TMVAFastInferencePrototype/Linear_event.hxx at master · sitongan/TMVAFastInferencePrototype · GitHub

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//Code generated automatically by TMVA for Inference of Model file [Linear_event.onnx] at [Mon May 17 20:37:02 2021]
#include<algorithm>
#include<vector>
namespace TMVA_SOFIE_Linear_event{
namespace BLAS{
	extern "C" void sgemm_(const char * transa, const char * transb, const int * m, const int * n, const int * k,
	                       const float * alpha, const float * A, const int * lda, const float * B, const int * ldb,
	                       const float * beta, float * C, const int * ldc);
	extern "C" void sgemv_(const char * trans, const int * m, const int * n, const float * alpha, const float * A,
	                       const int * lda, const float * X, const int * incx, const float * beta, const float * Y, const int * incy);
}//BLAS
float tensor_6bias[50] = {0.11743705, 0.034862563, -0.0882589072, 0.0364261568, -0.124690443, -0.130239025, -0.0992482975, -0.0840349048, 0.0848250687, -0.0350763872, -0.125840902, 0.0240709633, 0.00172457506, -0.0843005627, 0.0934766755, 0.0217792857, 0.0289114714, 0.000208690195, 0.124901414, -0.010485515, 0.042181205, -0.0365066975, -0.0338845998, -0.0509331897, 0.121999539, -0.0837921873, 0.0981798172, 0.147880167, 0.00600128341, -0.0964693874, -0.129413828, 0.107353419, -0.047475189, -0.0715770349, 0.106839582, -0.12282218, 0.0451751016, -0.0984491706, -0.0533152968, 0.157195807, -0.0661517382, -0.0364472084, -0.030660836, -0.0183054004, 0.0301248692, 0.034019284, 0.133405492, 0.115911707, -0.0737051442, 0.100111805};
float tensor_4weight[2500] = {-0.0816543624, 0.00226433575, -0.0399654135, 0.0354767554, -0.000382221129, 0.107768327, -0.0775545388, 0.127075508, 0.0960364193, -0.0518541187, 0.0169795454, -0.037438035, -0.0374177769, -0.0870580077, 0.0449804328, -0.0829727203, -0.134521022, 0.0748403966, -0.0361970142, -0.13030313, -0.12994054, 0.0713628531, -0.0282540172, 0.0420930088, 0.0476259775, -0.0786259472, -0.0139003545, 0.0124610066, -0.0638670251, -0.131948337, 0.0577753782, -0.131891847, 0.0968460143, 0.0311554223, 0.114533618, -0.135504395, 0.13559626, -0.0139267389, -0.128643408, 0.0972228199, -0.102488831, 0.126579657, 0.0881835371, -0.00287441909, -0.045941636, 0.0403012782, 0.0023971796, -0.083268404, -0.137731344, -0.0090622874, -0.123624064, 0.0788734257, 0.0750446618, 0.0130759329, 0.114278011, 0.0493201837, -0.0253942385, -0.0558254048, 0.0241133329, -0.0510510057, -0.115690917, -0.0817524195, 0.0914541781, -0.0167452786, -0.0985144824, -0.0709899813, -0.0188606717, 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float tensor_18bias[10] = {-0.113684192, 0.121798299, -0.116308749, -0.0473414436, 0.0382905975, -0.0705379993, -0.0210990068, 0.132127836, 0.0800660774, -0.0568331257};
float tensor_16bias[50] = {-0.0537384972, 0.160052702, 0.0777507722, 0.155062199, -0.000372417097, 0.0744346231, -0.00902234018, -0.0416349284, -0.0327844471, -0.101023614, 0.0594821721, -0.0890664086, 0.144085109, -0.0593391545, 0.0217189342, 0.143109426, -0.0370035954, 0.0574014187, -0.0276059676, 0.0389365107, -0.000805824995, -0.0248860028, -0.0925007537, -0.109317243, 0.0345011242, 0.126251072, -0.0442578718, -0.0834909752, -0.0689221621, 0.0875025168, 0.120724551, 0.133211017, 0.123541333, 0.0454147235, 0.0255576894, 0.0748735368, 0.0178100765, 0.124028154, -0.115493141, -0.0667942613, 0.110477179, 0.00497290213, 0.101388119, -0.0670208484, 0.0876818746, 0.0962640345, -0.0806797296, 0.0366541818, -0.0849216208, -0.0698148087};
