LAYERNAME	LAYERTYPE	INPUTNAMES	OUTPUTNAMES	INPUTSHAPES	OUTPUTSHAPES
image	ConstantInput			[[1,3,416,416]]	[[1,3,416,416]]
scalerPreprocessor	Scale	image	image2	[[1,3,416,416]]	[[1,3,416,416]]
convolution_W	ConstantInput			[[16,3,3,3]]	[[16,3,3,3]]
convolution	Conv	image2;convolution_W	convolution2d_1_output	[[1,3,416,416],[16,3,3,3]]	[[1,16,416,416]]
BatchNormalization_scale	ConstantInput			[[16]]	[[16]]
BatchNormalization_B	ConstantInput			[[16]]	[[16]]
BatchNormalization_mean	ConstantInput			[[16]]	[[16]]
BatchNormalization_variance	ConstantInput			[[16]]	[[16]]
batchnorm	BatchNorm	convolution2d_1_output;BatchNormalization_scale;BatchNormalization_B;BatchNormalization_mean;BatchNormalization_variance	batchnormalization_1_output	[[1,16,416,416],[16],[16],[16],[16]]	[[1,16,416,416],[16],[16],[16],[16]]
activation	Relu	batchnormalization_1_output	leakyrelu_1_output	[[1,16,416,416]]	[[1,16,416,416]]
pooling	Pooling	leakyrelu_1_output	maxpooling2d_1_output	[[1,16,416,416]]	[[1,16,208,208]]
convolution1_W	ConstantInput			[[32,16,3,3]]	[[32,16,3,3]]
convolution1	Conv	maxpooling2d_1_output;convolution1_W	convolution2d_2_output	[[1,16,208,208],[32,16,3,3]]	[[1,32,208,208]]
BatchNormalization_scale1	ConstantInput			[[32]]	[[32]]
BatchNormalization_B1	ConstantInput			[[32]]	[[32]]
BatchNormalization_mean1	ConstantInput			[[32]]	[[32]]
BatchNormalization_variance1	ConstantInput			[[32]]	[[32]]
batchnorm1	BatchNorm	convolution2d_2_output;BatchNormalization_scale1;BatchNormalization_B1;BatchNormalization_mean1;BatchNormalization_variance1	batchnormalization_2_output	[[1,32,208,208],[32],[32],[32],[32]]	[[1,32,208,208],[32],[32],[32],[32]]
activation1	Relu	batchnormalization_2_output	leakyrelu_2_output	[[1,32,208,208]]	[[1,32,208,208]]
pooling1	Pooling	leakyrelu_2_output	maxpooling2d_2_output	[[1,32,208,208]]	[[1,32,104,104]]
convolution2_W	ConstantInput			[[64,32,3,3]]	[[64,32,3,3]]
convolution2	Conv	maxpooling2d_2_output;convolution2_W	convolution2d_3_output	[[1,32,104,104],[64,32,3,3]]	[[1,64,104,104]]
BatchNormalization_scale2	ConstantInput			[[64]]	[[64]]
BatchNormalization_B2	ConstantInput			[[64]]	[[64]]
BatchNormalization_mean2	ConstantInput			[[64]]	[[64]]
BatchNormalization_variance2	ConstantInput			[[64]]	[[64]]
batchnorm2	BatchNorm	convolution2d_3_output;BatchNormalization_scale2;BatchNormalization_B2;BatchNormalization_mean2;BatchNormalization_variance2	batchnormalization_3_output	[[1,64,104,104],[64],[64],[64],[64]]	[[1,64,104,104],[64],[64],[64],[64]]
activation2	Relu	batchnormalization_3_output	leakyrelu_3_output	[[1,64,104,104]]	[[1,64,104,104]]
pooling2	Pooling	leakyrelu_3_output	maxpooling2d_3_output	[[1,64,104,104]]	[[1,64,52,52]]
convolution3_W	ConstantInput			[[128,64,3,3]]	[[128,64,3,3]]
convolution3	Conv	maxpooling2d_3_output;convolution3_W	convolution2d_4_output	[[1,64,52,52],[128,64,3,3]]	[[1,128,52,52]]
BatchNormalization_scale3	ConstantInput			[[128]]	[[128]]
BatchNormalization_B3	ConstantInput			[[128]]	[[128]]
BatchNormalization_mean3	ConstantInput			[[128]]	[[128]]
BatchNormalization_variance3	ConstantInput			[[128]]	[[128]]
batchnorm3	BatchNorm	convolution2d_4_output;BatchNormalization_scale3;BatchNormalization_B3;BatchNormalization_mean3;BatchNormalization_variance3	batchnormalization_4_output	[[1,128,52,52],[128],[128],[128],[128]]	[[1,128,52,52],[128],[128],[128],[128]]
activation3	Relu	batchnormalization_4_output	leakyrelu_4_output	[[1,128,52,52]]	[[1,128,52,52]]
pooling3	Pooling	leakyrelu_4_output	maxpooling2d_4_output	[[1,128,52,52]]	[[1,128,26,26]]
convolution4_W	ConstantInput			[[256,128,3,3]]	[[256,128,3,3]]
convolution4	Conv	maxpooling2d_4_output;convolution4_W	convolution2d_5_output	[[1,128,26,26],[256,128,3,3]]	[[1,256,26,26]]
BatchNormalization_scale4	ConstantInput			[[256]]	[[256]]
BatchNormalization_B4	ConstantInput			[[256]]	[[256]]
BatchNormalization_mean4	ConstantInput			[[256]]	[[256]]
