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dvc.lock
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schema: '2.0'
stages:
download_data:
cmd: kaggle competitions download -c ranzcr-clip-catheter-line-classification
-p data/
outs:
- path: data/ranzcr-clip-catheter-line-classification.zip
md5: f8a117e7ba1b5527c99c80b54beddeb5
size: 12561354247
unzip_train_img:
cmd: unzip data/ranzcr-clip-catheter-line-classification.zip 'train/*' -d 'data/'
deps:
- path: data/ranzcr-clip-catheter-line-classification.zip
md5: f8a117e7ba1b5527c99c80b54beddeb5
size: 12561354247
outs:
- path: data/train/
md5: 5571d6d885d1e550ac890552afb255f0.dir
size: 6912613778
nfiles: 30083
unzip_test_img:
cmd: unzip data/ranzcr-clip-catheter-line-classification.zip 'test/*' -d 'data/'
deps:
- path: data/ranzcr-clip-catheter-line-classification.zip
md5: f8a117e7ba1b5527c99c80b54beddeb5
size: 12561354247
outs:
- path: data/test/
md5: 45cbe64f56a418f4d1abebd38c184175.dir
size: 844424034
nfiles: 3582
unzip_train_labels:
cmd: unzip data/ranzcr-clip-catheter-line-classification.zip 'train.csv' -d 'data/'
deps:
- path: data/ranzcr-clip-catheter-line-classification.zip
md5: f8a117e7ba1b5527c99c80b54beddeb5
size: 12561354247
outs:
- path: data/train.csv
md5: f9305cb1f8dbb233c78385f20ab3ae72
size: 2918266
unzip_train_annotations:
cmd: unzip data/ranzcr-clip-catheter-line-classification.zip 'train_annotations.csv'
-d 'data/'
deps:
- path: data/ranzcr-clip-catheter-line-classification.zip
md5: f8a117e7ba1b5527c99c80b54beddeb5
size: 12561354247
outs:
- path: data/train_annotations.csv
md5: 00ad55b088b2f81c756a6b21bc8f2562
size: 4950273
create_folds:
cmd: python pipe/create_folds.py
deps:
- path: data/train.csv
md5: f9305cb1f8dbb233c78385f20ab3ae72
size: 2918266
- path: pipe/create_folds.py
md5: 78d346827bae71e4e2057bf148f94038
size: 723
outs:
- path: data/train_folds.csv
md5: 7f4f0d6630400e2b1218d530fcb99a63
size: 2978438
unzip_sample_submission:
cmd: unzip data/ranzcr-clip-catheter-line-classification.zip 'sample_submission.csv'
-d 'data/'
deps:
- path: data/ranzcr-clip-catheter-line-classification.zip
md5: f8a117e7ba1b5527c99c80b54beddeb5
size: 12561354247
outs:
- path: data/sample_submission.csv
md5: 3bf8eb33a1a25f1f79940d019c18ebbc
size: 311839
resize_images:
cmd: python pipe/resize_images.py
deps:
- path: data/test/
md5: 45cbe64f56a418f4d1abebd38c184175.dir
size: 844424034
nfiles: 3582
- path: data/train/
md5: 5571d6d885d1e550ac890552afb255f0.dir
size: 6912613778
nfiles: 30083
outs:
- path: data/test_1024/
md5: 29b494965aebb0664b74e29f3e345473.dir
size: 214944270
nfiles: 3582
- path: data/test_128/
md5: 105566336a8298b416d0ef82e347051d.dir
size: 8846772
nfiles: 3582
- path: data/test_192/
md5: 7872b7646f388e9b08695138794c757a.dir
size: 15818222
nfiles: 3582
- path: data/test_256/
md5: 0a364a5a19354e2080a27411a6996ab5.dir
size: 24363993
nfiles: 3582
- path: data/test_384/
md5: 85def42fb4ea189dc50f2950f3b88965.dir
size: 45232275
nfiles: 3582
