, 320, 32]; tensor type: NATIVE)","/model.0/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 320, 320, 32]; tensor type: NATIVE)",1x320x320x32,A D G C,"/model.0/act/Mul_output_0 encoding : bitwidth 8, min -0.197410047054, max 50.142150878906, scale 0.197410047054, offset -1.000000000000"
,,,"/model.0/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 320, 320, 32]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
3,/model.1/conv/Conv,Conv2d,"/model.0/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 320, 320, 32]; tensor type: NATIVE)","/model.1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 64]; tensor type: NATIVE)",1x160x160x64,A D G C,"model.1.conv.weight encoding : bitwidth 8, min -0.967206001282, max 0.794490695000, scale 0.006908614654, offset -140.000000000000"
,,,"model.1.conv.weight (data type: uFxp_8; tensor dimension: [3, 3, 32, 64]; tensor type: STATIC)",,,,"model.1.conv.bias encoding : bitwidth 8, min -3.702117681503, max 4.230991840363, scale 0.031110232696, offset -119.000000000000"
,,,model.1.conv.bias (data type: uFxp_8; tensor dimension: [64]; tensor type: STATIC),,,,"/model.1/conv/Conv_output_0 encoding : bitwidth 8, min -80.881690979004, max 81.518547058105, scale 0.636863648891, offset -127.000000000000"
,,,,,,,bias_op_name: model.1.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[1, 1], [1, 1]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [2, 2]"
,,,,,,,param count: 18k (0.256%)
,,,,,,,MACs per inference: 471M (5.74%)
4,/model.1/act/Sigmoid,Neuron,"/model.1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 64]; tensor type: NATIVE)","/model.1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 64]; tensor type: NATIVE)",1x160x160x64,A D G C,"/model.1/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 1.000000000000, scale 0.003921568859, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
5,/model.1/act/Mul,Eltwise_Binary,"/model.1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 64]; tensor type: NATIVE)","/model.1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 64]; tensor type: NATIVE)",1x160x160x64,A D G C,"/model.1/act/Mul_output_0 encoding : bitwidth 8, min -0.320762753487, max 81.473739624023, scale 0.320762753487, offset -1.000000000000"
,,,"/model.1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 64]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
6,/model.2/cv1/conv/Conv,Conv2d,"/model.1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 64]; tensor type: NATIVE)","/model.2/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)",1x160x160x32,A D G C,"model.2.cv1.conv.weight encoding : bitwidth 8, min -0.663011074066, max 0.260856807232, scale 0.003623011289, offset -183.000000000000"
,,,"model.2.cv1.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 64, 32]; tensor type: STATIC)",,,,"model.2.cv1.conv.bias encoding : bitwidth 8, min -0.212710559368, max 2.145602226257, scale 0.009248285554, offset -23.000000000000"
,,,model.2.cv1.conv.bias (data type: uFxp_8; tensor dimension: [32]; tensor type: STATIC),,,,"/model.2/cv1/conv/Conv_output_0 encoding : bitwidth 8, min -45.248344421387, max 22.227256774902, scale 0.264610201120, offset -171.000000000000"
,,,,,,,bias_op_name: model.2.cv1.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 2k (0.0288%)
,,,,,,,MACs per inference: 52M (0.638%)
7,/model.2/cv1/act/Sigmoid,Neuron,"/model.2/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)","/model.2/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)",1x160x160x32,A D G C,"/model.2/cv1/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 1.000000000000, scale 0.003921568859, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
8,/model.2/cv1/act/Mul,Eltwise_Binary,"/model.2/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)","/model.2/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)",1x160x160x32,A D G C,"/model.2/cv1/act/Mul_output_0 encoding : bitwidth 8, min -0.264801651239, max 22.243337631226, scale 0.088267214596, offset -3.000000000000"
,,,"/model.2/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
9,/model.2/m/m.0/cv1/conv/Conv,Conv2d,"/model.2/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)","/model.2/m/m.0/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)",1x160x160x32,A D G C,"model.2.m.0.cv1.conv.weight encoding : bitwidth 8, min -3.478188514709, max 1.619156718254, scale 0.019989589229, offset -174.000000000000"
,,,"model.2.m.0.cv1.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 32, 32]; tensor type: STATIC)",,,,"model.2.m.0.cv1.conv.bias encoding : bitwidth 8, min -4.383419990540, max 5.252546787262, scale 0.037788104266, offset -116.000000000000"
,,,model.2.m.0.cv1.conv.bias (data type: uFxp_8; tensor dimension: [32]; tensor type: STATIC),,,,"/model.2/m/m.0/cv1/conv/Conv_output_0 encoding : bitwidth 8, min -45.878349304199, max 15.053833007812, scale 0.238949730992, offset -192.000000000000"
,,,,,,,bias_op_name: model.2.m.0.cv1.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 1k (0.0146%)
,,,,,,,MACs per inference: 26M (0.319%)
10,/model.2/m/m.0/cv1/act/Sigmoid,Neuron,"/model.2/m/m.0/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)","/model.2/m/m.0/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)",1x160x160x32,A D G C,"/model.2/m/m.0/cv1/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999999761581, scale 0.003921567462, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
11,/model.2/m/m.0/cv1/act/Mul,Eltwise_Binary,"/model.2/m/m.0/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)","/model.2/m/m.0/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)",1x160x160x32,A D G C,"/model.2/m/m.0/cv1/act/Mul_output_0 encoding : bitwidth 8, min -0.301748454571, max 15.087422370911, scale 0.060349691659, offset -5.000000000000"
,,,"/model.2/m/m.0/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
12,/model.2/m/m.0/cv2/conv/Conv,Conv2d,"/model.2/m/m.0/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)","/model.2/m/m.0/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)",1x160x160x32,A D G C,"model.2.m.0.cv2.conv.weight encoding : bitwidth 8, min -2.201115131378, max 2.515560388565, scale 0.018496766686, offset -119.000000000000"
,,,"model.2.m.0.cv2.conv.weight (data type: uFxp_8; tensor dimension: [3, 3, 32, 32]; tensor type: STATIC)",,,,"model.2.m.0.cv2.conv.bias encoding : bitwidth 8, min -4.313523292542, max 6.470284938812, scale 0.042289443314, offset -102.000000000000"
,,,model.2.m.0.cv2.conv.bias (data type: uFxp_8; tensor dimension: [32]; tensor type: STATIC),,,,"/model.2/m/m.0/cv2/conv/Conv_output_0 encoding : bitwidth 8, min -27.113218307495, max 27.326709747314, scale 0.213489919901, offset -127.000000000000"
,,,,,,,bias_op_name: model.2.m.0.cv2.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[1, 1], [1, 1]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 9k (0.128%)
,,,,,,,MACs per inference: 235M (2.87%)
13,/model.2/m/m.0/cv2/act/Sigmoid,Neuron,"/model.2/m/m.0/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)","/model.2/m/m.0/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)",1x160x160x32,A D G C,"/model.2/m/m.0/cv2/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 1.000000000000, scale 0.003921568859, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
14,/model.2/m/m.0/cv2/act/Mul,Eltwise_Binary,"/model.2/m/m.0/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)","/model.2/m/m.0/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)",1x160x160x32,A D G C,"/model.2/m/m.0/cv2/act/Mul_output_0 encoding : bitwidth 8, min -0.324162214994, max 27.229625701904, scale 0.108054071665, offset -3.000000000000"
,,,"/model.2/m/m.0/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
15,/model.2/m/m.0/Add,Eltwise_Binary,"/model.2/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)","/model.2/m/m.0/Add_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)",1x160x160x32,A D G C,"/model.2/m/m.0/Add_output_0 encoding : bitwidth 8, min -0.542982876301, max 27.149143218994, scale 0.108596570790, offset -5.000000000000"
,,,"/model.2/m/m.0/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseAdd
,,,,,,,packageName: qti.aisw
16,/model.2/cv2/conv/Conv,Conv2d,"/model.1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 64]; tensor type: NATIVE)","/model.2/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)",1x160x160x32,A D G C,"model.2.cv2.conv.weight encoding : bitwidth 8, min -1.497491240501, max 0.635806322098, scale 0.008365873247, offset -179.000000000000"
,,,"model.2.cv2.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 64, 32]; tensor type: STATIC)",,,,"model.2.cv2.conv.bias encoding : bitwidth 8, min -1.860156536102, max 3.132895231247, scale 0.019580595195, offset -95.000000000000"
,,,model.2.cv2.conv.bias (data type: uFxp_8; tensor dimension: [32]; tensor type: STATIC),,,,"/model.2/cv2/conv/Conv_output_0 encoding : bitwidth 8, min -109.744178771973, max 42.346939086914, scale 0.596435785294, offset -184.000000000000"
,,,,,,,bias_op_name: model.2.cv2.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 2k (0.0288%)
,,,,,,,MACs per inference: 52M (0.638%)
17,/model.2/cv2/act/Sigmoid,Neuron,"/model.2/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)","/model.2/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)",1x160x160x32,A D G C,"/model.2/cv2/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 1.000000000000, scale 0.003921568859, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
18,/model.2/cv2/act/Mul,Eltwise_Binary,"/model.2/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)","/model.2/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)",1x160x160x32,A D G C,"/model.2/cv2/act/Mul_output_0 encoding : bitwidth 8, min -0.332378834486, max 42.045925140381, scale 0.166189417243, offset -2.000000000000"
,,,"/model.2/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
19,/model.2/Concat,Concat,"/model.2/m/m.0/Add_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)","/model.2/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 64]; tensor type: NATIVE)",1x160x160x64,A D G C,"/model.2/Concat_output_0 encoding : bitwidth 8, min -0.542982876301, max 42.045925140381, scale 0.167015329003, offset -3.000000000000"
,,,"/model.2/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 32]; tensor type: NATIVE)",,,,axis: 3
,,,,,,,packageName: qti.aisw
20,/model.2/cv3/conv/Conv,Conv2d,"/model.2/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 64]; tensor type: NATIVE)","/model.2/cv3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 64]; tensor type: NATIVE)",1x160x160x64,A D G C,"model.2.cv3.conv.weight encoding : bitwidth 8, min -0.952466607094, max 0.699771344662, scale 0.006479364354, offset -147.000000000000"
,,,"model.2.cv3.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 64, 64]; tensor type: STATIC)",,,,"model.2.cv3.conv.bias encoding : bitwidth 8, min -2.113106966019, max 6.439945220947, scale 0.033541381359, offset -63.000000000000"
,,,model.2.cv3.conv.bias (data type: uFxp_8; tensor dimension: [64]; tensor type: STATIC),,,,"/model.2/cv3/conv/Conv_output_0 encoding : bitwidth 8, min -27.003763198853, max 17.137002944946, scale 0.173101037741, offset -156.000000000000"
,,,,,,,bias_op_name: model.2.cv3.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 4k (0.0576%)
,,,,,,,MACs per inference: 104M (1.28%)
21,/model.2/cv3/act/Sigmoid,Neuron,"/model.2/cv3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 64]; tensor type: NATIVE)","/model.2/cv3/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 64]; tensor type: NATIVE)",1x160x160x64,A D G C,"/model.2/cv3/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 1.000000000000, scale 0.003921568859, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
22,/model.2/cv3/act/Mul,Eltwise_Binary,"/model.2/cv3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 64]; tensor type: NATIVE)","/model.2/cv3/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 64]; tensor type: NATIVE)",1x160x160x64,A D G C,"/model.2/cv3/act/Mul_output_0 encoding : bitwidth 8, min -0.272874474525, max 17.122873306274, scale 0.068218618631, offset -4.000000000000"
,,,"/model.2/cv3/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 64]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
23,/model.3/conv/Conv,Conv2d,"/model.2/cv3/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 160, 160, 64]; tensor type: NATIVE)","/model.3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)",1x80x80x128,A D G C,"model.3.conv.weight encoding : bitwidth 8, min -0.493704855442, max 0.582318544388, scale 0.004219699651, offset -117.000000000000"
,,,"model.3.conv.weight (data type: uFxp_8; tensor dimension: [3, 3, 64, 128]; tensor type: STATIC)",,,,"model.3.conv.bias encoding : bitwidth 8, min -3.168411254883, max 2.290675878525, scale 0.021408185363, offset -148.000000000000"
,,,model.3.conv.bias (data type: uFxp_8; tensor dimension: [128]; tensor type: STATIC),,,,"/model.3/conv/Conv_output_0 encoding : bitwidth 8, min -14.502480506897, max 9.052503585815, scale 0.092372484505, offset -157.000000000000"
,,,,,,,bias_op_name: model.3.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[1, 1], [1, 1]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [2, 2]"
,,,,,,,param count: 73k (1.02%)
,,,,,,,MACs per inference: 471M (5.74%)
24,/model.3/act/Sigmoid,Neuron,"/model.3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)","/model.3/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)",1x80x80x128,A D G C,"/model.3/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999882817268, scale 0.003921109252, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
25,/model.3/act/Mul,Eltwise_Binary,"/model.3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)","/model.3/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)",1x80x80x128,A D G C,"/model.3/act/Mul_output_0 encoding : bitwidth 8, min -0.292675435543, max 9.036354064941, scale 0.036584429443, offset -8.000000000000"
,,,"/model.3/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
26,/model.4/cv1/conv/Conv,Conv2d,"/model.3/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)","/model.4/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"model.4.cv1.conv.weight encoding : bitwidth 8, min -0.750764250755, max 0.355853587389, scale 0.004339677747, offset -173.000000000000"
