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miunangel
2025-08-16 20:46:31 +08:00
commit 3dc26db3b9
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2
MSGCoOp/configs/datasets/caltech101.yaml Normal file
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DATASET:
NAME: "Caltech101"

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MSGCoOp/configs/datasets/dtd.yaml Normal file
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DATASET:
NAME: "DescribableTextures"

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MSGCoOp/configs/datasets/eurosat.yaml Normal file
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DATASET:
NAME: "EuroSAT"

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MSGCoOp/configs/datasets/fgvc_aircraft.yaml Normal file
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DATASET:
NAME: "FGVCAircraft"

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MSGCoOp/configs/datasets/food101.yaml Normal file
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DATASET:
NAME: "Food101"

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MSGCoOp/configs/datasets/imagenet.yaml Normal file
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DATASET:
NAME: "ImageNet"

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MSGCoOp/configs/datasets/imagenet_a.yaml Normal file
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DATASET:
NAME: "ImageNetA"

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MSGCoOp/configs/datasets/imagenet_r.yaml Normal file
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DATASET:
NAME: "ImageNetR"

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MSGCoOp/configs/datasets/imagenet_sketch.yaml Normal file
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DATASET:
NAME: "ImageNetSketch"

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MSGCoOp/configs/datasets/imagenetv2.yaml Normal file
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DATASET:
NAME: "ImageNetV2"

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MSGCoOp/configs/datasets/oxford_flowers.yaml Normal file
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DATASET:
NAME: "OxfordFlowers"

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MSGCoOp/configs/datasets/oxford_pets.yaml Normal file
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DATASET:
NAME: "OxfordPets"

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MSGCoOp/configs/datasets/stanford_cars.yaml Normal file
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DATASET:
NAME: "StanfordCars"

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MSGCoOp/configs/datasets/sun397.yaml Normal file
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DATASET:
NAME: "SUN397"

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MSGCoOp/configs/datasets/ucf101.yaml Normal file
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DATASET:
NAME: "UCF101"

35
MSGCoOp/configs/trainers/CoCoOp/rn50_c4_ep10_batch1_ctxv1.yaml Normal file
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DATALOADER:
TRAIN_X:
BATCH_SIZE: 1
TEST:
BATCH_SIZE: 100
NUM_WORKERS: 8
INPUT:
SIZE: (224, 224)
INTERPOLATION: "bicubic"
PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
TRANSFORMS: ["random_resized_crop", "random_flip", "normalize"]
OPTIM:
NAME: "sgd"
LR: 0.002
MAX_EPOCH: 10
LR_SCHEDULER: "cosine"
WARMUP_EPOCH: 1
WARMUP_TYPE: "constant"
WARMUP_CONS_LR: 1e-5
TRAIN:
PRINT_FREQ: 20
MODEL:
BACKBONE:
NAME: "RN50"
TRAINER:
COCOOP:
N_CTX: 4
CTX_INIT: True
PREC: "fp16"

35
MSGCoOp/configs/trainers/CoCoOp/rn50_ep100_init.yaml Normal file
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DATALOADER:
TRAIN_X:
BATCH_SIZE: 1
TEST:
BATCH_SIZE: 100
NUM_WORKERS: 8
INPUT:
SIZE: (224, 224)
INTERPOLATION: "bicubic"
PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
TRANSFORMS: ["random_resized_crop", "random_flip", "normalize"]
OPTIM:
NAME: "sgd"
LR: 0.002
MAX_EPOCH: 100
LR_SCHEDULER: "cosine"
WARMUP_EPOCH: 1
WARMUP_TYPE: "constant"
WARMUP_CONS_LR: 1e-5
TRAIN:
PRINT_FREQ: 20
MODEL:
BACKBONE:
NAME: "RN50"
TRAINER:
COCOOP:
N_CTX: 16
CTX_INIT: True
PREC: "fp16"

