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@@ -138,3 +138,18 @@ few_shot/kvasir/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/prompt
 few_shot/kvasir/shots_8/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1/prompt_learner/model.pth.tar-100 filter=lfs diff=lfs merge=lfs -text
 few_shot/kvasir/shots_8/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/prompt_learner/model.pth.tar-100 filter=lfs diff=lfs merge=lfs -text
 few_shot/kvasir/shots_8/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/prompt_learner/model.pth.tar-100 filter=lfs diff=lfs merge=lfs -text
+few_shot/lungcolon/shots_1/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1/prompt_learner/model.pth.tar-100 filter=lfs diff=lfs merge=lfs -text
+few_shot/lungcolon/shots_1/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/prompt_learner/model.pth.tar-100 filter=lfs diff=lfs merge=lfs -text
+few_shot/lungcolon/shots_1/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/prompt_learner/model.pth.tar-100 filter=lfs diff=lfs merge=lfs -text
+few_shot/lungcolon/shots_16/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1/prompt_learner/model.pth.tar-100 filter=lfs diff=lfs merge=lfs -text
+few_shot/lungcolon/shots_16/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/prompt_learner/model.pth.tar-100 filter=lfs diff=lfs merge=lfs -text
+few_shot/lungcolon/shots_16/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/prompt_learner/model.pth.tar-100 filter=lfs diff=lfs merge=lfs -text
+few_shot/lungcolon/shots_2/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1/prompt_learner/model.pth.tar-100 filter=lfs diff=lfs merge=lfs -text
+few_shot/lungcolon/shots_2/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/prompt_learner/model.pth.tar-100 filter=lfs diff=lfs merge=lfs -text
+few_shot/lungcolon/shots_2/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/prompt_learner/model.pth.tar-100 filter=lfs diff=lfs merge=lfs -text
+few_shot/lungcolon/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1/prompt_learner/model.pth.tar-100 filter=lfs diff=lfs merge=lfs -text
+few_shot/lungcolon/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/prompt_learner/model.pth.tar-100 filter=lfs diff=lfs merge=lfs -text
+few_shot/lungcolon/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/prompt_learner/model.pth.tar-100 filter=lfs diff=lfs merge=lfs -text
+few_shot/lungcolon/shots_8/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1/prompt_learner/model.pth.tar-100 filter=lfs diff=lfs merge=lfs -text
+few_shot/lungcolon/shots_8/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/prompt_learner/model.pth.tar-100 filter=lfs diff=lfs merge=lfs -text
+few_shot/lungcolon/shots_8/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/prompt_learner/model.pth.tar-100 filter=lfs diff=lfs merge=lfs -text

few_shot/lungcolon/shots_1/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1/log.txt

@@ -0,0 +1,432 @@
+***************
+** Arguments **
+***************
+backbone: 
+config_file: configs/trainers/BiomedCoOp_BiomedCLIP/few_shot/lungcolon.yaml
+dataset_config_file: configs/datasets/lungcolon.yaml
+eval_only: False
+head: 
+load_epoch: None
+model_dir: 
+no_train: False
+opts: ['TRAINER.BIOMEDCOOP.N_CTX', '4', 'TRAINER.BIOMEDCOOP.CSC', 'False', 'TRAINER.BIOMEDCOOP.CLASS_TOKEN_POSITION', 'end', 'DATASET.NUM_SHOTS', '1']
+output_dir: output_reproduce/lungcolon/shots_1/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1
+resume: 
+root: DATA
+seed: 1
+source_domains: None
+target_domains: None
+trainer: BiomedCoOp_BiomedCLIP
+transforms: None
+************
+** Config **
+************
+DATALOADER:
+  K_TRANSFORMS: 1
+  NUM_WORKERS: 8
+  RETURN_IMG0: False
+  TEST:
+    BATCH_SIZE: 100
+    SAMPLER: SequentialSampler
+  TRAIN_U:
+    BATCH_SIZE: 32
+    N_DOMAIN: 0
+    N_INS: 16
+    SAME_AS_X: True
+    SAMPLER: RandomSampler
+  TRAIN_X:
+    BATCH_SIZE: 4
+    N_DOMAIN: 0
+    N_INS: 16
+    SAMPLER: RandomSampler
+DATASET:
+  ALL_AS_UNLABELED: False
+  CIFAR_C_LEVEL: 1
+  CIFAR_C_TYPE: 
+  NAME: LungColon
+  NUM_LABELED: -1
+  NUM_SHOTS: 1
+  ROOT: DATA
+  SOURCE_DOMAINS: ()
+  STL10_FOLD: -1
+  SUBSAMPLE_CLASSES: all
+  TARGET_DOMAINS: ()
+  VAL_PERCENT: 0.1
+INPUT:
+  COLORJITTER_B: 0.4
+  COLORJITTER_C: 0.4
+  COLORJITTER_H: 0.1
+  COLORJITTER_S: 0.4
+  CROP_PADDING: 4
+  CUTOUT_LEN: 16
+  CUTOUT_N: 1
+  GB_K: 21
+  GB_P: 0.5
+  GN_MEAN: 0.0
+  GN_STD: 0.15
+  INTERPOLATION: bicubic
+  NO_TRANSFORM: False
+  PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
+  PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
+  RANDAUGMENT_M: 10
+  RANDAUGMENT_N: 2
+  RGS_P: 0.2
+  SIZE: (224, 224)
+  TRANSFORMS: ('random_resized_crop', 'normalize')
+MODEL:
+  BACKBONE:
+    NAME: ViT-B/16
+    PRETRAINED: True
+  HEAD:
+    ACTIVATION: relu
+    BN: True
+    DROPOUT: 0.0
+    HIDDEN_LAYERS: ()
+    NAME: 
+  INIT_WEIGHTS: 
+OPTIM:
+  ADAM_BETA1: 0.9
+  ADAM_BETA2: 0.999
+  BASE_LR_MULT: 0.1
+  GAMMA: 0.1
+  LR: 0.0025
+  LR_SCHEDULER: cosine
+  MAX_EPOCH: 100
+  MOMENTUM: 0.9
+  NAME: sgd
+  NEW_LAYERS: ()
+  RMSPROP_ALPHA: 0.99
+  SGD_DAMPNING: 0
+  SGD_NESTEROV: False
+  STAGED_LR: False
+  STEPSIZE: (-1,)
+  WARMUP_CONS_LR: 1e-05
+  WARMUP_EPOCH: 1
+  WARMUP_MIN_LR: 1e-05
+  WARMUP_RECOUNT: True
+  WARMUP_TYPE: constant
+  WEIGHT_DECAY: 0.0005
+OUTPUT_DIR: output_reproduce/lungcolon/shots_1/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1
+RESUME: 
+SEED: 1
+TEST:
+  COMPUTE_CMAT: False
+  EVALUATOR: Classification
+  FINAL_MODEL: last_step
+  NO_TEST: False
+  PER_CLASS_RESULT: False
+  SPLIT: test
+TRAIN:
+  CHECKPOINT_FREQ: 0
+  COUNT_ITER: train_x
+  PRINT_FREQ: 20
+TRAINER:
+  BIOMEDCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    KDSP_LAMBDA: 0.5
+    N_CTX: 4
+    N_PROMPTS: 50
+    PREC: fp32
+    SCCM_LAMBDA: 0.5
+    TAU: 1.5
+  CG:
+    ALPHA_D: 0.5
+    ALPHA_F: 0.5
+    EPS_D: 1.0
+    EPS_F: 1.0
+  COCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: 
+    N_CTX: 4
+    PREC: fp32
+  COOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: 
+    N_CTX: 4
+    PREC: fp32
+  DAEL:
+    CONF_THRE: 0.95
+    STRONG_TRANSFORMS: ()
+    WEIGHT_U: 0.5
+  DDAIG:
+    ALPHA: 0.5
+    CLAMP: False
+    CLAMP_MAX: 1.0
+    CLAMP_MIN: -1.0
+    G_ARCH: 
+    LMDA: 0.3
+    WARMUP: 0
+  ENTMIN:
+    LMDA: 0.001
+  FIXMATCH:
+    CONF_THRE: 0.95
+    STRONG_TRANSFORMS: ()
+    WEIGHT_U: 1.0
+  KGCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    N_CTX: 4
+    PREC: fp32
+    W: 1.0
+  M3SDA:
+    LMDA: 0.5
+    N_STEP_F: 4
+  MCD:
+    N_STEP_F: 4
+  MEANTEA:
+    EMA_ALPHA: 0.999
+    RAMPUP: 5
+    WEIGHT_U: 1.0
+  MIXMATCH:
+    MIXUP_BETA: 0.75
+    RAMPUP: 20000
+    TEMP: 2.0
+    WEIGHT_U: 100.0
+  MME:
+    LMDA: 0.1
+  NAME: BiomedCoOp_BiomedCLIP
+  PROGRAD:
+    ALPHA: 0.0
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    GM: False
+    LAMBDA: 1.0
+    NAME: 
+    N_CTX: 4
+    PREC: fp32
+    T: 1.0
+  SE:
+    CONF_THRE: 0.95
+    EMA_ALPHA: 0.999
+    RAMPUP: 300
+USE_CUDA: True
+VERBOSE: True
+VERSION: 1
+Collecting env info ...
+** System info **
+PyTorch version: 2.0.1+cu118
+Is debug build: False
+CUDA used to build PyTorch: 11.8
+ROCM used to build PyTorch: N/A
+
+OS: Ubuntu 22.04.5 LTS (x86_64)
+GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
+Clang version: Could not collect
+CMake version: version 3.25.0
+Libc version: glibc-2.35
+
+Python version: 3.10.15 (main, Oct  3 2024, 07:27:34) [GCC 11.2.0] (64-bit runtime)
+Python platform: Linux-5.15.0-134-generic-x86_64-with-glibc2.35
+Is CUDA available: True
+CUDA runtime version: 12.8.61
+CUDA_MODULE_LOADING set to: LAZY
+GPU models and configuration: 
+GPU 0: NVIDIA A100-SXM4-40GB
+GPU 1: NVIDIA A100-SXM4-40GB
+GPU 2: NVIDIA A100-SXM4-40GB
+GPU 3: NVIDIA A100-SXM4-40GB
+
+Nvidia driver version: 570.124.06
+cuDNN version: Could not collect
+HIP runtime version: N/A
+MIOpen runtime version: N/A
+Is XNNPACK available: True
+
+CPU:
+Architecture:                         x86_64
+CPU op-mode(s):                       32-bit, 64-bit
+Address sizes:                        43 bits physical, 48 bits virtual
+Byte Order:                           Little Endian
+CPU(s):                               128
+On-line CPU(s) list:                  0-127
+Vendor ID:                            AuthenticAMD
+Model name:                           AMD EPYC 7502 32-Core Processor
+CPU family:                           23
+Model:                                49
+Thread(s) per core:                   2
+Core(s) per socket:                   32
+Socket(s):                            2
+Stepping:                             0
+Frequency boost:                      enabled
+CPU max MHz:                          2500.0000
+CPU min MHz:                          1500.0000
+BogoMIPS:                             4999.71
+Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl umip rdpid overflow_recov succor smca sme sev sev_es
+Virtualization:                       AMD-V
+L1d cache:                            2 MiB (64 instances)
+L1i cache:                            2 MiB (64 instances)
+L2 cache:                             32 MiB (64 instances)
+L3 cache:                             256 MiB (16 instances)
+NUMA node(s):                         2
+NUMA node0 CPU(s):                    0-31,64-95
+NUMA node1 CPU(s):                    32-63,96-127
+Vulnerability Gather data sampling:   Not affected
+Vulnerability Itlb multihit:          Not affected
+Vulnerability L1tf:                   Not affected
+Vulnerability Mds:                    Not affected
+Vulnerability Meltdown:               Not affected
+Vulnerability Mmio stale data:        Not affected
+Vulnerability Reg file data sampling: Not affected
+Vulnerability Retbleed:               Mitigation; untrained return thunk; SMT enabled with STIBP protection
+Vulnerability Spec rstack overflow:   Mitigation; safe RET
+Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl and seccomp
+Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
+Vulnerability Spectre v2:             Mitigation; Retpolines; IBPB conditional; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
+Vulnerability Srbds:                  Not affected
+Vulnerability Tsx async abort:        Not affected
+
+Versions of relevant libraries:
+[pip3] numpy==1.26.3
+[pip3] torch==2.0.1+cu118
+[pip3] torchvision==0.15.2+cu118
+[conda] numpy                     1.26.3                   pypi_0    pypi
+[conda] torch                     2.0.1+cu118              pypi_0    pypi
+[conda] torchvision               0.15.2+cu118             pypi_0    pypi
+        Pillow (10.2.0)
+
+Loading trainer: BiomedCoOp_BiomedCLIP
+Loading dataset: LungColon
+Reading split from /data/t_kol/BiomedCoOp/DATA/LungColon/split_LungColon.json
+Loading preprocessed few-shot data from /data/t_kol/BiomedCoOp/DATA/LungColon/split_fewshot/shot_1-seed_1.pkl
+Building transform_train
++ random resized crop (size=(224, 224))
++ to torch tensor of range [0, 1]
++ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
+Building transform_test
++ resize the smaller edge to 224
++ 224x224 center crop
++ to torch tensor of range [0, 1]
++ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
+***** Dataset statistics *****
+  Dataset: LungColon
+  # classes: 5
+  # train_x: 5
+  # val: 5
+  # test: 7,500
+Loading BiomedCLIP (backbone: ViT-B/16)
+Building custom CLIP
+Initial text context: "a photo of a"
+Number of context words (tokens) for Language prompting: 4
+Turning off gradients in both the image and the text encoder
+Parameters to be updated: {'prompt_learner.ctx'}
+Parameters count: 1
+Loading evaluator: Classification
+Trainer built successfully.
+No checkpoint found, train from scratch
+Initializing summary writer for tensorboard with log_dir=output_reproduce/lungcolon/shots_1/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1/tensorboard
+epoch [1/100][1/1]	time 0.643 (0.643)	data 0.330 (0.330)	eta 0:01:03	loss 3.6067 (3.6067)	acc 25.0000 (25.0000)	lr 2.500000e-03
+epoch [2/100][1/1]	time 0.422 (0.422)	data 0.349 (0.349)	eta 0:00:41	loss 0.3924 (0.3924)	acc 100.0000 (100.0000)	lr 2.499383e-03
+epoch [3/100][1/1]	time 0.472 (0.472)	data 0.382 (0.382)	eta 0:00:45	loss 1.9022 (1.9022)	acc 50.0000 (50.0000)	lr 2.497533e-03
+epoch [4/100][1/1]	time 0.485 (0.485)	data 0.392 (0.392)	eta 0:00:46	loss 0.4175 (0.4175)	acc 75.0000 (75.0000)	lr 2.494452e-03
+epoch [5/100][1/1]	time 0.468 (0.468)	data 0.378 (0.378)	eta 0:00:44	loss 1.6573 (1.6573)	acc 25.0000 (25.0000)	lr 2.490143e-03
+epoch [6/100][1/1]	time 0.490 (0.490)	data 0.399 (0.399)	eta 0:00:46	loss 1.7869 (1.7869)	acc 50.0000 (50.0000)	lr 2.484610e-03
+epoch [7/100][1/1]	time 0.503 (0.503)	data 0.414 (0.414)	eta 0:00:46	loss 0.8363 (0.8363)	acc 75.0000 (75.0000)	lr 2.477859e-03
+epoch [8/100][1/1]	time 0.504 (0.504)	data 0.413 (0.413)	eta 0:00:46	loss 2.0814 (2.0814)	acc 50.0000 (50.0000)	lr 2.469896e-03
+epoch [9/100][1/1]	time 0.500 (0.500)	data 0.410 (0.410)	eta 0:00:45	loss 0.9925 (0.9925)	acc 50.0000 (50.0000)	lr 2.460729e-03
+epoch [10/100][1/1]	time 0.499 (0.499)	data 0.408 (0.408)	eta 0:00:44	loss 0.9941 (0.9941)	acc 75.0000 (75.0000)	lr 2.450367e-03
+epoch [11/100][1/1]	time 0.484 (0.484)	data 0.394 (0.394)	eta 0:00:43	loss 1.1588 (1.1588)	acc 25.0000 (25.0000)	lr 2.438821e-03
+epoch [12/100][1/1]	time 0.503 (0.503)	data 0.410 (0.410)	eta 0:00:44	loss 0.4948 (0.4948)	acc 100.0000 (100.0000)	lr 2.426101e-03
+epoch [13/100][1/1]	time 0.616 (0.616)	data 0.528 (0.528)	eta 0:00:53	loss 0.4876 (0.4876)	acc 75.0000 (75.0000)	lr 2.412221e-03
+epoch [14/100][1/1]	time 0.568 (0.568)	data 0.477 (0.477)	eta 0:00:48	loss 0.9474 (0.9474)	acc 50.0000 (50.0000)	lr 2.397193e-03
+epoch [15/100][1/1]	time 0.524 (0.524)	data 0.435 (0.435)	eta 0:00:44	loss 0.4534 (0.4534)	acc 100.0000 (100.0000)	lr 2.381034e-03
+epoch [16/100][1/1]	time 0.646 (0.646)	data 0.556 (0.556)	eta 0:00:54	loss 0.7927 (0.7927)	acc 50.0000 (50.0000)	lr 2.363758e-03
+epoch [17/100][1/1]	time 0.625 (0.625)	data 0.533 (0.533)	eta 0:00:51	loss 0.3571 (0.3571)	acc 100.0000 (100.0000)	lr 2.345383e-03
+epoch [18/100][1/1]	time 0.539 (0.539)	data 0.449 (0.449)	eta 0:00:44	loss 0.8421 (0.8421)	acc 50.0000 (50.0000)	lr 2.325928e-03
+epoch [19/100][1/1]	time 0.455 (0.455)	data 0.366 (0.366)	eta 0:00:36	loss 0.4127 (0.4127)	acc 100.0000 (100.0000)	lr 2.305410e-03
+epoch [20/100][1/1]	time 0.467 (0.467)	data 0.378 (0.378)	eta 0:00:37	loss 0.4569 (0.4569)	acc 100.0000 (100.0000)	lr 2.283851e-03
+epoch [21/100][1/1]	time 0.515 (0.515)	data 0.424 (0.424)	eta 0:00:40	loss 0.7235 (0.7235)	acc 50.0000 (50.0000)	lr 2.261271e-03
+epoch [22/100][1/1]	time 0.499 (0.499)	data 0.407 (0.407)	eta 0:00:38	loss 0.5112 (0.5112)	acc 50.0000 (50.0000)	lr 2.237694e-03
+epoch [23/100][1/1]	time 0.512 (0.512)	data 0.422 (0.422)	eta 0:00:39	loss 0.2789 (0.2789)	acc 100.0000 (100.0000)	lr 2.213142e-03
+epoch [24/100][1/1]	time 0.519 (0.519)	data 0.428 (0.428)	eta 0:00:39	loss 1.4827 (1.4827)	acc 75.0000 (75.0000)	lr 2.187639e-03
+epoch [25/100][1/1]	time 0.510 (0.510)	data 0.420 (0.420)	eta 0:00:38	loss 2.0628 (2.0628)	acc 25.0000 (25.0000)	lr 2.161211e-03
+epoch [26/100][1/1]	time 0.514 (0.514)	data 0.425 (0.425)	eta 0:00:38	loss 0.3497 (0.3497)	acc 100.0000 (100.0000)	lr 2.133883e-03
+epoch [27/100][1/1]	time 0.510 (0.510)	data 0.419 (0.419)	eta 0:00:37	loss 0.4413 (0.4413)	acc 100.0000 (100.0000)	lr 2.105684e-03
+epoch [28/100][1/1]	time 0.513 (0.513)	data 0.419 (0.419)	eta 0:00:36	loss 0.6707 (0.6707)	acc 50.0000 (50.0000)	lr 2.076640e-03
+epoch [29/100][1/1]	time 0.512 (0.512)	data 0.423 (0.423)	eta 0:00:36	loss 0.1853 (0.1853)	acc 100.0000 (100.0000)	lr 2.046780e-03
+epoch [30/100][1/1]	time 0.500 (0.500)	data 0.409 (0.409)	eta 0:00:34	loss 0.7038 (0.7038)	acc 75.0000 (75.0000)	lr 2.016134e-03
+epoch [31/100][1/1]	time 0.518 (0.518)	data 0.424 (0.424)	eta 0:00:35	loss 1.7615 (1.7615)	acc 50.0000 (50.0000)	lr 1.984732e-03
+epoch [32/100][1/1]	time 0.513 (0.513)	data 0.423 (0.423)	eta 0:00:34	loss 0.4970 (0.4970)	acc 100.0000 (100.0000)	lr 1.952604e-03
+epoch [33/100][1/1]	time 0.466 (0.466)	data 0.376 (0.376)	eta 0:00:31	loss 1.0666 (1.0666)	acc 50.0000 (50.0000)	lr 1.919783e-03
+epoch [34/100][1/1]	time 0.511 (0.511)	data 0.421 (0.421)	eta 0:00:33	loss 0.6215 (0.6215)	acc 75.0000 (75.0000)	lr 1.886302e-03
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+epoch [44/100][1/1]	time 0.488 (0.488)	data 0.398 (0.398)	eta 0:00:27	loss 0.9266 (0.9266)	acc 75.0000 (75.0000)	lr 1.522679e-03
+epoch [45/100][1/1]	time 0.468 (0.468)	data 0.379 (0.379)	eta 0:00:25	loss 0.4179 (0.4179)	acc 100.0000 (100.0000)	lr 1.484227e-03
+epoch [46/100][1/1]	time 0.481 (0.481)	data 0.391 (0.391)	eta 0:00:25	loss 0.5529 (0.5529)	acc 100.0000 (100.0000)	lr 1.445543e-03
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+epoch [59/100][1/1]	time 0.462 (0.462)	data 0.378 (0.378)	eta 0:00:18	loss 0.1832 (0.1832)	acc 100.0000 (100.0000)	lr 9.391376e-04
+epoch [60/100][1/1]	time 0.539 (0.539)	data 0.446 (0.446)	eta 0:00:21	loss 0.5265 (0.5265)	acc 75.0000 (75.0000)	lr 9.012611e-04
+epoch [61/100][1/1]	time 0.531 (0.531)	data 0.441 (0.441)	eta 0:00:20	loss 0.4106 (0.4106)	acc 100.0000 (100.0000)	lr 8.637288e-04
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+epoch [67/100][1/1]	time 0.507 (0.507)	data 0.416 (0.416)	eta 0:00:16	loss 0.2188 (0.2188)	acc 100.0000 (100.0000)	lr 6.478079e-04
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+epoch [79/100][1/1]	time 0.496 (0.496)	data 0.406 (0.406)	eta 0:00:10	loss 0.1782 (0.1782)	acc 100.0000 (100.0000)	lr 2.868584e-04
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+epoch [82/100][1/1]	time 0.525 (0.525)	data 0.433 (0.433)	eta 0:00:09	loss 0.2119 (0.2119)	acc 100.0000 (100.0000)	lr 2.161493e-04
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+epoch [94/100][1/1]	time 0.509 (0.509)	data 0.419 (0.419)	eta 0:00:03	loss 1.1644 (1.1644)	acc 75.0000 (75.0000)	lr 3.010405e-05
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+epoch [96/100][1/1]	time 0.514 (0.514)	data 0.424 (0.424)	eta 0:00:02	loss 0.2298 (0.2298)	acc 100.0000 (100.0000)	lr 1.538957e-05
+epoch [97/100][1/1]	time 0.495 (0.495)	data 0.406 (0.406)	eta 0:00:01	loss 0.5259 (0.5259)	acc 75.0000 (75.0000)	lr 9.856623e-06
+epoch [98/100][1/1]	time 0.553 (0.553)	data 0.465 (0.465)	eta 0:00:01	loss 0.3089 (0.3089)	acc 100.0000 (100.0000)	lr 5.547544e-06
+epoch [99/100][1/1]	time 0.537 (0.537)	data 0.445 (0.445)	eta 0:00:00	loss 0.8927 (0.8927)	acc 75.0000 (75.0000)	lr 2.466589e-06
+epoch [100/100][1/1]	time 0.522 (0.522)	data 0.431 (0.431)	eta 0:00:00	loss 0.1738 (0.1738)	acc 100.0000 (100.0000)	lr 6.167995e-07
+Checkpoint saved to "output_reproduce/lungcolon/shots_1/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1/prompt_learner/model.pth.tar-100"
+Finished training
+Do evaluation on test set
+=> result
+* total: 7,500
+* correct: 5,766
+* accuracy: 76.88%
+* error: 23.12%
+* macro_f1: 76.32%
+Elapsed: 0:01:24

few_shot/lungcolon/shots_1/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1/prompt_learner/checkpoint