,,,"model.4.cv1.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 128, 64]; tensor type: STATIC)",,,,"model.4.cv1.conv.bias encoding : bitwidth 8, min -1.203034520149, max 1.156764030457, scale 0.009254111908, offset -130.000000000000"
,,,model.4.cv1.conv.bias (data type: uFxp_8; tensor dimension: [64]; tensor type: STATIC),,,,"/model.4/cv1/conv/Conv_output_0 encoding : bitwidth 8, min -6.989511966705, max 2.912296772003, scale 0.038830623031, offset -180.000000000000"
,,,,,,,bias_op_name: model.4.cv1.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 8k (0.114%)
,,,,,,,MACs per inference: 52M (0.638%)
27,/model.4/cv1/act/Sigmoid,Neuron,"/model.4/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.4/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"/model.4/cv1/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.948204636574, scale 0.003718449501, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
28,/model.4/cv1/act/Mul,Eltwise_Binary,"/model.4/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.4/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"/model.4/cv1/act/Mul_output_0 encoding : bitwidth 8, min -0.273758679628, max 2.761391878128, scale 0.011902551167, offset -23.000000000000"
,,,"/model.4/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
29,/model.4/m/m.0/cv1/conv/Conv,Conv2d,"/model.4/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.4/m/m.0/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"model.4.m.0.cv1.conv.weight encoding : bitwidth 8, min -2.917552232742, max 3.784932374954, scale 0.026284253225, offset -111.000000000000"
,,,"model.4.m.0.cv1.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 64, 64]; tensor type: STATIC)",,,,"model.4.m.0.cv1.conv.bias encoding : bitwidth 8, min -2.894704103470, max 3.815746307373, scale 0.026315491647, offset -110.000000000000"
,,,model.4.m.0.cv1.conv.bias (data type: uFxp_8; tensor dimension: [64]; tensor type: STATIC),,,,"/model.4/m/m.0/cv1/conv/Conv_output_0 encoding : bitwidth 8, min -10.419333457947, max 10.501375198364, scale 0.082041993737, offset -127.000000000000"
,,,,,,,bias_op_name: model.4.m.0.cv1.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 4k (0.0576%)
,,,,,,,MACs per inference: 26M (0.319%)
30,/model.4/m/m.0/cv1/act/Sigmoid,Neuron,"/model.4/m/m.0/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.4/m/m.0/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"/model.4/m/m.0/cv1/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999971747398, scale 0.003921458032, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
31,/model.4/m/m.0/cv1/act/Mul,Eltwise_Binary,"/model.4/m/m.0/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.4/m/m.0/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"/model.4/m/m.0/cv1/act/Mul_output_0 encoding : bitwidth 8, min -0.295209795237, max 10.458861351013, scale 0.042172830552, offset -7.000000000000"
,,,"/model.4/m/m.0/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
32,/model.4/m/m.0/cv2/conv/Conv,Conv2d,"/model.4/m/m.0/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.4/m/m.0/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"model.4.m.0.cv2.conv.weight encoding : bitwidth 8, min -0.385654598475, max 0.469492524862, scale 0.003353518201, offset -115.000000000000"
,,,"model.4.m.0.cv2.conv.weight (data type: uFxp_8; tensor dimension: [3, 3, 64, 64]; tensor type: STATIC)",,,,"model.4.m.0.cv2.conv.bias encoding : bitwidth 8, min -2.381798505783, max 2.363190650940, scale 0.018607800826, offset -128.000000000000"
,,,model.4.m.0.cv2.conv.bias (data type: uFxp_8; tensor dimension: [64]; tensor type: STATIC),,,,"/model.4/m/m.0/cv2/conv/Conv_output_0 encoding : bitwidth 8, min -7.265181541443, max 5.252529621124, scale 0.049089062959, offset -148.000000000000"
,,,,,,,bias_op_name: model.4.m.0.cv2.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[1, 1], [1, 1]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 36k (0.511%)
,,,,,,,MACs per inference: 235M (2.87%)
33,/model.4/m/m.0/cv2/act/Sigmoid,Neuron,"/model.4/m/m.0/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.4/m/m.0/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"/model.4/m/m.0/cv2/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.994718134403, scale 0.003900855314, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
34,/model.4/m/m.0/cv2/act/Mul,Eltwise_Binary,"/model.4/m/m.0/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.4/m/m.0/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"/model.4/m/m.0/cv2/act/Mul_output_0 encoding : bitwidth 8, min -0.279829889536, max 5.209141254425, scale 0.021525377408, offset -13.000000000000"
,,,"/model.4/m/m.0/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
35,/model.4/m/m.0/Add,Eltwise_Binary,"/model.4/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.4/m/m.0/Add_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"/model.4/m/m.0/Add_output_0 encoding : bitwidth 8, min -0.565369069576, max 4.979596614838, scale 0.021744962782, offset -26.000000000000"
,,,"/model.4/m/m.0/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseAdd
,,,,,,,packageName: qti.aisw
36,/model.4/m/m.1/cv1/conv/Conv,Conv2d,"/model.4/m/m.0/Add_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.4/m/m.1/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"model.4.m.1.cv1.conv.weight encoding : bitwidth 8, min -2.033593893051, max 1.423515796661, scale 0.013557292521, offset -150.000000000000"
,,,"model.4.m.1.cv1.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 64, 64]; tensor type: STATIC)",,,,"model.4.m.1.cv1.conv.bias encoding : bitwidth 8, min -2.210035324097, max 2.690477848053, scale 0.019217697904, offset -115.000000000000"
,,,model.4.m.1.cv1.conv.bias (data type: uFxp_8; tensor dimension: [64]; tensor type: STATIC),,,,"/model.4/m/m.1/cv1/conv/Conv_output_0 encoding : bitwidth 8, min -9.750625610352, max 7.759300708771, scale 0.068666376173, offset -142.000000000000"
,,,,,,,bias_op_name: model.4.m.1.cv1.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 4k (0.0576%)
,,,,,,,MACs per inference: 26M (0.319%)
37,/model.4/m/m.1/cv1/act/Sigmoid,Neuron,"/model.4/m/m.1/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.4/m/m.1/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"/model.4/m/m.1/cv1/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999576985836, scale 0.003919909708, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
38,/model.4/m/m.1/cv1/act/Mul,Eltwise_Binary,"/model.4/m/m.1/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.4/m/m.1/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"/model.4/m/m.1/cv1/act/Mul_output_0 encoding : bitwidth 8, min -0.283867895603, max 7.759055614471, scale 0.031540878117, offset -9.000000000000"
,,,"/model.4/m/m.1/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
39,/model.4/m/m.1/cv2/conv/Conv,Conv2d,"/model.4/m/m.1/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.4/m/m.1/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"model.4.m.1.cv2.conv.weight encoding : bitwidth 8, min -0.926929771900, max 0.798377454281, scale 0.006765910890, offset -137.000000000000"
,,,"model.4.m.1.cv2.conv.weight (data type: uFxp_8; tensor dimension: [3, 3, 64, 64]; tensor type: STATIC)",,,,"model.4.m.1.cv2.conv.bias encoding : bitwidth 8, min -1.380865335464, max 2.175909042358, scale 0.013948135078, offset -99.000000000000"
,,,model.4.m.1.cv2.conv.bias (data type: uFxp_8; tensor dimension: [64]; tensor type: STATIC),,,,"/model.4/m/m.1/cv2/conv/Conv_output_0 encoding : bitwidth 8, min -14.469618797302, max 10.802659988403, scale 0.099106974900, offset -146.000000000000"
,,,,,,,bias_op_name: model.4.m.1.cv2.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[1, 1], [1, 1]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 36k (0.511%)
,,,,,,,MACs per inference: 235M (2.87%)
40,/model.4/m/m.1/cv2/act/Sigmoid,Neuron,"/model.4/m/m.1/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.4/m/m.1/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"/model.4/m/m.1/cv2/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999979257584, scale 0.003921487369, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
41,/model.4/m/m.1/cv2/act/Mul,Eltwise_Binary,"/model.4/m/m.1/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.4/m/m.1/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"/model.4/m/m.1/cv2/act/Mul_output_0 encoding : bitwidth 8, min -0.260339528322, max 10.804090499878, scale 0.043389923871, offset -6.000000000000"
,,,"/model.4/m/m.1/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
42,/model.4/m/m.1/Add,Eltwise_Binary,"/model.4/m/m.0/Add_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.4/m/m.1/Add_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"/model.4/m/m.1/Add_output_0 encoding : bitwidth 8, min -0.851119041443, max 10.571794509888, scale 0.044795736670, offset -19.000000000000"
,,,"/model.4/m/m.1/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseAdd
,,,,,,,packageName: qti.aisw
43,/model.4/cv2/conv/Conv,Conv2d,"/model.3/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)","/model.4/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"model.4.cv2.conv.weight encoding : bitwidth 8, min -1.484934687614, max 1.473333716393, scale 0.011601052247, offset -128.000000000000"
,,,"model.4.cv2.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 128, 64]; tensor type: STATIC)",,,,"model.4.cv2.conv.bias encoding : bitwidth 8, min -4.333237648010, max 2.984481573105, scale 0.028696937487, offset -151.000000000000"
,,,model.4.cv2.conv.bias (data type: uFxp_8; tensor dimension: [64]; tensor type: STATIC),,,,"/model.4/cv2/conv/Conv_output_0 encoding : bitwidth 8, min -9.851132392883, max 9.036377906799, scale 0.074068665504, offset -133.000000000000"
,,,,,,,bias_op_name: model.4.cv2.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 8k (0.114%)
,,,,,,,MACs per inference: 52M (0.638%)
44,/model.4/cv2/act/Sigmoid,Neuron,"/model.4/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.4/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"/model.4/cv2/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999882578850, scale 0.003921108320, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
45,/model.4/cv2/act/Mul,Eltwise_Binary,"/model.4/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.4/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"/model.4/cv2/act/Mul_output_0 encoding : bitwidth 8, min -0.292616784573, max 9.034543037415, scale 0.036577098072, offset -8.000000000000"
,,,"/model.4/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
46,/model.4/Concat,Concat,"/model.4/m/m.1/Add_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.4/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)",1x80x80x128,A D G C,"/model.4/Concat_output_0 encoding : bitwidth 8, min -0.851119041443, max 10.571794509888, scale 0.044795736670, offset -19.000000000000"
,,,"/model.4/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",,,,axis: 3
,,,,,,,packageName: qti.aisw
47,/model.4/cv3/conv/Conv,Conv2d,"/model.4/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)","/model.4/cv3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)",1x80x80x128,A D G C,"model.4.cv3.conv.weight encoding : bitwidth 8, min -0.705637216568, max 0.678497374058, scale 0.005427978933, offset -130.000000000000"
,,,"model.4.cv3.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 128, 128]; tensor type: STATIC)",,,,"model.4.cv3.conv.bias encoding : bitwidth 8, min -2.350605010986, max 3.148516654968, scale 0.021565182135, offset -109.000000000000"
,,,model.4.cv3.conv.bias (data type: uFxp_8; tensor dimension: [128]; tensor type: STATIC),,,,"/model.4/cv3/conv/Conv_output_0 encoding : bitwidth 8, min -9.706686019897, max 8.493350982666, scale 0.071372695267, offset -136.000000000000"
,,,,,,,bias_op_name: model.4.cv3.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 16k (0.229%)
,,,,,,,MACs per inference: 104M (1.28%)
48,/model.4/cv3/act/Sigmoid,Neuron,"/model.4/cv3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)","/model.4/cv3/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)",1x80x80x128,A D G C,"/model.4/cv3/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999796688557, scale 0.003920771182, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
49,/model.4/cv3/act/Mul,Eltwise_Binary,"/model.4/cv3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)","/model.4/cv3/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)",1x80x80x128,A D G C,"/model.4/cv3/act/Mul_output_0 encoding : bitwidth 8, min -0.275364756584, max 8.501886367798, scale 0.034420594573, offset -8.000000000000"
,,,"/model.4/cv3/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
50,/model.5/conv/Conv,Conv2d,"/model.4/cv3/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)","/model.5/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)",1x40x40x256,A D G C,"model.5.conv.weight encoding : bitwidth 8, min -0.783310711384, max 0.505361795425, scale 0.005053617526, offset -155.000000000000"
,,,"model.5.conv.weight (data type: uFxp_8; tensor dimension: [3, 3, 128, 256]; tensor type: STATIC)",,,,"model.5.conv.bias encoding : bitwidth 8, min -3.494085311890, max 1.322086334229, scale 0.018886948004, offset -185.000000000000"
,,,model.5.conv.bias (data type: uFxp_8; tensor dimension: [256]; tensor type: STATIC),,,,"/model.5/conv/Conv_output_0 encoding : bitwidth 8, min -11.578801155090, max 9.662884712219, scale 0.083300732076, offset -139.000000000000"
,,,,,,,bias_op_name: model.5.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[1, 1], [1, 1]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [2, 2]"
,,,,,,,param count: 295k (4.08%)
,,,,,,,MACs per inference: 471M (5.74%)
51,/model.5/act/Sigmoid,Neuron,"/model.5/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)","/model.5/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)",1x40x40x256,A D G C,"/model.5/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999934315681, scale 0.003921310883, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