- path: data/test_512/
md5: 829fb8073ab10e5ace5d6d05253387b3.dir
size: 70444379
nfiles: 3582
- path: data/test_768/
md5: 9275cfb3acc8651983a9eb43ca03b174.dir
size: 133274447
nfiles: 3582
- path: data/train_1024/
md5: 2f49375e6e8e87e1fab5c5075d63b582.dir
size: 1773270872
nfiles: 30083
- path: data/train_128/
md5: 569de16f618eff737a4f2a8d3e70eec0.dir
size: 72692224
nfiles: 30083
- path: data/train_192/
md5: c480a05f5643a38909ccad7f71000599.dir
size: 130326145
nfiles: 30083
- path: data/train_256/
md5: e14002093f230017b4cc1810a53f0328.dir
size: 201194414
nfiles: 30083
- path: data/train_384/
md5: 142193318e2adfddd4fb6f8551589009.dir
size: 374049179
nfiles: 30083
- path: data/train_512/
md5: 088e837dc33da0b21e3f57644c085037.dir
size: 582432616
nfiles: 30083
- path: data/train_768/
md5: 8695f5a4249f99244a4c8c14e15eac0a.dir
size: 1100286799
nfiles: 30083
train_modlel_02:
cmd: python pipe/train.py --fold 0 --epochs 20 --arch resnet34 --metric multilabel_auc_macro
--opt adam --loss bce_with_logits --precision 16 --sz 128 --bs 512 --lr 0.02
--wd 0.02 --mom 0.9
deps:
- path: data/train_folds.csv
md5: c0a7355a820dd5f371ba3ffb54eeecd0
size: 2978438
- path: pipe/train.py
md5: 07a367a146265f74db1e04c9d0a0d049
size: 4289
outs:
- path: models/arch=resnet34_sz=128_fold=0.ckpt
md5: 58672e048799379a17223652040325fd
size: 85284057
- path: subs/oof/arch=resnet34_sz=128_fold=0.csv
md5: 125c6c3ae07a99c6d53e0830d10d2e2e
size: 986208
train_resnet18_256:
cmd: python pipe/train.py --train_data train_256 --test_data test_256 --fold -1
--epochs 15 --arch resnet18 --sz 256 --batch_size 128 --lr 1 --sched onecycle
deps:
- path: data/train_folds.csv
md5: 7a364fa00309d9d50641ae5edcfabcd3
size: 2978438
- path: pipe/train.py
md5: 97ab92d24da766cb621b43d4749ec8c8
size: 7224
outs:
- path: metrics/arch=resnet18_sz=256.metric
md5: 200784b2c007da87dad50f7d46c73b48
size: 31
- path: models/arch=resnet18_sz=256_fold=0.ckpt
md5: a90f7cd96c78bb32037f7d53f4e44f6c
size: 44787193
- path: models/arch=resnet18_sz=256_fold=1.ckpt
md5: 6b48bf222f4a67444615e48d02fc65f3
size: 44787193
- path: models/arch=resnet18_sz=256_fold=2.ckpt
md5: b744500a91a2af01cbb0f955f1c3555f
size: 44787193
- path: models/arch=resnet18_sz=256_fold=3.ckpt
md5: 8a6018657d4d944294718ed0e249be97
size: 44787193
- path: models/arch=resnet18_sz=256_fold=4.ckpt
md5: 1ddfb3ee80d990a2e27845355c8265ab
size: 44787193
- path: subs/arch=resnet18_sz=256_fold=0.csv
md5: 90c06f647ffcd6fe8adf8f2818dbde8b
size: 993174
- path: subs/arch=resnet18_sz=256_fold=1.csv
md5: 57d8fffd5ffeac0233186d711bd0277f
size: 994569
- path: subs/arch=resnet18_sz=256_fold=2.csv
md5: f541fb2734f23708a8286e5815431510
size: 991653
- path: subs/arch=resnet18_sz=256_fold=3.csv
md5: e00bdbbe2748947126720a6fb5761fba
size: 993150
- path: subs/arch=resnet18_sz=256_fold=4.csv
md5: d24589d03fac10bdbf9aeaf3c1d88587
size: 994248
- path: subs/oof/arch=resnet18_sz=256_fold=0.csv
md5: 4f203721e2017a27fb3530b95824a59e
size: 1678199