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+size 1132531909

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few_shot/lungcolon/shots_1/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/log.txt

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+***************
+** Arguments **
+***************
+backbone: 
+config_file: configs/trainers/BiomedCoOp_BiomedCLIP/few_shot/lungcolon.yaml
+dataset_config_file: configs/datasets/lungcolon.yaml
+eval_only: False
+head: 
+load_epoch: None
+model_dir: 
+no_train: False
+opts: ['TRAINER.BIOMEDCOOP.N_CTX', '4', 'TRAINER.BIOMEDCOOP.CSC', 'False', 'TRAINER.BIOMEDCOOP.CLASS_TOKEN_POSITION', 'end', 'DATASET.NUM_SHOTS', '1']
+output_dir: output_reproduce/lungcolon/shots_1/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2
+resume: 
+root: DATA
+seed: 2
+source_domains: None
+target_domains: None
+trainer: BiomedCoOp_BiomedCLIP
+transforms: None
+************
+** Config **
+************
+DATALOADER:
+  K_TRANSFORMS: 1
+  NUM_WORKERS: 8
+  RETURN_IMG0: False
+  TEST:
+    BATCH_SIZE: 100
+    SAMPLER: SequentialSampler
+  TRAIN_U:
+    BATCH_SIZE: 32
+    N_DOMAIN: 0
+    N_INS: 16
+    SAME_AS_X: True
+    SAMPLER: RandomSampler
+  TRAIN_X:
+    BATCH_SIZE: 4
+    N_DOMAIN: 0
+    N_INS: 16
+    SAMPLER: RandomSampler
+DATASET:
+  ALL_AS_UNLABELED: False
+  CIFAR_C_LEVEL: 1
+  CIFAR_C_TYPE: 
+  NAME: LungColon
+  NUM_LABELED: -1
+  NUM_SHOTS: 1
+  ROOT: DATA
+  SOURCE_DOMAINS: ()
+  STL10_FOLD: -1
+  SUBSAMPLE_CLASSES: all
+  TARGET_DOMAINS: ()
+  VAL_PERCENT: 0.1
+INPUT:
+  COLORJITTER_B: 0.4
+  COLORJITTER_C: 0.4
+  COLORJITTER_H: 0.1
+  COLORJITTER_S: 0.4
+  CROP_PADDING: 4
+  CUTOUT_LEN: 16
+  CUTOUT_N: 1
+  GB_K: 21
+  GB_P: 0.5
+  GN_MEAN: 0.0
+  GN_STD: 0.15
+  INTERPOLATION: bicubic
+  NO_TRANSFORM: False
+  PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
+  PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
+  RANDAUGMENT_M: 10
+  RANDAUGMENT_N: 2
+  RGS_P: 0.2
+  SIZE: (224, 224)
+  TRANSFORMS: ('random_resized_crop', 'normalize')
+MODEL:
+  BACKBONE:
+    NAME: ViT-B/16
+    PRETRAINED: True
+  HEAD:
+    ACTIVATION: relu
+    BN: True
+    DROPOUT: 0.0
+    HIDDEN_LAYERS: ()
+    NAME: 
+  INIT_WEIGHTS: 
+OPTIM:
+  ADAM_BETA1: 0.9
+  ADAM_BETA2: 0.999
+  BASE_LR_MULT: 0.1
+  GAMMA: 0.1
+  LR: 0.0025
+  LR_SCHEDULER: cosine
+  MAX_EPOCH: 100
+  MOMENTUM: 0.9
+  NAME: sgd
+  NEW_LAYERS: ()
+  RMSPROP_ALPHA: 0.99
+  SGD_DAMPNING: 0
+  SGD_NESTEROV: False
+  STAGED_LR: False
+  STEPSIZE: (-1,)
+  WARMUP_CONS_LR: 1e-05
+  WARMUP_EPOCH: 1
+  WARMUP_MIN_LR: 1e-05
+  WARMUP_RECOUNT: True
+  WARMUP_TYPE: constant
+  WEIGHT_DECAY: 0.0005
+OUTPUT_DIR: output_reproduce/lungcolon/shots_1/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2
+RESUME: 
+SEED: 2
+TEST:
+  COMPUTE_CMAT: False
+  EVALUATOR: Classification
+  FINAL_MODEL: last_step
+  NO_TEST: False
+  PER_CLASS_RESULT: False
+  SPLIT: test
+TRAIN:
+  CHECKPOINT_FREQ: 0
+  COUNT_ITER: train_x
+  PRINT_FREQ: 20
+TRAINER:
+  BIOMEDCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    KDSP_LAMBDA: 0.5
+    N_CTX: 4
+    N_PROMPTS: 50
+    PREC: fp32
+    SCCM_LAMBDA: 0.5
+    TAU: 1.5
+  CG:
+    ALPHA_D: 0.5
+    ALPHA_F: 0.5
+    EPS_D: 1.0
+    EPS_F: 1.0
+  COCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: 
+    N_CTX: 4
+    PREC: fp32
+  COOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: 
+    N_CTX: 4
+    PREC: fp32
+  DAEL:
+    CONF_THRE: 0.95
+    STRONG_TRANSFORMS: ()
+    WEIGHT_U: 0.5
+  DDAIG:
+    ALPHA: 0.5
+    CLAMP: False
+    CLAMP_MAX: 1.0
+    CLAMP_MIN: -1.0
+    G_ARCH: 
+    LMDA: 0.3
+    WARMUP: 0
+  ENTMIN:
+    LMDA: 0.001
+  FIXMATCH:
+    CONF_THRE: 0.95
+    STRONG_TRANSFORMS: ()
+    WEIGHT_U: 1.0
+  KGCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    N_CTX: 4
+    PREC: fp32
+    W: 1.0
+  M3SDA:
+    LMDA: 0.5
+    N_STEP_F: 4
+  MCD:
+    N_STEP_F: 4
+  MEANTEA:
+    EMA_ALPHA: 0.999
+    RAMPUP: 5
+    WEIGHT_U: 1.0
+  MIXMATCH:
+    MIXUP_BETA: 0.75
+    RAMPUP: 20000
+    TEMP: 2.0
+    WEIGHT_U: 100.0
+  MME:
+    LMDA: 0.1
+  NAME: BiomedCoOp_BiomedCLIP
+  PROGRAD:
+    ALPHA: 0.0
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    GM: False
+    LAMBDA: 1.0
+    NAME: 
+    N_CTX: 4
+    PREC: fp32
+    T: 1.0
+  SE:
+    CONF_THRE: 0.95
+    EMA_ALPHA: 0.999
+    RAMPUP: 300
+USE_CUDA: True
+VERBOSE: True
+VERSION: 1
+Collecting env info ...
+** System info **
+PyTorch version: 2.0.1+cu118
+Is debug build: False
+CUDA used to build PyTorch: 11.8
+ROCM used to build PyTorch: N/A
+
+OS: Ubuntu 22.04.5 LTS (x86_64)
+GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
+Clang version: Could not collect
+CMake version: version 3.25.0
+Libc version: glibc-2.35
+
+Python version: 3.10.15 (main, Oct  3 2024, 07:27:34) [GCC 11.2.0] (64-bit runtime)
+Python platform: Linux-5.15.0-134-generic-x86_64-with-glibc2.35
+Is CUDA available: True
+CUDA runtime version: 12.8.61
+CUDA_MODULE_LOADING set to: LAZY
+GPU models and configuration: 
+GPU 0: NVIDIA A100-SXM4-40GB
+GPU 1: NVIDIA A100-SXM4-40GB
+GPU 2: NVIDIA A100-SXM4-40GB
+GPU 3: NVIDIA A100-SXM4-40GB
+
+Nvidia driver version: 570.124.06
+cuDNN version: Could not collect
+HIP runtime version: N/A
+MIOpen runtime version: N/A
+Is XNNPACK available: True
+
+CPU:
+Architecture:                         x86_64
+CPU op-mode(s):                       32-bit, 64-bit
+Address sizes:                        43 bits physical, 48 bits virtual
+Byte Order:                           Little Endian
+CPU(s):                               128
+On-line CPU(s) list:                  0-127
+Vendor ID:                            AuthenticAMD
+Model name:                           AMD EPYC 7502 32-Core Processor
+CPU family:                           23
+Model:                                49
+Thread(s) per core:                   2
+Core(s) per socket:                   32
+Socket(s):                            2
+Stepping:                             0
+Frequency boost:                      enabled
+CPU max MHz:                          2500.0000
+CPU min MHz:                          1500.0000
+BogoMIPS:                             4999.71
+Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl umip rdpid overflow_recov succor smca sme sev sev_es
+Virtualization:                       AMD-V
+L1d cache:                            2 MiB (64 instances)
+L1i cache:                            2 MiB (64 instances)
+L2 cache:                             32 MiB (64 instances)
+L3 cache:                             256 MiB (16 instances)
+NUMA node(s):                         2
+NUMA node0 CPU(s):                    0-31,64-95
+NUMA node1 CPU(s):                    32-63,96-127
+Vulnerability Gather data sampling:   Not affected
+Vulnerability Itlb multihit:          Not affected
+Vulnerability L1tf:                   Not affected
+Vulnerability Mds:                    Not affected
+Vulnerability Meltdown:               Not affected
+Vulnerability Mmio stale data:        Not affected
+Vulnerability Reg file data sampling: Not affected
+Vulnerability Retbleed:               Mitigation; untrained return thunk; SMT enabled with STIBP protection
+Vulnerability Spec rstack overflow:   Mitigation; safe RET
+Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl and seccomp
+Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
+Vulnerability Spectre v2:             Mitigation; Retpolines; IBPB conditional; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
+Vulnerability Srbds:                  Not affected
+Vulnerability Tsx async abort:        Not affected
+
+Versions of relevant libraries:
+[pip3] numpy==1.26.3
+[pip3] torch==2.0.1+cu118
+[pip3] torchvision==0.15.2+cu118
+[conda] numpy                     1.26.3                   pypi_0    pypi
+[conda] torch                     2.0.1+cu118              pypi_0    pypi
+[conda] torchvision               0.15.2+cu118             pypi_0    pypi
+        Pillow (10.2.0)
+
+Loading trainer: BiomedCoOp_BiomedCLIP
+Loading dataset: LungColon
+Reading split from /data/t_kol/BiomedCoOp/DATA/LungColon/split_LungColon.json
+Loading preprocessed few-shot data from /data/t_kol/BiomedCoOp/DATA/LungColon/split_fewshot/shot_1-seed_2.pkl
+Building transform_train
++ random resized crop (size=(224, 224))
++ to torch tensor of range [0, 1]
++ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
+Building transform_test
++ resize the smaller edge to 224
++ 224x224 center crop
++ to torch tensor of range [0, 1]
++ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
+***** Dataset statistics *****
+  Dataset: LungColon
+  # classes: 5
+  # train_x: 5
+  # val: 5
+  # test: 7,500
+Loading BiomedCLIP (backbone: ViT-B/16)
+Building custom CLIP
+Initial text context: "a photo of a"
+Number of context words (tokens) for Language prompting: 4
+Turning off gradients in both the image and the text encoder
+Parameters to be updated: {'prompt_learner.ctx'}
+Parameters count: 1
+Loading evaluator: Classification
+Trainer built successfully.
+No checkpoint found, train from scratch
+Initializing summary writer for tensorboard with log_dir=output_reproduce/lungcolon/shots_1/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/tensorboard
+epoch [1/100][1/1]	time 0.670 (0.670)	data 0.333 (0.333)	eta 0:01:06	loss 2.7398 (2.7398)	acc 25.0000 (25.0000)	lr 2.500000e-03
+epoch [2/100][1/1]	time 0.481 (0.481)	data 0.408 (0.408)	eta 0:00:47	loss 1.5690 (1.5690)	acc 25.0000 (25.0000)	lr 2.499383e-03
+epoch [3/100][1/1]	time 0.503 (0.503)	data 0.414 (0.414)	eta 0:00:48	loss 0.9768 (0.9768)	acc 75.0000 (75.0000)	lr 2.497533e-03
+epoch [4/100][1/1]	time 0.485 (0.485)	data 0.395 (0.395)	eta 0:00:46	loss 1.1608 (1.1608)	acc 75.0000 (75.0000)	lr 2.494452e-03
+epoch [5/100][1/1]	time 0.514 (0.514)	data 0.424 (0.424)	eta 0:00:48	loss 3.0443 (3.0443)	acc 25.0000 (25.0000)	lr 2.490143e-03
+epoch [6/100][1/1]	time 0.525 (0.525)	data 0.435 (0.435)	eta 0:00:49	loss 2.2224 (2.2224)	acc 25.0000 (25.0000)	lr 2.484610e-03
+epoch [7/100][1/1]	time 0.517 (0.517)	data 0.427 (0.427)	eta 0:00:48	loss 0.9165 (0.9165)	acc 50.0000 (50.0000)	lr 2.477859e-03
+epoch [8/100][1/1]	time 0.515 (0.515)	data 0.425 (0.425)	eta 0:00:47	loss 0.5788 (0.5788)	acc 75.0000 (75.0000)	lr 2.469896e-03
+epoch [9/100][1/1]	time 0.528 (0.528)	data 0.438 (0.438)	eta 0:00:48	loss 0.3549 (0.3549)	acc 100.0000 (100.0000)	lr 2.460729e-03
+epoch [10/100][1/1]	time 0.530 (0.530)	data 0.441 (0.441)	eta 0:00:47	loss 1.8041 (1.8041)	acc 50.0000 (50.0000)	lr 2.450367e-03
+epoch [11/100][1/1]	time 0.536 (0.536)	data 0.444 (0.444)	eta 0:00:47	loss 0.9989 (0.9989)	acc 75.0000 (75.0000)	lr 2.438821e-03
+epoch [12/100][1/1]	time 0.493 (0.493)	data 0.402 (0.402)	eta 0:00:43	loss 0.9519 (0.9519)	acc 25.0000 (25.0000)	lr 2.426101e-03
+epoch [13/100][1/1]	time 0.505 (0.505)	data 0.416 (0.416)	eta 0:00:43	loss 1.6514 (1.6514)	acc 75.0000 (75.0000)	lr 2.412221e-03
+epoch [14/100][1/1]	time 0.524 (0.524)	data 0.435 (0.435)	eta 0:00:45	loss 1.8080 (1.8080)	acc 50.0000 (50.0000)	lr 2.397193e-03
+epoch [15/100][1/1]	time 0.514 (0.514)	data 0.424 (0.424)	eta 0:00:43	loss 1.3849 (1.3849)	acc 50.0000 (50.0000)	lr 2.381034e-03
+epoch [16/100][1/1]	time 0.539 (0.539)	data 0.450 (0.450)	eta 0:00:45	loss 0.2832 (0.2832)	acc 100.0000 (100.0000)	lr 2.363758e-03
+epoch [17/100][1/1]	time 0.501 (0.501)	data 0.412 (0.412)	eta 0:00:41	loss 1.1893 (1.1893)	acc 75.0000 (75.0000)	lr 2.345383e-03
+epoch [18/100][1/1]	time 0.541 (0.541)	data 0.451 (0.451)	eta 0:00:44	loss 1.3462 (1.3462)	acc 50.0000 (50.0000)	lr 2.325928e-03
+epoch [19/100][1/1]	time 0.540 (0.540)	data 0.448 (0.448)	eta 0:00:43	loss 0.1733 (0.1733)	acc 100.0000 (100.0000)	lr 2.305410e-03
+epoch [20/100][1/1]	time 0.526 (0.526)	data 0.434 (0.434)	eta 0:00:42	loss 1.7070 (1.7070)	acc 50.0000 (50.0000)	lr 2.283851e-03
+epoch [21/100][1/1]	time 0.548 (0.548)	data 0.456 (0.456)	eta 0:00:43	loss 1.0116 (1.0116)	acc 50.0000 (50.0000)	lr 2.261271e-03
+epoch [22/100][1/1]	time 0.544 (0.544)	data 0.452 (0.452)	eta 0:00:42	loss 1.1234 (1.1234)	acc 50.0000 (50.0000)	lr 2.237694e-03
+epoch [23/100][1/1]	time 0.534 (0.534)	data 0.442 (0.442)	eta 0:00:41	loss 0.3223 (0.3223)	acc 100.0000 (100.0000)	lr 2.213142e-03
+epoch [24/100][1/1]	time 0.533 (0.533)	data 0.440 (0.440)	eta 0:00:40	loss 0.6642 (0.6642)	acc 50.0000 (50.0000)	lr 2.187639e-03
+epoch [25/100][1/1]	time 0.526 (0.526)	data 0.434 (0.434)	eta 0:00:39	loss 1.6087 (1.6087)	acc 50.0000 (50.0000)	lr 2.161211e-03
+epoch [26/100][1/1]	time 0.550 (0.550)	data 0.460 (0.460)	eta 0:00:40	loss 1.5239 (1.5239)	acc 50.0000 (50.0000)	lr 2.133883e-03
+epoch [27/100][1/1]	time 0.547 (0.547)	data 0.456 (0.456)	eta 0:00:39	loss 0.5269 (0.5269)	acc 75.0000 (75.0000)	lr 2.105684e-03
+epoch [28/100][1/1]	time 0.528 (0.528)	data 0.438 (0.438)	eta 0:00:37	loss 0.3741 (0.3741)	acc 100.0000 (100.0000)	lr 2.076640e-03
+epoch [29/100][1/1]	time 0.524 (0.524)	data 0.435 (0.435)	eta 0:00:37	loss 0.7566 (0.7566)	acc 75.0000 (75.0000)	lr 2.046780e-03
+epoch [30/100][1/1]	time 0.559 (0.559)	data 0.468 (0.468)	eta 0:00:39	loss 0.2586 (0.2586)	acc 100.0000 (100.0000)	lr 2.016134e-03
+epoch [31/100][1/1]	time 0.539 (0.539)	data 0.448 (0.448)	eta 0:00:37	loss 0.6194 (0.6194)	acc 75.0000 (75.0000)	lr 1.984732e-03
+epoch [32/100][1/1]	time 0.527 (0.527)	data 0.435 (0.435)	eta 0:00:35	loss 0.6208 (0.6208)	acc 50.0000 (50.0000)	lr 1.952604e-03
+epoch [33/100][1/1]	time 0.556 (0.556)	data 0.464 (0.464)	eta 0:00:37	loss 0.5206 (0.5206)	acc 100.0000 (100.0000)	lr 1.919783e-03
+epoch [34/100][1/1]	time 0.536 (0.536)	data 0.445 (0.445)	eta 0:00:35	loss 0.9006 (0.9006)	acc 50.0000 (50.0000)	lr 1.886302e-03
+epoch [35/100][1/1]	time 0.528 (0.528)	data 0.438 (0.438)	eta 0:00:34	loss 1.3922 (1.3922)	acc 50.0000 (50.0000)	lr 1.852192e-03
+epoch [36/100][1/1]	time 0.527 (0.527)	data 0.437 (0.437)	eta 0:00:33	loss 0.2214 (0.2214)	acc 100.0000 (100.0000)	lr 1.817488e-03
+epoch [37/100][1/1]	time 0.526 (0.526)	data 0.436 (0.436)	eta 0:00:33	loss 0.4202 (0.4202)	acc 100.0000 (100.0000)	lr 1.782224e-03
+epoch [38/100][1/1]	time 0.498 (0.498)	data 0.409 (0.409)	eta 0:00:30	loss 0.6245 (0.6245)	acc 75.0000 (75.0000)	lr 1.746435e-03
+epoch [39/100][1/1]	time 0.526 (0.526)	data 0.437 (0.437)	eta 0:00:32	loss 0.9426 (0.9426)	acc 50.0000 (50.0000)	lr 1.710156e-03
+epoch [40/100][1/1]	time 0.516 (0.516)	data 0.427 (0.427)	eta 0:00:30	loss 1.4610 (1.4610)	acc 75.0000 (75.0000)	lr 1.673422e-03
+epoch [41/100][1/1]	time 0.550 (0.550)	data 0.460 (0.460)	eta 0:00:32	loss 0.6023 (0.6023)	acc 75.0000 (75.0000)	lr 1.636271e-03
+epoch [42/100][1/1]	time 0.530 (0.530)	data 0.441 (0.441)	eta 0:00:30	loss 0.6100 (0.6100)	acc 75.0000 (75.0000)	lr 1.598739e-03
+epoch [43/100][1/1]	time 0.529 (0.529)	data 0.438 (0.438)	eta 0:00:30	loss 1.1334 (1.1334)	acc 25.0000 (25.0000)	lr 1.560862e-03
+epoch [44/100][1/1]	time 0.540 (0.540)	data 0.448 (0.448)	eta 0:00:30	loss 0.3915 (0.3915)	acc 100.0000 (100.0000)	lr 1.522679e-03
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+epoch [54/100][1/1]	time 0.531 (0.531)	data 0.440 (0.440)	eta 0:00:24	loss 0.1661 (0.1661)	acc 100.0000 (100.0000)	lr 1.132365e-03
+epoch [55/100][1/1]	time 0.529 (0.529)	data 0.439 (0.439)	eta 0:00:23	loss 0.8857 (0.8857)	acc 75.0000 (75.0000)	lr 1.093333e-03
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+epoch [80/100][1/1]	time 0.535 (0.535)	data 0.445 (0.445)	eta 0:00:10	loss 0.4398 (0.4398)	acc 75.0000 (75.0000)	lr 2.623062e-04
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+epoch [83/100][1/1]	time 0.495 (0.495)	data 0.405 (0.405)	eta 0:00:08	loss 0.2825 (0.2825)	acc 100.0000 (100.0000)	lr 1.945901e-04
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+epoch [85/100][1/1]	time 0.537 (0.537)	data 0.446 (0.446)	eta 0:00:08	loss 0.3052 (0.3052)	acc 100.0000 (100.0000)	lr 1.546166e-04
+epoch [86/100][1/1]	time 0.508 (0.508)	data 0.419 (0.419)	eta 0:00:07	loss 0.3670 (0.3670)	acc 100.0000 (100.0000)	lr 1.362418e-04
+epoch [87/100][1/1]	time 0.528 (0.528)	data 0.436 (0.436)	eta 0:00:06	loss 0.5110 (0.5110)	acc 75.0000 (75.0000)	lr 1.189662e-04
+epoch [88/100][1/1]	time 0.535 (0.535)	data 0.443 (0.443)	eta 0:00:06	loss 0.2960 (0.2960)	acc 100.0000 (100.0000)	lr 1.028067e-04
+epoch [89/100][1/1]	time 0.535 (0.535)	data 0.443 (0.443)	eta 0:00:05	loss 0.2820 (0.2820)	acc 100.0000 (100.0000)	lr 8.777939e-05
+epoch [90/100][1/1]	time 0.544 (0.544)	data 0.452 (0.452)	eta 0:00:05	loss 0.2463 (0.2463)	acc 100.0000 (100.0000)	lr 7.389904e-05
+epoch [91/100][1/1]	time 0.534 (0.534)	data 0.444 (0.444)	eta 0:00:04	loss 0.4023 (0.4023)	acc 100.0000 (100.0000)	lr 6.117935e-05
+epoch [92/100][1/1]	time 0.526 (0.526)	data 0.437 (0.437)	eta 0:00:04	loss 0.7843 (0.7843)	acc 75.0000 (75.0000)	lr 4.963289e-05
+epoch [93/100][1/1]	time 0.520 (0.520)	data 0.433 (0.433)	eta 0:00:03	loss 0.8068 (0.8068)	acc 75.0000 (75.0000)	lr 3.927105e-05
+epoch [94/100][1/1]	time 0.520 (0.520)	data 0.434 (0.434)	eta 0:00:03	loss 0.3091 (0.3091)	acc 100.0000 (100.0000)	lr 3.010405e-05
+epoch [95/100][1/1]	time 0.528 (0.528)	data 0.438 (0.438)	eta 0:00:02	loss 0.3713 (0.3713)	acc 100.0000 (100.0000)	lr 2.214094e-05
+epoch [96/100][1/1]	time 0.526 (0.526)	data 0.436 (0.436)	eta 0:00:02	loss 0.3506 (0.3506)	acc 100.0000 (100.0000)	lr 1.538957e-05
+epoch [97/100][1/1]	time 0.537 (0.537)	data 0.444 (0.444)	eta 0:00:01	loss 0.6387 (0.6387)	acc 75.0000 (75.0000)	lr 9.856623e-06
+epoch [98/100][1/1]	time 0.531 (0.531)	data 0.442 (0.442)	eta 0:00:01	loss 0.4887 (0.4887)	acc 75.0000 (75.0000)	lr 5.547544e-06
+epoch [99/100][1/1]	time 0.515 (0.515)	data 0.422 (0.422)	eta 0:00:00	loss 0.4355 (0.4355)	acc 75.0000 (75.0000)	lr 2.466589e-06
+epoch [100/100][1/1]	time 0.545 (0.545)	data 0.453 (0.453)	eta 0:00:00	loss 0.3825 (0.3825)	acc 100.0000 (100.0000)	lr 6.167995e-07
+Checkpoint saved to "output_reproduce/lungcolon/shots_1/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/prompt_learner/model.pth.tar-100"
+Finished training
+Do evaluation on test set
+=> result
+* total: 7,500
+* correct: 6,100
+* accuracy: 81.33%
+* error: 18.67%
+* macro_f1: 80.80%
+Elapsed: 0:01:25

