torch-jit-export_predict = core.Net('torch-jit-export_predict')
torch-jit-export_predict.Conv(['0', '1', '2'], ['152'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.SpatialBN(['152', '3', '4', '5', '6'], ['153'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Relu(['153'], ['154'])
torch-jit-export_predict.Conv(['154', '8', '9'], ['155'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.SpatialBN(['155', '10', '11', '12', '13'], ['156'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Relu(['156'], ['157'])
torch-jit-export_predict.MaxPool(['157'], ['158'], strides=[2, 2], pads=[0, 0, 0, 0], kernels=[2, 2])
torch-jit-export_predict.Conv(['158', '15', '16'], ['159'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.SpatialBN(['159', '17', '18', '19', '20'], ['160'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Relu(['160'], ['161'])
torch-jit-export_predict.Conv(['161', '22', '23'], ['162'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.SpatialBN(['162', '24', '25', '26', '27'], ['163'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Relu(['163'], ['164'])
torch-jit-export_predict.MaxPool(['164'], ['165'], strides=[2, 2], pads=[0, 0, 0, 0], kernels=[2, 2])
torch-jit-export_predict.Conv(['165', '29', '30'], ['166'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.SpatialBN(['166', '31', '32', '33', '34'], ['167'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Relu(['167'], ['168'])
torch-jit-export_predict.Conv(['168', '36', '37'], ['169'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.SpatialBN(['169', '38', '39', '40', '41'], ['170'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Relu(['170'], ['171'])
torch-jit-export_predict.Conv(['171', '43', '44'], ['172'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.SpatialBN(['172', '45', '46', '47', '48'], ['173'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Relu(['173'], ['174'])
torch-jit-export_predict.MaxPool(['174'], ['175'], strides=[2, 2], pads=[0, 0, 0, 0], kernels=[2, 2])
torch-jit-export_predict.Conv(['175', '50', '51'], ['176'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.SpatialBN(['176', '52', '53', '54', '55'], ['177'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Relu(['177'], ['178'])
torch-jit-export_predict.Conv(['178', '57', '58'], ['179'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.SpatialBN(['179', '59', '60', '61', '62'], ['180'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Relu(['180'], ['181'])
torch-jit-export_predict.Conv(['181', '64', '65'], ['182'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.SpatialBN(['182', '66', '67', '68', '69'], ['183'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Relu(['183'], ['184'])
torch-jit-export_predict.MaxPool(['184'], ['185'], strides=[2, 2], pads=[0, 0, 0, 0], kernels=[2, 2])
torch-jit-export_predict.Conv(['185', '71', '72'], ['186'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.SpatialBN(['186', '73', '74', '75', '76'], ['187'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Relu(['187'], ['188'])
torch-jit-export_predict.Conv(['188', '78', '79'], ['189'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.SpatialBN(['189', '80', '81', '82', '83'], ['190'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Relu(['190'], ['191'])
torch-jit-export_predict.Conv(['191', '85', '86'], ['192'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.SpatialBN(['192', '87', '88', '89', '90'], ['193'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Relu(['193'], ['194'])
torch-jit-export_predict.Shape(['194'], ['196'])
torch-jit-export_predict.Gather(['196', '195'], ['197'])
torch-jit-export_predict.ExpandDims(['197'], ['199'], dims=[0])
torch-jit-export_predict.Concat(['199', '200'], ['201', 'OC2_DUMMY_0'], axis=0)
torch-jit-export_predict.Reshape(['194', '201'], ['202', 'OC2_DUMMY_1'])
torch-jit-export_predict.FC(['202', '92', '93'], ['203'])
torch-jit-export_predict.ExpandDims(['197'], ['207'], dims=[0])
torch-jit-export_predict.Concat(['207', '208', '209', '210'], ['211', 'OC2_DUMMY_2'], axis=0)
torch-jit-export_predict.Reshape(['203', '211'], ['212', 'OC2_DUMMY_3'])
torch-jit-export_predict.Conv(['184', '94', '95'], ['213'], strides=[1, 1], pads=[0, 0, 0, 0], kernels=[1, 1], group=1, dilations=[1, 1])
torch-jit-export_predict.Sigmoid(['213'], ['214'])
torch-jit-export_predict.Sigmoid(['212'], ['215'])
torch-jit-export_predict.Concat(['214', '215'], ['216', 'OC2_DUMMY_4'], axis=1)
torch-jit-export_predict.Conv(['216', '96', '97'], ['217'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.Relu(['217'], ['218'])
torch-jit-export_predict.SpatialBN(['218', '98', '99', '100', '101'], ['219'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Conv(['219', '103', '104'], ['220'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.Add(['220', '219'], ['221'])
torch-jit-export_predict.Relu(['221'], ['222'])
torch-jit-export_predict.SpatialBN(['222', '98', '99', '100', '101'], ['223'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Conv(['223', '103', '104'], ['224'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.Add(['224', '219'], ['225'])
torch-jit-export_predict.Relu(['225'], ['226'])
torch-jit-export_predict.SpatialBN(['226', '98', '99', '100', '101'], ['227'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Conv(['227', '103', '104'], ['228'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.Add(['228', '219'], ['229'])
torch-jit-export_predict.Relu(['229'], ['230'])
torch-jit-export_predict.SpatialBN(['230', '98', '99', '100', '101'], ['231'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Conv(['231', '105', '106'], ['232'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.Sigmoid(['232'], ['233'])