- path: subs/oof/arch=resnet18_sz=256_fold=1.csv
md5: 27e19c7055ca010230f0246ff0ae7bee
size: 1679626
- path: subs/oof/arch=resnet18_sz=256_fold=2.csv
md5: 3773f15529ddeec8ac40cd07c82b5c85
size: 1679875
- path: subs/oof/arch=resnet18_sz=256_fold=3.csv
md5: e6d4234aed69cc82c652943247385562
size: 1680644
- path: subs/oof/arch=resnet18_sz=256_fold=4.csv
md5: c5c09c85224c872e85515e8cb8a87332
size: 1678591
train_resnet18_512:
cmd: python pipe/train.py --train_data train_512 --test_data test_512 --fold -1
--epochs 15 --arch resnet18 --sz 512 --auto_batch_size power --lr 1 --sched
onecycle
deps:
- path: data/train_folds.csv
md5: 7a364fa00309d9d50641ae5edcfabcd3
size: 2978438
- path: pipe/train.py
md5: 97ab92d24da766cb621b43d4749ec8c8
size: 7224
outs:
- path: metrics/arch=resnet18_sz=512.metric
md5: 2310a59a6f2dbc8aa1b868287e705ad9
size: 31
- path: models/arch=resnet18_sz=512_fold=0.ckpt
md5: 418b214287bd6bf8870f9dcfd6129fcd
size: 44787201
- path: models/arch=resnet18_sz=512_fold=1.ckpt
md5: 7d75ff564bd3de5ce0d27b3dfec0bdcb
size: 44787198
- path: models/arch=resnet18_sz=512_fold=2.ckpt
md5: 4c77426416a120568d28e83ca3b6b599
size: 44787197
- path: models/arch=resnet18_sz=512_fold=3.ckpt
md5: 367b5fe5bd4ca0107421690d7fa60da2
size: 44787197
- path: models/arch=resnet18_sz=512_fold=4.ckpt
md5: bd24dcb589fe3f1be741bb541415e161
size: 44787198
- path: subs/arch=resnet18_sz=512_fold=0.csv
md5: 0a4cf03f080c057d3926f93f2bb85fe6
size: 994293
- path: subs/arch=resnet18_sz=512_fold=1.csv
md5: 86063ba3f5fa844b40aef0c5259f8d54
size: 995216
- path: subs/arch=resnet18_sz=512_fold=2.csv
md5: e8513a45c610331046faeb26eca41bed
size: 992202
- path: subs/arch=resnet18_sz=512_fold=3.csv
md5: a2f83ff1d408e4884532037f8a7eeba6
size: 997531
- path: subs/arch=resnet18_sz=512_fold=4.csv
md5: 51087d2261ec537608308ca6c9204445
size: 998571
- path: subs/oof/arch=resnet18_sz=512_fold=0.csv
md5: 3d7d33ab2227347a65c5a7ad2214b25c
size: 1678290
- path: subs/oof/arch=resnet18_sz=512_fold=1.csv
md5: 0f4d38917c582dda9f4136416f0d4918
size: 1678835
- path: subs/oof/arch=resnet18_sz=512_fold=2.csv
md5: 6463e058c216c9c3d6f2f890398d5578
size: 1678860
- path: subs/oof/arch=resnet18_sz=512_fold=3.csv
md5: 30b6300789b85f9cf8ce067ca905a696
size: 1685707
- path: subs/oof/arch=resnet18_sz=512_fold=4.csv
md5: e80d686815502a81e952250535ca5d08
size: 1683124
train_efficientnet_b4_256:
cmd: python pipe/train.py --train_data train_256 --test_data test_256 --fold -1
--epochs 15 --arch tf_efficientnet_b4_ns --sz 256 --batch_size 22 --lr 1 --sched
onecycle
deps:
- path: data/train_folds.csv
md5: 7a364fa00309d9d50641ae5edcfabcd3
size: 2978438
- path: pipe/train.py
md5: 2dfbac030cc5c89a17585ef832abdd7b
size: 8159
outs:
- path: metrics/arch=tf_efficientnet_b4_ns_sz=256.metric
md5: bd9e8cc3f4ccb693714fac3cff80ab2d
size: 49
- path: models/arch=tf_efficientnet_b4_ns_sz=256_fold=0.ckpt
md5: bc1e0ca47a6f9091e7b1871ed2de9cdf
size: 71032001
- path: models/arch=tf_efficientnet_b4_ns_sz=256_fold=1.ckpt