35
MSGCoOp/configs/trainers/CoCoOp/rn50_ep50.yaml Normal file
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DATALOADER:
TRAIN_X:
BATCH_SIZE: 1
TEST:
BATCH_SIZE: 100
NUM_WORKERS: 8
INPUT:
SIZE: (224, 224)
INTERPOLATION: "bicubic"
PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
TRANSFORMS: ["random_resized_crop", "random_flip", "normalize"]
OPTIM:
NAME: "sgd"
LR: 0.002
MAX_EPOCH: 50
LR_SCHEDULER: "cosine"
WARMUP_EPOCH: 1
WARMUP_TYPE: "constant"
WARMUP_CONS_LR: 1e-5
TRAIN:
PRINT_FREQ: 20
MODEL:
BACKBONE:
NAME: "RN50"
TRAINER:
COCOOP:
N_CTX: 16
CTX_INIT: True
PREC: "fp16"

35
MSGCoOp/configs/trainers/CoCoOp/vit_b16_c16_ep10_batch1.yaml Normal file
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DATALOADER:
TRAIN_X:
BATCH_SIZE: 1
TEST:
BATCH_SIZE: 100
NUM_WORKERS: 8
INPUT:
SIZE: (224, 224)
INTERPOLATION: "bicubic"
PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
TRANSFORMS: ["random_resized_crop", "random_flip", "normalize"]
OPTIM:
NAME: "sgd"
LR: 0.002
MAX_EPOCH: 10
LR_SCHEDULER: "cosine"
WARMUP_EPOCH: 1
WARMUP_TYPE: "constant"
WARMUP_CONS_LR: 1e-5
TRAIN:
PRINT_FREQ: 20
MODEL:
BACKBONE:
NAME: "ViT-B/16"
TRAINER:
COCOOP:
N_CTX: 16
CTX_INIT: ""
PREC: "fp16"

35
MSGCoOp/configs/trainers/CoCoOp/vit_b16_c4_ep10_batch1.yaml Normal file
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DATALOADER:
TRAIN_X:
BATCH_SIZE: 1
TEST:
BATCH_SIZE: 100
NUM_WORKERS: 8
INPUT:
SIZE: (224, 224)
INTERPOLATION: "bicubic"
PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
TRANSFORMS: ["random_resized_crop", "random_flip", "normalize"]
OPTIM:
NAME: "sgd"
LR: 0.002
MAX_EPOCH: 10
LR_SCHEDULER: "cosine"
WARMUP_EPOCH: 1
WARMUP_TYPE: "constant"
WARMUP_CONS_LR: 1e-5
TRAIN:
PRINT_FREQ: 20
MODEL:
BACKBONE:
NAME: "ViT-B/16"
TRAINER:
COCOOP:
N_CTX: 4
CTX_INIT: ""
PREC: "fp16"

35
MSGCoOp/configs/trainers/CoCoOp/vit_b16_c4_ep10_batch1_ctxv1.yaml Normal file
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DATALOADER:
TRAIN_X:
BATCH_SIZE: 1
TEST:
BATCH_SIZE: 100
NUM_WORKERS: 8
INPUT:
SIZE: (224, 224)
INTERPOLATION: "bicubic"
PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
TRANSFORMS: ["random_resized_crop", "random_flip", "normalize"]
OPTIM:
NAME: "sgd"
LR: 0.002
MAX_EPOCH: 10
LR_SCHEDULER: "cosine"
WARMUP_EPOCH: 1
WARMUP_TYPE: "constant"
WARMUP_CONS_LR: 1e-5
TRAIN:
PRINT_FREQ: 20
MODEL:
BACKBONE:
NAME: "ViT-B/16"
TRAINER:
COCOOP:
N_CTX: 4
CTX_INIT: "a photo of a"
PREC: "fp16"

35
MSGCoOp/configs/trainers/CoCoOp/vit_b16_c8_ep10_batch1.yaml Normal file
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DATALOADER:
TRAIN_X:
BATCH_SIZE: 1
TEST:
BATCH_SIZE: 100
NUM_WORKERS: 8
INPUT:
SIZE: (224, 224)
INTERPOLATION: "bicubic"
PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
TRANSFORMS: ["random_resized_crop", "random_flip", "normalize"]
OPTIM:
NAME: "sgd"
LR: 0.002
MAX_EPOCH: 10
LR_SCHEDULER: "cosine"
WARMUP_EPOCH: 1
WARMUP_TYPE: "constant"
WARMUP_CONS_LR: 1e-5
TRAIN:
PRINT_FREQ: 20
MODEL:
BACKBONE:
NAME: "ViT-B/16"
TRAINER:
COCOOP:
N_CTX: 8
CTX_INIT: ""
PREC: "fp16"