few_shot/lungcolon/shots_1/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/prompt_learner/checkpoint

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few_shot/lungcolon/shots_1/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/prompt_learner/model.pth.tar-100

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few_shot/lungcolon/shots_1/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/tensorboard/events.out.tfevents.1742384669.impactlab-server.2414944.0

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few_shot/lungcolon/shots_1/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/log.txt

@@ -0,0 +1,432 @@
+***************
+** Arguments **
+***************
+backbone: 
+config_file: configs/trainers/BiomedCoOp_BiomedCLIP/few_shot/lungcolon.yaml
+dataset_config_file: configs/datasets/lungcolon.yaml
+eval_only: False
+head: 
+load_epoch: None
+model_dir: 
+no_train: False
+opts: ['TRAINER.BIOMEDCOOP.N_CTX', '4', 'TRAINER.BIOMEDCOOP.CSC', 'False', 'TRAINER.BIOMEDCOOP.CLASS_TOKEN_POSITION', 'end', 'DATASET.NUM_SHOTS', '1']
+output_dir: output_reproduce/lungcolon/shots_1/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3
+resume: 
+root: DATA
+seed: 3
+source_domains: None
+target_domains: None
+trainer: BiomedCoOp_BiomedCLIP
+transforms: None
+************
+** Config **
+************
+DATALOADER:
+  K_TRANSFORMS: 1
+  NUM_WORKERS: 8
+  RETURN_IMG0: False
+  TEST:
+    BATCH_SIZE: 100
+    SAMPLER: SequentialSampler
+  TRAIN_U:
+    BATCH_SIZE: 32
+    N_DOMAIN: 0
+    N_INS: 16
+    SAME_AS_X: True
+    SAMPLER: RandomSampler
+  TRAIN_X:
+    BATCH_SIZE: 4
+    N_DOMAIN: 0
+    N_INS: 16
+    SAMPLER: RandomSampler
+DATASET:
+  ALL_AS_UNLABELED: False
+  CIFAR_C_LEVEL: 1
+  CIFAR_C_TYPE: 
+  NAME: LungColon
+  NUM_LABELED: -1
+  NUM_SHOTS: 1
+  ROOT: DATA
+  SOURCE_DOMAINS: ()
+  STL10_FOLD: -1
+  SUBSAMPLE_CLASSES: all
+  TARGET_DOMAINS: ()
+  VAL_PERCENT: 0.1
+INPUT:
+  COLORJITTER_B: 0.4
+  COLORJITTER_C: 0.4
+  COLORJITTER_H: 0.1
+  COLORJITTER_S: 0.4
+  CROP_PADDING: 4
+  CUTOUT_LEN: 16
+  CUTOUT_N: 1
+  GB_K: 21
+  GB_P: 0.5
+  GN_MEAN: 0.0
+  GN_STD: 0.15
+  INTERPOLATION: bicubic
+  NO_TRANSFORM: False
+  PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
+  PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
+  RANDAUGMENT_M: 10
+  RANDAUGMENT_N: 2
+  RGS_P: 0.2
+  SIZE: (224, 224)
+  TRANSFORMS: ('random_resized_crop', 'normalize')
+MODEL:
+  BACKBONE:
+    NAME: ViT-B/16
+    PRETRAINED: True
+  HEAD:
+    ACTIVATION: relu
+    BN: True
+    DROPOUT: 0.0
+    HIDDEN_LAYERS: ()
+    NAME: 
+  INIT_WEIGHTS: 
+OPTIM:
+  ADAM_BETA1: 0.9
+  ADAM_BETA2: 0.999
+  BASE_LR_MULT: 0.1
+  GAMMA: 0.1
+  LR: 0.0025
+  LR_SCHEDULER: cosine
+  MAX_EPOCH: 100
+  MOMENTUM: 0.9
+  NAME: sgd
+  NEW_LAYERS: ()
+  RMSPROP_ALPHA: 0.99
+  SGD_DAMPNING: 0
+  SGD_NESTEROV: False
+  STAGED_LR: False
+  STEPSIZE: (-1,)
+  WARMUP_CONS_LR: 1e-05
+  WARMUP_EPOCH: 1
+  WARMUP_MIN_LR: 1e-05
+  WARMUP_RECOUNT: True
+  WARMUP_TYPE: constant
+  WEIGHT_DECAY: 0.0005
+OUTPUT_DIR: output_reproduce/lungcolon/shots_1/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3
+RESUME: 
+SEED: 3
+TEST:
+  COMPUTE_CMAT: False
+  EVALUATOR: Classification
+  FINAL_MODEL: last_step
+  NO_TEST: False
+  PER_CLASS_RESULT: False
+  SPLIT: test
+TRAIN:
+  CHECKPOINT_FREQ: 0
+  COUNT_ITER: train_x
+  PRINT_FREQ: 20
+TRAINER:
+  BIOMEDCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    KDSP_LAMBDA: 0.5
+    N_CTX: 4
+    N_PROMPTS: 50
+    PREC: fp32
+    SCCM_LAMBDA: 0.5
+    TAU: 1.5
+  CG:
+    ALPHA_D: 0.5
+    ALPHA_F: 0.5
+    EPS_D: 1.0
+    EPS_F: 1.0
+  COCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: 
+    N_CTX: 4
+    PREC: fp32
+  COOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: 
+    N_CTX: 4
+    PREC: fp32
+  DAEL:
+    CONF_THRE: 0.95
+    STRONG_TRANSFORMS: ()
+    WEIGHT_U: 0.5
+  DDAIG:
+    ALPHA: 0.5
+    CLAMP: False
+    CLAMP_MAX: 1.0
+    CLAMP_MIN: -1.0
+    G_ARCH: 
+    LMDA: 0.3
+    WARMUP: 0
+  ENTMIN:
+    LMDA: 0.001
+  FIXMATCH:
+    CONF_THRE: 0.95
+    STRONG_TRANSFORMS: ()
+    WEIGHT_U: 1.0
+  KGCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    N_CTX: 4
+    PREC: fp32
+    W: 1.0
+  M3SDA:
+    LMDA: 0.5
+    N_STEP_F: 4
+  MCD:
+    N_STEP_F: 4
+  MEANTEA:
+    EMA_ALPHA: 0.999
+    RAMPUP: 5
+    WEIGHT_U: 1.0
+  MIXMATCH:
+    MIXUP_BETA: 0.75
+    RAMPUP: 20000
+    TEMP: 2.0
+    WEIGHT_U: 100.0
+  MME:
+    LMDA: 0.1
+  NAME: BiomedCoOp_BiomedCLIP
+  PROGRAD:
+    ALPHA: 0.0
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    GM: False
+    LAMBDA: 1.0
+    NAME: 
+    N_CTX: 4
+    PREC: fp32
+    T: 1.0
+  SE:
+    CONF_THRE: 0.95
+    EMA_ALPHA: 0.999
+    RAMPUP: 300
+USE_CUDA: True
+VERBOSE: True
+VERSION: 1
+Collecting env info ...
+** System info **
+PyTorch version: 2.0.1+cu118
+Is debug build: False
+CUDA used to build PyTorch: 11.8
+ROCM used to build PyTorch: N/A
+
+OS: Ubuntu 22.04.5 LTS (x86_64)
+GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
+Clang version: Could not collect
+CMake version: version 3.25.0
+Libc version: glibc-2.35
+
+Python version: 3.10.15 (main, Oct  3 2024, 07:27:34) [GCC 11.2.0] (64-bit runtime)
+Python platform: Linux-5.15.0-134-generic-x86_64-with-glibc2.35
+Is CUDA available: True
+CUDA runtime version: 12.8.61
+CUDA_MODULE_LOADING set to: LAZY
+GPU models and configuration: 
+GPU 0: NVIDIA A100-SXM4-40GB
+GPU 1: NVIDIA A100-SXM4-40GB
+GPU 2: NVIDIA A100-SXM4-40GB
+GPU 3: NVIDIA A100-SXM4-40GB
+
+Nvidia driver version: 570.124.06
+cuDNN version: Could not collect
+HIP runtime version: N/A
+MIOpen runtime version: N/A
+Is XNNPACK available: True
+
+CPU:
+Architecture:                         x86_64
+CPU op-mode(s):                       32-bit, 64-bit
+Address sizes:                        43 bits physical, 48 bits virtual
+Byte Order:                           Little Endian
+CPU(s):                               128
+On-line CPU(s) list:                  0-127
+Vendor ID:                            AuthenticAMD
+Model name:                           AMD EPYC 7502 32-Core Processor
+CPU family:                           23
+Model:                                49
+Thread(s) per core:                   2
+Core(s) per socket:                   32
+Socket(s):                            2
+Stepping:                             0
+Frequency boost:                      enabled
+CPU max MHz:                          2500.0000
+CPU min MHz:                          1500.0000
+BogoMIPS:                             4999.71
+Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl umip rdpid overflow_recov succor smca sme sev sev_es
+Virtualization:                       AMD-V
+L1d cache:                            2 MiB (64 instances)
+L1i cache:                            2 MiB (64 instances)
+L2 cache:                             32 MiB (64 instances)
+L3 cache:                             256 MiB (16 instances)
+NUMA node(s):                         2
+NUMA node0 CPU(s):                    0-31,64-95
+NUMA node1 CPU(s):                    32-63,96-127
+Vulnerability Gather data sampling:   Not affected
+Vulnerability Itlb multihit:          Not affected
+Vulnerability L1tf:                   Not affected
+Vulnerability Mds:                    Not affected
+Vulnerability Meltdown:               Not affected
+Vulnerability Mmio stale data:        Not affected
+Vulnerability Reg file data sampling: Not affected
+Vulnerability Retbleed:               Mitigation; untrained return thunk; SMT enabled with STIBP protection
+Vulnerability Spec rstack overflow:   Mitigation; safe RET
+Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl and seccomp
+Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
+Vulnerability Spectre v2:             Mitigation; Retpolines; IBPB conditional; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
+Vulnerability Srbds:                  Not affected
+Vulnerability Tsx async abort:        Not affected
+
+Versions of relevant libraries:
+[pip3] numpy==1.26.3
+[pip3] torch==2.0.1+cu118
+[pip3] torchvision==0.15.2+cu118
+[conda] numpy                     1.26.3                   pypi_0    pypi
+[conda] torch                     2.0.1+cu118              pypi_0    pypi
+[conda] torchvision               0.15.2+cu118             pypi_0    pypi
+        Pillow (10.2.0)
+
+Loading trainer: BiomedCoOp_BiomedCLIP
+Loading dataset: LungColon
+Reading split from /data/t_kol/BiomedCoOp/DATA/LungColon/split_LungColon.json
+Loading preprocessed few-shot data from /data/t_kol/BiomedCoOp/DATA/LungColon/split_fewshot/shot_1-seed_3.pkl
+Building transform_train
++ random resized crop (size=(224, 224))
++ to torch tensor of range [0, 1]
++ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
+Building transform_test
++ resize the smaller edge to 224
++ 224x224 center crop
++ to torch tensor of range [0, 1]
++ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
+***** Dataset statistics *****
+  Dataset: LungColon
+  # classes: 5
+  # train_x: 5
+  # val: 5
+  # test: 7,500
+Loading BiomedCLIP (backbone: ViT-B/16)
+Building custom CLIP
+Initial text context: "a photo of a"
+Number of context words (tokens) for Language prompting: 4
+Turning off gradients in both the image and the text encoder
+Parameters to be updated: {'prompt_learner.ctx'}
+Parameters count: 1
+Loading evaluator: Classification
+Trainer built successfully.
+No checkpoint found, train from scratch
+Initializing summary writer for tensorboard with log_dir=output_reproduce/lungcolon/shots_1/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/tensorboard
+epoch [1/100][1/1]	time 0.636 (0.636)	data 0.333 (0.333)	eta 0:01:02	loss 2.7824 (2.7824)	acc 0.0000 (0.0000)	lr 2.500000e-03
+epoch [2/100][1/1]	time 0.497 (0.497)	data 0.419 (0.419)	eta 0:00:48	loss 1.9266 (1.9266)	acc 50.0000 (50.0000)	lr 2.499383e-03
+epoch [3/100][1/1]	time 0.508 (0.508)	data 0.420 (0.420)	eta 0:00:49	loss 2.5068 (2.5068)	acc 50.0000 (50.0000)	lr 2.497533e-03
+epoch [4/100][1/1]	time 0.516 (0.516)	data 0.426 (0.426)	eta 0:00:49	loss 2.1831 (2.1831)	acc 50.0000 (50.0000)	lr 2.494452e-03
+epoch [5/100][1/1]	time 0.549 (0.549)	data 0.457 (0.457)	eta 0:00:52	loss 1.8218 (1.8218)	acc 25.0000 (25.0000)	lr 2.490143e-03
+epoch [6/100][1/1]	time 0.524 (0.524)	data 0.433 (0.433)	eta 0:00:49	loss 1.4551 (1.4551)	acc 50.0000 (50.0000)	lr 2.484610e-03
+epoch [7/100][1/1]	time 0.534 (0.534)	data 0.444 (0.444)	eta 0:00:49	loss 1.4141 (1.4141)	acc 25.0000 (25.0000)	lr 2.477859e-03
+epoch [8/100][1/1]	time 0.550 (0.550)	data 0.460 (0.460)	eta 0:00:50	loss 2.3141 (2.3141)	acc 25.0000 (25.0000)	lr 2.469896e-03
+epoch [9/100][1/1]	time 0.532 (0.532)	data 0.442 (0.442)	eta 0:00:48	loss 0.5955 (0.5955)	acc 100.0000 (100.0000)	lr 2.460729e-03
+epoch [10/100][1/1]	time 0.500 (0.500)	data 0.410 (0.410)	eta 0:00:44	loss 1.4390 (1.4390)	acc 50.0000 (50.0000)	lr 2.450367e-03
+epoch [11/100][1/1]	time 0.516 (0.516)	data 0.426 (0.426)	eta 0:00:45	loss 0.7238 (0.7238)	acc 75.0000 (75.0000)	lr 2.438821e-03
+epoch [12/100][1/1]	time 0.546 (0.546)	data 0.457 (0.457)	eta 0:00:48	loss 2.3065 (2.3065)	acc 75.0000 (75.0000)	lr 2.426101e-03
+epoch [13/100][1/1]	time 0.553 (0.553)	data 0.462 (0.462)	eta 0:00:48	loss 1.4363 (1.4363)	acc 50.0000 (50.0000)	lr 2.412221e-03
+epoch [14/100][1/1]	time 0.535 (0.535)	data 0.446 (0.446)	eta 0:00:46	loss 2.2962 (2.2962)	acc 50.0000 (50.0000)	lr 2.397193e-03
+epoch [15/100][1/1]	time 0.533 (0.533)	data 0.442 (0.442)	eta 0:00:45	loss 0.5370 (0.5370)	acc 75.0000 (75.0000)	lr 2.381034e-03
+epoch [16/100][1/1]	time 0.540 (0.540)	data 0.450 (0.450)	eta 0:00:45	loss 1.1131 (1.1131)	acc 25.0000 (25.0000)	lr 2.363758e-03
+epoch [17/100][1/1]	time 0.526 (0.526)	data 0.434 (0.434)	eta 0:00:43	loss 2.5456 (2.5456)	acc 25.0000 (25.0000)	lr 2.345383e-03
+epoch [18/100][1/1]	time 0.536 (0.536)	data 0.443 (0.443)	eta 0:00:43	loss 1.0077 (1.0077)	acc 75.0000 (75.0000)	lr 2.325928e-03
+epoch [19/100][1/1]	time 0.551 (0.551)	data 0.462 (0.462)	eta 0:00:44	loss 1.0131 (1.0131)	acc 50.0000 (50.0000)	lr 2.305410e-03
+epoch [20/100][1/1]	time 0.499 (0.499)	data 0.410 (0.410)	eta 0:00:39	loss 1.7645 (1.7645)	acc 50.0000 (50.0000)	lr 2.283851e-03
+epoch [21/100][1/1]	time 0.553 (0.553)	data 0.463 (0.463)	eta 0:00:43	loss 0.3329 (0.3329)	acc 100.0000 (100.0000)	lr 2.261271e-03
+epoch [22/100][1/1]	time 0.551 (0.551)	data 0.459 (0.459)	eta 0:00:42	loss 0.3454 (0.3454)	acc 100.0000 (100.0000)	lr 2.237694e-03
+epoch [23/100][1/1]	time 0.504 (0.504)	data 0.412 (0.412)	eta 0:00:38	loss 2.1488 (2.1488)	acc 50.0000 (50.0000)	lr 2.213142e-03
+epoch [24/100][1/1]	time 0.538 (0.538)	data 0.449 (0.449)	eta 0:00:40	loss 1.5072 (1.5072)	acc 50.0000 (50.0000)	lr 2.187639e-03
+epoch [25/100][1/1]	time 0.533 (0.533)	data 0.441 (0.441)	eta 0:00:39	loss 1.6716 (1.6716)	acc 50.0000 (50.0000)	lr 2.161211e-03
+epoch [26/100][1/1]	time 0.538 (0.538)	data 0.446 (0.446)	eta 0:00:39	loss 0.6508 (0.6508)	acc 75.0000 (75.0000)	lr 2.133883e-03
+epoch [27/100][1/1]	time 0.539 (0.539)	data 0.448 (0.448)	eta 0:00:39	loss 0.8025 (0.8025)	acc 75.0000 (75.0000)	lr 2.105684e-03
+epoch [28/100][1/1]	time 0.537 (0.537)	data 0.447 (0.447)	eta 0:00:38	loss 0.9806 (0.9806)	acc 50.0000 (50.0000)	lr 2.076640e-03
+epoch [29/100][1/1]	time 0.517 (0.517)	data 0.428 (0.428)	eta 0:00:36	loss 1.4591 (1.4591)	acc 50.0000 (50.0000)	lr 2.046780e-03
+epoch [30/100][1/1]	time 0.523 (0.523)	data 0.433 (0.433)	eta 0:00:36	loss 0.4595 (0.4595)	acc 100.0000 (100.0000)	lr 2.016134e-03
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+epoch [46/100][1/1]	time 0.530 (0.530)	data 0.441 (0.441)	eta 0:00:28	loss 0.8654 (0.8654)	acc 75.0000 (75.0000)	lr 1.445543e-03
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+epoch [60/100][1/1]	time 0.537 (0.537)	data 0.446 (0.446)	eta 0:00:21	loss 0.3551 (0.3551)	acc 100.0000 (100.0000)	lr 9.012611e-04
+epoch [61/100][1/1]	time 0.507 (0.507)	data 0.417 (0.417)	eta 0:00:19	loss 0.9933 (0.9933)	acc 50.0000 (50.0000)	lr 8.637288e-04
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+epoch [82/100][1/1]	time 0.486 (0.486)	data 0.397 (0.397)	eta 0:00:08	loss 1.6578 (1.6578)	acc 75.0000 (75.0000)	lr 2.161493e-04
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+epoch [94/100][1/1]	time 0.548 (0.548)	data 0.457 (0.457)	eta 0:00:03	loss 0.4888 (0.4888)	acc 100.0000 (100.0000)	lr 3.010405e-05
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+epoch [97/100][1/1]	time 0.577 (0.577)	data 0.485 (0.485)	eta 0:00:01	loss 2.2358 (2.2358)	acc 75.0000 (75.0000)	lr 9.856623e-06
+epoch [98/100][1/1]	time 0.559 (0.559)	data 0.466 (0.466)	eta 0:00:01	loss 1.3712 (1.3712)	acc 50.0000 (50.0000)	lr 5.547544e-06
+epoch [99/100][1/1]	time 0.587 (0.587)	data 0.497 (0.497)	eta 0:00:00	loss 1.0385 (1.0385)	acc 75.0000 (75.0000)	lr 2.466589e-06
+epoch [100/100][1/1]	time 0.584 (0.584)	data 0.491 (0.491)	eta 0:00:00	loss 1.3290 (1.3290)	acc 50.0000 (50.0000)	lr 6.167995e-07
+Checkpoint saved to "output_reproduce/lungcolon/shots_1/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/prompt_learner/model.pth.tar-100"
+Finished training
+Do evaluation on test set
+=> result
+* total: 7,500
+* correct: 5,585
+* accuracy: 74.47%
+* error: 25.53%
+* macro_f1: 72.71%
+Elapsed: 0:01:27

few_shot/lungcolon/shots_1/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/prompt_learner/checkpoint