52,/model.5/act/Mul,Eltwise_Binary,"/model.5/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)","/model.5/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)",1x40x40x256,A D G C,"/model.5/act/Mul_output_0 encoding : bitwidth 8, min -0.272005200386, max 9.636755943298, scale 0.038857888430, offset -7.000000000000"
,,,"/model.5/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
53,/model.6/cv1/conv/Conv,Conv2d,"/model.5/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)","/model.6/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"model.6.cv1.conv.weight encoding : bitwidth 8, min -0.493675291538, max 0.705250442028, scale 0.004701669328, offset -105.000000000000"
,,,"model.6.cv1.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 256, 128]; tensor type: STATIC)",,,,"model.6.cv1.conv.bias encoding : bitwidth 8, min -1.553875684738, max 0.776937842369, scale 0.009140444919, offset -170.000000000000"
,,,model.6.cv1.conv.bias (data type: uFxp_8; tensor dimension: [128]; tensor type: STATIC),,,,"/model.6/cv1/conv/Conv_output_0 encoding : bitwidth 8, min -7.697322368622, max 4.198539257050, scale 0.046650439501, offset -165.000000000000"
,,,,,,,bias_op_name: model.6.cv1.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 32k (0.455%)
,,,,,,,MACs per inference: 52M (0.638%)
54,/model.6/cv1/act/Sigmoid,Neuron,"/model.6/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.6/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.6/cv1/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.985425829887, scale 0.003864414990, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
55,/model.6/cv1/act/Mul,Eltwise_Binary,"/model.6/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.6/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.6/cv1/act/Mul_output_0 encoding : bitwidth 8, min -0.278016000986, max 4.152863979340, scale 0.017376000062, offset -16.000000000000"
,,,"/model.6/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
56,/model.6/m/m.0/cv1/conv/Conv,Conv2d,"/model.6/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.6/m/m.0/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"model.6.m.0.cv1.conv.weight encoding : bitwidth 8, min -2.751099348068, max 3.244886159897, scale 0.023513669148, offset -117.000000000000"
,,,"model.6.m.0.cv1.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 128, 128]; tensor type: STATIC)",,,,"model.6.m.0.cv1.conv.bias encoding : bitwidth 8, min -4.255024909973, max 3.964909791946, scale 0.032235037535, offset -132.000000000000"
,,,model.6.m.0.cv1.conv.bias (data type: uFxp_8; tensor dimension: [128]; tensor type: STATIC),,,,"/model.6/m/m.0/cv1/conv/Conv_output_0 encoding : bitwidth 8, min -8.896930694580, max 14.984305381775, scale 0.093651905656, offset -95.000000000000"
,,,,,,,bias_op_name: model.6.m.0.cv1.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 16k (0.229%)
,,,,,,,MACs per inference: 26M (0.319%)
57,/model.6/m/m.0/cv1/act/Sigmoid,Neuron,"/model.6/m/m.0/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.6/m/m.0/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.6/m/m.0/cv1/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999999642372, scale 0.003921566997, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
58,/model.6/m/m.0/cv1/act/Mul,Eltwise_Binary,"/model.6/m/m.0/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.6/m/m.0/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.6/m/m.0/cv1/act/Mul_output_0 encoding : bitwidth 8, min -0.299638718367, max 14.981935501099, scale 0.059927742928, offset -5.000000000000"
,,,"/model.6/m/m.0/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
59,/model.6/m/m.0/cv2/conv/Conv,Conv2d,"/model.6/m/m.0/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.6/m/m.0/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"model.6.m.0.cv2.conv.weight encoding : bitwidth 8, min -0.515836954117, max 0.240130990744, scale 0.002964580199, offset -174.000000000000"
,,,"model.6.m.0.cv2.conv.weight (data type: uFxp_8; tensor dimension: [3, 3, 128, 128]; tensor type: STATIC)",,,,"model.6.m.0.cv2.conv.bias encoding : bitwidth 8, min -1.657193779945, max 1.104795932770, scale 0.010831331834, offset -153.000000000000"
,,,model.6.m.0.cv2.conv.bias (data type: uFxp_8; tensor dimension: [128]; tensor type: STATIC),,,,"/model.6/m/m.0/cv2/conv/Conv_output_0 encoding : bitwidth 8, min -6.511816978455, max 5.608717918396, scale 0.047531507909, offset -137.000000000000"
,,,,,,,bias_op_name: model.6.m.0.cv2.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[1, 1], [1, 1]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 147k (2.04%)
,,,,,,,MACs per inference: 235M (2.87%)
60,/model.6/m/m.0/cv2/act/Sigmoid,Neuron,"/model.6/m/m.0/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.6/m/m.0/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.6/m/m.0/cv2/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.996263563633, scale 0.003906915896, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
61,/model.6/m/m.0/cv2/act/Mul,Eltwise_Binary,"/model.6/m/m.0/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.6/m/m.0/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.6/m/m.0/cv2/act/Mul_output_0 encoding : bitwidth 8, min -0.274987041950, max 5.568487644196, scale 0.022915586829, offset -12.000000000000"
,,,"/model.6/m/m.0/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
62,/model.6/m/m.0/Add,Eltwise_Binary,"/model.6/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.6/m/m.0/Add_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.6/m/m.0/Add_output_0 encoding : bitwidth 8, min -0.565468609333, max 8.446687698364, scale 0.035341788083, offset -16.000000000000"
,,,"/model.6/m/m.0/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseAdd
,,,,,,,packageName: qti.aisw
63,/model.6/m/m.1/cv1/conv/Conv,Conv2d,"/model.6/m/m.0/Add_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.6/m/m.1/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"model.6.m.1.cv1.conv.weight encoding : bitwidth 8, min -2.055269718170, max 1.770232319832, scale 0.015001968481, offset -137.000000000000"
,,,"model.6.m.1.cv1.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 128, 128]; tensor type: STATIC)",,,,"model.6.m.1.cv1.conv.bias encoding : bitwidth 8, min -3.761196374893, max 1.947762370110, scale 0.022388072684, offset -168.000000000000"
,,,model.6.m.1.cv1.conv.bias (data type: uFxp_8; tensor dimension: [128]; tensor type: STATIC),,,,"/model.6/m/m.1/cv1/conv/Conv_output_0 encoding : bitwidth 8, min -10.461092948914, max 14.944418907166, scale 0.099629461765, offset -105.000000000000"
,,,,,,,bias_op_name: model.6.m.1.cv1.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 16k (0.229%)
,,,,,,,MACs per inference: 26M (0.319%)
64,/model.6/m/m.1/cv1/act/Sigmoid,Neuron,"/model.6/m/m.1/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.6/m/m.1/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.6/m/m.1/cv1/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999999642372, scale 0.003921566997, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
65,/model.6/m/m.1/cv1/act/Mul,Eltwise_Binary,"/model.6/m/m.1/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.6/m/m.1/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.6/m/m.1/cv1/act/Mul_output_0 encoding : bitwidth 8, min -0.297961235046, max 14.898060798645, scale 0.059592243284, offset -5.000000000000"
,,,"/model.6/m/m.1/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
66,/model.6/m/m.1/cv2/conv/Conv,Conv2d,"/model.6/m/m.1/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.6/m/m.1/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"model.6.m.1.cv2.conv.weight encoding : bitwidth 8, min -0.645956516266, max 0.539071679115, scale 0.004647169262, offset -139.000000000000"
,,,"model.6.m.1.cv2.conv.weight (data type: uFxp_8; tensor dimension: [3, 3, 128, 128]; tensor type: STATIC)",,,,"model.6.m.1.cv2.conv.bias encoding : bitwidth 8, min -1.319130182266, max 1.711304068565, scale 0.011884056032, offset -111.000000000000"
,,,model.6.m.1.cv2.conv.bias (data type: uFxp_8; tensor dimension: [128]; tensor type: STATIC),,,,"/model.6/m/m.1/cv2/conv/Conv_output_0 encoding : bitwidth 8, min -8.371196746826, max 7.559065818787, scale 0.062471620739, offset -134.000000000000"
,,,,,,,bias_op_name: model.6.m.1.cv2.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[1, 1], [1, 1]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 147k (2.04%)
,,,,,,,MACs per inference: 235M (2.87%)
67,/model.6/m/m.1/cv2/act/Sigmoid,Neuron,"/model.6/m/m.1/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.6/m/m.1/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.6/m/m.1/cv2/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999474942684, scale 0.003919509705, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
68,/model.6/m/m.1/cv2/act/Mul,Eltwise_Binary,"/model.6/m/m.1/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.6/m/m.1/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.6/m/m.1/cv2/act/Mul_output_0 encoding : bitwidth 8, min -0.276207715273, max 7.549677371979, scale 0.030689746141, offset -9.000000000000"
,,,"/model.6/m/m.1/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
69,/model.6/m/m.1/Add,Eltwise_Binary,"/model.6/m/m.0/Add_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.6/m/m.1/Add_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.6/m/m.1/Add_output_0 encoding : bitwidth 8, min -0.824027717113, max 12.308914184570, scale 0.051501732320, offset -16.000000000000"
,,,"/model.6/m/m.1/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseAdd
,,,,,,,packageName: qti.aisw
70,/model.6/m/m.2/cv1/conv/Conv,Conv2d,"/model.6/m/m.1/Add_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.6/m/m.2/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"model.6.m.2.cv1.conv.weight encoding : bitwidth 8, min -1.093924880028, max 0.927458047867, scale 0.007926992141, offset -138.000000000000"
,,,"model.6.m.2.cv1.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 128, 128]; tensor type: STATIC)",,,,"model.6.m.2.cv1.conv.bias encoding : bitwidth 8, min -2.395335435867, max 2.570604085922, scale 0.019474273548, offset -123.000000000000"
,,,model.6.m.2.cv1.conv.bias (data type: uFxp_8; tensor dimension: [128]; tensor type: STATIC),,,,"/model.6/m/m.2/cv1/conv/Conv_output_0 encoding : bitwidth 8, min -11.003333091736, max 9.627917289734, scale 0.080906860530, offset -136.000000000000"
,,,,,,,bias_op_name: model.6.m.2.cv1.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 16k (0.229%)
,,,,,,,MACs per inference: 26M (0.319%)
71,/model.6/m/m.2/cv1/act/Sigmoid,Neuron,"/model.6/m/m.2/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.6/m/m.2/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.6/m/m.2/cv1/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999931812286, scale 0.003921301104, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
72,/model.6/m/m.2/cv1/act/Mul,Eltwise_Binary,"/model.6/m/m.2/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.6/m/m.2/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.6/m/m.2/cv1/act/Mul_output_0 encoding : bitwidth 8, min -0.270947933197, max 9.599298477173, scale 0.038706846535, offset -7.000000000000"
,,,"/model.6/m/m.2/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
73,/model.6/m/m.2/cv2/conv/Conv,Conv2d,"/model.6/m/m.2/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.6/m/m.2/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"model.6.m.2.cv2.conv.weight encoding : bitwidth 8, min -1.265535950661, max 1.072954297066, scale 0.009170549922, offset -138.000000000000"
,,,"model.6.m.2.cv2.conv.weight (data type: uFxp_8; tensor dimension: [3, 3, 128, 128]; tensor type: STATIC)",,,,"model.6.m.2.cv2.conv.bias encoding : bitwidth 8, min -2.845954895020, max 3.201699495316, scale 0.023716291413, offset -120.000000000000"
,,,model.6.m.2.cv2.conv.bias (data type: uFxp_8; tensor dimension: [128]; tensor type: STATIC),,,,"/model.6/m/m.2/cv2/conv/Conv_output_0 encoding : bitwidth 8, min -17.124294281006, max 12.784575462341, scale 0.117289684713, offset -146.000000000000"
,,,,,,,bias_op_name: model.6.m.2.cv2.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[1, 1], [1, 1]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 147k (2.04%)
,,,,,,,MACs per inference: 235M (2.87%)
74,/model.6/m/m.2/cv2/act/Sigmoid,Neuron,"/model.6/m/m.2/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.6/m/m.2/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.6/m/m.2/cv2/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999997258186, scale 0.003921557683, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
75,/model.6/m/m.2/cv2/act/Mul,Eltwise_Binary,"/model.6/m/m.2/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.6/m/m.2/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.6/m/m.2/cv2/act/Mul_output_0 encoding : bitwidth 8, min -0.256245702505, max 12.812285423279, scale 0.051249142736, offset -5.000000000000"
,,,"/model.6/m/m.2/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
76,/model.6/m/m.2/Add,Eltwise_Binary,"/model.6/m/m.1/Add_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.6/m/m.2/Add_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.6/m/m.2/Add_output_0 encoding : bitwidth 8, min -1.108739852905, max 12.354529380798, scale 0.052797134966, offset -21.000000000000"
,,,"/model.6/m/m.2/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseAdd
,,,,,,,packageName: qti.aisw
77,/model.6/cv2/conv/Conv,Conv2d,"/model.5/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)","/model.6/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"model.6.cv2.conv.weight encoding : bitwidth 8, min -1.415374517441, max 0.854565739632, scale 0.008901726454, offset -159.000000000000"
,,,"model.6.cv2.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 256, 128]; tensor type: STATIC)",,,,"model.6.cv2.conv.bias encoding : bitwidth 8, min -1.796695113182, max 1.197796702385, scale 0.011743105017, offset -153.000000000000"
,,,model.6.cv2.conv.bias (data type: uFxp_8; tensor dimension: [128]; tensor type: STATIC),,,,"/model.6/cv2/conv/Conv_output_0 encoding : bitwidth 8, min -14.010455131531, max 11.692178726196, scale 0.100794643164, offset -139.000000000000"
