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implement onnx export for inception3/4, resnext, mobilenetv2 #346
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5d17168
add inceptionv4 backbone; the performance is not checked
lostkevin 03c825d
fix for inception DDP training
lostkevin 1b8ff54
Merge branch 'dev_fix_inception' into dev_inceptionv4
lostkevin 6c4a183
add inceptionv4 backbone/training settings
lostkevin 80105f2
fix config
lostkevin 1cf7cfe
add converted backbone, top-1 acc 80.08
lostkevin 83ea6b7
fix bug caused by the comment duplicated BasicConv2d
lostkevin 1388f0c
fix onnx export for inception3/4, resnext, mobilenetv2
lostkevin 4e2f393
fix format
lostkevin d05b7e7
fix upon comments
lostkevin bf3cf8b
fix bug when work_dir in test_export does not exist
lostkevin a392bb0
fit jit test
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215 changes: 215 additions & 0 deletions
215
configs/classification/imagenet/inception/inceptionv4_b32x8_100e.py
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Original file line number | Diff line number | Diff line change |
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_base_ = 'configs/base.py' | ||
|
||
num_classes = 1000 | ||
# model settings | ||
model = dict( | ||
type='Classification', | ||
backbone=dict(type='Inception4', num_classes=num_classes), | ||
head=[ | ||
dict( | ||
type='ClsHead', | ||
with_fc=False, | ||
in_channels=1536, | ||
loss_config=dict( | ||
type='CrossEntropyLossWithLabelSmooth', | ||
label_smooth=0, | ||
), | ||
num_classes=num_classes, | ||
input_feature_index=[1], | ||
), | ||
dict( | ||
type='ClsHead', | ||
with_fc=False, | ||
in_channels=768, | ||
loss_config=dict( | ||
type='CrossEntropyLossWithLabelSmooth', | ||
label_smooth=0, | ||
), | ||
num_classes=num_classes, | ||
input_feature_index=[0], | ||
) | ||
]) | ||
|
||
class_list = [ | ||
'0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', | ||
'14', '15', '16', '17', '18', '19', '20', '21', '22', '23', '24', '25', | ||
'26', '27', '28', '29', '30', '31', '32', '33', '34', '35', '36', '37', | ||
'38', '39', '40', '41', '42', '43', '44', '45', '46', '47', '48', '49', | ||
'50', '51', '52', '53', '54', '55', '56', '57', '58', '59', '60', '61', | ||
'62', '63', '64', '65', '66', '67', '68', '69', '70', '71', '72', '73', | ||
'74', '75', '76', '77', '78', '79', '80', '81', '82', '83', '84', '85', | ||
'86', '87', '88', '89', '90', '91', '92', '93', '94', '95', '96', '97', | ||
'98', '99', '100', '101', '102', '103', '104', '105', '106', '107', '108', | ||
'109', '110', '111', '112', '113', '114', '115', '116', '117', '118', | ||
'119', '120', '121', '122', '123', '124', '125', '126', '127', '128', | ||
'129', '130', '131', '132', '133', '134', '135', '136', '137', '138', | ||
'139', '140', '141', '142', '143', '144', '145', '146', '147', '148', | ||
'149', '150', '151', '152', '153', '154', '155', '156', '157', '158', | ||
'159', '160', '161', '162', '163', '164', '165', '166', '167', '168', | ||
'169', '170', '171', '172', '173', '174', '175', '176', '177', '178', | ||
'179', '180', '181', '182', '183', '184', '185', '186', '187', '188', | ||
'189', '190', '191', '192', '193', '194', '195', '196', '197', '198', | ||
'199', '200', '201', '202', '203', '204', '205', '206', '207', '208', | ||
'209', '210', '211', '212', '213', '214', '215', '216', '217', '218', | ||
'219', '220', '221', '222', '223', '224', '225', '226', '227', '228', | ||
'229', '230', '231', '232', '233', '234', '235', '236', '237', '238', | ||
'239', '240', '241', '242', '243', '244', '245', '246', '247', '248', | ||
'249', '250', '251', '252', '253', '254', '255', '256', '257', '258', | ||
'259', '260', '261', '262', '263', '264', '265', '266', '267', '268', | ||
'269', '270', '271', '272', '273', '274', '275', '276', '277', '278', | ||
'279', '280', '281', '282', '283', '284', '285', '286', '287', '288', | ||
'289', '290', '291', '292', '293', '294', '295', '296', '297', '298', | ||