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+size 1132531909

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few_shot/lungcolon/shots_16/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1/log.txt

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+***************
+** Arguments **
+***************
+backbone: 
+config_file: configs/trainers/BiomedCoOp_BiomedCLIP/few_shot/lungcolon.yaml
+dataset_config_file: configs/datasets/lungcolon.yaml
+eval_only: False
+head: 
+load_epoch: None
+model_dir: 
+no_train: False
+opts: ['TRAINER.BIOMEDCOOP.N_CTX', '4', 'TRAINER.BIOMEDCOOP.CSC', 'False', 'TRAINER.BIOMEDCOOP.CLASS_TOKEN_POSITION', 'end', 'DATASET.NUM_SHOTS', '16']
+output_dir: output_reproduce/lungcolon/shots_16/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1
+resume: 
+root: DATA
+seed: 1
+source_domains: None
+target_domains: None
+trainer: BiomedCoOp_BiomedCLIP
+transforms: None
+************
+** Config **
+************
+DATALOADER:
+  K_TRANSFORMS: 1
+  NUM_WORKERS: 8
+  RETURN_IMG0: False
+  TEST:
+    BATCH_SIZE: 100
+    SAMPLER: SequentialSampler
+  TRAIN_U:
+    BATCH_SIZE: 32
+    N_DOMAIN: 0
+    N_INS: 16
+    SAME_AS_X: True
+    SAMPLER: RandomSampler
+  TRAIN_X:
+    BATCH_SIZE: 4
+    N_DOMAIN: 0
+    N_INS: 16
+    SAMPLER: RandomSampler
+DATASET:
+  ALL_AS_UNLABELED: False
+  CIFAR_C_LEVEL: 1
+  CIFAR_C_TYPE: 
+  NAME: LungColon
+  NUM_LABELED: -1
+  NUM_SHOTS: 16
+  ROOT: DATA
+  SOURCE_DOMAINS: ()
+  STL10_FOLD: -1
+  SUBSAMPLE_CLASSES: all
+  TARGET_DOMAINS: ()
+  VAL_PERCENT: 0.1
+INPUT:
+  COLORJITTER_B: 0.4
+  COLORJITTER_C: 0.4
+  COLORJITTER_H: 0.1
+  COLORJITTER_S: 0.4
+  CROP_PADDING: 4
+  CUTOUT_LEN: 16
+  CUTOUT_N: 1
+  GB_K: 21
+  GB_P: 0.5
+  GN_MEAN: 0.0
+  GN_STD: 0.15
+  INTERPOLATION: bicubic
+  NO_TRANSFORM: False
+  PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
+  PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
+  RANDAUGMENT_M: 10
+  RANDAUGMENT_N: 2
+  RGS_P: 0.2
+  SIZE: (224, 224)
+  TRANSFORMS: ('random_resized_crop', 'normalize')
+MODEL:
+  BACKBONE:
+    NAME: ViT-B/16
+    PRETRAINED: True
+  HEAD:
+    ACTIVATION: relu
+    BN: True
+    DROPOUT: 0.0
+    HIDDEN_LAYERS: ()
+    NAME: 
+  INIT_WEIGHTS: 
+OPTIM:
+  ADAM_BETA1: 0.9
+  ADAM_BETA2: 0.999
+  BASE_LR_MULT: 0.1
+  GAMMA: 0.1
+  LR: 0.0025
+  LR_SCHEDULER: cosine
+  MAX_EPOCH: 100
+  MOMENTUM: 0.9
+  NAME: sgd
+  NEW_LAYERS: ()
+  RMSPROP_ALPHA: 0.99
+  SGD_DAMPNING: 0
+  SGD_NESTEROV: False
+  STAGED_LR: False
+  STEPSIZE: (-1,)
+  WARMUP_CONS_LR: 1e-05
+  WARMUP_EPOCH: 1
+  WARMUP_MIN_LR: 1e-05
+  WARMUP_RECOUNT: True
+  WARMUP_TYPE: constant
+  WEIGHT_DECAY: 0.0005
+OUTPUT_DIR: output_reproduce/lungcolon/shots_16/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1
+RESUME: 
+SEED: 1
+TEST:
+  COMPUTE_CMAT: False
+  EVALUATOR: Classification
+  FINAL_MODEL: last_step
+  NO_TEST: False
+  PER_CLASS_RESULT: False
+  SPLIT: test
+TRAIN:
+  CHECKPOINT_FREQ: 0
+  COUNT_ITER: train_x
+  PRINT_FREQ: 20
+TRAINER:
+  BIOMEDCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    KDSP_LAMBDA: 0.5
+    N_CTX: 4
+    N_PROMPTS: 50
+    PREC: fp32
+    SCCM_LAMBDA: 0.5
+    TAU: 1.5
+  CG:
+    ALPHA_D: 0.5
+    ALPHA_F: 0.5
+    EPS_D: 1.0
+    EPS_F: 1.0
+  COCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: 
+    N_CTX: 4
+    PREC: fp32
+  COOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: 
+    N_CTX: 4
+    PREC: fp32
+  DAEL:
+    CONF_THRE: 0.95
+    STRONG_TRANSFORMS: ()
+    WEIGHT_U: 0.5
+  DDAIG:
+    ALPHA: 0.5
+    CLAMP: False
+    CLAMP_MAX: 1.0
+    CLAMP_MIN: -1.0
+    G_ARCH: 
+    LMDA: 0.3
+    WARMUP: 0
+  ENTMIN:
+    LMDA: 0.001
+  FIXMATCH:
+    CONF_THRE: 0.95
+    STRONG_TRANSFORMS: ()
+    WEIGHT_U: 1.0
+  KGCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    N_CTX: 4
+    PREC: fp32
+    W: 1.0
+  M3SDA:
+    LMDA: 0.5
+    N_STEP_F: 4
+  MCD:
+    N_STEP_F: 4
+  MEANTEA:
+    EMA_ALPHA: 0.999
+    RAMPUP: 5
+    WEIGHT_U: 1.0
+  MIXMATCH:
+    MIXUP_BETA: 0.75
+    RAMPUP: 20000
+    TEMP: 2.0
+    WEIGHT_U: 100.0
+  MME:
+    LMDA: 0.1
+  NAME: BiomedCoOp_BiomedCLIP
+  PROGRAD:
+    ALPHA: 0.0
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    GM: False
+    LAMBDA: 1.0
+    NAME: 
+    N_CTX: 4
+    PREC: fp32
+    T: 1.0
+  SE:
+    CONF_THRE: 0.95
+    EMA_ALPHA: 0.999
+    RAMPUP: 300
+USE_CUDA: True
+VERBOSE: True
+VERSION: 1
+Collecting env info ...
+** System info **
+PyTorch version: 2.0.1+cu118
+Is debug build: False
+CUDA used to build PyTorch: 11.8
+ROCM used to build PyTorch: N/A
+
+OS: Ubuntu 22.04.5 LTS (x86_64)
+GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
+Clang version: Could not collect
+CMake version: version 3.25.0
+Libc version: glibc-2.35
+
+Python version: 3.10.15 (main, Oct  3 2024, 07:27:34) [GCC 11.2.0] (64-bit runtime)
+Python platform: Linux-5.15.0-134-generic-x86_64-with-glibc2.35
+Is CUDA available: True
+CUDA runtime version: 12.8.61
+CUDA_MODULE_LOADING set to: LAZY
+GPU models and configuration: 
+GPU 0: NVIDIA A100-SXM4-40GB
+GPU 1: NVIDIA A100-SXM4-40GB
+GPU 2: NVIDIA A100-SXM4-40GB
+GPU 3: NVIDIA A100-SXM4-40GB
+
+Nvidia driver version: 570.124.06
+cuDNN version: Could not collect
+HIP runtime version: N/A
+MIOpen runtime version: N/A
+Is XNNPACK available: True
+
+CPU:
+Architecture:                         x86_64
+CPU op-mode(s):                       32-bit, 64-bit
+Address sizes:                        43 bits physical, 48 bits virtual
+Byte Order:                           Little Endian
+CPU(s):                               128
+On-line CPU(s) list:                  0-127
+Vendor ID:                            AuthenticAMD
+Model name:                           AMD EPYC 7502 32-Core Processor
+CPU family:                           23
+Model:                                49
+Thread(s) per core:                   2
+Core(s) per socket:                   32
+Socket(s):                            2
+Stepping:                             0
+Frequency boost:                      enabled
+CPU max MHz:                          2500.0000
+CPU min MHz:                          1500.0000
+BogoMIPS:                             4999.71
+Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl umip rdpid overflow_recov succor smca sme sev sev_es
+Virtualization:                       AMD-V
+L1d cache:                            2 MiB (64 instances)
+L1i cache:                            2 MiB (64 instances)
+L2 cache:                             32 MiB (64 instances)
+L3 cache:                             256 MiB (16 instances)
+NUMA node(s):                         2
+NUMA node0 CPU(s):                    0-31,64-95
+NUMA node1 CPU(s):                    32-63,96-127
+Vulnerability Gather data sampling:   Not affected
+Vulnerability Itlb multihit:          Not affected
+Vulnerability L1tf:                   Not affected
+Vulnerability Mds:                    Not affected
+Vulnerability Meltdown:               Not affected
+Vulnerability Mmio stale data:        Not affected
+Vulnerability Reg file data sampling: Not affected
+Vulnerability Retbleed:               Mitigation; untrained return thunk; SMT enabled with STIBP protection
+Vulnerability Spec rstack overflow:   Mitigation; safe RET
+Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl and seccomp
+Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
+Vulnerability Spectre v2:             Mitigation; Retpolines; IBPB conditional; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
+Vulnerability Srbds:                  Not affected
+Vulnerability Tsx async abort:        Not affected
+
+Versions of relevant libraries:
+[pip3] numpy==1.26.3
+[pip3] torch==2.0.1+cu118
+[pip3] torchvision==0.15.2+cu118
+[conda] numpy                     1.26.3                   pypi_0    pypi
+[conda] torch                     2.0.1+cu118              pypi_0    pypi
+[conda] torchvision               0.15.2+cu118             pypi_0    pypi
+        Pillow (10.2.0)
+
+Loading trainer: BiomedCoOp_BiomedCLIP
+Loading dataset: LungColon
+Reading split from /data/t_kol/BiomedCoOp/DATA/LungColon/split_LungColon.json
+Loading preprocessed few-shot data from /data/t_kol/BiomedCoOp/DATA/LungColon/split_fewshot/shot_16-seed_1.pkl
+Building transform_train
++ random resized crop (size=(224, 224))
++ to torch tensor of range [0, 1]
++ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
+Building transform_test
++ resize the smaller edge to 224
++ 224x224 center crop
++ to torch tensor of range [0, 1]
++ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
+***** Dataset statistics *****
+  Dataset: LungColon
+  # classes: 5
+  # train_x: 80
+  # val: 20
+  # test: 7,500
+Loading BiomedCLIP (backbone: ViT-B/16)
+Building custom CLIP
+Initial text context: "a photo of a"
+Number of context words (tokens) for Language prompting: 4
+Turning off gradients in both the image and the text encoder
+Parameters to be updated: {'prompt_learner.ctx'}
+Parameters count: 1
+Loading evaluator: Classification
+Trainer built successfully.
+No checkpoint found, train from scratch
+Initializing summary writer for tensorboard with log_dir=output_reproduce/lungcolon/shots_16/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1/tensorboard
+epoch [1/100][20/20]	time 0.073 (0.105)	data 0.003 (0.022)	eta 0:03:28	loss 0.7168 (2.1508)	acc 75.0000 (41.2500)	lr 2.500000e-03
+epoch [2/100][20/20]	time 0.072 (0.092)	data 0.003 (0.023)	eta 0:03:01	loss 0.7488 (1.2940)	acc 75.0000 (55.0000)	lr 2.499383e-03
+epoch [3/100][20/20]	time 0.072 (0.093)	data 0.003 (0.023)	eta 0:03:00	loss 2.8389 (1.1355)	acc 25.0000 (57.5000)	lr 2.497533e-03
+epoch [4/100][20/20]	time 0.072 (0.093)	data 0.002 (0.023)	eta 0:02:58	loss 1.2232 (0.9316)	acc 50.0000 (65.0000)	lr 2.494452e-03
+epoch [5/100][20/20]	time 0.072 (0.093)	data 0.002 (0.024)	eta 0:02:56	loss 0.3435 (0.9358)	acc 75.0000 (67.5000)	lr 2.490143e-03
+epoch [6/100][20/20]	time 0.072 (0.094)	data 0.002 (0.024)	eta 0:02:56	loss 1.2140 (0.8487)	acc 25.0000 (72.5000)	lr 2.484610e-03
+epoch [7/100][20/20]	time 0.072 (0.095)	data 0.002 (0.025)	eta 0:02:56	loss 0.7139 (0.9990)	acc 75.0000 (62.5000)	lr 2.477859e-03
+epoch [8/100][20/20]	time 0.073 (0.093)	data 0.003 (0.024)	eta 0:02:51	loss 0.7520 (0.8303)	acc 75.0000 (73.7500)	lr 2.469896e-03
+epoch [9/100][20/20]	time 0.073 (0.095)	data 0.003 (0.025)	eta 0:02:52	loss 0.0447 (0.7392)	acc 100.0000 (72.5000)	lr 2.460729e-03
+epoch [10/100][20/20]	time 0.073 (0.093)	data 0.003 (0.024)	eta 0:02:47	loss 0.2304 (0.7196)	acc 100.0000 (68.7500)	lr 2.450367e-03
+epoch [11/100][20/20]	time 0.073 (0.094)	data 0.003 (0.025)	eta 0:02:47	loss 0.5283 (0.6772)	acc 100.0000 (76.2500)	lr 2.438821e-03
+epoch [12/100][20/20]	time 0.073 (0.095)	data 0.003 (0.026)	eta 0:02:47	loss 0.3888 (0.6942)	acc 75.0000 (76.2500)	lr 2.426101e-03
+epoch [13/100][20/20]	time 0.072 (0.093)	data 0.003 (0.023)	eta 0:02:41	loss 0.5414 (0.6792)	acc 75.0000 (78.7500)	lr 2.412221e-03
+epoch [14/100][20/20]	time 0.072 (0.093)	data 0.003 (0.024)	eta 0:02:40	loss 0.7437 (0.6008)	acc 50.0000 (77.5000)	lr 2.397193e-03
+epoch [15/100][20/20]	time 0.072 (0.095)	data 0.002 (0.025)	eta 0:02:41	loss 0.5639 (0.6314)	acc 75.0000 (73.7500)	lr 2.381034e-03
+epoch [16/100][20/20]	time 0.072 (0.093)	data 0.003 (0.024)	eta 0:02:36	loss 0.5213 (0.6213)	acc 75.0000 (76.2500)	lr 2.363758e-03