,,,,,,,bias_op_name: model.6.cv2.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 32k (0.455%)
,,,,,,,MACs per inference: 52M (0.638%)
78,/model.6/cv2/act/Sigmoid,Neuron,"/model.6/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.6/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.6/cv2/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999991416931, scale 0.003921534866, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
79,/model.6/cv2/act/Mul,Eltwise_Binary,"/model.6/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.6/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.6/cv2/act/Mul_output_0 encoding : bitwidth 8, min -0.281164944172, max 11.668344497681, scale 0.046860821545, offset -6.000000000000"
,,,"/model.6/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
80,/model.6/Concat,Concat,"/model.6/m/m.2/Add_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.6/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)",1x40x40x256,A D G C,"/model.6/Concat_output_0 encoding : bitwidth 8, min -1.108739852905, max 12.354529380798, scale 0.052797134966, offset -21.000000000000"
,,,"/model.6/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",,,,axis: 3
,,,,,,,packageName: qti.aisw
81,/model.6/cv3/conv/Conv,Conv2d,"/model.6/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)","/model.6/cv3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)",1x40x40x256,A D G C,"model.6.cv3.conv.weight encoding : bitwidth 8, min -0.495371192694, max 0.652989268303, scale 0.004503374454, offset -110.000000000000"
,,,"model.6.cv3.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 256, 256]; tensor type: STATIC)",,,,"model.6.cv3.conv.bias encoding : bitwidth 8, min -1.792519807816, max 1.195013284683, scale 0.011715816334, offset -153.000000000000"
,,,model.6.cv3.conv.bias (data type: uFxp_8; tensor dimension: [256]; tensor type: STATIC),,,,"/model.6/cv3/conv/Conv_output_0 encoding : bitwidth 8, min -9.899106025696, max 9.224166870117, scale 0.074993230402, offset -132.000000000000"
,,,,,,,bias_op_name: model.6.cv3.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 65k (0.911%)
,,,,,,,MACs per inference: 104M (1.28%)
82,/model.6/cv3/act/Sigmoid,Neuron,"/model.6/cv3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)","/model.6/cv3/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)",1x40x40x256,A D G C,"/model.6/cv3/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999900698662, scale 0.003921179101, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
83,/model.6/cv3/act/Mul,Eltwise_Binary,"/model.6/cv3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)","/model.6/cv3/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)",1x40x40x256,A D G C,"/model.6/cv3/act/Mul_output_0 encoding : bitwidth 8, min -0.260651916265, max 9.234524726868, scale 0.037235986441, offset -7.000000000000"
,,,"/model.6/cv3/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
84,/model.7/conv/Conv,Conv2d,"/model.6/cv3/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)","/model.7/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)",1x20x20x512,A D G C,"model.7.conv.weight encoding : bitwidth 8, min -0.260625928640, max 0.417533397675, scale 0.002659448422, offset -98.000000000000"
,,,"model.7.conv.weight (data type: uFxp_8; tensor dimension: [3, 3, 256, 512]; tensor type: STATIC)",,,,"model.7.conv.bias encoding : bitwidth 8, min -2.772828817368, max 1.155345320702, scale 0.015404604375, offset -180.000000000000"
,,,model.7.conv.bias (data type: uFxp_8; tensor dimension: [512]; tensor type: STATIC),,,,"/model.7/conv/Conv_output_0 encoding : bitwidth 8, min -10.148357391357, max 8.879812240601, scale 0.074620276690, offset -136.000000000000"
,,,,,,,bias_op_name: model.7.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[1, 1], [1, 1]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [2, 2]"
,,,,,,,param count: 1M (16.3%)
,,,,,,,MACs per inference: 471M (5.74%)
85,/model.7/act/Sigmoid,Neuron,"/model.7/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)","/model.7/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)",1x20x20x512,A D G C,"/model.7/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999861955643, scale 0.003921027295, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
86,/model.7/act/Mul,Eltwise_Binary,"/model.7/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)","/model.7/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)",1x20x20x512,A D G C,"/model.7/act/Mul_output_0 encoding : bitwidth 8, min -0.287544369698, max 8.877932548523, scale 0.035943046212, offset -8.000000000000"
,,,"/model.7/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
87,/model.8/cv1/conv/Conv,Conv2d,"/model.7/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)","/model.8/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"model.8.cv1.conv.weight encoding : bitwidth 8, min -0.473426491022, max 0.532604813576, scale 0.003945220727, offset -120.000000000000"
,,,"model.8.cv1.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 512, 256]; tensor type: STATIC)",,,,"model.8.cv1.conv.bias encoding : bitwidth 8, min -2.308641195297, max 0.175339832902, scale 0.009741102345, offset -237.000000000000"
,,,model.8.cv1.conv.bias (data type: uFxp_8; tensor dimension: [256]; tensor type: STATIC),,,,"/model.8/cv1/conv/Conv_output_0 encoding : bitwidth 8, min -8.896193504333, max 8.289635658264, scale 0.067395411432, offset -132.000000000000"
,,,,,,,bias_op_name: model.8.cv1.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 131k (1.82%)
,,,,,,,MACs per inference: 52M (0.638%)
88,/model.8/cv1/act/Sigmoid,Neuron,"/model.8/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.8/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"/model.8/cv1/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999754250050, scale 0.003920604941, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
89,/model.8/cv1/act/Mul,Eltwise_Binary,"/model.8/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.8/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"/model.8/cv1/act/Mul_output_0 encoding : bitwidth 8, min -0.269402176142, max 8.317792892456, scale 0.033675272018, offset -8.000000000000"
,,,"/model.8/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
90,/model.8/m/m.0/cv1/conv/Conv,Conv2d,"/model.8/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.8/m/m.0/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"model.8.m.0.cv1.conv.weight encoding : bitwidth 8, min -3.390120267868, max 2.490700721741, scale 0.023062042892, offset -147.000000000000"
,,,"model.8.m.0.cv1.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 256, 256]; tensor type: STATIC)",,,,"model.8.m.0.cv1.conv.bias encoding : bitwidth 8, min -6.821268081665, max 3.532442331314, scale 0.040602784604, offset -168.000000000000"
,,,model.8.m.0.cv1.conv.bias (data type: uFxp_8; tensor dimension: [256]; tensor type: STATIC),,,,"/model.8/m/m.0/cv1/conv/Conv_output_0 encoding : bitwidth 8, min -14.056965827942, max 16.065103530884, scale 0.118125766516, offset -119.000000000000"
,,,,,,,bias_op_name: model.8.m.0.cv1.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 65k (0.911%)
,,,,,,,MACs per inference: 26M (0.319%)
91,/model.8/m/m.0/cv1/act/Sigmoid,Neuron,"/model.8/m/m.0/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.8/m/m.0/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"/model.8/m/m.0/cv1/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999999880791, scale 0.003921567928, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
92,/model.8/m/m.0/cv1/act/Mul,Eltwise_Binary,"/model.8/m/m.0/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.8/m/m.0/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"/model.8/m/m.0/cv1/act/Mul_output_0 encoding : bitwidth 8, min -0.255562931299, max 16.036573410034, scale 0.063890732825, offset -4.000000000000"
,,,"/model.8/m/m.0/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
93,/model.8/m/m.0/cv2/conv/Conv,Conv2d,"/model.8/m/m.0/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.8/m/m.0/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"model.8.m.0.cv2.conv.weight encoding : bitwidth 8, min -0.438855737448, max 0.456409960985, scale 0.003510845825, offset -125.000000000000"
,,,"model.8.m.0.cv2.conv.weight (data type: uFxp_8; tensor dimension: [3, 3, 256, 256]; tensor type: STATIC)",,,,"model.8.m.0.cv2.conv.bias encoding : bitwidth 8, min -2.217036247253, max 3.066555023193, scale 0.020719965920, offset -107.000000000000"
,,,model.8.m.0.cv2.conv.bias (data type: uFxp_8; tensor dimension: [256]; tensor type: STATIC),,,,"/model.8/m/m.0/cv2/conv/Conv_output_0 encoding : bitwidth 8, min -12.797893524170, max 15.580044746399, scale 0.111286029220, offset -115.000000000000"
,,,,,,,bias_op_name: model.8.m.0.cv2.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[1, 1], [1, 1]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 590k (8.17%)
,,,,,,,MACs per inference: 235M (2.87%)
94,/model.8/m/m.0/cv2/act/Sigmoid,Neuron,"/model.8/m/m.0/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.8/m/m.0/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"/model.8/m/m.0/cv2/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999999880791, scale 0.003921567928, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
95,/model.8/m/m.0/cv2/act/Mul,Eltwise_Binary,"/model.8/m/m.0/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.8/m/m.0/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"/model.8/m/m.0/cv2/act/Mul_output_0 encoding : bitwidth 8, min -0.248301342130, max 15.580908775330, scale 0.062075335532, offset -4.000000000000"
,,,"/model.8/m/m.0/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
96,/model.8/m/m.0/Add,Eltwise_Binary,"/model.8/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.8/m/m.0/Add_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"/model.8/m/m.0/Add_output_0 encoding : bitwidth 8, min -0.561771094799, max 15.355076789856, scale 0.062419012189, offset -9.000000000000"
,,,"/model.8/m/m.0/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseAdd
,,,,,,,packageName: qti.aisw
97,/model.8/cv2/conv/Conv,Conv2d,"/model.7/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)","/model.8/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"model.8.cv2.conv.weight encoding : bitwidth 8, min -0.543772697449, max 0.592801392078, scale 0.004457153380, offset -122.000000000000"
,,,"model.8.cv2.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 512, 256]; tensor type: STATIC)",,,,"model.8.cv2.conv.bias encoding : bitwidth 8, min -1.480291366577, max 0.000000000000, scale 0.005805063993, offset -255.000000000000"
,,,model.8.cv2.conv.bias (data type: uFxp_8; tensor dimension: [256]; tensor type: STATIC),,,,"/model.8/cv2/conv/Conv_output_0 encoding : bitwidth 8, min -11.263742446899, max 12.279325485229, scale 0.092325754464, offset -122.000000000000"
,,,,,,,bias_op_name: model.8.cv2.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 131k (1.82%)
,,,,,,,MACs per inference: 52M (0.638%)
98,/model.8/cv2/act/Sigmoid,Neuron,"/model.8/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.8/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"/model.8/cv2/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999995470047, scale 0.003921550699, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
99,/model.8/cv2/act/Mul,Eltwise_Binary,"/model.8/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.8/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"/model.8/cv2/act/Mul_output_0 encoding : bitwidth 8, min -0.296278685331, max 12.295565605164, scale 0.049379780889, offset -6.000000000000"
,,,"/model.8/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
100,/model.8/Concat,Concat,"/model.8/m/m.0/Add_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.8/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)",1x20x20x512,A D G C,"/model.8/Concat_output_0 encoding : bitwidth 8, min -0.561771094799, max 15.355076789856, scale 0.062419012189, offset -9.000000000000"
,,,"/model.8/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",,,,axis: 3
,,,,,,,packageName: qti.aisw
101,/model.8/cv3/conv/Conv,Conv2d,"/model.8/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)","/model.8/cv3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)",1x20x20x512,A D G C,"model.8.cv3.conv.weight encoding : bitwidth 8, min -0.564996063709, max 0.677021145821, scale 0.004870655946, offset -116.000000000000"
,,,"model.8.cv3.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 512, 512]; tensor type: STATIC)",,,,"model.8.cv3.conv.bias encoding : bitwidth 8, min -1.563238859177, max 0.568450510502, scale 0.008359566331, offset -187.000000000000"
,,,model.8.cv3.conv.bias (data type: uFxp_8; tensor dimension: [512]; tensor type: STATIC),,,,"/model.8/cv3/conv/Conv_output_0 encoding : bitwidth 8, min -11.965930938721, max 11.326530456543, scale 0.091342985630, offset -131.000000000000"
,,,,,,,bias_op_name: model.8.cv3.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 262k (3.63%)
,,,,,,,MACs per inference: 104M (1.28%)
102,/model.8/cv3/act/Sigmoid,Neuron,"/model.8/cv3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)","/model.8/cv3/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)",1x20x20x512,A D G C,"/model.8/cv3/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999987363815, scale 0.003921519034, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
103,/model.8/cv3/act/Mul,Eltwise_Binary,"/model.8/cv3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)","/model.8/cv3/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)",1x20x20x512,A D G C,"/model.8/cv3/act/Mul_output_0 encoding : bitwidth 8, min -0.272010624409, max 11.288440704346, scale 0.045335106552, offset -6.000000000000"
,,,"/model.8/cv3/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
104,/model.9/cv1/conv/Conv,Conv2d,"/model.8/cv3/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)","/model.9/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"model.9.cv1.conv.weight encoding : bitwidth 8, min -0.561515927315, max 0.548457443714, scale 0.004352836870, offset -129.000000000000"