BatchNormalization_variance4	ConstantInput			[[256]]	[[256]]
batchnorm4	BatchNorm	convolution2d_5_output;BatchNormalization_scale4;BatchNormalization_B4;BatchNormalization_mean4;BatchNormalization_variance4	batchnormalization_5_output	[[1,256,26,26],[256],[256],[256],[256]]	[[1,256,26,26],[256],[256],[256],[256]]
activation4	Relu	batchnormalization_5_output	leakyrelu_5_output	[[1,256,26,26]]	[[1,256,26,26]]
pooling4	Pooling	leakyrelu_5_output	maxpooling2d_5_output	[[1,256,26,26]]	[[1,256,13,13]]
convolution5_W	ConstantInput			[[512,256,3,3]]	[[512,256,3,3]]
convolution5	Conv	maxpooling2d_5_output;convolution5_W	convolution2d_6_output	[[1,256,13,13],[512,256,3,3]]	[[1,512,13,13]]
BatchNormalization_scale5	ConstantInput			[[512]]	[[512]]
BatchNormalization_B5	ConstantInput			[[512]]	[[512]]
BatchNormalization_mean5	ConstantInput			[[512]]	[[512]]
BatchNormalization_variance5	ConstantInput			[[512]]	[[512]]
batchnorm5	BatchNorm	convolution2d_6_output;BatchNormalization_scale5;BatchNormalization_B5;BatchNormalization_mean5;BatchNormalization_variance5	batchnormalization_6_output	[[1,512,13,13],[512],[512],[512],[512]]	[[1,512,13,13],[512],[512],[512],[512]]
activation5	Relu	batchnormalization_6_output	leakyrelu_6_output	[[1,512,13,13]]	[[1,512,13,13]]
pooling5	Pooling	leakyrelu_6_output	maxpooling2d_6_output	[[1,512,13,13]]	[[1,512,12,12]]
convolution6_W	ConstantInput			[[1024,512,3,3]]	[[1024,512,3,3]]
convolution6	Conv	maxpooling2d_6_output;convolution6_W	convolution2d_7_output	[[1,512,12,12],[1024,512,3,3]]	[[1,1024,12,12]]
BatchNormalization_scale6	ConstantInput			[[1024]]	[[1024]]
BatchNormalization_B6	ConstantInput			[[1024]]	[[1024]]
BatchNormalization_mean6	ConstantInput			[[1024]]	[[1024]]
BatchNormalization_variance6	ConstantInput			[[1024]]	[[1024]]
batchnorm6	BatchNorm	convolution2d_7_output;BatchNormalization_scale6;BatchNormalization_B6;BatchNormalization_mean6;BatchNormalization_variance6	batchnormalization_7_output	[[1,1024,12,12],[1024],[1024],[1024],[1024]]	[[1,1024,12,12],[1024],[1024],[1024],[1024]]
activation6	Relu	batchnormalization_7_output	leakyrelu_7_output	[[1,1024,12,12]]	[[1,1024,12,12]]
convolution7_W	ConstantInput			[[1024,1024,3,3]]	[[1024,1024,3,3]]
convolution7	Conv	leakyrelu_7_output;convolution7_W	convolution2d_8_output	[[1,1024,12,12],[1024,1024,3,3]]	[[1,1024,12,12]]
BatchNormalization_scale7	ConstantInput			[[1024]]	[[1024]]
BatchNormalization_B7	ConstantInput			[[1024]]	[[1024]]
BatchNormalization_mean7	ConstantInput			[[1024]]	[[1024]]
BatchNormalization_variance7	ConstantInput			[[1024]]	[[1024]]
batchnorm7	BatchNorm	convolution2d_8_output;BatchNormalization_scale7;BatchNormalization_B7;BatchNormalization_mean7;BatchNormalization_variance7	batchnormalization_8_output	[[1,1024,12,12],[1024],[1024],[1024],[1024]]	[[1,1024,12,12],[1024],[1024],[1024],[1024]]
activation7	Relu	batchnormalization_8_output	leakyrelu_8_output	[[1,1024,12,12]]	[[1,1024,12,12]]
convolution8_W	ConstantInput			[[125,1024,1,1]]	[[125,1024,1,1]]
convolution8_B	ConstantInput			[[125]]	[[125]]
convolution8	Conv	leakyrelu_8_output;convolution8_W;convolution8_B	grid	[[1,1024,12,12],[125,1024,1,1],[125]]	[[1,125,12,12]]

Tiny YOLO-v2

Model Plot

Layer Information

Per Layer Timing

Tesla K80

Batch Size 2

Batch Size 4

Batch Size 8

Batch Size 16

Batch Size 32

Tesla M60

Batch Size 2

Batch Size 4

Batch Size 8

Batch Size 16

Batch Size 32

GRID K520

Batch Size 2

Batch Size 4

Batch Size 8

Batch Size 16

Batch Size 32

TITAN Xp

Batch Size 2

Batch Size 4

Batch Size 8

Batch Size 16

Batch Size 32

TITAN V

Batch Size 2

Batch Size 4

Batch Size 8

Batch Size 16

Batch Size 32

Tesla V100-SXM2-16GB

Batch Size 2

Batch Size 4

Batch Size 8

Batch Size 16

Batch Size 32

Quadro RTX 6000

Batch Size 2

Batch Size 4

Batch Size 8

Batch Size 16

Batch Size 32

Tesla T4

Batch Size 2

Batch Size 4

Batch Size 8

Batch Size 16

Batch Size 32