float tensor_8bias[50] = {0.102051869, -0.0178657137, -0.0390091464, -0.150461301, -0.0739682466, -0.057161428, -0.0415797159, -0.112682387, -0.00751589239, -0.0619791783, -0.0929356888, 0.15137884, 0.102855653, 0.0609929562, 0.0534329042, -0.130050972, -0.126791283, 0.0792580396, -0.0156272706, 0.0958549455, -0.0516368635, 0.0923676267, 0.0337775946, -0.0431587771, -0.0720473006, -0.0146768363, -0.0297905058, 0.0348105058, -0.0366752297, 0.0116601093, -0.082319662, -0.0845309198, -0.139789909, 0.143905073, 0.154106006, -0.000177997877, -0.0463561416, -0.0308935419, -0.044693619, 0.161166966, -0.134416848, 0.0787707344, 0.159274489, -0.0373313203, -0.0223374069, 0.0940257385, -0.0628078952, 0.162983224, 0.0296818037, 0.113034829};
float tensor_6weight[2500] = {0.0489631109, 0.0937118605, 0.172893375, 0.109562017, 0.0375068337, 0.0910925269, -0.0498189554, -0.0917754024, -0.0225276798, 0.0379311815, 0.0787891522, 0.103837341, 0.0523024648, 0.0894822851, -0.111124605, 0.131665155, 0.0283745378, 0.00596336555, -0.0765224323, -0.0333618037, 0.0339765027, 0.00256500463, 0.148543537, 0.0928062201, -0.0694231018, 0.0416461974, 0.0986706316, 0.104882061, 0.101162732, 0.171008229, -0.112932652, 0.092600733, -0.0845532268, -0.0457399487, -0.0263328124, 0.128212944, 0.0039986372, -0.00276351813, 0.0395175666, 0.0586967282, -0.0674899146, 0.0518566817, -0.101665571, -0.00309433672, 0.0111714154, 0.111966237, -0.0983771756, 0.0239476934, -0.0637314692, -0.0632277131, 0.0632674098, -0.0224505812, -0.0395391062, -0.0220744982, 0.0133986622, -0.138868675, -0.125856131, -0.013393566, 0.0826233327, -0.0122388005, -0.140361115, 0.140446022, 0.0952187926, 0.0640365183, 0.0641996711, 0.0784211606, 0.136958286, 0.0776972473, 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float tensor_0bias[50] = {0.113831677, -0.0516641513, -0.0584901758, -0.0378762968, 0.104214713, 0.015873475, 0.107028559, 0.1197301, 0.0100806579, 0.0936502293, 0.0192132052, 0.078284435, -0.0660643727, 0.114138693, 0.0651234388, 0.0832673535, -0.0289821029, -0.0578927398, 0.0487054959, 0.0257891603, -0.00172951072, 0.0256149396, 0.0193127617, 0.0457875207, 0.0412775353, 0.000686742365, -0.0321569517, 0.0634227991, 0.0904813036, -0.00782169681, 0.00215601129, 0.0232264996, 0.0556999519, 0.107680134, 0.0684185699, -0.022286607, -0.0618678257, 0.0239612535, 0.0903714746, -0.0536040552, -0.0668440536, 0.112769008, -0.100794926, 0.00479773711, -0.01810796, 0.0258228257, 0.0649340078, -0.0605447404, -0.0603834279, 0.0364964306};
float tensor_12bias[50] = {-0.0476042256, -0.129093021, 0.0768762082, -0.0541792735, -0.0107035488, 0.125418395, -0.0192244779, -0.0273368265, -0.0741859749, -0.0847827941, 0.0401888937, -0.0754052997, -0.13067624, 0.0533674322, -0.0765022784, 0.0389329009, -0.0652100816, 0.135587618, -0.0301984698, 0.00957513694, -0.0923883244, 0.154045239, 0.146726146, -0.105914474, -0.126684144, 0.100673862, -0.00150537491, -0.043580763, 0.0607040264, 0.14598307, -0.0847611129, 0.130537897, 0.15647465, -0.0550367907, 0.103866242, -0.104147926, -0.0865428075, 0.0102117015, 0.135107383, 0.0757682472, 0.104484119, 0.00581380958, -0.0674747452, 0.0260530878, -0.123745665, -0.0592386276, 0.120776847, 0.0601776689, 0.0566131845, -0.127929151};