,,,"model.9.cv1.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 512, 256]; tensor type: STATIC)",,,,"model.9.cv1.conv.bias encoding : bitwidth 8, min 0.000000000000, max 2.725049734116, scale 0.010686469264, offset 0.000000000000"
,,,model.9.cv1.conv.bias (data type: uFxp_8; tensor dimension: [256]; tensor type: STATIC),,,,"/model.9/cv1/conv/Conv_output_0 encoding : bitwidth 8, min -9.059063911438, max 8.574992179871, scale 0.069153159857, offset -131.000000000000"
,,,,,,,bias_op_name: model.9.cv1.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 131k (1.82%)
,,,,,,,MACs per inference: 52M (0.638%)
105,/model.9/cv1/act/Sigmoid,Neuron,"/model.9/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.9/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"/model.9/cv1/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999807894230, scale 0.003920815419, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
106,/model.9/cv1/act/Mul,Eltwise_Binary,"/model.9/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.9/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"/model.9/cv1/act/Mul_output_0 encoding : bitwidth 8, min -0.277153849602, max 8.557125091553, scale 0.034644231200, offset -8.000000000000"
,,,"/model.9/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
107,/model.9/m/MaxPool,Pool,"/model.9/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.9/m/MaxPool_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"/model.9/m/MaxPool_output_0 encoding : bitwidth 8, min -0.277153849602, max 8.557125091553, scale 0.034644231200, offset -8.000000000000"
,,,,,,,"filter_size: [5, 5]"
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[2, 2], [2, 2]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,pool_type: PoolMax2d
,,,,,,,"stride: [1, 1]"
108,/model.9/m_1/MaxPool,Pool,"/model.9/m/MaxPool_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.9/m_1/MaxPool_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"/model.9/m_1/MaxPool_output_0 encoding : bitwidth 8, min -0.277153849602, max 8.557125091553, scale 0.034644231200, offset -8.000000000000"
,,,,,,,"filter_size: [5, 5]"
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[2, 2], [2, 2]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,pool_type: PoolMax2d
,,,,,,,"stride: [1, 1]"
109,/model.9/m_2/MaxPool,Pool,"/model.9/m_1/MaxPool_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.9/m_2/MaxPool_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"/model.9/m_2/MaxPool_output_0 encoding : bitwidth 8, min -0.277153849602, max 8.557125091553, scale 0.034644231200, offset -8.000000000000"
,,,,,,,"filter_size: [5, 5]"
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[2, 2], [2, 2]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,pool_type: PoolMax2d
,,,,,,,"stride: [1, 1]"
110,/model.9/Concat,Concat,"/model.9/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.9/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 1024]; tensor type: NATIVE)",1x20x20x1024,A D G C,"/model.9/Concat_output_0 encoding : bitwidth 8, min -0.277153849602, max 8.557125091553, scale 0.034644231200, offset -8.000000000000"
,,,"/model.9/m/MaxPool_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",,,,axis: 3
,,,"/model.9/m_1/MaxPool_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",,,,packageName: qti.aisw
,,,"/model.9/m_2/MaxPool_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",,,,
111,/model.9/cv2/conv/Conv,Conv2d,"/model.9/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 1024]; tensor type: NATIVE)","/model.9/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)",1x20x20x512,A D G C,"model.9.cv2.conv.weight encoding : bitwidth 8, min -0.536085247993, max 0.575310945511, scale 0.004358416423, offset -123.000000000000"
,,,"model.9.cv2.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 1024, 512]; tensor type: STATIC)",,,,"model.9.cv2.conv.bias encoding : bitwidth 8, min -6.057131767273, max 4.820111751556, scale 0.042655855417, offset -142.000000000000"
,,,model.9.cv2.conv.bias (data type: uFxp_8; tensor dimension: [512]; tensor type: STATIC),,,,"/model.9/cv2/conv/Conv_output_0 encoding : bitwidth 8, min -9.022978782654, max 10.311975479126, scale 0.075823351741, offset -119.000000000000"
,,,,,,,bias_op_name: model.9.cv2.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 524k (7.26%)
,,,,,,,MACs per inference: 209M (2.55%)
112,/model.9/cv2/act/Sigmoid,Neuron,"/model.9/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)","/model.9/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)",1x20x20x512,A D G C,"/model.9/cv2/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999966859818, scale 0.003921438474, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
113,/model.9/cv2/act/Mul,Eltwise_Binary,"/model.9/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)","/model.9/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)",1x20x20x512,A D G C,"/model.9/cv2/act/Mul_output_0 encoding : bitwidth 8, min -0.290832757950, max 10.303789138794, scale 0.041547536850, offset -7.000000000000"
,,,"/model.9/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
114,/model.10/conv/Conv,Conv2d,"/model.9/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)","/model.10/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"model.10.conv.weight encoding : bitwidth 8, min -1.641803860664, max 1.391964077950, scale 0.011897129007, offset -138.000000000000"
,,,"model.10.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 512, 256]; tensor type: STATIC)",,,,"model.10.conv.bias encoding : bitwidth 8, min -4.102542400360, max 1.403501272202, scale 0.021592328325, offset -190.000000000000"
,,,model.10.conv.bias (data type: uFxp_8; tensor dimension: [256]; tensor type: STATIC),,,,"/model.10/conv/Conv_output_0 encoding : bitwidth 8, min -10.016740798950, max 9.631481170654, scale 0.077051848173, offset -130.000000000000"
,,,,,,,bias_op_name: model.10.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 131k (1.82%)
,,,,,,,MACs per inference: 52M (0.638%)
115,/model.10/act/Sigmoid,Neuron,"/model.10/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.10/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"/model.10/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999934434891, scale 0.003921311349, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
116,/model.10/act/Mul,Eltwise_Binary,"/model.10/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.10/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"/model.10/act/Mul_output_0 encoding : bitwidth 8, min -0.272066891193, max 9.638940811157, scale 0.038866698742, offset -7.000000000000"
,,,"/model.10/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
117,/model.11/Resize,Resize,"/model.10/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.11/Resize_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)",1x40x40x256,A D G C,"/model.11/Resize_output_0 encoding : bitwidth 8, min -0.272066891193, max 9.638940811157, scale 0.038866698742, offset -7.000000000000"
,,,,,,,align_corners: False
,,,,,,,half_pixel_centers: False
,,,,,,,interpolation_mode: 0
,,,,,,,packageName: qti.aisw
,,,,,,,scale_height: 2
,,,,,,,scale_width: 2
,,,,,,,transformation_mode: 3
118,/model.12/Concat,Concat,"/model.11/Resize_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)","/model.12/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 512]; tensor type: NATIVE)",1x40x40x512,A D G C,"/model.12/Concat_output_0 encoding : bitwidth 8, min -0.272066891193, max 9.638940811157, scale 0.038866698742, offset -7.000000000000"
,,,"/model.6/cv3/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)",,,,axis: 3
,,,,,,,packageName: qti.aisw
119,/model.13/cv1/conv/Conv,Conv2d,"/model.12/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 512]; tensor type: NATIVE)","/model.13/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"model.13.cv1.conv.weight encoding : bitwidth 8, min -0.919384360313, max 0.612922906876, scale 0.006009048317, offset -153.000000000000"
,,,"model.13.cv1.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 512, 128]; tensor type: STATIC)",,,,"model.13.cv1.conv.bias encoding : bitwidth 8, min -2.566460132599, max 1.601994276047, scale 0.016346879303, offset -157.000000000000"
,,,model.13.cv1.conv.bias (data type: uFxp_8; tensor dimension: [128]; tensor type: STATIC),,,,"/model.13/cv1/conv/Conv_output_0 encoding : bitwidth 8, min -8.336511611938, max 6.426061153412, scale 0.057892441750, offset -144.000000000000"
,,,,,,,bias_op_name: model.13.cv1.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 65k (0.909%)
,,,,,,,MACs per inference: 104M (1.28%)
120,/model.13/cv1/act/Sigmoid,Neuron,"/model.13/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.13/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.13/cv1/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.998347520828, scale 0.003915088251, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
121,/model.13/cv1/act/Mul,Eltwise_Binary,"/model.13/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.13/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.13/cv1/act/Mul_output_0 encoding : bitwidth 8, min -0.287799328566, max 6.383912563324, scale 0.026163576171, offset -11.000000000000"
,,,"/model.13/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
122,/model.13/m/m.0/cv1/conv/Conv,Conv2d,"/model.13/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.13/m/m.0/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"model.13.m.0.cv1.conv.weight encoding : bitwidth 8, min -1.729861855507, max 1.230640053749, scale 0.011609811336, offset -149.000000000000"
,,,"model.13.m.0.cv1.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 128, 128]; tensor type: STATIC)",,,,"model.13.m.0.cv1.conv.bias encoding : bitwidth 8, min -2.920843124390, max 3.037676811218, scale 0.023366745561, offset -125.000000000000"
,,,model.13.m.0.cv1.conv.bias (data type: uFxp_8; tensor dimension: [128]; tensor type: STATIC),,,,"/model.13/m/m.0/cv1/conv/Conv_output_0 encoding : bitwidth 8, min -9.514687538147, max 9.148738861084, scale 0.073189906776, offset -130.000000000000"
,,,,,,,bias_op_name: model.13.m.0.cv1.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 16k (0.229%)
,,,,,,,MACs per inference: 26M (0.319%)
123,/model.13/m/m.0/cv1/act/Sigmoid,Neuron,"/model.13/m/m.0/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.13/m/m.0/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.13/m/m.0/cv1/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999889850616, scale 0.003921136726, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
124,/model.13/m/m.0/cv1/act/Mul,Eltwise_Binary,"/model.13/m/m.0/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.13/m/m.0/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.13/m/m.0/cv1/act/Mul_output_0 encoding : bitwidth 8, min -0.294617235661, max 9.096307754517, scale 0.036827154458, offset -8.000000000000"
,,,"/model.13/m/m.0/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
125,/model.13/m/m.0/cv2/conv/Conv,Conv2d,"/model.13/m/m.0/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.13/m/m.0/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"model.13.m.0.cv2.conv.weight encoding : bitwidth 8, min -0.930533289909, max 0.590530693531, scale 0.005964956712, offset -156.000000000000"
,,,"model.13.m.0.cv2.conv.weight (data type: uFxp_8; tensor dimension: [3, 3, 128, 128]; tensor type: STATIC)",,,,"model.13.m.0.cv2.conv.bias encoding : bitwidth 8, min -2.707828283310, max 1.718429446220, scale 0.017357872799, offset -156.000000000000"
,,,model.13.m.0.cv2.conv.bias (data type: uFxp_8; tensor dimension: [128]; tensor type: STATIC),,,,"/model.13/m/m.0/cv2/conv/Conv_output_0 encoding : bitwidth 8, min -9.669938087463, max 8.595500946045, scale 0.071629174054, offset -135.000000000000"
,,,,,,,bias_op_name: model.13.m.0.cv2.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[1, 1], [1, 1]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 147k (2.04%)
,,,,,,,MACs per inference: 235M (2.87%)
126,/model.13/m/m.0/cv2/act/Sigmoid,Neuron,"/model.13/m/m.0/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.13/m/m.0/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.13/m/m.0/cv2/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999819695950, scale 0.003920861520, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
127,/model.13/m/m.0/cv2/act/Mul,Eltwise_Binary,"/model.13/m/m.0/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.13/m/m.0/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.13/m/m.0/cv2/act/Mul_output_0 encoding : bitwidth 8, min -0.279145300388, max 8.618611335754, scale 0.034893162549, offset -8.000000000000"
,,,"/model.13/m/m.0/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
128,/model.13/cv2/conv/Conv,Conv2d,"/model.12/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 512]; tensor type: NATIVE)","/model.13/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"model.13.cv2.conv.weight encoding : bitwidth 8, min -0.739760279655, max 0.446647703648, scale 0.004652580246, offset -159.000000000000"
,,,"model.13.cv2.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 512, 128]; tensor type: STATIC)",,,,"model.13.cv2.conv.bias encoding : bitwidth 8, min -1.692828416824, max 1.074294924736, scale 0.010851464234, offset -156.000000000000"
,,,model.13.cv2.conv.bias (data type: uFxp_8; tensor dimension: [128]; tensor type: STATIC),,,,"/model.13/cv2/conv/Conv_output_0 encoding : bitwidth 8, min -9.059016227722, max 7.441334724426, scale 0.064707256854, offset -140.000000000000"
,,,,,,,bias_op_name: model.13.cv2.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 65k (0.909%)
,,,,,,,MACs per inference: 104M (1.28%)
129,/model.13/cv2/act/Sigmoid,Neuron,"/model.13/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.13/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.13/cv2/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999421715736, scale 0.003919300623, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
130,/model.13/cv2/act/Mul,Eltwise_Binary,"/model.13/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.13/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.13/cv2/act/Mul_output_0 encoding : bitwidth 8, min -0.272789984941, max 7.456259727478, scale 0.030309999362, offset -9.000000000000"
,,,"/model.13/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