md5: 741fbad628a17a75244da7e0d3ab4291
size: 71032001
- path: models/arch=tf_efficientnet_b4_ns_sz=256_fold=2.ckpt
md5: 3227695bfacb4b61f17534b8c92d430c
size: 71032001
- path: models/arch=tf_efficientnet_b4_ns_sz=256_fold=3.ckpt
md5: 7c0821d6bf95220c47e0f2c86d83e92e
size: 71032001
- path: models/arch=tf_efficientnet_b4_ns_sz=256_fold=4.ckpt
md5: 329b4ed99b0ea1ef0f365578a9f86df5
size: 71032001
- path: subs/arch=tf_efficientnet_b4_ns_sz=256_fold=0.csv
md5: 5230282872626885db68bd6bfc9d17d2
size: 994046
- path: subs/arch=tf_efficientnet_b4_ns_sz=256_fold=1.csv
md5: ff13e4d7746903b6e6bf23c3012ce077
size: 989997
- path: subs/arch=tf_efficientnet_b4_ns_sz=256_fold=2.csv
md5: 995818cc457d53adb53364e06f7e8825
size: 991256
- path: subs/arch=tf_efficientnet_b4_ns_sz=256_fold=3.csv
md5: c8b1d07acb34b9f50cd7794daf44878f
size: 992262
- path: subs/arch=tf_efficientnet_b4_ns_sz=256_fold=4.csv
md5: 8bff869fffc12588d077f5906ccdd08d
size: 990444
- path: subs/oof/arch=tf_efficientnet_b4_ns_sz=256_fold=0.csv
md5: fd11768d79e28f48f32d329c9bc6cffa
size: 1676231
- path: subs/oof/arch=tf_efficientnet_b4_ns_sz=256_fold=1.csv
md5: 036b82adc98aa8b2e8e726a2b0ae31b7
size: 1671098
- path: subs/oof/arch=tf_efficientnet_b4_ns_sz=256_fold=2.csv
md5: a7bd54d47f8e9dec34e5cbc3c60ab39b
size: 1677398
- path: subs/oof/arch=tf_efficientnet_b4_ns_sz=256_fold=3.csv
md5: 4a7948a30acfc25b95a641f2071f3e99
size: 1677331
- path: subs/oof/arch=tf_efficientnet_b4_ns_sz=256_fold=4.csv
md5: 57509c9dcad5e1cb1ebb909220cdb203
size: 1671019
train_efficientnet_b4_512:
cmd: python pipe/train.py --train_data train_1024 --test_data test_1024 --fold
-1 --epochs 5 --arch tf_efficientnet_b4_ns --sz 512 --batch_size 32 --lr 1 --sched
onecycle
deps:
- path: data/train_folds.csv
md5: 7a364fa00309d9d50641ae5edcfabcd3
size: 2978438
- path: pipe/train.py
md5: 9fa4cbc5ffe416f796e046ab1f5b97aa
size: 8840
outs:
- path: metrics/arch=tf_efficientnet_b4_ns_sz=512.metric
md5: 8f249f493c246e633f4feaf66fe0755d
size: 49
- path: models/arch=tf_efficientnet_b4_ns_sz=512_fold=0.ckpt
md5: b50c09f05c3fa2edd67cf5d8f56e9f4b
size: 71032001
- path: models/arch=tf_efficientnet_b4_ns_sz=512_fold=1.ckpt
md5: 4e9fd595aebb4eab6e93ba71b6e685e7
size: 71032001
- path: models/arch=tf_efficientnet_b4_ns_sz=512_fold=2.ckpt
md5: 0c0d03a0ff939f067e048a1c96f9ead0
size: 71032001
- path: models/arch=tf_efficientnet_b4_ns_sz=512_fold=3.ckpt
md5: cebf80349f593f420722dbaacdfb1e03
size: 71032001
- path: models/arch=tf_efficientnet_b4_ns_sz=512_fold=4.ckpt
md5: ad292afdefcb7106bf1d8bbb34034d31
size: 71032001
- path: subs/arch=tf_efficientnet_b4_ns_sz=512_fold=0.csv
md5: 2a9d108e226095387969d7854505149b
size: 999503
- path: subs/arch=tf_efficientnet_b4_ns_sz=512_fold=1.csv
md5: b071f6b03cb4bcaceeb8eea8a7cfaf20
size: 999754
- path: subs/arch=tf_efficientnet_b4_ns_sz=512_fold=2.csv
md5: 0464bc8e1ba695af872b7ef8afe1f408
size: 1000900
- path: subs/arch=tf_efficientnet_b4_ns_sz=512_fold=3.csv
md5: 160d19a783da83ed81ca79ff558b971d