29
MSGCoOp/configs/trainers/CoOp/rn50.yaml Normal file
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DATALOADER:
TRAIN_X:
BATCH_SIZE: 32
TEST:
BATCH_SIZE: 100
NUM_WORKERS: 8
INPUT:
SIZE: (224, 224)
INTERPOLATION: "bicubic"
PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
TRANSFORMS: ["random_resized_crop", "random_flip", "normalize"]
OPTIM:
NAME: "sgd"
LR: 0.002
MAX_EPOCH: 200
LR_SCHEDULER: "cosine"
WARMUP_EPOCH: 1
WARMUP_TYPE: "constant"
WARMUP_CONS_LR: 1e-5
TRAIN:
PRINT_FREQ: 5
MODEL:
BACKBONE:
NAME: "RN50"

29
MSGCoOp/configs/trainers/CoOp/rn50_ep100.yaml Normal file
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DATALOADER:
TRAIN_X:
BATCH_SIZE: 32
TEST:
BATCH_SIZE: 100
NUM_WORKERS: 8
INPUT:
SIZE: (224, 224)
INTERPOLATION: "bicubic"
PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
TRANSFORMS: ["random_resized_crop", "random_flip", "normalize"]
OPTIM:
NAME: "sgd"
LR: 0.002
MAX_EPOCH: 100
LR_SCHEDULER: "cosine"
WARMUP_EPOCH: 1
WARMUP_TYPE: "constant"
WARMUP_CONS_LR: 1e-5
TRAIN:
PRINT_FREQ: 5
MODEL:
BACKBONE:
NAME: "RN50"

29
MSGCoOp/configs/trainers/CoOp/rn50_ep50.yaml Normal file
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DATALOADER:
TRAIN_X:
BATCH_SIZE: 32
TEST:
BATCH_SIZE: 100
NUM_WORKERS: 8
INPUT:
SIZE: (224, 224)
INTERPOLATION: "bicubic"
PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
TRANSFORMS: ["random_resized_crop", "random_flip", "normalize"]
OPTIM:
NAME: "sgd"
LR: 0.002
MAX_EPOCH: 50
LR_SCHEDULER: "cosine"
WARMUP_EPOCH: 1
WARMUP_TYPE: "constant"
WARMUP_CONS_LR: 1e-5
TRAIN:
PRINT_FREQ: 5
MODEL:
BACKBONE:
NAME: "RN50"

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MSGCoOp/configs/trainers/CoOp/rn50_val.yaml Normal file
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DATALOADER:
TRAIN_X:
BATCH_SIZE: 32
TEST:
BATCH_SIZE: 32
NUM_WORKERS: 8
INPUT:
SIZE: (224, 224)
INTERPOLATION: "bicubic"
PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
TRANSFORMS: ["random_resized_crop", "random_flip", "normalize"]
MODEL:
BACKBONE:
NAME: "RN50"

33
MSGCoOp/configs/trainers/KgCoOp/rn50_ep100.yaml Normal file
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DATALOADER:
TRAIN_X:
BATCH_SIZE: 128
TEST:
BATCH_SIZE: 100
NUM_WORKERS: 8
INPUT:
SIZE: (224, 224)
INTERPOLATION: "bicubic"
PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
TRANSFORMS: ["random_resized_crop", "random_flip", "normalize"]
OPTIM:
NAME: "sgd"
LR: 0.002
MAX_EPOCH: 100
LR_SCHEDULER: "cosine"
WARMUP_EPOCH: 1
WARMUP_TYPE: "constant"
WARMUP_CONS_LR: 1e-5
TRAIN:
PRINT_FREQ: 5
MODEL:
BACKBONE:
NAME: "RN50"
TRAINER:
COOP:
CTX_INIT: True