131,/model.13/Concat,Concat,"/model.13/m/m.0/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.13/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)",1x40x40x256,A D G C,"/model.13/Concat_output_0 encoding : bitwidth 8, min -0.279145300388, max 8.618611335754, scale 0.034893162549, offset -8.000000000000"
,,,"/model.13/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",,,,axis: 3
,,,,,,,packageName: qti.aisw
132,/model.13/cv3/conv/Conv,Conv2d,"/model.13/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)","/model.13/cv3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)",1x40x40x256,A D G C,"model.13.cv3.conv.weight encoding : bitwidth 8, min -1.190755844116, max 1.238386154175, scale 0.009526046924, offset -125.000000000000"
,,,"model.13.cv3.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 256, 256]; tensor type: STATIC)",,,,"model.13.cv3.conv.bias encoding : bitwidth 8, min -2.107271432877, max 1.843862533569, scale 0.015494642779, offset -136.000000000000"
,,,model.13.cv3.conv.bias (data type: uFxp_8; tensor dimension: [256]; tensor type: STATIC),,,,"/model.13/cv3/conv/Conv_output_0 encoding : bitwidth 8, min -11.302448272705, max 10.867738723755, scale 0.086941912770, offset -130.000000000000"
,,,,,,,bias_op_name: model.13.cv3.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 65k (0.911%)
,,,,,,,MACs per inference: 104M (1.28%)
133,/model.13/cv3/act/Sigmoid,Neuron,"/model.13/cv3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)","/model.13/cv3/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)",1x40x40x256,A D G C,"/model.13/cv3/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999980092049, scale 0.003921490628, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
134,/model.13/cv3/act/Mul,Eltwise_Binary,"/model.13/cv3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)","/model.13/cv3/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)",1x40x40x256,A D G C,"/model.13/cv3/act/Mul_output_0 encoding : bitwidth 8, min -0.261263161898, max 10.842421531677, scale 0.043543860316, offset -6.000000000000"
,,,"/model.13/cv3/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
135,/model.14/conv/Conv,Conv2d,"/model.13/cv3/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)","/model.14/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"model.14.conv.weight encoding : bitwidth 8, min -0.655613541603, max 0.640366733074, scale 0.005082275718, offset -129.000000000000"
,,,"model.14.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 256, 128]; tensor type: STATIC)",,,,"model.14.conv.bias encoding : bitwidth 8, min -1.311692237854, max 1.904476165771, scale 0.012612424791, offset -104.000000000000"
,,,model.14.conv.bias (data type: uFxp_8; tensor dimension: [128]; tensor type: STATIC),,,,"/model.14/conv/Conv_output_0 encoding : bitwidth 8, min -8.487384796143, max 8.160946846008, scale 0.065287575126, offset -130.000000000000"
,,,,,,,bias_op_name: model.14.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 32k (0.455%)
,,,,,,,MACs per inference: 52M (0.638%)
136,/model.14/act/Sigmoid,Neuron,"/model.14/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.14/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.14/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999711334705, scale 0.003920436837, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
137,/model.14/act/Mul,Eltwise_Binary,"/model.14/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.14/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.14/act/Mul_output_0 encoding : bitwidth 8, min -0.264346867800, max 8.161709785461, scale 0.033043358475, offset -8.000000000000"
,,,"/model.14/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
138,/model.15/Resize,Resize,"/model.14/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.15/Resize_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)",1x80x80x128,A D G C,"/model.15/Resize_output_0 encoding : bitwidth 8, min -0.264346867800, max 8.161709785461, scale 0.033043358475, offset -8.000000000000"
,,,,,,,align_corners: False
,,,,,,,half_pixel_centers: False
,,,,,,,interpolation_mode: 0
,,,,,,,packageName: qti.aisw
,,,,,,,scale_height: 2
,,,,,,,scale_width: 2
,,,,,,,transformation_mode: 3
139,/model.16/Concat,Concat,"/model.15/Resize_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)","/model.16/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 256]; tensor type: NATIVE)",1x80x80x256,A D G C,"/model.16/Concat_output_0 encoding : bitwidth 8, min -0.275364756584, max 8.501886367798, scale 0.034420594573, offset -8.000000000000"
,,,"/model.4/cv3/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)",,,,axis: 3
,,,,,,,packageName: qti.aisw
140,/model.17/cv1/conv/Conv,Conv2d,"/model.16/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 256]; tensor type: NATIVE)","/model.17/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"model.17.cv1.conv.weight encoding : bitwidth 8, min -0.694504261017, max 0.769120454788, scale 0.005739704706, offset -121.000000000000"
,,,"model.17.cv1.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 256, 64]; tensor type: STATIC)",,,,"model.17.cv1.conv.bias encoding : bitwidth 8, min -1.668810963631, max 1.555028319359, scale 0.012642507441, offset -132.000000000000"
,,,model.17.cv1.conv.bias (data type: uFxp_8; tensor dimension: [64]; tensor type: STATIC),,,,"/model.17/cv1/conv/Conv_output_0 encoding : bitwidth 8, min -7.591745376587, max 3.534088373184, scale 0.043630722910, offset -174.000000000000"
,,,,,,,bias_op_name: model.17.cv1.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 16k (0.228%)
,,,,,,,MACs per inference: 104M (1.28%)
141,/model.17/cv1/act/Sigmoid,Neuron,"/model.17/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.17/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"/model.17/cv1/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.971900105476, scale 0.003811372910, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
142,/model.17/cv1/act/Mul,Eltwise_Binary,"/model.17/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.17/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"/model.17/cv1/act/Mul_output_0 encoding : bitwidth 8, min -0.277354001999, max 3.445028781891, scale 0.014597579837, offset -19.000000000000"
,,,"/model.17/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
143,/model.17/m/m.0/cv1/conv/Conv,Conv2d,"/model.17/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.17/m/m.0/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"model.17.m.0.cv1.conv.weight encoding : bitwidth 8, min -2.548283815384, max 1.487817883492, scale 0.015827849507, offset -161.000000000000"
,,,"model.17.m.0.cv1.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 64, 64]; tensor type: STATIC)",,,,"model.17.m.0.cv1.conv.bias encoding : bitwidth 8, min -3.135540008545, max 2.340916872025, scale 0.021476302296, offset -146.000000000000"
,,,model.17.m.0.cv1.conv.bias (data type: uFxp_8; tensor dimension: [64]; tensor type: STATIC),,,,"/model.17/m/m.0/cv1/conv/Conv_output_0 encoding : bitwidth 8, min -7.187534332275, max 6.093779087067, scale 0.052083581686, offset -138.000000000000"
,,,,,,,bias_op_name: model.17.m.0.cv1.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 4k (0.0576%)
,,,,,,,MACs per inference: 26M (0.319%)
144,/model.17/m/m.0/cv1/act/Sigmoid,Neuron,"/model.17/m/m.0/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.17/m/m.0/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"/model.17/m/m.0/cv1/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.997767806053, scale 0.003912814893, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
145,/model.17/m/m.0/cv1/act/Mul,Eltwise_Binary,"/model.17/m/m.0/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.17/m/m.0/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"/model.17/m/m.0/cv1/act/Mul_output_0 encoding : bitwidth 8, min -0.274670541286, max 6.092692375183, scale 0.024970050901, offset -11.000000000000"
,,,"/model.17/m/m.0/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
146,/model.17/m/m.0/cv2/conv/Conv,Conv2d,"/model.17/m/m.0/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.17/m/m.0/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"model.17.m.0.cv2.conv.weight encoding : bitwidth 8, min -1.583908319473, max 1.301067590714, scale 0.011313631199, offset -140.000000000000"
,,,"model.17.m.0.cv2.conv.weight (data type: uFxp_8; tensor dimension: [3, 3, 64, 64]; tensor type: STATIC)",,,,"model.17.m.0.cv2.conv.bias encoding : bitwidth 8, min -3.522543191910, max 3.131149530411, scale 0.026092913002, offset -135.000000000000"
,,,model.17.m.0.cv2.conv.bias (data type: uFxp_8; tensor dimension: [64]; tensor type: STATIC),,,,"/model.17/m/m.0/cv2/conv/Conv_output_0 encoding : bitwidth 8, min -28.754776000977, max 19.169849395752, scale 0.187939703465, offset -153.000000000000"
,,,,,,,bias_op_name: model.17.m.0.cv2.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[1, 1], [1, 1]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 36k (0.511%)
,,,,,,,MACs per inference: 235M (2.87%)
147,/model.17/m/m.0/cv2/act/Sigmoid,Neuron,"/model.17/m/m.0/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.17/m/m.0/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"/model.17/m/m.0/cv2/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 1.000000000000, scale 0.003921568859, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
148,/model.17/m/m.0/cv2/act/Mul,Eltwise_Binary,"/model.17/m/m.0/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.17/m/m.0/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"/model.17/m/m.0/cv2/act/Mul_output_0 encoding : bitwidth 8, min -0.304205387831, max 19.088888168335, scale 0.076051346958, offset -4.000000000000"
,,,"/model.17/m/m.0/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
149,/model.17/cv2/conv/Conv,Conv2d,"/model.16/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 256]; tensor type: NATIVE)","/model.17/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"model.17.cv2.conv.weight encoding : bitwidth 8, min -1.464563965797, max 1.386304736137, scale 0.011179877445, offset -131.000000000000"
,,,"model.17.cv2.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 256, 64]; tensor type: STATIC)",,,,"model.17.cv2.conv.bias encoding : bitwidth 8, min -2.078991174698, max 1.937241792679, scale 0.015749933198, offset -132.000000000000"
,,,model.17.cv2.conv.bias (data type: uFxp_8; tensor dimension: [64]; tensor type: STATIC),,,,"/model.17/cv2/conv/Conv_output_0 encoding : bitwidth 8, min -12.551083564758, max 7.834434509277, scale 0.079943209887, offset -157.000000000000"
,,,,,,,bias_op_name: model.17.cv2.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 16k (0.228%)
,,,,,,,MACs per inference: 104M (1.28%)
150,/model.17/cv2/act/Sigmoid,Neuron,"/model.17/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.17/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"/model.17/cv2/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999592721462, scale 0.003919971641, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
151,/model.17/cv2/act/Mul,Eltwise_Binary,"/model.17/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.17/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",1x80x80x64,A D G C,"/model.17/cv2/act/Mul_output_0 encoding : bitwidth 8, min -0.285204678774, max 7.795594215393, scale 0.031689409167, offset -9.000000000000"
,,,"/model.17/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
152,/model.17/Concat,Concat,"/model.17/m/m.0/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)","/model.17/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)",1x80x80x128,A D G C,"/model.17/Concat_output_0 encoding : bitwidth 8, min -0.304205387831, max 19.088888168335, scale 0.076051346958, offset -4.000000000000"
,,,"/model.17/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 64]; tensor type: NATIVE)",,,,axis: 3
,,,,,,,packageName: qti.aisw
153,/model.17/cv3/conv/Conv,Conv2d,"/model.17/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)","/model.17/cv3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)",1x80x80x128,A D G C,"model.17.cv3.conv.weight encoding : bitwidth 8, min -3.034088134766, max 3.360064506531, scale 0.025075107813, offset -121.000000000000"
,,,"model.17.cv3.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 128, 128]; tensor type: STATIC)",,,,"model.17.cv3.conv.bias encoding : bitwidth 8, min -4.244307518005, max 23.506933212280, scale 0.108828395605, offset -39.000000000000"
,,,model.17.cv3.conv.bias (data type: uFxp_8; tensor dimension: [128]; tensor type: STATIC),,,,"/model.17/cv3/conv/Conv_output_0 encoding : bitwidth 8, min -31.562791824341, max 30.348838806152, scale 0.242790713906, offset -130.000000000000"
,,,,,,,bias_op_name: model.17.cv3.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 16k (0.229%)
,,,,,,,MACs per inference: 104M (1.28%)
154,/model.17/cv3/act/Sigmoid,Neuron,"/model.17/cv3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)","/model.17/cv3/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)",1x80x80x128,A D G C,"/model.17/cv3/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 1.000000000000, scale 0.003921568859, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
155,/model.17/cv3/act/Mul,Eltwise_Binary,"/model.17/cv3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)","/model.17/cv3/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)",1x80x80x128,A D G C,"/model.17/cv3/act/Mul_output_0 encoding : bitwidth 8, min -0.240747287869, max 30.454532623291, scale 0.120373643935, offset -2.000000000000"
,,,"/model.17/cv3/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
156,/model.18/conv/Conv,Conv2d,"/model.17/cv3/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)","/model.18/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"model.18.conv.weight encoding : bitwidth 8, min -0.216575950384, max 0.239844426513, scale 0.001789883827, offset -121.000000000000"
,,,"model.18.conv.weight (data type: uFxp_8; tensor dimension: [3, 3, 128, 128]; tensor type: STATIC)",,,,"model.18.conv.bias encoding : bitwidth 8, min -1.761729598045, max 1.890636563301, scale 0.014323004521, offset -123.000000000000"