float tensor_10bias[50] = {0.049075231, -0.0136722326, -0.131101966, -0.110771269, 0.103306532, 0.0141783534, 0.126833066, 0.0228366796, -0.117138706, -0.0430683345, -0.0730045363, -0.0680313706, -0.120767705, -0.105842307, 0.145061374, 0.0244614575, 0.0597288348, 0.0119230412, -0.0207567215, -0.00693285465, -0.0725066736, -0.109216787, -0.0340837017, 0.0560642406, 0.0728756487, -0.0951568559, 0.0313263498, 0.148480237, -0.0432067439, -0.0671626106, 0.122903481, 0.0729967728, -0.0224931948, -0.0984232426, -0.0433254242, 0.00124312937, -0.0546170101, 0.133956209, -0.0884937868, -0.107657254, -0.0104880035, -0.0027641356, -0.0013808012, 0.121982254, 0.128564849, -0.0365806408, -0.154219598, -0.113903195, 0.0956676751, -0.00857159961};
float tensor_0weight[5000] = {0.0140755363, -0.0314627923, -0.106416292, -0.0158274975, 0.0516018532, -0.0239030365, 0.0392079242, -0.0360903926, -0.0184718259, 0.00225428212, 0.117046557, -0.0174612757, -0.0546416901, 0.115371093, -0.134247109, -0.127707571, -0.122530863, -0.0407832898, 0.0457908623, 0.133616045, -0.0353497528, -0.0163051486, 0.124191314, -0.0488181338, 0.0835923776, -0.0297006946, -0.103730388, -0.00348424911, -0.0954237133, -0.0147937993, 0.119027302, 0.0487853214, -0.00394543074, 0.0202327315, 0.0441630222, 0.112209328, -0.123534143, -0.0321295857, -0.00467968453, -0.0239419863, -0.0232208353, 0.0146574788, -0.0290244948, -0.0186320283, -0.0605580471, 0.124154054, 0.0541881286, -0.0845651105, 0.040790081, 0.0274265334, -0.0548911951, 0.0475940406, -0.00891916268, -0.128545582, 0.0524918698, -0.0456963629, 0.00137847802, 0.106424421, 0.125029951, -0.043143414, -0.0462884344, 0.0945330262, 0.132328033, 0.0848311335, 0.0941167772, 0.0174138248, -0.00741389161, 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float tensor_35[50];
float tensor_34[50];
float tensor_31[50];
float tensor_29[50];
float tensor_28[50];
float tensor_27[50];
float tensor_26[50];
float tensor_36[50];
float tensor_33[50];
float tensor_30[50];
float tensor_32[50];
float tensor_23[50];
float tensor_25[50];
float tensor_37[50];
float tensor_24[50];
float tensor_39[10];
float tensor_38[50];
float tensor_22[50];
float tensor_21[50];
std::vector<float> infer(float* tensor_input1){
	float op_0_alpha = 1;
	float op_0_beta = 1;
	char op_0_trans = 't';
	int op_0_lda = 100;
	int op_0_m = 100;
	int op_0_n = 50;
	int op_0_incxy = 1;
	std::copy(tensor_0bias, tensor_0bias + 50, tensor_21);
	BLAS::sgemv_(&op_0_trans, &op_0_m, &op_0_n, &op_0_alpha, tensor_0weight, &op_0_lda, tensor_input1, &op_0_incxy, &op_0_beta, tensor_21, &op_0_incxy);
	for (int id = 0; id < 50 ; id++){
		tensor_22[id] = ((tensor_21[id] > 0 )? tensor_21[id] : 0);
	}
	float op_2_alpha = 1;
	float op_2_beta = 1;
	char op_2_trans = 't';
	int op_2_lda = 50;
	int op_2_m = 50;
	int op_2_n = 50;
	int op_2_incxy = 1;
	std::copy(tensor_2bias, tensor_2bias + 50, tensor_23);
	BLAS::sgemv_(&op_2_trans, &op_2_m, &op_2_n, &op_2_alpha, tensor_2weight, &op_2_lda, tensor_22, &op_2_incxy, &op_2_beta, tensor_23, &op_2_incxy);
	for (int id = 0; id < 50 ; id++){
		tensor_24[id] = ((tensor_23[id] > 0 )? tensor_23[id] : 0);
	}
	float op_4_alpha = 1;
	float op_4_beta = 1;
	char op_4_trans = 't';
	int op_4_lda = 50;
	int op_4_m = 50;
	int op_4_n = 50;
	int op_4_incxy = 1;
	std::copy(tensor_4bias, tensor_4bias + 50, tensor_25);
	BLAS::sgemv_(&op_4_trans, &op_4_m, &op_4_n, &op_4_alpha, tensor_4weight, &op_4_lda, tensor_24, &op_4_incxy, &op_4_beta, tensor_25, &op_4_incxy);