33
MSGCoOp/configs/trainers/KgCoOp/vit_b16_ep100_ctxv1.yaml Normal file
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DATALOADER:
TRAIN_X:
BATCH_SIZE: 128
TEST:
BATCH_SIZE: 100
NUM_WORKERS: 8
INPUT:
SIZE: (224, 224)
INTERPOLATION: "bicubic"
PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
TRANSFORMS: ["random_resized_crop", "random_flip", "normalize"]
OPTIM:
NAME: "sgd"
LR: 0.002
MAX_EPOCH: 100
LR_SCHEDULER: "cosine"
WARMUP_EPOCH: 1
WARMUP_TYPE: "constant"
WARMUP_CONS_LR: 1e-5
TRAIN:
PRINT_FREQ: 5
MODEL:
BACKBONE:
NAME: "ViT-B/16"
TRAINER:
COOP:
CTX_INIT: True

33
MSGCoOp/configs/trainers/MSGCoOp/vit_b16_ep100_ctxv1.yaml Normal file
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DATALOADER:
TRAIN_X:
BATCH_SIZE: 128
TEST:
BATCH_SIZE: 100
NUM_WORKERS: 8
INPUT:
SIZE: (224, 224)
INTERPOLATION: "bicubic"
PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
TRANSFORMS: ["random_resized_crop", "random_flip", "normalize"]
OPTIM:
NAME: "sgd"
LR: 0.002
MAX_EPOCH: 100
LR_SCHEDULER: "cosine"
WARMUP_EPOCH: 1
WARMUP_TYPE: "constant"
WARMUP_CONS_LR: 1e-5
TRAIN:
PRINT_FREQ: 5
MODEL:
BACKBONE:
NAME: "ViT-B/16"
TRAINER:
COOP:
CTX_INIT: True

37
MSGCoOp/configs/trainers/ProGrad/rn50.yaml Normal file
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DATALOADER:
TRAIN_X:
BATCH_SIZE: 32
TEST:
BATCH_SIZE: 100
NUM_WORKERS: 8
INPUT:
SIZE: (224, 224)
INTERPOLATION: "bicubic"
PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
TRANSFORMS: ["random_resized_crop", "random_flip", "normalize"]
OPTIM:
NAME: "sgd"
LR: 0.002
MAX_EPOCH: 200
LR_SCHEDULER: "cosine"
WARMUP_EPOCH: 1
WARMUP_TYPE: "constant"
WARMUP_CONS_LR: 1e-5
LOSS:
NAME: "prograd"
T: 1.0
TRAIN:
PRINT_FREQ: 5
MODEL:
BACKBONE:
NAME: "RN50"
TRAINER:
COOP:
CTX_INIT: True

37
MSGCoOp/configs/trainers/ProGrad/rn50_ep100.yaml Normal file
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DATALOADER:
TRAIN_X:
BATCH_SIZE: 32
TEST:
BATCH_SIZE: 100
NUM_WORKERS: 8
INPUT:
SIZE: (224, 224)
INTERPOLATION: "bicubic"
PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
TRANSFORMS: ["random_resized_crop", "random_flip", "normalize"]
OPTIM:
NAME: "sgd"
LR: 0.002
MAX_EPOCH: 100
LR_SCHEDULER: "cosine"
WARMUP_EPOCH: 1
WARMUP_TYPE: "constant"
WARMUP_CONS_LR: 1e-5
LOSS:
NAME: "prograd"
T: 1.0
TRAIN:
PRINT_FREQ: 5
MODEL:
BACKBONE:
NAME: "RN50"
TRAINER:
COOP:
CTX_INIT: True

37
MSGCoOp/configs/trainers/ProGrad/rn50_ep50.yaml Normal file
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DATALOADER:
TRAIN_X:
BATCH_SIZE: 32
TEST:
BATCH_SIZE: 100
NUM_WORKERS: 8
INPUT:
SIZE: (224, 224)
INTERPOLATION: "bicubic"
PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
TRANSFORMS: ["random_resized_crop", "random_flip", "normalize"]
OPTIM:
NAME: "sgd"
LR: 0.002
MAX_EPOCH: 50
LR_SCHEDULER: "cosine"
WARMUP_EPOCH: 1
WARMUP_TYPE: "constant"
WARMUP_CONS_LR: 1e-5
LOSS:
NAME: "prograd"
T: 1.0
TRAIN:
PRINT_FREQ: 5
MODEL:
BACKBONE:
NAME: "RN50"
TRAINER:
COOP:
CTX_INIT: True