+epoch [17/100][20/20]	time 0.072 (0.094)	data 0.002 (0.025)	eta 0:02:36	loss 0.5303 (0.5907)	acc 75.0000 (82.5000)	lr 2.345383e-03
+epoch [18/100][20/20]	time 0.072 (0.094)	data 0.002 (0.024)	eta 0:02:34	loss 0.4337 (0.5835)	acc 100.0000 (81.2500)	lr 2.325928e-03
+epoch [19/100][20/20]	time 0.072 (0.093)	data 0.002 (0.023)	eta 0:02:30	loss 0.3017 (0.6380)	acc 100.0000 (76.2500)	lr 2.305410e-03
+epoch [20/100][20/20]	time 0.072 (0.094)	data 0.002 (0.025)	eta 0:02:30	loss 0.3420 (0.6110)	acc 75.0000 (81.2500)	lr 2.283851e-03
+epoch [21/100][20/20]	time 0.072 (0.094)	data 0.002 (0.025)	eta 0:02:28	loss 0.2297 (0.5828)	acc 100.0000 (81.2500)	lr 2.261271e-03
+epoch [22/100][20/20]	time 0.072 (0.093)	data 0.002 (0.024)	eta 0:02:25	loss 0.1196 (0.7154)	acc 100.0000 (75.0000)	lr 2.237694e-03
+epoch [23/100][20/20]	time 0.072 (0.093)	data 0.002 (0.023)	eta 0:02:22	loss 0.4981 (0.7658)	acc 100.0000 (80.0000)	lr 2.213142e-03
+epoch [24/100][20/20]	time 0.072 (0.094)	data 0.002 (0.025)	eta 0:02:23	loss 0.7876 (0.7360)	acc 75.0000 (77.5000)	lr 2.187639e-03
+epoch [25/100][20/20]	time 0.073 (0.094)	data 0.003 (0.024)	eta 0:02:21	loss 1.1551 (0.7065)	acc 75.0000 (77.5000)	lr 2.161211e-03
+epoch [26/100][20/20]	time 0.073 (0.094)	data 0.003 (0.025)	eta 0:02:19	loss 0.5521 (0.5376)	acc 75.0000 (80.0000)	lr 2.133883e-03
+epoch [27/100][20/20]	time 0.073 (0.095)	data 0.003 (0.026)	eta 0:02:18	loss 0.9030 (0.6151)	acc 75.0000 (80.0000)	lr 2.105684e-03
+epoch [28/100][20/20]	time 0.072 (0.094)	data 0.002 (0.025)	eta 0:02:15	loss 0.7737 (0.5209)	acc 50.0000 (82.5000)	lr 2.076640e-03
+epoch [29/100][20/20]	time 0.073 (0.093)	data 0.003 (0.023)	eta 0:02:11	loss 0.9221 (0.4567)	acc 50.0000 (90.0000)	lr 2.046780e-03
+epoch [30/100][20/20]	time 0.071 (0.093)	data 0.002 (0.025)	eta 0:02:10	loss 0.4003 (0.5109)	acc 75.0000 (82.5000)	lr 2.016134e-03
+epoch [31/100][20/20]	time 0.072 (0.093)	data 0.002 (0.024)	eta 0:02:08	loss 0.3840 (0.6163)	acc 75.0000 (77.5000)	lr 1.984732e-03
+epoch [32/100][20/20]	time 0.072 (0.093)	data 0.002 (0.024)	eta 0:02:06	loss 0.5565 (0.5920)	acc 75.0000 (83.7500)	lr 1.952604e-03
+epoch [33/100][20/20]	time 0.071 (0.092)	data 0.002 (0.023)	eta 0:02:03	loss 0.9621 (0.5381)	acc 50.0000 (82.5000)	lr 1.919783e-03
+epoch [34/100][20/20]	time 0.072 (0.094)	data 0.002 (0.024)	eta 0:02:03	loss 0.7007 (0.5347)	acc 50.0000 (82.5000)	lr 1.886302e-03
+epoch [35/100][20/20]	time 0.073 (0.092)	data 0.003 (0.022)	eta 0:01:58	loss 0.6329 (0.6074)	acc 100.0000 (80.0000)	lr 1.852192e-03
+epoch [36/100][20/20]	time 0.072 (0.091)	data 0.003 (0.021)	eta 0:01:56	loss 0.6613 (0.5427)	acc 75.0000 (85.0000)	lr 1.817488e-03
+epoch [37/100][20/20]	time 0.072 (0.091)	data 0.002 (0.021)	eta 0:01:54	loss 0.1816 (0.6377)	acc 100.0000 (82.5000)	lr 1.782224e-03
+epoch [38/100][20/20]	time 0.072 (0.091)	data 0.003 (0.022)	eta 0:01:53	loss 0.3777 (0.4555)	acc 75.0000 (83.7500)	lr 1.746435e-03
+epoch [39/100][20/20]	time 0.072 (0.091)	data 0.002 (0.022)	eta 0:01:51	loss 0.3138 (0.4770)	acc 100.0000 (86.2500)	lr 1.710156e-03
+epoch [40/100][20/20]	time 0.073 (0.092)	data 0.003 (0.023)	eta 0:01:50	loss 0.8345 (0.4983)	acc 75.0000 (85.0000)	lr 1.673422e-03
+epoch [41/100][20/20]	time 0.072 (0.092)	data 0.002 (0.022)	eta 0:01:48	loss 0.7751 (0.4780)	acc 75.0000 (82.5000)	lr 1.636271e-03
+epoch [42/100][20/20]	time 0.072 (0.091)	data 0.002 (0.021)	eta 0:01:45	loss 0.7390 (0.5779)	acc 75.0000 (77.5000)	lr 1.598739e-03
+epoch [43/100][20/20]	time 0.072 (0.092)	data 0.002 (0.022)	eta 0:01:44	loss 0.4476 (0.5461)	acc 75.0000 (81.2500)	lr 1.560862e-03
+epoch [44/100][20/20]	time 0.072 (0.091)	data 0.003 (0.022)	eta 0:01:41	loss 0.9554 (0.5312)	acc 50.0000 (85.0000)	lr 1.522679e-03
+epoch [45/100][20/20]	time 0.073 (0.091)	data 0.003 (0.021)	eta 0:01:40	loss 0.6248 (0.5365)	acc 75.0000 (80.0000)	lr 1.484227e-03
+epoch [46/100][20/20]	time 0.073 (0.091)	data 0.003 (0.021)	eta 0:01:37	loss 0.3899 (0.4807)	acc 100.0000 (87.5000)	lr 1.445543e-03
+epoch [47/100][20/20]	time 0.072 (0.092)	data 0.003 (0.022)	eta 0:01:37	loss 0.6328 (0.4633)	acc 75.0000 (85.0000)	lr 1.406667e-03
+epoch [48/100][20/20]	time 0.072 (0.091)	data 0.003 (0.021)	eta 0:01:34	loss 0.8516 (0.5554)	acc 50.0000 (85.0000)	lr 1.367635e-03
+epoch [49/100][20/20]	time 0.072 (0.092)	data 0.002 (0.022)	eta 0:01:33	loss 0.4224 (0.5655)	acc 100.0000 (83.7500)	lr 1.328488e-03
+epoch [50/100][20/20]	time 0.072 (0.091)	data 0.003 (0.022)	eta 0:01:31	loss 0.9096 (0.4602)	acc 50.0000 (85.0000)	lr 1.289263e-03
+epoch [51/100][20/20]	time 0.072 (0.091)	data 0.003 (0.021)	eta 0:01:29	loss 1.3380 (0.4791)	acc 50.0000 (90.0000)	lr 1.250000e-03
+epoch [52/100][20/20]	time 0.072 (0.093)	data 0.002 (0.024)	eta 0:01:29	loss 1.4317 (0.4887)	acc 50.0000 (85.0000)	lr 1.210737e-03
+epoch [53/100][20/20]	time 0.071 (0.090)	data 0.002 (0.021)	eta 0:01:24	loss 0.4214 (0.4681)	acc 100.0000 (87.5000)	lr 1.171512e-03
+epoch [54/100][20/20]	time 0.072 (0.090)	data 0.002 (0.021)	eta 0:01:23	loss 0.4749 (0.5127)	acc 100.0000 (87.5000)	lr 1.132365e-03
+epoch [55/100][20/20]	time 0.072 (0.091)	data 0.002 (0.022)	eta 0:01:22	loss 0.8093 (0.4869)	acc 50.0000 (85.0000)	lr 1.093333e-03
+epoch [56/100][20/20]	time 0.072 (0.091)	data 0.003 (0.022)	eta 0:01:20	loss 1.0420 (0.5255)	acc 50.0000 (86.2500)	lr 1.054457e-03
+epoch [57/100][20/20]	time 0.073 (0.091)	data 0.003 (0.021)	eta 0:01:18	loss 0.4722 (0.4784)	acc 100.0000 (83.7500)	lr 1.015773e-03
+epoch [58/100][20/20]	time 0.072 (0.091)	data 0.002 (0.022)	eta 0:01:16	loss 0.4219 (0.5341)	acc 75.0000 (80.0000)	lr 9.773209e-04
+epoch [59/100][20/20]	time 0.072 (0.092)	data 0.003 (0.022)	eta 0:01:15	loss 1.0387 (0.5401)	acc 50.0000 (83.7500)	lr 9.391376e-04
+epoch [60/100][20/20]	time 0.073 (0.091)	data 0.003 (0.022)	eta 0:01:13	loss 0.2237 (0.5965)	acc 100.0000 (85.0000)	lr 9.012611e-04
+epoch [61/100][20/20]	time 0.072 (0.091)	data 0.002 (0.021)	eta 0:01:10	loss 0.2547 (0.3846)	acc 100.0000 (93.7500)	lr 8.637288e-04
+epoch [62/100][20/20]	time 0.072 (0.091)	data 0.002 (0.022)	eta 0:01:09	loss 0.3551 (0.5184)	acc 100.0000 (82.5000)	lr 8.265776e-04
+epoch [63/100][20/20]	time 0.072 (0.093)	data 0.003 (0.023)	eta 0:01:08	loss 0.1919 (0.4782)	acc 100.0000 (88.7500)	lr 7.898443e-04
+epoch [64/100][20/20]	time 0.073 (0.091)	data 0.003 (0.021)	eta 0:01:05	loss 0.6188 (0.5025)	acc 75.0000 (87.5000)	lr 7.535651e-04
+epoch [65/100][20/20]	time 0.072 (0.091)	data 0.003 (0.021)	eta 0:01:03	loss 0.8456 (0.4718)	acc 75.0000 (90.0000)	lr 7.177759e-04
+epoch [66/100][20/20]	time 0.073 (0.091)	data 0.003 (0.021)	eta 0:01:01	loss 0.2457 (0.4699)	acc 100.0000 (87.5000)	lr 6.825119e-04
+epoch [67/100][20/20]	time 0.072 (0.093)	data 0.003 (0.023)	eta 0:01:01	loss 0.7694 (0.4507)	acc 75.0000 (90.0000)	lr 6.478079e-04
+epoch [68/100][20/20]	time 0.072 (0.091)	data 0.003 (0.021)	eta 0:00:58	loss 0.4857 (0.5805)	acc 75.0000 (82.5000)	lr 6.136982e-04
+epoch [69/100][20/20]	time 0.071 (0.092)	data 0.002 (0.022)	eta 0:00:56	loss 0.2563 (0.4897)	acc 100.0000 (90.0000)	lr 5.802165e-04
+epoch [70/100][20/20]	time 0.071 (0.091)	data 0.002 (0.023)	eta 0:00:54	loss 0.7013 (0.5240)	acc 75.0000 (85.0000)	lr 5.473958e-04
+epoch [71/100][20/20]	time 0.072 (0.093)	data 0.003 (0.023)	eta 0:00:53	loss 0.9993 (0.4842)	acc 50.0000 (81.2500)	lr 5.152684e-04
+epoch [72/100][20/20]	time 0.072 (0.092)	data 0.003 (0.022)	eta 0:00:51	loss 0.1600 (0.5019)	acc 100.0000 (88.7500)	lr 4.838662e-04
+epoch [73/100][20/20]	time 0.073 (0.092)	data 0.003 (0.022)	eta 0:00:49	loss 0.5255 (0.5962)	acc 75.0000 (85.0000)	lr 4.532200e-04
+epoch [74/100][20/20]	time 0.073 (0.091)	data 0.003 (0.022)	eta 0:00:47	loss 0.4264 (0.5759)	acc 75.0000 (85.0000)	lr 4.233602e-04
+epoch [75/100][20/20]	time 0.072 (0.092)	data 0.002 (0.022)	eta 0:00:45	loss 0.2961 (0.4711)	acc 100.0000 (91.2500)	lr 3.943161e-04
+epoch [76/100][20/20]	time 0.072 (0.091)	data 0.002 (0.022)	eta 0:00:43	loss 0.5531 (0.5303)	acc 75.0000 (87.5000)	lr 3.661165e-04
+epoch [77/100][20/20]	time 0.072 (0.092)	data 0.002 (0.022)	eta 0:00:42	loss 0.6397 (0.4866)	acc 75.0000 (90.0000)	lr 3.387892e-04
+epoch [78/100][20/20]	time 0.073 (0.091)	data 0.003 (0.022)	eta 0:00:40	loss 0.2916 (0.4246)	acc 100.0000 (87.5000)	lr 3.123612e-04
+epoch [79/100][20/20]	time 0.072 (0.093)	data 0.003 (0.023)	eta 0:00:38	loss 0.2518 (0.4295)	acc 100.0000 (87.5000)	lr 2.868584e-04
+epoch [80/100][20/20]	time 0.072 (0.092)	data 0.002 (0.022)	eta 0:00:36	loss 0.6303 (0.4676)	acc 75.0000 (83.7500)	lr 2.623062e-04
+epoch [81/100][20/20]	time 0.072 (0.092)	data 0.002 (0.022)	eta 0:00:34	loss 0.3142 (0.5289)	acc 100.0000 (85.0000)	lr 2.387288e-04
+epoch [82/100][20/20]	time 0.072 (0.092)	data 0.003 (0.022)	eta 0:00:33	loss 0.3035 (0.4468)	acc 100.0000 (90.0000)	lr 2.161493e-04
+epoch [83/100][20/20]	time 0.073 (0.091)	data 0.003 (0.022)	eta 0:00:30	loss 0.2489 (0.4346)	acc 100.0000 (90.0000)	lr 1.945901e-04
+epoch [84/100][20/20]	time 0.072 (0.091)	data 0.003 (0.022)	eta 0:00:29	loss 0.4637 (0.5304)	acc 75.0000 (82.5000)	lr 1.740725e-04
+epoch [85/100][20/20]	time 0.072 (0.092)	data 0.003 (0.022)	eta 0:00:27	loss 0.1216 (0.4907)	acc 100.0000 (87.5000)	lr 1.546166e-04
+epoch [86/100][20/20]	time 0.072 (0.093)	data 0.003 (0.023)	eta 0:00:25	loss 0.2119 (0.5585)	acc 100.0000 (82.5000)	lr 1.362418e-04
+epoch [87/100][20/20]	time 0.072 (0.091)	data 0.002 (0.022)	eta 0:00:23	loss 0.1511 (0.4655)	acc 100.0000 (87.5000)	lr 1.189662e-04
+epoch [88/100][20/20]	time 0.073 (0.091)	data 0.003 (0.022)	eta 0:00:21	loss 0.5350 (0.3362)	acc 75.0000 (92.5000)	lr 1.028067e-04
+epoch [89/100][20/20]	time 0.072 (0.091)	data 0.003 (0.021)	eta 0:00:19	loss 2.3665 (0.5846)	acc 75.0000 (81.2500)	lr 8.777939e-05
+epoch [90/100][20/20]	time 0.072 (0.091)	data 0.002 (0.022)	eta 0:00:18	loss 0.1820 (0.4774)	acc 100.0000 (86.2500)	lr 7.389904e-05
+epoch [91/100][20/20]	time 0.072 (0.092)	data 0.002 (0.022)	eta 0:00:16	loss 0.1393 (0.4233)	acc 100.0000 (86.2500)	lr 6.117935e-05
+epoch [92/100][20/20]	time 0.072 (0.091)	data 0.003 (0.021)	eta 0:00:14	loss 0.4273 (0.4134)	acc 100.0000 (90.0000)	lr 4.963289e-05
+epoch [93/100][20/20]	time 0.073 (0.092)	data 0.003 (0.022)	eta 0:00:12	loss 0.2563 (0.5005)	acc 100.0000 (88.7500)	lr 3.927105e-05
+epoch [94/100][20/20]	time 0.073 (0.093)	data 0.003 (0.023)	eta 0:00:11	loss 1.0325 (0.5840)	acc 50.0000 (87.5000)	lr 3.010405e-05
+epoch [95/100][20/20]	time 0.072 (0.091)	data 0.003 (0.022)	eta 0:00:09	loss 0.2495 (0.5616)	acc 100.0000 (82.5000)	lr 2.214094e-05
+epoch [96/100][20/20]	time 0.073 (0.091)	data 0.003 (0.021)	eta 0:00:07	loss 0.2503 (0.3790)	acc 100.0000 (93.7500)	lr 1.538957e-05
+epoch [97/100][20/20]	time 0.073 (0.093)	data 0.003 (0.023)	eta 0:00:05	loss 0.4299 (0.4399)	acc 100.0000 (88.7500)	lr 9.856623e-06
+epoch [98/100][20/20]	time 0.072 (0.092)	data 0.003 (0.022)	eta 0:00:03	loss 0.4352 (0.4764)	acc 75.0000 (85.0000)	lr 5.547544e-06
+epoch [99/100][20/20]	time 0.073 (0.091)	data 0.003 (0.021)	eta 0:00:01	loss 0.7464 (0.4882)	acc 75.0000 (86.2500)	lr 2.466589e-06
+epoch [100/100][20/20]	time 0.073 (0.093)	data 0.003 (0.023)	eta 0:00:00	loss 0.2999 (0.5161)	acc 100.0000 (85.0000)	lr 6.167995e-07
+Checkpoint saved to "output_reproduce/lungcolon/shots_16/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1/prompt_learner/model.pth.tar-100"
+Finished training
+Do evaluation on test set
+=> result
+* total: 7,500
+* correct: 7,011
+* accuracy: 93.48%
+* error: 6.52%
+* macro_f1: 93.41%
+Elapsed: 0:03:37