size: 998228
- path: subs/arch=tf_efficientnet_b4_ns_sz=512_fold=4.csv
md5: 5e7a2b18cab6a080dd7f3cd7a66ed0fd
size: 996537
- path: subs/oof/arch=tf_efficientnet_b4_ns_sz=512_fold=0.csv
md5: d5f5c9c7b4eaef7e9d8bd2ec4594c737
size: 1668531
- path: subs/oof/arch=tf_efficientnet_b4_ns_sz=512_fold=1.csv
md5: 5dec21676d59981c849ffdb65f5c1dff
size: 1671022
- path: subs/oof/arch=tf_efficientnet_b4_ns_sz=512_fold=2.csv
md5: a2eb95d767e19210db53c513008a974f
size: 1671474
- path: subs/oof/arch=tf_efficientnet_b4_ns_sz=512_fold=3.csv
md5: b8174b190fe201af011a49ec9682e4aa
size: 1670604
- path: subs/oof/arch=tf_efficientnet_b4_ns_sz=512_fold=4.csv
md5: e9468e76b7672018833b04f1c28adfa2
size: 1673483
train_resnest14d_128:
cmd: python pipe/train.py --train_data train_256 --test_data test_256 --fold -1
--epochs 15 --arch resnest14d --sz 128 --batch_size 128 --lr 1 --wd 0.00001
--label_smoothing 0.05 --sched onecycle --aug baseline --precision 32 --opt
sam
deps:
- path: data/train_128/
md5: 569de16f618eff737a4f2a8d3e70eec0.dir
size: 72692224
nfiles: 30083
- path: data/train_256/
md5: e14002093f230017b4cc1810a53f0328.dir
size: 201194414
nfiles: 30083
- path: data/train_folds.csv
md5: 7f4f0d6630400e2b1218d530fcb99a63
size: 2978438
- path: pipe/train.py
md5: 9b71fb58eccf4b3ebeb5a9ddb6897b13
size: 5926
outs:
- path: metrics/arch=resnest14d_sz=128.metric
md5: 64996527a23e0be4ae24d41cea0d4139
size: 49
- path: models/arch=resnest14d_sz=128_fold=0.ckpt
md5: 64f0fa42b9cd3119057037942d3037db
size: 68863867
- path: models/arch=resnest14d_sz=128_fold=1.ckpt
md5: 3b4ad10e67eb914eac3d795992372f0e
size: 68863869
- path: models/arch=resnest14d_sz=128_fold=2.ckpt
md5: 3e57540710d115a74c4f372a0ed0415b
size: 68863867
- path: models/arch=resnest14d_sz=128_fold=3.ckpt
md5: fdf913d79fff161623730824f78c0ca1
size: 68863868
- path: models/arch=resnest14d_sz=128_fold=4.ckpt
md5: 24501a33be1377b3a624cb5322ae4816
size: 68863867
train_resnest200e_512:
cmd: python pipe/train.py --train_data train_1024 --test_data test_1024 --fold
-1 --epochs 10 --arch resnest200e --sz 512 --batch_size 8 --lr .1 --wd 0.00001
--label_smoothing 0.05 --sched onecycle --aug baseline --precision 32 --opt
sam
deps:
- path: data/train_folds.csv
md5: 7f4f0d6630400e2b1218d530fcb99a63
size: 2978438
- path: pipe/train.py
md5: 9b71fb58eccf4b3ebeb5a9ddb6897b13
size: 5926
outs:
- path: metrics/arch=resnest200e_sz=512.metric
md5: 7434334635819f0a43856bc3a6e9a282
size: 49
- path: models/arch=resnest200e_sz=512_fold=0.ckpt
md5: a058edde977443dae635fe1dd4613608
size: 547410695
- path: models/arch=resnest200e_sz=512_fold=1.ckpt
md5: 1798fc5fd57122abb26ec38e14d197d0
size: 547410698
- path: models/arch=resnest200e_sz=512_fold=2.ckpt
md5: fc42d22cad2afc170281981be4bb0580
size: 547410696
- path: models/arch=resnest200e_sz=512_fold=3.ckpt
md5: 8ed2bbf5d55a5ca356d49648cea62d4f
size: 547410695
- path: models/arch=resnest200e_sz=512_fold=4.ckpt
md5: e4b37cdfefffbb6d47e9eba16b44db14
size: 547410695