torch-jit-export_predict.ConvTranspose(['233', '146', '147'], ['234'], dilations=[1, 1], group=1, kernels=[4, 4], pads=[1, 1, 1, 1], strides=[2, 2])
torch-jit-export_predict.Conv(['174', '107', '108'], ['235'], strides=[1, 1], pads=[0, 0, 0, 0], kernels=[1, 1], group=1, dilations=[1, 1])
torch-jit-export_predict.Sigmoid(['235'], ['236'])
torch-jit-export_predict.Sigmoid(['234'], ['237'])
torch-jit-export_predict.Concat(['236', '237'], ['238', 'OC2_DUMMY_5'], axis=1)
torch-jit-export_predict.Conv(['238', '109', '110'], ['239'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.Relu(['239'], ['240'])
torch-jit-export_predict.SpatialBN(['240', '111', '112', '113', '114'], ['241'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Conv(['241', '116', '117'], ['242'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.Add(['242', '241'], ['243'])
torch-jit-export_predict.Relu(['243'], ['244'])
torch-jit-export_predict.SpatialBN(['244', '111', '112', '113', '114'], ['245'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Conv(['245', '116', '117'], ['246'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.Add(['246', '241'], ['247'])
torch-jit-export_predict.Relu(['247'], ['248'])
torch-jit-export_predict.SpatialBN(['248', '111', '112', '113', '114'], ['249'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Conv(['249', '116', '117'], ['250'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.Add(['250', '241'], ['251'])
torch-jit-export_predict.Relu(['251'], ['252'])
torch-jit-export_predict.SpatialBN(['252', '111', '112', '113', '114'], ['253'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Conv(['253', '118', '119'], ['254'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.Sigmoid(['254'], ['255'])
torch-jit-export_predict.ConvTranspose(['255', '148', '149'], ['256'], dilations=[1, 1], group=1, kernels=[4, 4], pads=[1, 1, 1, 1], strides=[2, 2])
torch-jit-export_predict.Conv(['164', '120', '121'], ['257'], strides=[1, 1], pads=[0, 0, 0, 0], kernels=[1, 1], group=1, dilations=[1, 1])
torch-jit-export_predict.Sigmoid(['257'], ['258'])
torch-jit-export_predict.Sigmoid(['256'], ['259'])
torch-jit-export_predict.Concat(['258', '259'], ['260', 'OC2_DUMMY_6'], axis=1)
torch-jit-export_predict.Conv(['260', '122', '123'], ['261'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.Relu(['261'], ['262'])
torch-jit-export_predict.SpatialBN(['262', '124', '125', '126', '127'], ['263'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Conv(['263', '129', '130'], ['264'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.Add(['264', '263'], ['265'])
torch-jit-export_predict.Relu(['265'], ['266'])
torch-jit-export_predict.SpatialBN(['266', '124', '125', '126', '127'], ['267'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Conv(['267', '129', '130'], ['268'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.Add(['268', '263'], ['269'])
torch-jit-export_predict.Relu(['269'], ['270'])
torch-jit-export_predict.SpatialBN(['270', '124', '125', '126', '127'], ['271'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Conv(['271', '129', '130'], ['272'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.Add(['272', '263'], ['273'])
torch-jit-export_predict.Relu(['273'], ['274'])
torch-jit-export_predict.SpatialBN(['274', '124', '125', '126', '127'], ['275'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Conv(['275', '131', '132'], ['276'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.Sigmoid(['276'], ['277'])
torch-jit-export_predict.ConvTranspose(['277', '150', '151'], ['278'], dilations=[1, 1], group=1, kernels=[4, 4], pads=[1, 1, 1, 1], strides=[2, 2])
torch-jit-export_predict.Conv(['157', '133', '134'], ['279'], strides=[1, 1], pads=[0, 0, 0, 0], kernels=[1, 1], group=1, dilations=[1, 1])
torch-jit-export_predict.Sigmoid(['279'], ['280'])
torch-jit-export_predict.Sigmoid(['278'], ['281'])
torch-jit-export_predict.Concat(['280', '281'], ['282', 'OC2_DUMMY_7'], axis=1)
torch-jit-export_predict.Conv(['282', '135', '136'], ['283'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.Relu(['283'], ['284'])
torch-jit-export_predict.SpatialBN(['284', '137', '138', '139', '140'], ['285'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Conv(['285', '142', '143'], ['286'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.Add(['286', '285'], ['287'])
torch-jit-export_predict.Relu(['287'], ['288'])
torch-jit-export_predict.SpatialBN(['288', '137', '138', '139', '140'], ['289'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Conv(['289', '142', '143'], ['290'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.Add(['290', '285'], ['291'])
torch-jit-export_predict.Relu(['291'], ['292'])
torch-jit-export_predict.SpatialBN(['292', '137', '138', '139', '140'], ['293'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Conv(['293', '142', '143'], ['294'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.Add(['294', '285'], ['295'])
torch-jit-export_predict.Relu(['295'], ['296'])
torch-jit-export_predict.SpatialBN(['296', '137', '138', '139', '140'], ['297'], momentum=1.0, epsilon=9.999999747378752e-06, is_test=1)
torch-jit-export_predict.Conv(['297', '144', '145'], ['298'], strides=[1, 1], pads=[1, 1, 1, 1], kernels=[3, 3], group=1, dilations=[1, 1])
torch-jit-export_predict.Sigmoid(['298'], ['299'])
torch-jit-export_predict.Sigmoid(['212'], ['300'])
torch-jit-export_predict.Sigmoid(['233'], ['301'])
torch-jit-export_predict.Sigmoid(['255'], ['302'])
torch-jit-export_predict.Sigmoid(['277'], ['303'])
torch-jit-export_predict.Sigmoid(['299'], ['304'])
Input blob: 0
Output blob: 304