few_shot/lungcolon/shots_16/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1/prompt_learner/checkpoint

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few_shot/lungcolon/shots_16/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1/tensorboard/events.out.tfevents.1742386109.impactlab-server.3540279.0

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few_shot/lungcolon/shots_16/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/log.txt

@@ -0,0 +1,432 @@
+***************
+** Arguments **
+***************
+backbone: 
+config_file: configs/trainers/BiomedCoOp_BiomedCLIP/few_shot/lungcolon.yaml
+dataset_config_file: configs/datasets/lungcolon.yaml
+eval_only: False
+head: 
+load_epoch: None
+model_dir: 
+no_train: False
+opts: ['TRAINER.BIOMEDCOOP.N_CTX', '4', 'TRAINER.BIOMEDCOOP.CSC', 'False', 'TRAINER.BIOMEDCOOP.CLASS_TOKEN_POSITION', 'end', 'DATASET.NUM_SHOTS', '16']
+output_dir: output_reproduce/lungcolon/shots_16/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2
+resume: 
+root: DATA
+seed: 2
+source_domains: None
+target_domains: None
+trainer: BiomedCoOp_BiomedCLIP
+transforms: None
+************
+** Config **
+************
+DATALOADER:
+  K_TRANSFORMS: 1
+  NUM_WORKERS: 8
+  RETURN_IMG0: False
+  TEST:
+    BATCH_SIZE: 100
+    SAMPLER: SequentialSampler
+  TRAIN_U:
+    BATCH_SIZE: 32
+    N_DOMAIN: 0
+    N_INS: 16
+    SAME_AS_X: True
+    SAMPLER: RandomSampler
+  TRAIN_X:
+    BATCH_SIZE: 4
+    N_DOMAIN: 0
+    N_INS: 16
+    SAMPLER: RandomSampler
+DATASET:
+  ALL_AS_UNLABELED: False
+  CIFAR_C_LEVEL: 1
+  CIFAR_C_TYPE: 
+  NAME: LungColon
+  NUM_LABELED: -1
+  NUM_SHOTS: 16
+  ROOT: DATA
+  SOURCE_DOMAINS: ()
+  STL10_FOLD: -1
+  SUBSAMPLE_CLASSES: all
+  TARGET_DOMAINS: ()
+  VAL_PERCENT: 0.1
+INPUT:
+  COLORJITTER_B: 0.4
+  COLORJITTER_C: 0.4
+  COLORJITTER_H: 0.1
+  COLORJITTER_S: 0.4
+  CROP_PADDING: 4
+  CUTOUT_LEN: 16
+  CUTOUT_N: 1
+  GB_K: 21
+  GB_P: 0.5
+  GN_MEAN: 0.0
+  GN_STD: 0.15
+  INTERPOLATION: bicubic
+  NO_TRANSFORM: False
+  PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
+  PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
+  RANDAUGMENT_M: 10
+  RANDAUGMENT_N: 2
+  RGS_P: 0.2
+  SIZE: (224, 224)
+  TRANSFORMS: ('random_resized_crop', 'normalize')
+MODEL:
+  BACKBONE:
+    NAME: ViT-B/16
+    PRETRAINED: True
+  HEAD:
+    ACTIVATION: relu
+    BN: True
+    DROPOUT: 0.0
+    HIDDEN_LAYERS: ()
+    NAME: 
+  INIT_WEIGHTS: 
+OPTIM:
+  ADAM_BETA1: 0.9
+  ADAM_BETA2: 0.999
+  BASE_LR_MULT: 0.1
+  GAMMA: 0.1
+  LR: 0.0025
+  LR_SCHEDULER: cosine
+  MAX_EPOCH: 100
+  MOMENTUM: 0.9
+  NAME: sgd
+  NEW_LAYERS: ()
+  RMSPROP_ALPHA: 0.99
+  SGD_DAMPNING: 0
+  SGD_NESTEROV: False
+  STAGED_LR: False
+  STEPSIZE: (-1,)
+  WARMUP_CONS_LR: 1e-05
+  WARMUP_EPOCH: 1
+  WARMUP_MIN_LR: 1e-05
+  WARMUP_RECOUNT: True
+  WARMUP_TYPE: constant
+  WEIGHT_DECAY: 0.0005
+OUTPUT_DIR: output_reproduce/lungcolon/shots_16/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2
+RESUME: 
+SEED: 2
+TEST:
+  COMPUTE_CMAT: False
+  EVALUATOR: Classification
+  FINAL_MODEL: last_step
+  NO_TEST: False
+  PER_CLASS_RESULT: False
+  SPLIT: test
+TRAIN:
+  CHECKPOINT_FREQ: 0
+  COUNT_ITER: train_x
+  PRINT_FREQ: 20
+TRAINER:
+  BIOMEDCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    KDSP_LAMBDA: 0.5
+    N_CTX: 4
+    N_PROMPTS: 50
+    PREC: fp32
+    SCCM_LAMBDA: 0.5
+    TAU: 1.5
+  CG:
+    ALPHA_D: 0.5
+    ALPHA_F: 0.5
+    EPS_D: 1.0
+    EPS_F: 1.0
+  COCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: 
+    N_CTX: 4
+    PREC: fp32
+  COOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: 
+    N_CTX: 4
+    PREC: fp32
+  DAEL:
+    CONF_THRE: 0.95
+    STRONG_TRANSFORMS: ()
+    WEIGHT_U: 0.5
+  DDAIG:
+    ALPHA: 0.5
+    CLAMP: False
+    CLAMP_MAX: 1.0
+    CLAMP_MIN: -1.0
+    G_ARCH: 
+    LMDA: 0.3
+    WARMUP: 0
+  ENTMIN:
+    LMDA: 0.001
+  FIXMATCH:
+    CONF_THRE: 0.95
+    STRONG_TRANSFORMS: ()
+    WEIGHT_U: 1.0
+  KGCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    N_CTX: 4
+    PREC: fp32
+    W: 1.0
+  M3SDA:
+    LMDA: 0.5
+    N_STEP_F: 4
+  MCD:
+    N_STEP_F: 4
+  MEANTEA:
+    EMA_ALPHA: 0.999
+    RAMPUP: 5
+    WEIGHT_U: 1.0
+  MIXMATCH:
+    MIXUP_BETA: 0.75
+    RAMPUP: 20000
+    TEMP: 2.0
+    WEIGHT_U: 100.0
+  MME:
+    LMDA: 0.1
+  NAME: BiomedCoOp_BiomedCLIP
+  PROGRAD:
+    ALPHA: 0.0
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    GM: False
+    LAMBDA: 1.0
+    NAME: 
+    N_CTX: 4
+    PREC: fp32
+    T: 1.0
+  SE:
+    CONF_THRE: 0.95
+    EMA_ALPHA: 0.999
+    RAMPUP: 300
+USE_CUDA: True
+VERBOSE: True
+VERSION: 1
+Collecting env info ...
+** System info **
+PyTorch version: 2.0.1+cu118
+Is debug build: False
+CUDA used to build PyTorch: 11.8
+ROCM used to build PyTorch: N/A
+
+OS: Ubuntu 22.04.5 LTS (x86_64)
+GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
+Clang version: Could not collect
+CMake version: version 3.25.0
+Libc version: glibc-2.35
+
+Python version: 3.10.15 (main, Oct  3 2024, 07:27:34) [GCC 11.2.0] (64-bit runtime)
+Python platform: Linux-5.15.0-134-generic-x86_64-with-glibc2.35
+Is CUDA available: True
+CUDA runtime version: 12.8.61
+CUDA_MODULE_LOADING set to: LAZY
+GPU models and configuration: 
+GPU 0: NVIDIA A100-SXM4-40GB
+GPU 1: NVIDIA A100-SXM4-40GB
+GPU 2: NVIDIA A100-SXM4-40GB
+GPU 3: NVIDIA A100-SXM4-40GB
+
+Nvidia driver version: 570.124.06
+cuDNN version: Could not collect
+HIP runtime version: N/A
+MIOpen runtime version: N/A
+Is XNNPACK available: True
+
+CPU:
+Architecture:                         x86_64
+CPU op-mode(s):                       32-bit, 64-bit
+Address sizes:                        43 bits physical, 48 bits virtual
+Byte Order:                           Little Endian
+CPU(s):                               128
+On-line CPU(s) list:                  0-127
+Vendor ID:                            AuthenticAMD
+Model name:                           AMD EPYC 7502 32-Core Processor
+CPU family:                           23
+Model:                                49
+Thread(s) per core:                   2
+Core(s) per socket:                   32
+Socket(s):                            2
+Stepping:                             0
+Frequency boost:                      enabled
+CPU max MHz:                          2500.0000
+CPU min MHz:                          1500.0000
+BogoMIPS:                             4999.71
+Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl umip rdpid overflow_recov succor smca sme sev sev_es
+Virtualization:                       AMD-V
+L1d cache:                            2 MiB (64 instances)
+L1i cache:                            2 MiB (64 instances)
+L2 cache:                             32 MiB (64 instances)
+L3 cache:                             256 MiB (16 instances)
+NUMA node(s):                         2
+NUMA node0 CPU(s):                    0-31,64-95
+NUMA node1 CPU(s):                    32-63,96-127
+Vulnerability Gather data sampling:   Not affected
+Vulnerability Itlb multihit:          Not affected
+Vulnerability L1tf:                   Not affected
+Vulnerability Mds:                    Not affected
+Vulnerability Meltdown:               Not affected
+Vulnerability Mmio stale data:        Not affected
+Vulnerability Reg file data sampling: Not affected
+Vulnerability Retbleed:               Mitigation; untrained return thunk; SMT enabled with STIBP protection
+Vulnerability Spec rstack overflow:   Mitigation; safe RET
+Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl and seccomp
+Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
+Vulnerability Spectre v2:             Mitigation; Retpolines; IBPB conditional; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
+Vulnerability Srbds:                  Not affected
+Vulnerability Tsx async abort:        Not affected
+
+Versions of relevant libraries:
+[pip3] numpy==1.26.3
+[pip3] torch==2.0.1+cu118
+[pip3] torchvision==0.15.2+cu118
+[conda] numpy                     1.26.3                   pypi_0    pypi
+[conda] torch                     2.0.1+cu118              pypi_0    pypi
+[conda] torchvision               0.15.2+cu118             pypi_0    pypi
+        Pillow (10.2.0)
+
+Loading trainer: BiomedCoOp_BiomedCLIP
+Loading dataset: LungColon
+Reading split from /data/t_kol/BiomedCoOp/DATA/LungColon/split_LungColon.json
+Loading preprocessed few-shot data from /data/t_kol/BiomedCoOp/DATA/LungColon/split_fewshot/shot_16-seed_2.pkl
+Building transform_train
++ random resized crop (size=(224, 224))
++ to torch tensor of range [0, 1]
++ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
+Building transform_test
++ resize the smaller edge to 224
++ 224x224 center crop
++ to torch tensor of range [0, 1]
++ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
+***** Dataset statistics *****
+  Dataset: LungColon
+  # classes: 5
+  # train_x: 80
+  # val: 20
+  # test: 7,500
+Loading BiomedCLIP (backbone: ViT-B/16)
+Building custom CLIP
+Initial text context: "a photo of a"
+Number of context words (tokens) for Language prompting: 4
+Turning off gradients in both the image and the text encoder
+Parameters to be updated: {'prompt_learner.ctx'}
+Parameters count: 1
+Loading evaluator: Classification
+Trainer built successfully.
+No checkpoint found, train from scratch
+Initializing summary writer for tensorboard with log_dir=output_reproduce/lungcolon/shots_16/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/tensorboard
+epoch [1/100][20/20]	time 0.072 (0.106)	data 0.002 (0.022)	eta 0:03:29	loss 2.0046 (1.9377)	acc 25.0000 (40.0000)	lr 2.500000e-03
+epoch [2/100][20/20]	time 0.072 (0.094)	data 0.002 (0.025)	eta 0:03:04	loss 1.0821 (1.7341)	acc 50.0000 (42.5000)	lr 2.499383e-03
+epoch [3/100][20/20]	time 0.072 (0.094)	data 0.002 (0.025)	eta 0:03:02	loss 1.0303 (1.2471)	acc 25.0000 (53.7500)	lr 2.497533e-03
+epoch [4/100][20/20]	time 0.072 (0.094)	data 0.002 (0.024)	eta 0:03:00	loss 1.4089 (1.2390)	acc 25.0000 (48.7500)	lr 2.494452e-03
+epoch [5/100][20/20]	time 0.073 (0.093)	data 0.003 (0.023)	eta 0:02:56	loss 0.9616 (0.9133)	acc 75.0000 (62.5000)	lr 2.490143e-03
+epoch [6/100][20/20]	time 0.072 (0.094)	data 0.002 (0.025)	eta 0:02:57	loss 1.1653 (1.0292)	acc 75.0000 (65.0000)	lr 2.484610e-03
+epoch [7/100][20/20]	time 0.072 (0.094)	data 0.002 (0.025)	eta 0:02:54	loss 0.5909 (0.8991)	acc 75.0000 (62.5000)	lr 2.477859e-03
+epoch [8/100][20/20]	time 0.072 (0.092)	data 0.003 (0.023)	eta 0:02:49	loss 0.7750 (0.8802)	acc 50.0000 (73.7500)	lr 2.469896e-03
+epoch [9/100][20/20]	time 0.072 (0.094)	data 0.003 (0.024)	eta 0:02:50	loss 0.1322 (0.6972)	acc 100.0000 (76.2500)	lr 2.460729e-03
+epoch [10/100][20/20]	time 0.072 (0.093)	data 0.003 (0.023)	eta 0:02:47	loss 1.4962 (0.9158)	acc 25.0000 (70.0000)	lr 2.450367e-03
+epoch [11/100][20/20]	time 0.072 (0.093)	data 0.003 (0.024)	eta 0:02:45	loss 2.4292 (0.8314)	acc 50.0000 (71.2500)	lr 2.438821e-03
+epoch [12/100][20/20]	time 0.072 (0.094)	data 0.003 (0.025)	eta 0:02:45	loss 1.7381 (0.7904)	acc 50.0000 (77.5000)	lr 2.426101e-03
+epoch [13/100][20/20]	time 0.073 (0.093)	data 0.003 (0.023)	eta 0:02:41	loss 1.5522 (0.8763)	acc 25.0000 (71.2500)	lr 2.412221e-03
+epoch [14/100][20/20]	time 0.072 (0.093)	data 0.003 (0.024)	eta 0:02:40	loss 2.6416 (0.8042)	acc 25.0000 (76.2500)	lr 2.397193e-03
+epoch [15/100][20/20]	time 0.072 (0.092)	data 0.003 (0.023)	eta 0:02:36	loss 1.4983 (0.7159)	acc 0.0000 (76.2500)	lr 2.381034e-03
+epoch [16/100][20/20]	time 0.072 (0.093)	data 0.002 (0.024)	eta 0:02:36	loss 1.0472 (0.9198)	acc 50.0000 (67.5000)	lr 2.363758e-03
+epoch [17/100][20/20]	time 0.072 (0.094)	data 0.002 (0.024)	eta 0:02:35	loss 0.4205 (0.7511)	acc 75.0000 (68.7500)	lr 2.345383e-03
+epoch [18/100][20/20]	time 0.071 (0.094)	data 0.002 (0.025)	eta 0:02:34	loss 1.0796 (0.7240)	acc 75.0000 (73.7500)	lr 2.325928e-03
+epoch [19/100][20/20]	time 0.072 (0.093)	data 0.002 (0.023)	eta 0:02:29	loss 1.0432 (0.7700)	acc 75.0000 (72.5000)	lr 2.305410e-03
+epoch [20/100][20/20]	time 0.072 (0.093)	data 0.002 (0.023)	eta 0:02:28	loss 1.0929 (0.8402)	acc 75.0000 (75.0000)	lr 2.283851e-03
+epoch [21/100][20/20]	time 0.072 (0.094)	data 0.002 (0.024)	eta 0:02:27	loss 0.0619 (0.7263)	acc 100.0000 (72.5000)	lr 2.261271e-03
+epoch [22/100][20/20]	time 0.072 (0.093)	data 0.002 (0.023)	eta 0:02:25	loss 0.4795 (0.6803)	acc 75.0000 (80.0000)	lr 2.237694e-03
+epoch [23/100][20/20]	time 0.072 (0.092)	data 0.002 (0.023)	eta 0:02:21	loss 0.7988 (0.6725)	acc 75.0000 (81.2500)	lr 2.213142e-03
+epoch [24/100][20/20]	time 0.072 (0.092)	data 0.003 (0.023)	eta 0:02:20	loss 0.5278 (0.7713)	acc 75.0000 (72.5000)	lr 2.187639e-03
+epoch [25/100][20/20]	time 0.072 (0.094)	data 0.002 (0.024)	eta 0:02:20	loss 0.7264 (0.6664)	acc 50.0000 (76.2500)	lr 2.161211e-03
+epoch [26/100][20/20]	time 0.072 (0.093)	data 0.002 (0.024)	eta 0:02:18	loss 0.2672 (0.6664)	acc 100.0000 (78.7500)	lr 2.133883e-03
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+epoch [29/100][20/20]	time 0.073 (0.094)	data 0.003 (0.025)	eta 0:02:13	loss 0.3155 (0.6339)	acc 75.0000 (81.2500)	lr 2.046780e-03
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+epoch [37/100][20/20]	time 0.072 (0.092)	data 0.002 (0.022)	eta 0:01:55	loss 0.5377 (0.7813)	acc 100.0000 (76.2500)	lr 1.782224e-03
+epoch [38/100][20/20]	time 0.073 (0.090)	data 0.003 (0.021)	eta 0:01:52	loss 0.6492 (0.7094)	acc 75.0000 (77.5000)	lr 1.746435e-03
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+epoch [41/100][20/20]	time 0.072 (0.092)	data 0.002 (0.022)	eta 0:01:48	loss 0.1646 (0.6218)	acc 100.0000 (82.5000)	lr 1.636271e-03
+epoch [42/100][20/20]	time 0.073 (0.092)	data 0.003 (0.023)	eta 0:01:47	loss 0.4369 (0.5786)	acc 75.0000 (82.5000)	lr 1.598739e-03
+epoch [43/100][20/20]	time 0.072 (0.092)	data 0.002 (0.022)	eta 0:01:44	loss 1.2615 (0.6798)	acc 50.0000 (77.5000)	lr 1.560862e-03
+epoch [44/100][20/20]	time 0.073 (0.092)	data 0.003 (0.022)	eta 0:01:42	loss 0.3427 (0.6785)	acc 75.0000 (78.7500)	lr 1.522679e-03
+epoch [45/100][20/20]	time 0.073 (0.090)	data 0.003 (0.021)	eta 0:01:39	loss 1.1742 (0.5712)	acc 50.0000 (78.7500)	lr 1.484227e-03
+epoch [46/100][20/20]	time 0.072 (0.092)	data 0.003 (0.022)	eta 0:01:39	loss 0.3616 (0.5737)	acc 100.0000 (85.0000)	lr 1.445543e-03
+epoch [47/100][20/20]	time 0.072 (0.092)	data 0.002 (0.022)	eta 0:01:37	loss 1.1248 (0.6973)	acc 75.0000 (80.0000)	lr 1.406667e-03
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+epoch [49/100][20/20]	time 0.072 (0.092)	data 0.003 (0.022)	eta 0:01:33	loss 0.2672 (0.5126)	acc 100.0000 (85.0000)	lr 1.328488e-03
+epoch [50/100][20/20]	time 0.071 (0.091)	data 0.002 (0.022)	eta 0:01:30	loss 0.8758 (0.6206)	acc 75.0000 (83.7500)	lr 1.289263e-03
+epoch [51/100][20/20]	time 0.072 (0.092)	data 0.002 (0.022)	eta 0:01:29	loss 0.6136 (0.6509)	acc 75.0000 (78.7500)	lr 1.250000e-03
+epoch [52/100][20/20]	time 0.073 (0.093)	data 0.003 (0.023)	eta 0:01:29	loss 0.8976 (0.6918)	acc 75.0000 (78.7500)	lr 1.210737e-03
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+epoch [54/100][20/20]	time 0.072 (0.090)	data 0.003 (0.021)	eta 0:01:23	loss 0.5565 (0.6550)	acc 100.0000 (83.7500)	lr 1.132365e-03
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+epoch [56/100][20/20]	time 0.072 (0.092)	data 0.003 (0.022)	eta 0:01:20	loss 0.6425 (0.6702)	acc 75.0000 (83.7500)	lr 1.054457e-03
+epoch [57/100][20/20]	time 0.072 (0.092)	data 0.003 (0.022)	eta 0:01:18	loss 0.8206 (0.6408)	acc 75.0000 (82.5000)	lr 1.015773e-03
+epoch [58/100][20/20]	time 0.072 (0.091)	data 0.003 (0.021)	eta 0:01:16	loss 0.5558 (0.4931)	acc 75.0000 (88.7500)	lr 9.773209e-04
+epoch [59/100][20/20]	time 0.072 (0.092)	data 0.002 (0.022)	eta 0:01:15	loss 0.6359 (0.5567)	acc 75.0000 (82.5000)	lr 9.391376e-04
+epoch [60/100][20/20]	time 0.073 (0.093)	data 0.003 (0.023)	eta 0:01:14	loss 0.2892 (0.5178)	acc 100.0000 (82.5000)	lr 9.012611e-04
+epoch [61/100][20/20]	time 0.072 (0.092)	data 0.003 (0.023)	eta 0:01:11	loss 0.4741 (0.6486)	acc 100.0000 (80.0000)	lr 8.637288e-04
+epoch [62/100][20/20]	time 0.073 (0.091)	data 0.003 (0.021)	eta 0:01:08	loss 0.3800 (0.5695)	acc 100.0000 (85.0000)	lr 8.265776e-04
+epoch [63/100][20/20]	time 0.072 (0.092)	data 0.002 (0.022)	eta 0:01:07	loss 0.9261 (0.6170)	acc 75.0000 (81.2500)	lr 7.898443e-04
+epoch [64/100][20/20]	time 0.073 (0.092)	data 0.003 (0.022)	eta 0:01:06	loss 0.2331 (0.5652)	acc 100.0000 (82.5000)	lr 7.535651e-04
+epoch [65/100][20/20]	time 0.072 (0.092)	data 0.003 (0.022)	eta 0:01:04	loss 0.7296 (0.4739)	acc 75.0000 (91.2500)	lr 7.177759e-04
+epoch [66/100][20/20]	time 0.073 (0.091)	data 0.003 (0.022)	eta 0:01:02	loss 0.3539 (0.6337)	acc 75.0000 (80.0000)	lr 6.825119e-04
+epoch [67/100][20/20]	time 0.072 (0.091)	data 0.003 (0.021)	eta 0:00:59	loss 0.4303 (0.4661)	acc 75.0000 (86.2500)	lr 6.478079e-04
+epoch [68/100][20/20]	time 0.072 (0.092)	data 0.003 (0.022)	eta 0:00:58	loss 0.1405 (0.6656)	acc 100.0000 (80.0000)	lr 6.136982e-04
+epoch [69/100][20/20]	time 0.073 (0.092)	data 0.003 (0.022)	eta 0:00:57	loss 0.5409 (0.6769)	acc 75.0000 (76.2500)	lr 5.802165e-04
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+epoch [71/100][20/20]	time 0.072 (0.091)	data 0.003 (0.022)	eta 0:00:52	loss 0.2063 (0.5184)	acc 100.0000 (85.0000)	lr 5.152684e-04
+epoch [72/100][20/20]	time 0.073 (0.091)	data 0.003 (0.022)	eta 0:00:51	loss 1.3122 (0.5698)	acc 75.0000 (87.5000)	lr 4.838662e-04
+epoch [73/100][20/20]	time 0.072 (0.092)	data 0.002 (0.023)	eta 0:00:49	loss 0.6439 (0.5180)	acc 75.0000 (86.2500)	lr 4.532200e-04
+epoch [74/100][20/20]	time 0.073 (0.092)	data 0.003 (0.022)	eta 0:00:47	loss 0.4377 (0.6334)	acc 75.0000 (81.2500)	lr 4.233602e-04
+epoch [75/100][20/20]	time 0.072 (0.092)	data 0.003 (0.022)	eta 0:00:45	loss 1.1107 (0.5148)	acc 75.0000 (85.0000)	lr 3.943161e-04
+epoch [76/100][20/20]	time 0.072 (0.091)	data 0.002 (0.022)	eta 0:00:43	loss 0.6395 (0.4946)	acc 75.0000 (86.2500)	lr 3.661165e-04
+epoch [77/100][20/20]	time 0.072 (0.091)	data 0.003 (0.021)	eta 0:00:41	loss 0.3139 (0.5376)	acc 100.0000 (83.7500)	lr 3.387892e-04
+epoch [78/100][20/20]	time 0.072 (0.091)	data 0.003 (0.021)	eta 0:00:39	loss 2.0697 (0.5104)	acc 50.0000 (85.0000)	lr 3.123612e-04
+epoch [79/100][20/20]	time 0.073 (0.092)	data 0.003 (0.023)	eta 0:00:38	loss 1.2688 (0.6007)	acc 75.0000 (81.2500)	lr 2.868584e-04
+epoch [80/100][20/20]	time 0.071 (0.091)	data 0.002 (0.022)	eta 0:00:36	loss 0.7835 (0.4777)	acc 50.0000 (86.2500)	lr 2.623062e-04
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+epoch [82/100][20/20]	time 0.071 (0.092)	data 0.002 (0.022)	eta 0:00:32	loss 1.3713 (0.6034)	acc 50.0000 (78.7500)	lr 2.161493e-04
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+epoch [89/100][20/20]	time 0.072 (0.091)	data 0.002 (0.022)	eta 0:00:20	loss 0.6137 (0.6255)	acc 75.0000 (78.7500)	lr 8.777939e-05
+epoch [90/100][20/20]	time 0.073 (0.092)	data 0.003 (0.023)	eta 0:00:18	loss 0.9575 (0.4693)	acc 50.0000 (90.0000)	lr 7.389904e-05
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+epoch [92/100][20/20]	time 0.072 (0.092)	data 0.003 (0.022)	eta 0:00:14	loss 0.4711 (0.5602)	acc 75.0000 (82.5000)	lr 4.963289e-05
+epoch [93/100][20/20]	time 0.072 (0.091)	data 0.003 (0.021)	eta 0:00:12	loss 0.2218 (0.6124)	acc 100.0000 (77.5000)	lr 3.927105e-05
+epoch [94/100][20/20]	time 0.072 (0.091)	data 0.003 (0.022)	eta 0:00:10	loss 0.4099 (0.6346)	acc 100.0000 (85.0000)	lr 3.010405e-05
+epoch [95/100][20/20]	time 0.072 (0.092)	data 0.002 (0.022)	eta 0:00:09	loss 0.3195 (0.5418)	acc 100.0000 (85.0000)	lr 2.214094e-05
+epoch [96/100][20/20]	time 0.073 (0.092)	data 0.003 (0.023)	eta 0:00:07	loss 0.7124 (0.5289)	acc 50.0000 (83.7500)	lr 1.538957e-05
+epoch [97/100][20/20]	time 0.071 (0.092)	data 0.002 (0.023)	eta 0:00:05	loss 0.2497 (0.5901)	acc 100.0000 (86.2500)	lr 9.856623e-06
+epoch [98/100][20/20]	time 0.072 (0.091)	data 0.003 (0.022)	eta 0:00:03	loss 0.1247 (0.5339)	acc 100.0000 (92.5000)	lr 5.547544e-06
+epoch [99/100][20/20]	time 0.072 (0.092)	data 0.003 (0.022)	eta 0:00:01	loss 0.4069 (0.5255)	acc 100.0000 (86.2500)	lr 2.466589e-06
+epoch [100/100][20/20]	time 0.073 (0.092)	data 0.003 (0.022)	eta 0:00:00	loss 2.0668 (0.5584)	acc 25.0000 (83.7500)	lr 6.167995e-07
+Checkpoint saved to "output_reproduce/lungcolon/shots_16/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/prompt_learner/model.pth.tar-100"
+Finished training
+Do evaluation on test set
+=> result
+* total: 7,500
+* correct: 6,923
+* accuracy: 92.31%
+* error: 7.69%
+* macro_f1: 92.15%
+Elapsed: 0:03:37

few_shot/lungcolon/shots_16/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/prompt_learner/checkpoint

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few_shot/lungcolon/shots_16/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/prompt_learner/model.pth.tar-100

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+size 1132531909

few_shot/lungcolon/shots_16/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/tensorboard/events.out.tfevents.1742386343.impactlab-server.3691768.0

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few_shot/lungcolon/shots_16/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/log.txt