'299', '300', '301', '302', '303', '304', '305', '306', '307', '308', | ||
'309', '310', '311', '312', '313', '314', '315', '316', '317', '318', | ||
'319', '320', '321', '322', '323', '324', '325', '326', '327', '328', | ||
'329', '330', '331', '332', '333', '334', '335', '336', '337', '338', | ||
'339', '340', '341', '342', '343', '344', '345', '346', '347', '348', | ||
'349', '350', '351', '352', '353', '354', '355', '356', '357', '358', | ||
'359', '360', '361', '362', '363', '364', '365', '366', '367', '368', | ||
'369', '370', '371', '372', '373', '374', '375', '376', '377', '378', | ||
'379', '380', '381', '382', '383', '384', '385', '386', '387', '388', | ||
'389', '390', '391', '392', '393', '394', '395', '396', '397', '398', | ||
'399', '400', '401', '402', '403', '404', '405', '406', '407', '408', | ||
'409', '410', '411', '412', '413', '414', '415', '416', '417', '418', | ||
'419', '420', '421', '422', '423', '424', '425', '426', '427', '428', | ||
'429', '430', '431', '432', '433', '434', '435', '436', '437', '438', | ||
'439', '440', '441', '442', '443', '444', '445', '446', '447', '448', | ||
'449', '450', '451', '452', '453', '454', '455', '456', '457', '458', | ||
'459', '460', '461', '462', '463', '464', '465', '466', '467', '468', | ||
'469', '470', '471', '472', '473', '474', '475', '476', '477', '478', | ||
'479', '480', '481', '482', '483', '484', '485', '486', '487', '488', | ||
'489', '490', '491', '492', '493', '494', '495', '496', '497', '498', | ||
'499', '500', '501', '502', '503', '504', '505', '506', '507', '508', | ||
'509', '510', '511', '512', '513', '514', '515', '516', '517', '518', | ||
'519', '520', '521', '522', '523', '524', '525', '526', '527', '528', | ||
'529', '530', '531', '532', '533', '534', '535', '536', '537', '538', | ||
'539', '540', '541', '542', '543', '544', '545', '546', '547', '548', | ||
'549', '550', '551', '552', '553', '554', '555', '556', '557', '558', | ||
'559', '560', '561', '562', '563', '564', '565', '566', '567', '568', | ||
'569', '570', '571', '572', '573', '574', '575', '576', '577', '578', | ||
'579', '580', '581', '582', '583', '584', '585', '586', '587', '588', | ||
'589', '590', '591', '592', '593', '594', '595', '596', '597', '598', | ||
'599', '600', '601', '602', '603', '604', '605', '606', '607', '608', | ||
'609', '610', '611', '612', '613', '614', '615', '616', '617', '618', | ||
'619', '620', '621', '622', '623', '624', '625', '626', '627', '628', | ||
'629', '630', '631', '632', '633', '634', '635', '636', '637', '638', | ||
'639', '640', '641', '642', '643', '644', '645', '646', '647', '648', | ||
'649', '650', '651', '652', '653', '654', '655', '656', '657', '658', | ||
'659', '660', '661', '662', '663', '664', '665', '666', '667', '668', | ||
'669', '670', '671', '672', '673', '674', '675', '676', '677', '678', | ||
'679', '680', '681', '682', '683', '684', '685', '686', '687', '688', | ||
'689', '690', '691', '692', '693', '694', '695', '696', '697', '698', | ||
'699', '700', '701', '702', '703', '704', '705', '706', '707', '708', | ||
'709', '710', '711', '712', '713', '714', '715', '716', '717', '718', | ||
'719', '720', '721', '722', '723', '724', '725', '726', '727', '728', | ||
'729', '730', '731', '732', '733', '734', '735', '736', '737', '738', | ||
'739', '740', '741', '742', '743', '744', '745', '746', '747', '748', | ||
'749', '750', '751', '752', '753', '754', '755', '756', '757', '758', | ||
'759', '760', '761', '762', '763', '764', '765', '766', '767', '768', | ||
'769', '770', '771', '772', '773', '774', '775', '776', '777', '778', | ||
'779', '780', '781', '782', '783', '784', '785', '786', '787', '788', | ||
'789', '790', '791', '792', '793', '794', '795', '796', '797', '798', | ||
'799', '800', '801', '802', '803', '804', '805', '806', '807', '808', | ||
'809', '810', '811', '812', '813', '814', '815', '816', '817', '818', | ||