,,,model.18.conv.bias (data type: uFxp_8; tensor dimension: [128]; tensor type: STATIC),,,,"/model.18/conv/Conv_output_0 encoding : bitwidth 8, min -10.283090591431, max 9.432609558105, scale 0.077316470444, offset -133.000000000000"
,,,,,,,bias_op_name: model.18.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[1, 1], [1, 1]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [2, 2]"
,,,,,,,param count: 147k (2.04%)
,,,,,,,MACs per inference: 235M (2.87%)
157,/model.18/act/Sigmoid,Neuron,"/model.18/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.18/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.18/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999918699265, scale 0.003921249881, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
158,/model.18/act/Mul,Eltwise_Binary,"/model.18/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.18/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.18/act/Mul_output_0 encoding : bitwidth 8, min -0.266148805618, max 9.429271697998, scale 0.038021255285, offset -7.000000000000"
,,,"/model.18/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
159,/model.19/Concat,Concat,"/model.18/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.19/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)",1x40x40x256,A D G C,"/model.19/Concat_output_0 encoding : bitwidth 8, min -0.266148805618, max 9.429271697998, scale 0.038021255285, offset -7.000000000000"
,,,"/model.14/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",,,,axis: 3
,,,,,,,packageName: qti.aisw
160,/model.20/cv1/conv/Conv,Conv2d,"/model.19/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)","/model.20/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"model.20.cv1.conv.weight encoding : bitwidth 8, min -1.073780179024, max 0.984971284866, scale 0.008073534817, offset -133.000000000000"
,,,"model.20.cv1.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 256, 128]; tensor type: STATIC)",,,,"model.20.cv1.conv.bias encoding : bitwidth 8, min -2.355036258698, max 1.934494137764, scale 0.016821688041, offset -140.000000000000"
,,,model.20.cv1.conv.bias (data type: uFxp_8; tensor dimension: [128]; tensor type: STATIC),,,,"/model.20/cv1/conv/Conv_output_0 encoding : bitwidth 8, min -10.538304328918, max 9.367381095886, scale 0.078061513603, offset -135.000000000000"
,,,,,,,bias_op_name: model.20.cv1.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 32k (0.455%)
,,,,,,,MACs per inference: 52M (0.638%)
161,/model.20/cv1/act/Sigmoid,Neuron,"/model.20/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.20/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.20/cv1/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999913215637, scale 0.003921228461, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
162,/model.20/cv1/act/Mul,Eltwise_Binary,"/model.20/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.20/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.20/cv1/act/Mul_output_0 encoding : bitwidth 8, min -0.264339983463, max 9.365188598633, scale 0.037762857974, offset -7.000000000000"
,,,"/model.20/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
163,/model.20/m/m.0/cv1/conv/Conv,Conv2d,"/model.20/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.20/m/m.0/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"model.20.m.0.cv1.conv.weight encoding : bitwidth 8, min -1.074177265167, max 0.814893126488, scale 0.007408119272, offset -145.000000000000"
,,,"model.20.m.0.cv1.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 128, 128]; tensor type: STATIC)",,,,"model.20.m.0.cv1.conv.bias encoding : bitwidth 8, min -1.550282835960, max 1.828538656235, scale 0.013250280172, offset -117.000000000000"
,,,model.20.m.0.cv1.conv.bias (data type: uFxp_8; tensor dimension: [128]; tensor type: STATIC),,,,"/model.20/m/m.0/cv1/conv/Conv_output_0 encoding : bitwidth 8, min -9.779955863953, max 8.291701316833, scale 0.070869244635, offset -138.000000000000"
,,,,,,,bias_op_name: model.20.m.0.cv1.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 16k (0.229%)
,,,,,,,MACs per inference: 26M (0.319%)
164,/model.20/m/m.0/cv1/act/Sigmoid,Neuron,"/model.20/m/m.0/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.20/m/m.0/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.20/m/m.0/cv1/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999742090702, scale 0.003920557443, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
165,/model.20/m/m.0/cv1/act/Mul,Eltwise_Binary,"/model.20/m/m.0/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.20/m/m.0/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.20/m/m.0/cv1/act/Mul_output_0 encoding : bitwidth 8, min -0.267896771431, max 8.271312713623, scale 0.033487096429, offset -8.000000000000"
,,,"/model.20/m/m.0/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
166,/model.20/m/m.0/cv2/conv/Conv,Conv2d,"/model.20/m/m.0/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.20/m/m.0/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"model.20.m.0.cv2.conv.weight encoding : bitwidth 8, min -1.163091063499, max 1.190783619881, scale 0.009230880998, offset -126.000000000000"
,,,"model.20.m.0.cv2.conv.weight (data type: uFxp_8; tensor dimension: [3, 3, 128, 128]; tensor type: STATIC)",,,,"model.20.m.0.cv2.conv.bias encoding : bitwidth 8, min -2.654482126236, max 2.286342382431, scale 0.019375782460, offset -137.000000000000"
,,,model.20.m.0.cv2.conv.bias (data type: uFxp_8; tensor dimension: [128]; tensor type: STATIC),,,,"/model.20/m/m.0/cv2/conv/Conv_output_0 encoding : bitwidth 8, min -20.948463439941, max 11.038711547852, scale 0.125439912081, offset -167.000000000000"
,,,,,,,bias_op_name: model.20.m.0.cv2.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[1, 1], [1, 1]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 147k (2.04%)
,,,,,,,MACs per inference: 235M (2.87%)
167,/model.20/m/m.0/cv2/act/Sigmoid,Neuron,"/model.20/m/m.0/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.20/m/m.0/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.20/m/m.0/cv2/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999983429909, scale 0.003921503667, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
168,/model.20/m/m.0/cv2/act/Mul,Eltwise_Binary,"/model.20/m/m.0/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.20/m/m.0/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.20/m/m.0/cv2/act/Mul_output_0 encoding : bitwidth 8, min -0.265586823225, max 11.021853446960, scale 0.044264473021, offset -6.000000000000"
,,,"/model.20/m/m.0/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
169,/model.20/cv2/conv/Conv,Conv2d,"/model.19/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)","/model.20/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"model.20.cv2.conv.weight encoding : bitwidth 8, min -1.762340426445, max 0.640851080418, scale 0.009424280375, offset -187.000000000000"
,,,"model.20.cv2.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 256, 128]; tensor type: STATIC)",,,,"model.20.cv2.conv.bias encoding : bitwidth 8, min -1.125674605370, max 1.744795680046, scale 0.011256746016, offset -100.000000000000"
,,,model.20.cv2.conv.bias (data type: uFxp_8; tensor dimension: [128]; tensor type: STATIC),,,,"/model.20/cv2/conv/Conv_output_0 encoding : bitwidth 8, min -9.777501106262, max 8.691112518311, scale 0.072425939143, offset -135.000000000000"
,,,,,,,bias_op_name: model.20.cv2.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 32k (0.455%)
,,,,,,,MACs per inference: 52M (0.638%)
170,/model.20/cv2/act/Sigmoid,Neuron,"/model.20/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.20/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.20/cv2/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999835014343, scale 0.003920921590, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
171,/model.20/cv2/act/Mul,Eltwise_Binary,"/model.20/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.20/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",1x40x40x128,A D G C,"/model.20/cv2/act/Mul_output_0 encoding : bitwidth 8, min -0.281923919916, max 8.704401016235, scale 0.035240489990, offset -8.000000000000"
,,,"/model.20/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
172,/model.20/Concat,Concat,"/model.20/m/m.0/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)","/model.20/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)",1x40x40x256,A D G C,"/model.20/Concat_output_0 encoding : bitwidth 8, min -0.281923919916, max 11.021853446960, scale 0.044328536838, offset -6.000000000000"
,,,"/model.20/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 128]; tensor type: NATIVE)",,,,axis: 3
,,,,,,,packageName: qti.aisw
173,/model.20/cv3/conv/Conv,Conv2d,"/model.20/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)","/model.20/cv3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)",1x40x40x256,A D G C,"model.20.cv3.conv.weight encoding : bitwidth 8, min -2.630712985992, max 2.490140438080, scale 0.020081778988, offset -131.000000000000"
,,,"model.20.cv3.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 256, 256]; tensor type: STATIC)",,,,"model.20.cv3.conv.bias encoding : bitwidth 8, min -3.289961338043, max 5.929161071777, scale 0.036153420806, offset -91.000000000000"
,,,model.20.cv3.conv.bias (data type: uFxp_8; tensor dimension: [256]; tensor type: STATIC),,,,"/model.20/cv3/conv/Conv_output_0 encoding : bitwidth 8, min -26.976886749268, max 36.134178161621, scale 0.247494369745, offset -109.000000000000"
,,,,,,,bias_op_name: model.20.cv3.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 65k (0.911%)
,,,,,,,MACs per inference: 104M (1.28%)
174,/model.20/cv3/act/Sigmoid,Neuron,"/model.20/cv3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)","/model.20/cv3/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)",1x40x40x256,A D G C,"/model.20/cv3/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 1.000000000000, scale 0.003921568859, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
175,/model.20/cv3/act/Mul,Eltwise_Binary,"/model.20/cv3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)","/model.20/cv3/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)",1x40x40x256,A D G C,"/model.20/cv3/act/Mul_output_0 encoding : bitwidth 8, min -0.285433709621, max 36.107364654541, scale 0.142716854811, offset -2.000000000000"
,,,"/model.20/cv3/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
176,/model.21/conv/Conv,Conv2d,"/model.20/cv3/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)","/model.21/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"model.21.conv.weight encoding : bitwidth 8, min -0.244086831808, max 0.316653192043, scale 0.002198980423, offset -111.000000000000"
,,,"model.21.conv.weight (data type: uFxp_8; tensor dimension: [3, 3, 256, 256]; tensor type: STATIC)",,,,"model.21.conv.bias encoding : bitwidth 8, min -1.796820759773, max 1.475959897041, scale 0.012834434398, offset -140.000000000000"
,,,model.21.conv.bias (data type: uFxp_8; tensor dimension: [256]; tensor type: STATIC),,,,"/model.21/conv/Conv_output_0 encoding : bitwidth 8, min -10.369099617004, max 11.850399017334, scale 0.087135285139, offset -119.000000000000"
,,,,,,,bias_op_name: model.21.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[1, 1], [1, 1]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [2, 2]"
,,,,,,,param count: 590k (8.17%)
,,,,,,,MACs per inference: 235M (2.87%)
177,/model.21/act/Sigmoid,Neuron,"/model.21/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.21/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"/model.21/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999992847443, scale 0.003921540454, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
178,/model.21/act/Mul,Eltwise_Binary,"/model.21/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.21/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"/model.21/act/Mul_output_0 encoding : bitwidth 8, min -0.285382300615, max 11.843365669250, scale 0.047563716769, offset -6.000000000000"
,,,"/model.21/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
179,/model.22/Concat,Concat,"/model.21/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.22/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)",1x20x20x512,A D G C,"/model.22/Concat_output_0 encoding : bitwidth 8, min -0.285382300615, max 11.843365669250, scale 0.047563716769, offset -6.000000000000"
,,,"/model.10/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",,,,axis: 3
,,,,,,,packageName: qti.aisw
180,/model.23/cv1/conv/Conv,Conv2d,"/model.22/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)","/model.23/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"model.23.cv1.conv.weight encoding : bitwidth 8, min -1.523377776146, max 1.066364526749, scale 0.010155851953, offset -150.000000000000"
,,,"model.23.cv1.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 512, 256]; tensor type: STATIC)",,,,"model.23.cv1.conv.bias encoding : bitwidth 8, min -1.085077881813, max 0.666155397892, scale 0.006867581513, offset -158.000000000000"
,,,model.23.cv1.conv.bias (data type: uFxp_8; tensor dimension: [256]; tensor type: STATIC),,,,"/model.23/cv1/conv/Conv_output_0 encoding : bitwidth 8, min -11.866764068604, max 10.885301589966, scale 0.089223787189, offset -133.000000000000"
,,,,,,,bias_op_name: model.23.cv1.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 131k (1.82%)
,,,,,,,MACs per inference: 52M (0.638%)
181,/model.23/cv1/act/Sigmoid,Neuron,"/model.23/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.23/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"/model.23/cv1/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999981760979, scale 0.003921497148, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
182,/model.23/cv1/act/Mul,Eltwise_Binary,"/model.23/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.23/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"/model.23/cv1/act/Mul_output_0 encoding : bitwidth 8, min -0.263338238001, max 10.928536415100, scale 0.043889705092, offset -6.000000000000"
,,,"/model.23/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