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+***************
+** Arguments **
+***************
+backbone: 
+config_file: configs/trainers/BiomedCoOp_BiomedCLIP/few_shot/lungcolon.yaml
+dataset_config_file: configs/datasets/lungcolon.yaml
+eval_only: False
+head: 
+load_epoch: None
+model_dir: 
+no_train: False
+opts: ['TRAINER.BIOMEDCOOP.N_CTX', '4', 'TRAINER.BIOMEDCOOP.CSC', 'False', 'TRAINER.BIOMEDCOOP.CLASS_TOKEN_POSITION', 'end', 'DATASET.NUM_SHOTS', '16']
+output_dir: output_reproduce/lungcolon/shots_16/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3
+resume: 
+root: DATA
+seed: 3
+source_domains: None
+target_domains: None
+trainer: BiomedCoOp_BiomedCLIP
+transforms: None
+************
+** Config **
+************
+DATALOADER:
+  K_TRANSFORMS: 1
+  NUM_WORKERS: 8
+  RETURN_IMG0: False
+  TEST:
+    BATCH_SIZE: 100
+    SAMPLER: SequentialSampler
+  TRAIN_U:
+    BATCH_SIZE: 32
+    N_DOMAIN: 0
+    N_INS: 16
+    SAME_AS_X: True
+    SAMPLER: RandomSampler
+  TRAIN_X:
+    BATCH_SIZE: 4
+    N_DOMAIN: 0
+    N_INS: 16
+    SAMPLER: RandomSampler
+DATASET:
+  ALL_AS_UNLABELED: False
+  CIFAR_C_LEVEL: 1
+  CIFAR_C_TYPE: 
+  NAME: LungColon
+  NUM_LABELED: -1
+  NUM_SHOTS: 16
+  ROOT: DATA
+  SOURCE_DOMAINS: ()
+  STL10_FOLD: -1
+  SUBSAMPLE_CLASSES: all
+  TARGET_DOMAINS: ()
+  VAL_PERCENT: 0.1
+INPUT:
+  COLORJITTER_B: 0.4
+  COLORJITTER_C: 0.4
+  COLORJITTER_H: 0.1
+  COLORJITTER_S: 0.4
+  CROP_PADDING: 4
+  CUTOUT_LEN: 16
+  CUTOUT_N: 1
+  GB_K: 21
+  GB_P: 0.5
+  GN_MEAN: 0.0
+  GN_STD: 0.15
+  INTERPOLATION: bicubic
+  NO_TRANSFORM: False
+  PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
+  PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
+  RANDAUGMENT_M: 10
+  RANDAUGMENT_N: 2
+  RGS_P: 0.2
+  SIZE: (224, 224)
+  TRANSFORMS: ('random_resized_crop', 'normalize')
+MODEL:
+  BACKBONE:
+    NAME: ViT-B/16
+    PRETRAINED: True
+  HEAD:
+    ACTIVATION: relu
+    BN: True
+    DROPOUT: 0.0
+    HIDDEN_LAYERS: ()
+    NAME: 
+  INIT_WEIGHTS: 
+OPTIM:
+  ADAM_BETA1: 0.9
+  ADAM_BETA2: 0.999
+  BASE_LR_MULT: 0.1
+  GAMMA: 0.1
+  LR: 0.0025
+  LR_SCHEDULER: cosine
+  MAX_EPOCH: 100
+  MOMENTUM: 0.9
+  NAME: sgd
+  NEW_LAYERS: ()
+  RMSPROP_ALPHA: 0.99
+  SGD_DAMPNING: 0
+  SGD_NESTEROV: False
+  STAGED_LR: False
+  STEPSIZE: (-1,)
+  WARMUP_CONS_LR: 1e-05
+  WARMUP_EPOCH: 1
+  WARMUP_MIN_LR: 1e-05
+  WARMUP_RECOUNT: True
+  WARMUP_TYPE: constant
+  WEIGHT_DECAY: 0.0005
+OUTPUT_DIR: output_reproduce/lungcolon/shots_16/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3
+RESUME: 
+SEED: 3
+TEST:
+  COMPUTE_CMAT: False
+  EVALUATOR: Classification
+  FINAL_MODEL: last_step
+  NO_TEST: False
+  PER_CLASS_RESULT: False
+  SPLIT: test
+TRAIN:
+  CHECKPOINT_FREQ: 0
+  COUNT_ITER: train_x
+  PRINT_FREQ: 20
+TRAINER:
+  BIOMEDCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    KDSP_LAMBDA: 0.5
+    N_CTX: 4
+    N_PROMPTS: 50
+    PREC: fp32
+    SCCM_LAMBDA: 0.5
+    TAU: 1.5
+  CG:
+    ALPHA_D: 0.5
+    ALPHA_F: 0.5
+    EPS_D: 1.0
+    EPS_F: 1.0
+  COCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: 
+    N_CTX: 4
+    PREC: fp32
+  COOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: 
+    N_CTX: 4
+    PREC: fp32
+  DAEL:
+    CONF_THRE: 0.95
+    STRONG_TRANSFORMS: ()
+    WEIGHT_U: 0.5
+  DDAIG:
+    ALPHA: 0.5
+    CLAMP: False
+    CLAMP_MAX: 1.0
+    CLAMP_MIN: -1.0
+    G_ARCH: 
+    LMDA: 0.3
+    WARMUP: 0
+  ENTMIN:
+    LMDA: 0.001
+  FIXMATCH:
+    CONF_THRE: 0.95
+    STRONG_TRANSFORMS: ()
+    WEIGHT_U: 1.0
+  KGCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    N_CTX: 4
+    PREC: fp32
+    W: 1.0
+  M3SDA:
+    LMDA: 0.5
+    N_STEP_F: 4
+  MCD:
+    N_STEP_F: 4
+  MEANTEA:
+    EMA_ALPHA: 0.999
+    RAMPUP: 5
+    WEIGHT_U: 1.0
+  MIXMATCH:
+    MIXUP_BETA: 0.75
+    RAMPUP: 20000
+    TEMP: 2.0
+    WEIGHT_U: 100.0
+  MME:
+    LMDA: 0.1
+  NAME: BiomedCoOp_BiomedCLIP
+  PROGRAD:
+    ALPHA: 0.0
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    GM: False
+    LAMBDA: 1.0
+    NAME: 
+    N_CTX: 4
+    PREC: fp32
+    T: 1.0
+  SE:
+    CONF_THRE: 0.95
+    EMA_ALPHA: 0.999
+    RAMPUP: 300
+USE_CUDA: True
+VERBOSE: True
+VERSION: 1
+Collecting env info ...
+** System info **
+PyTorch version: 2.0.1+cu118
+Is debug build: False
+CUDA used to build PyTorch: 11.8
+ROCM used to build PyTorch: N/A
+
+OS: Ubuntu 22.04.5 LTS (x86_64)
+GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
+Clang version: Could not collect
+CMake version: version 3.25.0
+Libc version: glibc-2.35
+
+Python version: 3.10.15 (main, Oct  3 2024, 07:27:34) [GCC 11.2.0] (64-bit runtime)
+Python platform: Linux-5.15.0-134-generic-x86_64-with-glibc2.35
+Is CUDA available: True
+CUDA runtime version: 12.8.61
+CUDA_MODULE_LOADING set to: LAZY
+GPU models and configuration: 
+GPU 0: NVIDIA A100-SXM4-40GB
+GPU 1: NVIDIA A100-SXM4-40GB
+GPU 2: NVIDIA A100-SXM4-40GB
+GPU 3: NVIDIA A100-SXM4-40GB
+
+Nvidia driver version: 570.124.06
+cuDNN version: Could not collect
+HIP runtime version: N/A
+MIOpen runtime version: N/A
+Is XNNPACK available: True
+
+CPU:
+Architecture:                         x86_64
+CPU op-mode(s):                       32-bit, 64-bit
+Address sizes:                        43 bits physical, 48 bits virtual
+Byte Order:                           Little Endian
+CPU(s):                               128
+On-line CPU(s) list:                  0-127
+Vendor ID:                            AuthenticAMD
+Model name:                           AMD EPYC 7502 32-Core Processor
+CPU family:                           23
+Model:                                49
+Thread(s) per core:                   2
+Core(s) per socket:                   32
+Socket(s):                            2
+Stepping:                             0
+Frequency boost:                      enabled
+CPU max MHz:                          2500.0000
+CPU min MHz:                          1500.0000
+BogoMIPS:                             4999.71
+Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl umip rdpid overflow_recov succor smca sme sev sev_es
+Virtualization:                       AMD-V
+L1d cache:                            2 MiB (64 instances)
+L1i cache:                            2 MiB (64 instances)
+L2 cache:                             32 MiB (64 instances)
+L3 cache:                             256 MiB (16 instances)
+NUMA node(s):                         2
+NUMA node0 CPU(s):                    0-31,64-95
+NUMA node1 CPU(s):                    32-63,96-127
+Vulnerability Gather data sampling:   Not affected
+Vulnerability Itlb multihit:          Not affected
+Vulnerability L1tf:                   Not affected
+Vulnerability Mds:                    Not affected
+Vulnerability Meltdown:               Not affected
+Vulnerability Mmio stale data:        Not affected
+Vulnerability Reg file data sampling: Not affected
+Vulnerability Retbleed:               Mitigation; untrained return thunk; SMT enabled with STIBP protection
+Vulnerability Spec rstack overflow:   Mitigation; safe RET
+Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl and seccomp
+Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
+Vulnerability Spectre v2:             Mitigation; Retpolines; IBPB conditional; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
+Vulnerability Srbds:                  Not affected
+Vulnerability Tsx async abort:        Not affected
+
+Versions of relevant libraries:
+[pip3] numpy==1.26.3
+[pip3] torch==2.0.1+cu118
+[pip3] torchvision==0.15.2+cu118
+[conda] numpy                     1.26.3                   pypi_0    pypi
+[conda] torch                     2.0.1+cu118              pypi_0    pypi
+[conda] torchvision               0.15.2+cu118             pypi_0    pypi
+        Pillow (10.2.0)
+
+Loading trainer: BiomedCoOp_BiomedCLIP
+Loading dataset: LungColon
+Reading split from /data/t_kol/BiomedCoOp/DATA/LungColon/split_LungColon.json
+Loading preprocessed few-shot data from /data/t_kol/BiomedCoOp/DATA/LungColon/split_fewshot/shot_16-seed_3.pkl
+Building transform_train
++ random resized crop (size=(224, 224))
++ to torch tensor of range [0, 1]
++ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
+Building transform_test
++ resize the smaller edge to 224
++ 224x224 center crop
++ to torch tensor of range [0, 1]
++ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
+***** Dataset statistics *****
+  Dataset: LungColon
+  # classes: 5
+  # train_x: 80
+  # val: 20
+  # test: 7,500
+Loading BiomedCLIP (backbone: ViT-B/16)
+Building custom CLIP
+Initial text context: "a photo of a"
+Number of context words (tokens) for Language prompting: 4
+Turning off gradients in both the image and the text encoder
+Parameters to be updated: {'prompt_learner.ctx'}
+Parameters count: 1
+Loading evaluator: Classification
+Trainer built successfully.
+No checkpoint found, train from scratch
+Initializing summary writer for tensorboard with log_dir=output_reproduce/lungcolon/shots_16/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/tensorboard
+epoch [1/100][20/20]	time 0.072 (0.104)	data 0.003 (0.022)	eta 0:03:25	loss 2.1982 (2.2922)	acc 25.0000 (33.7500)	lr 2.500000e-03
+epoch [2/100][20/20]	time 0.072 (0.093)	data 0.002 (0.024)	eta 0:03:02	loss 0.9765 (1.6905)	acc 50.0000 (43.7500)	lr 2.499383e-03
+epoch [3/100][20/20]	time 0.072 (0.093)	data 0.002 (0.024)	eta 0:03:01	loss 0.7385 (1.2364)	acc 75.0000 (57.5000)	lr 2.497533e-03
+epoch [4/100][20/20]	time 0.072 (0.094)	data 0.002 (0.024)	eta 0:03:00	loss 1.9654 (1.2152)	acc 25.0000 (60.0000)	lr 2.494452e-03
+epoch [5/100][20/20]	time 0.072 (0.094)	data 0.003 (0.025)	eta 0:02:58	loss 1.4169 (0.9219)	acc 50.0000 (70.0000)	lr 2.490143e-03
+epoch [6/100][20/20]	time 0.072 (0.093)	data 0.002 (0.024)	eta 0:02:55	loss 1.5240 (1.1067)	acc 75.0000 (62.5000)	lr 2.484610e-03
+epoch [7/100][20/20]	time 0.073 (0.095)	data 0.003 (0.025)	eta 0:02:55	loss 0.5307 (0.9425)	acc 75.0000 (70.0000)	lr 2.477859e-03
+epoch [8/100][20/20]	time 0.072 (0.093)	data 0.002 (0.024)	eta 0:02:51	loss 0.9309 (0.8349)	acc 75.0000 (70.0000)	lr 2.469896e-03
+epoch [9/100][20/20]	time 0.071 (0.093)	data 0.002 (0.024)	eta 0:02:49	loss 0.7953 (0.8255)	acc 75.0000 (63.7500)	lr 2.460729e-03
+epoch [10/100][20/20]	time 0.072 (0.094)	data 0.002 (0.024)	eta 0:02:48	loss 0.8587 (0.8098)	acc 50.0000 (77.5000)	lr 2.450367e-03
+epoch [11/100][20/20]	time 0.073 (0.096)	data 0.003 (0.026)	eta 0:02:50	loss 1.2834 (0.7865)	acc 50.0000 (68.7500)	lr 2.438821e-03
+epoch [12/100][20/20]	time 0.072 (0.094)	data 0.002 (0.024)	eta 0:02:45	loss 1.6338 (0.8443)	acc 25.0000 (68.7500)	lr 2.426101e-03
+epoch [13/100][20/20]	time 0.073 (0.094)	data 0.003 (0.024)	eta 0:02:42	loss 1.0630 (0.7504)	acc 50.0000 (68.7500)	lr 2.412221e-03
+epoch [14/100][20/20]	time 0.073 (0.096)	data 0.003 (0.026)	eta 0:02:44	loss 0.2261 (0.7644)	acc 100.0000 (76.2500)	lr 2.397193e-03
+epoch [15/100][20/20]	time 0.072 (0.095)	data 0.002 (0.025)	eta 0:02:41	loss 1.1296 (0.7953)	acc 75.0000 (68.7500)	lr 2.381034e-03
+epoch [16/100][20/20]	time 0.073 (0.096)	data 0.003 (0.026)	eta 0:02:40	loss 0.8001 (0.7706)	acc 75.0000 (68.7500)	lr 2.363758e-03
+epoch [17/100][20/20]	time 0.073 (0.093)	data 0.003 (0.024)	eta 0:02:35	loss 0.8432 (0.8176)	acc 75.0000 (72.5000)	lr 2.345383e-03
+epoch [18/100][20/20]	time 0.072 (0.094)	data 0.003 (0.024)	eta 0:02:33	loss 1.9321 (0.7195)	acc 50.0000 (76.2500)	lr 2.325928e-03
+epoch [19/100][20/20]	time 0.073 (0.095)	data 0.003 (0.025)	eta 0:02:33	loss 0.3464 (0.5513)	acc 100.0000 (82.5000)	lr 2.305410e-03
+epoch [20/100][20/20]	time 0.072 (0.094)	data 0.003 (0.024)	eta 0:02:29	loss 0.7142 (0.6905)	acc 75.0000 (77.5000)	lr 2.283851e-03
+epoch [21/100][20/20]	time 0.073 (0.095)	data 0.003 (0.025)	eta 0:02:30	loss 0.6052 (0.6161)	acc 75.0000 (80.0000)	lr 2.261271e-03
+epoch [22/100][20/20]	time 0.073 (0.095)	data 0.003 (0.025)	eta 0:02:27	loss 0.6790 (0.5276)	acc 50.0000 (80.0000)	lr 2.237694e-03
+epoch [23/100][20/20]	time 0.072 (0.093)	data 0.003 (0.024)	eta 0:02:23	loss 0.6813 (0.6754)	acc 75.0000 (81.2500)	lr 2.213142e-03
+epoch [24/100][20/20]	time 0.072 (0.094)	data 0.003 (0.025)	eta 0:02:23	loss 0.6119 (0.8242)	acc 75.0000 (76.2500)	lr 2.187639e-03
+epoch [25/100][20/20]	time 0.072 (0.094)	data 0.003 (0.025)	eta 0:02:21	loss 0.7554 (0.7332)	acc 100.0000 (77.5000)	lr 2.161211e-03
+epoch [26/100][20/20]	time 0.071 (0.094)	data 0.002 (0.025)	eta 0:02:19	loss 0.3068 (0.6533)	acc 100.0000 (78.7500)	lr 2.133883e-03
+epoch [27/100][20/20]	time 0.072 (0.095)	data 0.002 (0.025)	eta 0:02:18	loss 0.3852 (0.5266)	acc 100.0000 (83.7500)	lr 2.105684e-03
+epoch [28/100][20/20]	time 0.071 (0.095)	data 0.002 (0.025)	eta 0:02:16	loss 0.6619 (0.5242)	acc 100.0000 (86.2500)	lr 2.076640e-03
+epoch [29/100][20/20]	time 0.071 (0.093)	data 0.002 (0.025)	eta 0:02:12	loss 0.9410 (0.6588)	acc 75.0000 (85.0000)	lr 2.046780e-03
+epoch [30/100][20/20]	time 0.072 (0.095)	data 0.003 (0.025)	eta 0:02:13	loss 0.9235 (0.6599)	acc 75.0000 (77.5000)	lr 2.016134e-03
+epoch [31/100][20/20]	time 0.072 (0.094)	data 0.002 (0.024)	eta 0:02:09	loss 0.2722 (0.8042)	acc 100.0000 (76.2500)	lr 1.984732e-03
+epoch [32/100][20/20]	time 0.071 (0.095)	data 0.002 (0.026)	eta 0:02:09	loss 0.9647 (0.4901)	acc 50.0000 (87.5000)	lr 1.952604e-03
+epoch [33/100][20/20]	time 0.071 (0.093)	data 0.002 (0.024)	eta 0:02:05	loss 0.8265 (0.7086)	acc 75.0000 (75.0000)	lr 1.919783e-03
+epoch [34/100][20/20]	time 0.073 (0.093)	data 0.003 (0.024)	eta 0:02:03	loss 0.5356 (0.5426)	acc 75.0000 (83.7500)	lr 1.886302e-03
+epoch [35/100][20/20]	time 0.073 (0.091)	data 0.003 (0.021)	eta 0:01:57	loss 0.1608 (0.6035)	acc 100.0000 (78.7500)	lr 1.852192e-03
+epoch [36/100][20/20]	time 0.072 (0.090)	data 0.003 (0.021)	eta 0:01:55	loss 0.4866 (0.5678)	acc 75.0000 (76.2500)	lr 1.817488e-03
+epoch [37/100][20/20]	time 0.072 (0.091)	data 0.002 (0.022)	eta 0:01:54	loss 0.6164 (0.5629)	acc 100.0000 (87.5000)	lr 1.782224e-03
+epoch [38/100][20/20]	time 0.072 (0.091)	data 0.002 (0.022)	eta 0:01:52	loss 0.3954 (0.5813)	acc 100.0000 (83.7500)	lr 1.746435e-03
+epoch [39/100][20/20]	time 0.071 (0.091)	data 0.002 (0.022)	eta 0:01:51	loss 0.6838 (0.5255)	acc 75.0000 (86.2500)	lr 1.710156e-03
+epoch [40/100][20/20]	time 0.072 (0.092)	data 0.003 (0.023)	eta 0:01:50	loss 0.8440 (0.5659)	acc 75.0000 (82.5000)	lr 1.673422e-03
+epoch [41/100][20/20]	time 0.072 (0.092)	data 0.002 (0.023)	eta 0:01:48	loss 0.8161 (0.6878)	acc 75.0000 (81.2500)	lr 1.636271e-03
+epoch [42/100][20/20]	time 0.072 (0.093)	data 0.003 (0.024)	eta 0:01:48	loss 0.0670 (0.5631)	acc 100.0000 (85.0000)	lr 1.598739e-03
+epoch [43/100][20/20]	time 0.071 (0.092)	data 0.002 (0.023)	eta 0:01:44	loss 0.6825 (0.5340)	acc 50.0000 (88.7500)	lr 1.560862e-03
+epoch [44/100][20/20]	time 0.071 (0.091)	data 0.002 (0.022)	eta 0:01:42	loss 0.6752 (0.6234)	acc 75.0000 (82.5000)	lr 1.522679e-03
+epoch [45/100][20/20]	time 0.072 (0.091)	data 0.003 (0.022)	eta 0:01:40	loss 0.3117 (0.5278)	acc 100.0000 (85.0000)	lr 1.484227e-03
+epoch [46/100][20/20]	time 0.072 (0.092)	data 0.003 (0.022)	eta 0:01:39	loss 0.9813 (0.5950)	acc 75.0000 (82.5000)	lr 1.445543e-03
+epoch [47/100][20/20]	time 0.072 (0.092)	data 0.003 (0.022)	eta 0:01:37	loss 0.2830 (0.4673)	acc 100.0000 (86.2500)	lr 1.406667e-03
+epoch [48/100][20/20]	time 0.072 (0.091)	data 0.002 (0.022)	eta 0:01:34	loss 0.2127 (0.5268)	acc 100.0000 (83.7500)	lr 1.367635e-03
+epoch [49/100][20/20]	time 0.072 (0.091)	data 0.003 (0.021)	eta 0:01:32	loss 1.0007 (0.5019)	acc 75.0000 (86.2500)	lr 1.328488e-03
+epoch [50/100][20/20]	time 0.072 (0.093)	data 0.002 (0.023)	eta 0:01:32	loss 1.2965 (0.6569)	acc 75.0000 (85.0000)	lr 1.289263e-03
+epoch [51/100][20/20]	time 0.071 (0.092)	data 0.002 (0.023)	eta 0:01:29	loss 0.2170 (0.5551)	acc 100.0000 (85.0000)	lr 1.250000e-03
+epoch [52/100][20/20]	time 0.072 (0.091)	data 0.003 (0.022)	eta 0:01:27	loss 0.3031 (0.4455)	acc 100.0000 (91.2500)	lr 1.210737e-03
+epoch [53/100][20/20]	time 0.072 (0.093)	data 0.003 (0.023)	eta 0:01:27	loss 0.1014 (0.5101)	acc 100.0000 (82.5000)	lr 1.171512e-03
+epoch [54/100][20/20]	time 0.072 (0.092)	data 0.002 (0.023)	eta 0:01:24	loss 0.1312 (0.5334)	acc 100.0000 (88.7500)	lr 1.132365e-03
+epoch [55/100][20/20]	time 0.072 (0.093)	data 0.002 (0.023)	eta 0:01:23	loss 0.5023 (0.5666)	acc 75.0000 (83.7500)	lr 1.093333e-03
+epoch [56/100][20/20]	time 0.072 (0.091)	data 0.002 (0.021)	eta 0:01:19	loss 0.2921 (0.5059)	acc 100.0000 (87.5000)	lr 1.054457e-03
+epoch [57/100][20/20]	time 0.072 (0.093)	data 0.003 (0.023)	eta 0:01:19	loss 0.4626 (0.6046)	acc 75.0000 (78.7500)	lr 1.015773e-03
+epoch [58/100][20/20]	time 0.072 (0.092)	data 0.003 (0.022)	eta 0:01:17	loss 0.0984 (0.5606)	acc 100.0000 (83.7500)	lr 9.773209e-04
+epoch [59/100][20/20]	time 0.072 (0.092)	data 0.003 (0.022)	eta 0:01:15	loss 0.3113 (0.5909)	acc 100.0000 (78.7500)	lr 9.391376e-04
+epoch [60/100][20/20]	time 0.072 (0.091)	data 0.002 (0.022)	eta 0:01:12	loss 1.2662 (0.4821)	acc 50.0000 (86.2500)	lr 9.012611e-04
+epoch [61/100][20/20]	time 0.072 (0.092)	data 0.002 (0.022)	eta 0:01:11	loss 0.6724 (0.5747)	acc 75.0000 (81.2500)	lr 8.637288e-04
+epoch [62/100][20/20]	time 0.072 (0.091)	data 0.002 (0.022)	eta 0:01:09	loss 0.1522 (0.4532)	acc 100.0000 (88.7500)	lr 8.265776e-04
+epoch [63/100][20/20]	time 0.073 (0.093)	data 0.003 (0.023)	eta 0:01:08	loss 0.4284 (0.3889)	acc 75.0000 (91.2500)	lr 7.898443e-04
+epoch [64/100][20/20]	time 0.073 (0.093)	data 0.003 (0.024)	eta 0:01:07	loss 0.3077 (0.5084)	acc 100.0000 (86.2500)	lr 7.535651e-04
+epoch [65/100][20/20]	time 0.071 (0.091)	data 0.002 (0.022)	eta 0:01:03	loss 0.8366 (0.5363)	acc 50.0000 (83.7500)	lr 7.177759e-04
+epoch [66/100][20/20]	time 0.072 (0.091)	data 0.002 (0.022)	eta 0:01:02	loss 0.5479 (0.4798)	acc 100.0000 (87.5000)	lr 6.825119e-04
+epoch [67/100][20/20]	time 0.072 (0.092)	data 0.002 (0.022)	eta 0:01:00	loss 0.9878 (0.5086)	acc 75.0000 (85.0000)	lr 6.478079e-04
+epoch [68/100][20/20]	time 0.072 (0.091)	data 0.002 (0.021)	eta 0:00:58	loss 0.1830 (0.4571)	acc 100.0000 (91.2500)	lr 6.136982e-04
+epoch [69/100][20/20]	time 0.072 (0.091)	data 0.003 (0.022)	eta 0:00:56	loss 0.4679 (0.5146)	acc 75.0000 (86.2500)	lr 5.802165e-04
+epoch [70/100][20/20]	time 0.071 (0.092)	data 0.002 (0.022)	eta 0:00:54	loss 2.4001 (0.5574)	acc 75.0000 (87.5000)	lr 5.473958e-04
+epoch [71/100][20/20]	time 0.072 (0.092)	data 0.003 (0.023)	eta 0:00:53	loss 0.4688 (0.4629)	acc 100.0000 (86.2500)	lr 5.152684e-04
+epoch [72/100][20/20]	time 0.072 (0.092)	data 0.002 (0.022)	eta 0:00:51	loss 0.6355 (0.5202)	acc 75.0000 (86.2500)	lr 4.838662e-04
+epoch [73/100][20/20]	time 0.072 (0.092)	data 0.003 (0.022)	eta 0:00:49	loss 0.2395 (0.5892)	acc 100.0000 (86.2500)	lr 4.532200e-04
+epoch [74/100][20/20]	time 0.072 (0.092)	data 0.003 (0.022)	eta 0:00:47	loss 0.7495 (0.6058)	acc 50.0000 (82.5000)	lr 4.233602e-04
+epoch [75/100][20/20]	time 0.072 (0.091)	data 0.003 (0.022)	eta 0:00:45	loss 0.5794 (0.7358)	acc 50.0000 (73.7500)	lr 3.943161e-04
+epoch [76/100][20/20]	time 0.072 (0.092)	data 0.003 (0.022)	eta 0:00:43	loss 1.5834 (0.5184)	acc 75.0000 (90.0000)	lr 3.661165e-04
+epoch [77/100][20/20]	time 0.071 (0.092)	data 0.002 (0.022)	eta 0:00:42	loss 0.2329 (0.5173)	acc 100.0000 (86.2500)	lr 3.387892e-04
+epoch [78/100][20/20]	time 0.071 (0.091)	data 0.002 (0.022)	eta 0:00:40	loss 0.2719 (0.3977)	acc 100.0000 (90.0000)	lr 3.123612e-04
+epoch [79/100][20/20]	time 0.072 (0.092)	data 0.002 (0.023)	eta 0:00:38	loss 0.5560 (0.5965)	acc 75.0000 (82.5000)	lr 2.868584e-04
+epoch [80/100][20/20]	time 0.072 (0.091)	data 0.002 (0.021)	eta 0:00:36	loss 0.4090 (0.5489)	acc 75.0000 (80.0000)	lr 2.623062e-04
+epoch [81/100][20/20]	time 0.072 (0.091)	data 0.002 (0.022)	eta 0:00:34	loss 0.3254 (0.5287)	acc 100.0000 (86.2500)	lr 2.387288e-04
+epoch [82/100][20/20]	time 0.072 (0.092)	data 0.002 (0.023)	eta 0:00:33	loss 0.4526 (0.4604)	acc 100.0000 (90.0000)	lr 2.161493e-04
+epoch [83/100][20/20]	time 0.072 (0.093)	data 0.002 (0.023)	eta 0:00:31	loss 0.8879 (0.5835)	acc 75.0000 (83.7500)	lr 1.945901e-04
+epoch [84/100][20/20]	time 0.072 (0.092)	data 0.002 (0.022)	eta 0:00:29	loss 0.3519 (0.5118)	acc 100.0000 (85.0000)	lr 1.740725e-04
+epoch [85/100][20/20]	time 0.072 (0.091)	data 0.002 (0.021)	eta 0:00:27	loss 0.7948 (0.5286)	acc 75.0000 (85.0000)	lr 1.546166e-04
+epoch [86/100][20/20]	time 0.071 (0.092)	data 0.002 (0.023)	eta 0:00:25	loss 0.5409 (0.4649)	acc 75.0000 (83.7500)	lr 1.362418e-04
+epoch [87/100][20/20]	time 0.072 (0.091)	data 0.003 (0.021)	eta 0:00:23	loss 0.3036 (0.5218)	acc 100.0000 (83.7500)	lr 1.189662e-04
+epoch [88/100][20/20]	time 0.072 (0.092)	data 0.003 (0.022)	eta 0:00:22	loss 0.2435 (0.4877)	acc 100.0000 (87.5000)	lr 1.028067e-04
+epoch [89/100][20/20]	time 0.072 (0.092)	data 0.003 (0.023)	eta 0:00:20	loss 0.0898 (0.5118)	acc 100.0000 (85.0000)	lr 8.777939e-05
+epoch [90/100][20/20]	time 0.072 (0.090)	data 0.002 (0.021)	eta 0:00:18	loss 0.2008 (0.4907)	acc 100.0000 (91.2500)	lr 7.389904e-05
+epoch [91/100][20/20]	time 0.072 (0.091)	data 0.002 (0.021)	eta 0:00:16	loss 0.2498 (0.4803)	acc 100.0000 (87.5000)	lr 6.117935e-05
+epoch [92/100][20/20]	time 0.072 (0.092)	data 0.002 (0.022)	eta 0:00:14	loss 0.4161 (0.4329)	acc 100.0000 (91.2500)	lr 4.963289e-05
+epoch [93/100][20/20]	time 0.073 (0.092)	data 0.003 (0.022)	eta 0:00:12	loss 0.4284 (0.5261)	acc 100.0000 (86.2500)	lr 3.927105e-05
+epoch [94/100][20/20]	time 0.072 (0.092)	data 0.003 (0.023)	eta 0:00:11	loss 0.2391 (0.3947)	acc 100.0000 (92.5000)	lr 3.010405e-05
+epoch [95/100][20/20]	time 0.073 (0.093)	data 0.003 (0.023)	eta 0:00:09	loss 0.2293 (0.3982)	acc 100.0000 (93.7500)	lr 2.214094e-05
+epoch [96/100][20/20]	time 0.072 (0.092)	data 0.002 (0.022)	eta 0:00:07	loss 1.1158 (0.5315)	acc 50.0000 (82.5000)	lr 1.538957e-05
+epoch [97/100][20/20]	time 0.072 (0.091)	data 0.003 (0.021)	eta 0:00:05	loss 0.9487 (0.5509)	acc 50.0000 (80.0000)	lr 9.856623e-06
+epoch [98/100][20/20]	time 0.072 (0.091)	data 0.002 (0.022)	eta 0:00:03	loss 0.2702 (0.5752)	acc 100.0000 (82.5000)	lr 5.547544e-06
+epoch [99/100][20/20]	time 0.071 (0.091)	data 0.002 (0.022)	eta 0:00:01	loss 0.1804 (0.4419)	acc 100.0000 (87.5000)	lr 2.466589e-06
+epoch [100/100][20/20]	time 0.072 (0.092)	data 0.003 (0.023)	eta 0:00:00	loss 0.3670 (0.5254)	acc 100.0000 (85.0000)	lr 6.167995e-07
+Checkpoint saved to "output_reproduce/lungcolon/shots_16/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/prompt_learner/model.pth.tar-100"
+Finished training
+Do evaluation on test set
+=> result
+* total: 7,500
+* correct: 6,919
+* accuracy: 92.25%
+* error: 7.75%
+* macro_f1: 92.15%
+Elapsed: 0:03:37