'819', '820', '821', '822', '823', '824', '825', '826', '827', '828', | ||
'829', '830', '831', '832', '833', '834', '835', '836', '837', '838', | ||
'839', '840', '841', '842', '843', '844', '845', '846', '847', '848', | ||
'849', '850', '851', '852', '853', '854', '855', '856', '857', '858', | ||
'859', '860', '861', '862', '863', '864', '865', '866', '867', '868', | ||
'869', '870', '871', '872', '873', '874', '875', '876', '877', '878', | ||
'879', '880', '881', '882', '883', '884', '885', '886', '887', '888', | ||
'889', '890', '891', '892', '893', '894', '895', '896', '897', '898', | ||
'899', '900', '901', '902', '903', '904', '905', '906', '907', '908', | ||
'909', '910', '911', '912', '913', '914', '915', '916', '917', '918', | ||
'919', '920', '921', '922', '923', '924', '925', '926', '927', '928', | ||
'929', '930', '931', '932', '933', '934', '935', '936', '937', '938', | ||
'939', '940', '941', '942', '943', '944', '945', '946', '947', '948', | ||
'949', '950', '951', '952', '953', '954', '955', '956', '957', '958', | ||
'959', '960', '961', '962', '963', '964', '965', '966', '967', '968', | ||
'969', '970', '971', '972', '973', '974', '975', '976', '977', '978', | ||
'979', '980', '981', '982', '983', '984', '985', '986', '987', '988', | ||
'989', '990', '991', '992', '993', '994', '995', '996', '997', '998', '999' | ||
] | ||
|
||
data_source_type = 'ClsSourceImageList' | ||
base_root = 'data/imagenet_raw/' | ||
data_train_list = base_root + 'meta/train_labeled.txt' | ||
data_train_root = base_root + 'train/' | ||
data_test_list = base_root + 'meta/val_labeled.txt' | ||
data_test_root = base_root + 'validation/' | ||
image_size2 = 299 | ||
image_size1 = int((256 / 224) * image_size2) | ||
|
||
dataset_type = 'ClsDataset' | ||
img_norm_cfg = dict(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5]) | ||
train_pipeline = [ | ||
dict(type='RandomResizedCrop', size=image_size2), | ||
dict(type='RandomHorizontalFlip'), | ||
dict(type='ToTensor'), | ||
dict(type='Normalize', **img_norm_cfg), | ||
dict(type='Collect', keys=['img', 'gt_labels']) | ||
] | ||
test_pipeline = [ | ||
dict(type='Resize', size=image_size1), | ||
dict(type='CenterCrop', size=image_size2), | ||
dict(type='ToTensor'), | ||
dict(type='Normalize', **img_norm_cfg), | ||
dict(type='Collect', keys=['img', 'gt_labels']) | ||
] | ||
|
||
data = dict( | ||
imgs_per_gpu=32, # total 256 | ||
workers_per_gpu=4, | ||
train=dict( | ||
type=dataset_type, | ||
data_source=dict( | ||
list_file=data_train_list, | ||
root=data_train_root, | ||
type=data_source_type), | ||
pipeline=train_pipeline), | ||
val=dict( | ||
type=dataset_type, | ||
data_source=dict( | ||
list_file=data_test_list, | ||
root=data_test_root, | ||
type=data_source_type), | ||
pipeline=test_pipeline)) | ||
|
||
eval_config = dict(initial=False, interval=1, gpu_collect=True) | ||
eval_pipelines = [ | ||
dict( | ||
mode='test', | ||
data=data['val'], | ||
dist_eval=True, | ||
evaluators=[ | ||
dict(type='ClsEvaluator', topk=(1, 5), class_list=class_list) | ||
], | ||
) | ||
] | ||
|
||
# optimizer | ||
optimizer = dict(type='SGD', lr=0.1, momentum=0.9, weight_decay=0.0001) | ||
|
||
# learning policy | ||
lr_config = dict(policy='step', step=[30, 60, 90]) | ||
checkpoint_config = dict(interval=10) | ||
|
||
# runtime settings | ||
total_epochs = 100 | ||
|
||
predict = dict( | ||
type='ClassificationPredictor', | ||
pipelines=[ | ||
dict(type='Resize', size=image_size1), | ||
dict(type='CenterCrop', size=image_size2), | ||
dict(type='ToTensor'), | ||
dict(type='Normalize', **img_norm_cfg), | ||
dict(type='Collect', keys=['img']) | ||
]) | ||
|
||
log_config = dict( | ||
interval=10, | ||
hooks=[dict(type='TextLoggerHook'), | ||
dict(type='TensorboardLoggerHook')]) | ||
|
||
export = dict(export_type='raw', export_neck=True) |
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inception这几个配置文件可以提取一个base 配置吗,看起来重复度很高
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OK