183,/model.23/m/m.0/cv1/conv/Conv,Conv2d,"/model.23/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.23/m/m.0/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"model.23.m.0.cv1.conv.weight encoding : bitwidth 8, min -1.685556530952, max 0.872877478600, scale 0.010033074766, offset -168.000000000000"
,,,"model.23.m.0.cv1.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 256, 256]; tensor type: STATIC)",,,,"model.23.m.0.cv1.conv.bias encoding : bitwidth 8, min -1.530789494514, max 0.893752872944, scale 0.009508009069, offset -161.000000000000"
,,,model.23.m.0.cv1.conv.bias (data type: uFxp_8; tensor dimension: [256]; tensor type: STATIC),,,,"/model.23/m/m.0/cv1/conv/Conv_output_0 encoding : bitwidth 8, min -15.418869018555, max 10.793209075928, scale 0.102792464197, offset -150.000000000000"
,,,,,,,bias_op_name: model.23.m.0.cv1.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 65k (0.911%)
,,,,,,,MACs per inference: 26M (0.319%)
184,/model.23/m/m.0/cv1/act/Sigmoid,Neuron,"/model.23/m/m.0/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.23/m/m.0/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"/model.23/m/m.0/cv1/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999979376793, scale 0.003921487834, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
185,/model.23/m/m.0/cv1/act/Mul,Eltwise_Binary,"/model.23/m/m.0/cv1/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.23/m/m.0/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"/model.23/m/m.0/cv1/act/Mul_output_0 encoding : bitwidth 8, min -0.260445982218, max 10.808507919312, scale 0.043407663703, offset -6.000000000000"
,,,"/model.23/m/m.0/cv1/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
186,/model.23/m/m.0/cv2/conv/Conv,Conv2d,"/model.23/m/m.0/cv1/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.23/m/m.0/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"model.23.m.0.cv2.conv.weight encoding : bitwidth 8, min -0.849559187889, max 0.743364274502, scale 0.006246758625, offset -136.000000000000"
,,,"model.23.m.0.cv2.conv.weight (data type: uFxp_8; tensor dimension: [3, 3, 256, 256]; tensor type: STATIC)",,,,"model.23.m.0.cv2.conv.bias encoding : bitwidth 8, min -1.472622156143, max 1.135146141052, scale 0.010226542130, offset -144.000000000000"
,,,model.23.m.0.cv2.conv.bias (data type: uFxp_8; tensor dimension: [256]; tensor type: STATIC),,,,"/model.23/m/m.0/cv2/conv/Conv_output_0 encoding : bitwidth 8, min -21.891305923462, max 14.834240913391, scale 0.144021749496, offset -152.000000000000"
,,,,,,,bias_op_name: model.23.m.0.cv2.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[1, 1], [1, 1]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 590k (8.17%)
,,,,,,,MACs per inference: 235M (2.87%)
187,/model.23/m/m.0/cv2/act/Sigmoid,Neuron,"/model.23/m/m.0/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.23/m/m.0/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"/model.23/m/m.0/cv2/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999999642372, scale 0.003921566997, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
188,/model.23/m/m.0/cv2/act/Mul,Eltwise_Binary,"/model.23/m/m.0/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.23/m/m.0/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"/model.23/m/m.0/cv2/act/Mul_output_0 encoding : bitwidth 8, min -0.295445173979, max 14.772258758545, scale 0.059089034796, offset -5.000000000000"
,,,"/model.23/m/m.0/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
189,/model.23/cv2/conv/Conv,Conv2d,"/model.22/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)","/model.23/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"model.23.cv2.conv.weight encoding : bitwidth 8, min -0.951136946678, max 0.634091317654, scale 0.006216581445, offset -153.000000000000"
,,,"model.23.cv2.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 512, 256]; tensor type: STATIC)",,,,"model.23.cv2.conv.bias encoding : bitwidth 8, min -0.701622962952, max 1.124028563499, scale 0.007159417961, offset -98.000000000000"
,,,model.23.cv2.conv.bias (data type: uFxp_8; tensor dimension: [256]; tensor type: STATIC),,,,"/model.23/cv2/conv/Conv_output_0 encoding : bitwidth 8, min -10.045610427856, max 9.214770317078, scale 0.075530901551, offset -133.000000000000"
,,,,,,,bias_op_name: model.23.cv2.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 131k (1.82%)
,,,,,,,MACs per inference: 52M (0.638%)
190,/model.23/cv2/act/Sigmoid,Neuron,"/model.23/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.23/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"/model.23/cv2/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 0.999902367592, scale 0.003921185620, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
191,/model.23/cv2/act/Mul,Eltwise_Binary,"/model.23/cv2/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.23/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",1x20x20x256,A D G C,"/model.23/cv2/act/Mul_output_0 encoding : bitwidth 8, min -0.261125952005, max 9.251319885254, scale 0.037303708494, offset -7.000000000000"
,,,"/model.23/cv2/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
192,/model.23/Concat,Concat,"/model.23/m/m.0/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)","/model.23/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)",1x20x20x512,A D G C,"/model.23/Concat_output_0 encoding : bitwidth 8, min -0.295445173979, max 14.772258758545, scale 0.059089034796, offset -5.000000000000"
,,,"/model.23/cv2/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 256]; tensor type: NATIVE)",,,,axis: 3
,,,,,,,packageName: qti.aisw
193,/model.23/cv3/conv/Conv,Conv2d,"/model.23/Concat_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)","/model.23/cv3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)",1x20x20x512,A D G C,"model.23.cv3.conv.weight encoding : bitwidth 8, min -1.523797392845, max 1.119524598122, scale 0.010365968570, offset -147.000000000000"
,,,"model.23.cv3.conv.weight (data type: uFxp_8; tensor dimension: [1, 1, 512, 512]; tensor type: STATIC)",,,,"model.23.cv3.conv.bias encoding : bitwidth 8, min -2.342321634293, max 3.400871038437, scale 0.022522324696, offset -104.000000000000"
,,,model.23.cv3.conv.bias (data type: uFxp_8; tensor dimension: [512]; tensor type: STATIC),,,,"/model.23/cv3/conv/Conv_output_0 encoding : bitwidth 8, min -35.740745544434, max 26.683158874512, scale 0.244799613953, offset -146.000000000000"
,,,,,,,bias_op_name: model.23.cv3.conv.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 262k (3.63%)
,,,,,,,MACs per inference: 104M (1.28%)
194,/model.23/cv3/act/Sigmoid,Neuron,"/model.23/cv3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)","/model.23/cv3/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)",1x20x20x512,A D G C,"/model.23/cv3/act/Sigmoid_output_0 encoding : bitwidth 8, min 0.000000000000, max 1.000000000000, scale 0.003921568859, offset 0.000000000000"
,,,,,,,neuron_type: Sigmoid
,,,,,,,packageName: qti.aisw
195,/model.23/cv3/act/Mul,Eltwise_Binary,"/model.23/cv3/conv/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)","/model.23/cv3/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)",1x20x20x512,A D G C,"/model.23/cv3/act/Mul_output_0 encoding : bitwidth 8, min -0.317239880562, max 26.648151397705, scale 0.105746626854, offset -3.000000000000"
,,,"/model.23/cv3/act/Sigmoid_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)",,,,eltwise_type: ElementWiseMultiply
,,,,,,,packageName: qti.aisw
196,/model.24/m.0/Conv,Conv2d,"/model.17/cv3/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 128]; tensor type: NATIVE)","/model.24/m.0/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 80, 80, 255]; tensor type: APP_READ)",1x80x80x255,A D G C,"model.24.m.0.weight encoding : bitwidth 8, min -0.530882358551, max 0.526734828949, scale 0.004147518426, offset -128.000000000000"
,,,"model.24.m.0.weight (data type: uFxp_8; tensor dimension: [1, 1, 128, 255]; tensor type: STATIC)",,,,"model.24.m.0.bias encoding : bitwidth 8, min -6.843443393707, max 0.947083711624, scale 0.030551087111, offset -224.000000000000"
,,,model.24.m.0.bias (data type: uFxp_8; tensor dimension: [255]; tensor type: STATIC),,,,"/model.24/m.0/Conv_output_0 encoding : bitwidth 8, min -21.809829711914, max 8.415749549866, scale 0.118531689048, offset -184.000000000000"
,,,,,,,bias_op_name: model.24.m.0.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 32k (0.455%)
,,,,,,,MACs per inference: 208M (2.54%)
197,/model.24/m.1/Conv,Conv2d,"/model.20/cv3/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 256]; tensor type: NATIVE)","/model.24/m.1/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 40, 40, 255]; tensor type: APP_READ)",1x40x40x255,A D G C,"model.24.m.1.weight encoding : bitwidth 8, min -0.545375704765, max 0.492466121912, scale 0.004069968127, offset -134.000000000000"
,,,"model.24.m.1.weight (data type: uFxp_8; tensor dimension: [1, 1, 256, 255]; tensor type: STATIC)",,,,"model.24.m.1.bias encoding : bitwidth 8, min -7.413815498352, max 0.770266532898, scale 0.032094437629, offset -231.000000000000"
,,,model.24.m.1.bias (data type: uFxp_8; tensor dimension: [255]; tensor type: STATIC),,,,"/model.24/m.1/Conv_output_0 encoding : bitwidth 8, min -17.698301315308, max 8.540459632874, scale 0.102897107601, offset -172.000000000000"
,,,,,,,bias_op_name: model.24.m.1.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 65k (0.907%)
,,,,,,,MACs per inference: 104M (1.27%)
198,/model.24/m.2/Conv,Conv2d,"/model.23/cv3/act/Mul_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 512]; tensor type: NATIVE)","/model.24/m.2/Conv_output_0 (data type: uFxp_8; tensor dimension: [1, 20, 20, 255]; tensor type: APP_READ)",1x20x20x255,A D G C,"model.24.m.2.weight encoding : bitwidth 8, min -0.374947339296, max 0.389945238829, scale 0.002999578835, offset -125.000000000000"
,,,"model.24.m.2.weight (data type: uFxp_8; tensor dimension: [1, 1, 512, 255]; tensor type: STATIC)",,,,"model.24.m.2.bias encoding : bitwidth 8, min -8.147713661194, max 0.298087090254, scale 0.033120788634, offset -246.000000000000"
,,,model.24.m.2.bias (data type: uFxp_8; tensor dimension: [255]; tensor type: STATIC),,,,"/model.24/m.2/Conv_output_0 encoding : bitwidth 8, min -15.595368385315, max 7.660882949829, scale 0.091200985014, offset -171.000000000000"
,,,,,,,bias_op_name: model.24.m.2.bias
,,,,,,,"dilation: [1, 1]"
,,,,,,,group: 1
,,,,,,,packageName: qti.aisw
,,,,,,,"pad_amount: [[0, 0], [0, 0]]"
,,,,,,,padding_size_strategy: 5
,,,,,,,"stride: [1, 1]"
,,,,,,,param count: 130k (1.81%)
,,,,,,,MACs per inference: 52M (0.636%)
Note: The supported runtimes column assumes a processor target of Snapdragon 855
Key : A:AIP
      D:DSP
      G:GPU
      C:CPU
""
Input Name,Dimensions,Type,Encoding Info
images,"1,640,640,3",uFxp_8,"bitwidth 8, min 0.000000000000, max 1.000000000000, scale 0.003921568859, offset 0.000000000000"
Total parameters: 7225885 (27 MB assuming single precision float. This does not represent the actual memory requirement for the model. It provides a rough estimate of the contribution from the parameters 4xNo of Params in bytes)
Total MACs per inference: 8216M (100%)
"Converter command: snpe-onnx-to-dlc adjust_nms_features_dims=True align_matmul_ranks=True batch=None converter_op_package_lib= copyright_file=None custom_io= custom_op_config_paths=None debug=-1 define_symbol=None disable_batchnorm_folding=False dry_run=None dumpIR=False dump_custom_io_config_template= dump_inferred_model=False dump_value_info=False enable_match_gathernd=False enable_strict_validation=False expand_gru_op_structure=True expand_lstm_op_structure=False extract_color_transform=True float_bw=32 force_prune_cast_ops=False handle_gather_negative_indices=True inject_cast_for_gather=True input_dim=[['images', '1,3,640,640']] input_dtype=[] input_encoding=[] input_layout=[] input_type=[] keep_disconnected_nodes=False keep_int64_inputs=False keep_quant_nodes=False match_caffe_ssd_to_tf=True model_version=None no_simplification=False op_package_lib= out_names=['/model.24/m.0/Conv_output_0', '/model.24/m.1/Conv_output_0', '/model.24/m.2/Conv_output_0'] package_name=None perform_axes_to_spatial_first_order=True prepare_inputs_as_params=False preprocess_roi_pool_inputs=True preserve_io=[] quantization_overrides= squash_box_decoder=True unroll_gru_time_steps=True unroll_lstm_time_steps=True use_convert_quantization_nodes=False validation_target=[]"
Quantizer command: snpe-dlc-quant help=false version=false verbose=false quiet=false silent=false debug=[] debug1=false debug2=false debug3=false log-mask=[] log-file=[] log-dir=[] log-file-include-hostname=false input_dlc=[/data0/ai-transform-data/data/6cdbbbe9-4694-4093-8527-b8fc6a5b1e3a/yolov5s_save_path/cutoff_yolov5s.dlc] input_list=[/home/dlc_quan_temp/LIIZa0nmTrzAKOR/quant.txt] no_weight_quantization=false output_dlc=[/data0/ai-transform-data/data/6cdbbbe9-4694-4093-8527-b8fc6a5b1e3a/yolov5s_save_path/cutoff_yolov5s.dlc] use_enhanced_quantizer=false use_adjusted_weights_quantizer=false optimizations=[] override_params=false use_encoding_optimizations=false udo_package_path=[/home/model_convert_plantform/Aidlux_UDO216_SO/libUdoAidluxUdoPackageReg.so] use_symmetric_quantize_weights=false use_native_dtype=false use_native_input_files=false use_native_output_files=false float_fallback=false use_dynamic_16_bit_weights=false bitwidth=[] weights_bitwidth=[8] act_bitwidth=[8] float_bitwidth=[] bias_bitwidth=[8] float_bias_bitwidth=[] clip_alpha=[] axis_quant=false restrict_quantization_steps=[]
DLC created with converter version: 2.16.4.231110151339_60331
"Ops used by DLC: Concat, Conv2d, Eltwise_Binary, Neuron, Pool, Resize"
Est. Steady-State Memory Needed to Run: 379.8 MiB
""
Cache Info:
Cache Record Name,SNPE Version,Cache Version,Identifier,Information,Subnets
backend.metadata0,2.16.4,3.3.0.0,HTP_V75_SM8650_8MB,Record Size: 7.19 MB,Total Subnets: 1
,,,,Optimization Level: 2,subnet_0:
,,,,Contains Udo: False,  Start Op ID: 0
,,,,,  End Op ID: 198
,,,,,  Input Tensors:
,,,,,"    images [1, 640, 640, 3] (UFIXED_POINT_8)"
,,,,,  Output Tensors:
,,,,,"    /model.24/m.0/Conv_output_0 [1, 80, 80, 255] (UFIXED_POINT_8)"
,,,,,"    /model.24/m.1/Conv_output_0 [1, 40, 40, 255] (UFIXED_POINT_8)"
,,,,,"    /model.24/m.2/Conv_output_0 [1, 20, 20, 255] (UFIXED_POINT_8)"