	for (int id = 0; id < 50 ; id++){
		tensor_26[id] = ((tensor_25[id] > 0 )? tensor_25[id] : 0);
	}
	float op_6_alpha = 1;
	float op_6_beta = 1;
	char op_6_trans = 't';
	int op_6_lda = 50;
	int op_6_m = 50;
	int op_6_n = 50;
	int op_6_incxy = 1;
	std::copy(tensor_6bias, tensor_6bias + 50, tensor_27);
	BLAS::sgemv_(&op_6_trans, &op_6_m, &op_6_n, &op_6_alpha, tensor_6weight, &op_6_lda, tensor_26, &op_6_incxy, &op_6_beta, tensor_27, &op_6_incxy);
	for (int id = 0; id < 50 ; id++){
		tensor_28[id] = ((tensor_27[id] > 0 )? tensor_27[id] : 0);
	}
	float op_8_alpha = 1;
	float op_8_beta = 1;
	char op_8_trans = 't';
	int op_8_lda = 50;
	int op_8_m = 50;
	int op_8_n = 50;
	int op_8_incxy = 1;
	std::copy(tensor_8bias, tensor_8bias + 50, tensor_29);
	BLAS::sgemv_(&op_8_trans, &op_8_m, &op_8_n, &op_8_alpha, tensor_8weight, &op_8_lda, tensor_28, &op_8_incxy, &op_8_beta, tensor_29, &op_8_incxy);
	for (int id = 0; id < 50 ; id++){
		tensor_30[id] = ((tensor_29[id] > 0 )? tensor_29[id] : 0);
	}
	float op_10_alpha = 1;
	float op_10_beta = 1;
	char op_10_trans = 't';
	int op_10_lda = 50;
	int op_10_m = 50;
	int op_10_n = 50;
	int op_10_incxy = 1;
	std::copy(tensor_10bias, tensor_10bias + 50, tensor_31);
	BLAS::sgemv_(&op_10_trans, &op_10_m, &op_10_n, &op_10_alpha, tensor_10weight, &op_10_lda, tensor_30, &op_10_incxy, &op_10_beta, tensor_31, &op_10_incxy);
	for (int id = 0; id < 50 ; id++){
		tensor_32[id] = ((tensor_31[id] > 0 )? tensor_31[id] : 0);
	}
	float op_12_alpha = 1;
	float op_12_beta = 1;
	char op_12_trans = 't';
	int op_12_lda = 50;
	int op_12_m = 50;
	int op_12_n = 50;
	int op_12_incxy = 1;
	std::copy(tensor_12bias, tensor_12bias + 50, tensor_33);
	BLAS::sgemv_(&op_12_trans, &op_12_m, &op_12_n, &op_12_alpha, tensor_12weight, &op_12_lda, tensor_32, &op_12_incxy, &op_12_beta, tensor_33, &op_12_incxy);
	for (int id = 0; id < 50 ; id++){
		tensor_34[id] = ((tensor_33[id] > 0 )? tensor_33[id] : 0);
	}
	float op_14_alpha = 1;
	float op_14_beta = 1;
	char op_14_trans = 't';
	int op_14_lda = 50;
	int op_14_m = 50;
	int op_14_n = 50;
	int op_14_incxy = 1;
	std::copy(tensor_14bias, tensor_14bias + 50, tensor_35);
	BLAS::sgemv_(&op_14_trans, &op_14_m, &op_14_n, &op_14_alpha, tensor_14weight, &op_14_lda, tensor_34, &op_14_incxy, &op_14_beta, tensor_35, &op_14_incxy);
	for (int id = 0; id < 50 ; id++){
		tensor_36[id] = ((tensor_35[id] > 0 )? tensor_35[id] : 0);
	}
	float op_16_alpha = 1;
	float op_16_beta = 1;
	char op_16_trans = 't';
	int op_16_lda = 50;
	int op_16_m = 50;
	int op_16_n = 50;
	int op_16_incxy = 1;
	std::copy(tensor_16bias, tensor_16bias + 50, tensor_37);
	BLAS::sgemv_(&op_16_trans, &op_16_m, &op_16_n, &op_16_alpha, tensor_16weight, &op_16_lda, tensor_36, &op_16_incxy, &op_16_beta, tensor_37, &op_16_incxy);
	for (int id = 0; id < 50 ; id++){
		tensor_38[id] = ((tensor_37[id] > 0 )? tensor_37[id] : 0);
	}
	float op_18_alpha = 1;
	float op_18_beta = 1;
	char op_18_trans = 't';
	int op_18_lda = 50;
	int op_18_m = 50;
	int op_18_n = 10;
	int op_18_incxy = 1;
	std::copy(tensor_18bias, tensor_18bias + 10, tensor_39);
	BLAS::sgemv_(&op_18_trans, &op_18_m, &op_18_n, &op_18_alpha, tensor_18weight, &op_18_lda, tensor_38, &op_18_incxy, &op_18_beta, tensor_39, &op_18_incxy);
	std::vector<float> ret (tensor_39, tensor_39 + sizeof(tensor_39) / sizeof(tensor_39[0]));
	return ret;
}
} //TMVA_SOFIE_Linear_event