few_shot/lungcolon/shots_16/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/prompt_learner/checkpoint

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few_shot/lungcolon/shots_16/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/tensorboard/events.out.tfevents.1742386577.impactlab-server.3811074.0

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few_shot/lungcolon/shots_2/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1/log.txt

@@ -0,0 +1,532 @@
+***************
+** Arguments **
+***************
+backbone: 
+config_file: configs/trainers/BiomedCoOp_BiomedCLIP/few_shot/lungcolon.yaml
+dataset_config_file: configs/datasets/lungcolon.yaml
+eval_only: False
+head: 
+load_epoch: None
+model_dir: 
+no_train: False
+opts: ['TRAINER.BIOMEDCOOP.N_CTX', '4', 'TRAINER.BIOMEDCOOP.CSC', 'False', 'TRAINER.BIOMEDCOOP.CLASS_TOKEN_POSITION', 'end', 'DATASET.NUM_SHOTS', '2']
+output_dir: output_reproduce/lungcolon/shots_2/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1
+resume: 
+root: DATA
+seed: 1
+source_domains: None
+target_domains: None
+trainer: BiomedCoOp_BiomedCLIP
+transforms: None
+************
+** Config **
+************
+DATALOADER:
+  K_TRANSFORMS: 1
+  NUM_WORKERS: 8
+  RETURN_IMG0: False
+  TEST:
+    BATCH_SIZE: 100
+    SAMPLER: SequentialSampler
+  TRAIN_U:
+    BATCH_SIZE: 32
+    N_DOMAIN: 0
+    N_INS: 16
+    SAME_AS_X: True
+    SAMPLER: RandomSampler
+  TRAIN_X:
+    BATCH_SIZE: 4
+    N_DOMAIN: 0
+    N_INS: 16
+    SAMPLER: RandomSampler
+DATASET:
+  ALL_AS_UNLABELED: False
+  CIFAR_C_LEVEL: 1
+  CIFAR_C_TYPE: 
+  NAME: LungColon
+  NUM_LABELED: -1
+  NUM_SHOTS: 2
+  ROOT: DATA
+  SOURCE_DOMAINS: ()
+  STL10_FOLD: -1
+  SUBSAMPLE_CLASSES: all
+  TARGET_DOMAINS: ()
+  VAL_PERCENT: 0.1
+INPUT:
+  COLORJITTER_B: 0.4
+  COLORJITTER_C: 0.4
+  COLORJITTER_H: 0.1
+  COLORJITTER_S: 0.4
+  CROP_PADDING: 4
+  CUTOUT_LEN: 16
+  CUTOUT_N: 1
+  GB_K: 21
+  GB_P: 0.5
+  GN_MEAN: 0.0
+  GN_STD: 0.15
+  INTERPOLATION: bicubic
+  NO_TRANSFORM: False
+  PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
+  PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
+  RANDAUGMENT_M: 10
+  RANDAUGMENT_N: 2
+  RGS_P: 0.2
+  SIZE: (224, 224)
+  TRANSFORMS: ('random_resized_crop', 'normalize')
+MODEL:
+  BACKBONE:
+    NAME: ViT-B/16
+    PRETRAINED: True
+  HEAD:
+    ACTIVATION: relu
+    BN: True
+    DROPOUT: 0.0
+    HIDDEN_LAYERS: ()
+    NAME: 
+  INIT_WEIGHTS: 
+OPTIM:
+  ADAM_BETA1: 0.9
+  ADAM_BETA2: 0.999
+  BASE_LR_MULT: 0.1
+  GAMMA: 0.1
+  LR: 0.0025
+  LR_SCHEDULER: cosine
+  MAX_EPOCH: 100
+  MOMENTUM: 0.9
+  NAME: sgd
+  NEW_LAYERS: ()
+  RMSPROP_ALPHA: 0.99
+  SGD_DAMPNING: 0
+  SGD_NESTEROV: False
+  STAGED_LR: False
+  STEPSIZE: (-1,)
+  WARMUP_CONS_LR: 1e-05
+  WARMUP_EPOCH: 1
+  WARMUP_MIN_LR: 1e-05
+  WARMUP_RECOUNT: True
+  WARMUP_TYPE: constant
+  WEIGHT_DECAY: 0.0005
+OUTPUT_DIR: output_reproduce/lungcolon/shots_2/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1
+RESUME: 
+SEED: 1
+TEST:
+  COMPUTE_CMAT: False
+  EVALUATOR: Classification
+  FINAL_MODEL: last_step
+  NO_TEST: False
+  PER_CLASS_RESULT: False
+  SPLIT: test
+TRAIN:
+  CHECKPOINT_FREQ: 0
+  COUNT_ITER: train_x
+  PRINT_FREQ: 20
+TRAINER:
+  BIOMEDCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    KDSP_LAMBDA: 0.5
+    N_CTX: 4
+    N_PROMPTS: 50
+    PREC: fp32
+    SCCM_LAMBDA: 0.5
+    TAU: 1.5
+  CG:
+    ALPHA_D: 0.5
+    ALPHA_F: 0.5
+    EPS_D: 1.0
+    EPS_F: 1.0
+  COCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: 
+    N_CTX: 4
+    PREC: fp32
+  COOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: 
+    N_CTX: 4
+    PREC: fp32
+  DAEL:
+    CONF_THRE: 0.95
+    STRONG_TRANSFORMS: ()
+    WEIGHT_U: 0.5
+  DDAIG:
+    ALPHA: 0.5
+    CLAMP: False
+    CLAMP_MAX: 1.0
+    CLAMP_MIN: -1.0
+    G_ARCH: 
+    LMDA: 0.3
+    WARMUP: 0
+  ENTMIN:
+    LMDA: 0.001
+  FIXMATCH:
+    CONF_THRE: 0.95
+    STRONG_TRANSFORMS: ()
+    WEIGHT_U: 1.0
+  KGCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    N_CTX: 4
+    PREC: fp32
+    W: 1.0
+  M3SDA:
+    LMDA: 0.5
+    N_STEP_F: 4
+  MCD:
+    N_STEP_F: 4
+  MEANTEA:
+    EMA_ALPHA: 0.999
+    RAMPUP: 5
+    WEIGHT_U: 1.0
+  MIXMATCH:
+    MIXUP_BETA: 0.75
+    RAMPUP: 20000
+    TEMP: 2.0
+    WEIGHT_U: 100.0
+  MME:
+    LMDA: 0.1
+  NAME: BiomedCoOp_BiomedCLIP
+  PROGRAD:
+    ALPHA: 0.0
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    GM: False
+    LAMBDA: 1.0
+    NAME: 
+    N_CTX: 4
+    PREC: fp32
+    T: 1.0
+  SE:
+    CONF_THRE: 0.95
+    EMA_ALPHA: 0.999
+    RAMPUP: 300
+USE_CUDA: True
+VERBOSE: True
+VERSION: 1
+Collecting env info ...
+** System info **
+PyTorch version: 2.0.1+cu118
+Is debug build: False
+CUDA used to build PyTorch: 11.8
+ROCM used to build PyTorch: N/A
+
+OS: Ubuntu 22.04.5 LTS (x86_64)
+GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
+Clang version: Could not collect
+CMake version: version 3.25.0
+Libc version: glibc-2.35
+
+Python version: 3.10.15 (main, Oct  3 2024, 07:27:34) [GCC 11.2.0] (64-bit runtime)
+Python platform: Linux-5.15.0-134-generic-x86_64-with-glibc2.35
+Is CUDA available: True
+CUDA runtime version: 12.8.61
+CUDA_MODULE_LOADING set to: LAZY
+GPU models and configuration: 
+GPU 0: NVIDIA A100-SXM4-40GB
+GPU 1: NVIDIA A100-SXM4-40GB
+GPU 2: NVIDIA A100-SXM4-40GB
+GPU 3: NVIDIA A100-SXM4-40GB
+
+Nvidia driver version: 570.124.06
+cuDNN version: Could not collect
+HIP runtime version: N/A
+MIOpen runtime version: N/A
+Is XNNPACK available: True
+
+CPU:
+Architecture:                         x86_64
+CPU op-mode(s):                       32-bit, 64-bit
+Address sizes:                        43 bits physical, 48 bits virtual
+Byte Order:                           Little Endian
+CPU(s):                               128
+On-line CPU(s) list:                  0-127
+Vendor ID:                            AuthenticAMD
+Model name:                           AMD EPYC 7502 32-Core Processor
+CPU family:                           23
+Model:                                49
+Thread(s) per core:                   2
+Core(s) per socket:                   32
+Socket(s):                            2
+Stepping:                             0
+Frequency boost:                      enabled
+CPU max MHz:                          2500.0000
+CPU min MHz:                          1500.0000
+BogoMIPS:                             4999.71
+Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl umip rdpid overflow_recov succor smca sme sev sev_es
+Virtualization:                       AMD-V
+L1d cache:                            2 MiB (64 instances)
+L1i cache:                            2 MiB (64 instances)
+L2 cache:                             32 MiB (64 instances)
+L3 cache:                             256 MiB (16 instances)
+NUMA node(s):                         2
+NUMA node0 CPU(s):                    0-31,64-95
+NUMA node1 CPU(s):                    32-63,96-127
+Vulnerability Gather data sampling:   Not affected
+Vulnerability Itlb multihit:          Not affected
+Vulnerability L1tf:                   Not affected
+Vulnerability Mds:                    Not affected
+Vulnerability Meltdown:               Not affected
+Vulnerability Mmio stale data:        Not affected
+Vulnerability Reg file data sampling: Not affected
+Vulnerability Retbleed:               Mitigation; untrained return thunk; SMT enabled with STIBP protection
+Vulnerability Spec rstack overflow:   Mitigation; safe RET
+Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl and seccomp
+Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
+Vulnerability Spectre v2:             Mitigation; Retpolines; IBPB conditional; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
+Vulnerability Srbds:                  Not affected
+Vulnerability Tsx async abort:        Not affected
+
+Versions of relevant libraries:
+[pip3] numpy==1.26.3
+[pip3] torch==2.0.1+cu118
+[pip3] torchvision==0.15.2+cu118
+[conda] numpy                     1.26.3                   pypi_0    pypi
+[conda] torch                     2.0.1+cu118              pypi_0    pypi
+[conda] torchvision               0.15.2+cu118             pypi_0    pypi
+        Pillow (10.2.0)
+
+Loading trainer: BiomedCoOp_BiomedCLIP
+Loading dataset: LungColon
+Reading split from /data/t_kol/BiomedCoOp/DATA/LungColon/split_LungColon.json
+Loading preprocessed few-shot data from /data/t_kol/BiomedCoOp/DATA/LungColon/split_fewshot/shot_2-seed_1.pkl
+Building transform_train
++ random resized crop (size=(224, 224))
++ to torch tensor of range [0, 1]
++ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
+Building transform_test
++ resize the smaller edge to 224
++ 224x224 center crop
++ to torch tensor of range [0, 1]
++ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
+***** Dataset statistics *****
+  Dataset: LungColon
+  # classes: 5
+  # train_x: 10
+  # val: 10
+  # test: 7,500
+Loading BiomedCLIP (backbone: ViT-B/16)
+Building custom CLIP
+Initial text context: "a photo of a"
+Number of context words (tokens) for Language prompting: 4
+Turning off gradients in both the image and the text encoder
+Parameters to be updated: {'prompt_learner.ctx'}
+Parameters count: 1
+Loading evaluator: Classification
+Trainer built successfully.
+No checkpoint found, train from scratch
+Initializing summary writer for tensorboard with log_dir=output_reproduce/lungcolon/shots_2/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1/tensorboard
+epoch [1/100][1/2]	time 0.734 (0.734)	data 0.413 (0.413)	eta 0:02:26	loss 2.3723 (2.3723)	acc 50.0000 (50.0000)	lr 1.000000e-05
+epoch [1/100][2/2]	time 0.071 (0.403)	data 0.001 (0.207)	eta 0:01:19	loss 2.2916 (2.3320)	acc 25.0000 (37.5000)	lr 2.500000e-03
+epoch [2/100][1/2]	time 0.522 (0.522)	data 0.449 (0.449)	eta 0:01:42	loss 4.6372 (4.6372)	acc 25.0000 (25.0000)	lr 2.500000e-03
+epoch [2/100][2/2]	time 0.073 (0.297)	data 0.003 (0.226)	eta 0:00:58	loss 2.4328 (3.5350)	acc 25.0000 (25.0000)	lr 2.499383e-03
+epoch [3/100][1/2]	time 0.534 (0.534)	data 0.461 (0.461)	eta 0:01:44	loss 1.0786 (1.0786)	acc 50.0000 (50.0000)	lr 2.499383e-03
+epoch [3/100][2/2]	time 0.070 (0.302)	data 0.001 (0.231)	eta 0:00:58	loss 3.1773 (2.1279)	acc 50.0000 (50.0000)	lr 2.497533e-03
+epoch [4/100][1/2]	time 0.583 (0.583)	data 0.510 (0.510)	eta 0:01:52	loss 1.8445 (1.8445)	acc 50.0000 (50.0000)	lr 2.497533e-03
+epoch [4/100][2/2]	time 0.072 (0.327)	data 0.001 (0.255)	eta 0:01:02	loss 1.8520 (1.8483)	acc 25.0000 (37.5000)	lr 2.494452e-03
+epoch [5/100][1/2]	time 0.545 (0.545)	data 0.473 (0.473)	eta 0:01:44	loss 0.7927 (0.7927)	acc 75.0000 (75.0000)	lr 2.494452e-03
+epoch [5/100][2/2]	time 0.072 (0.309)	data 0.003 (0.238)	eta 0:00:58	loss 1.7513 (1.2720)	acc 0.0000 (37.5000)	lr 2.490143e-03
+epoch [6/100][1/2]	time 0.564 (0.564)	data 0.491 (0.491)	eta 0:01:46	loss 1.3174 (1.3174)	acc 50.0000 (50.0000)	lr 2.490143e-03
+epoch [6/100][2/2]	time 0.073 (0.318)	data 0.003 (0.247)	eta 0:00:59	loss 1.9191 (1.6182)	acc 25.0000 (37.5000)	lr 2.484610e-03
+epoch [7/100][1/2]	time 0.564 (0.564)	data 0.490 (0.490)	eta 0:01:45	loss 1.5931 (1.5931)	acc 25.0000 (25.0000)	lr 2.484610e-03
+epoch [7/100][2/2]	time 0.071 (0.317)	data 0.001 (0.246)	eta 0:00:59	loss 0.8236 (1.2084)	acc 50.0000 (37.5000)	lr 2.477859e-03
+epoch [8/100][1/2]	time 0.573 (0.573)	data 0.496 (0.496)	eta 0:01:45	loss 1.0040 (1.0040)	acc 75.0000 (75.0000)	lr 2.477859e-03
+epoch [8/100][2/2]	time 0.072 (0.323)	data 0.002 (0.249)	eta 0:00:59	loss 1.8880 (1.4460)	acc 50.0000 (62.5000)	lr 2.469896e-03
+epoch [9/100][1/2]	time 0.545 (0.545)	data 0.472 (0.472)	eta 0:01:39	loss 0.8241 (0.8241)	acc 50.0000 (50.0000)	lr 2.469896e-03
+epoch [9/100][2/2]	time 0.071 (0.308)	data 0.003 (0.237)	eta 0:00:56	loss 1.1740 (0.9990)	acc 50.0000 (50.0000)	lr 2.460729e-03
+epoch [10/100][1/2]	time 0.580 (0.580)	data 0.502 (0.502)	eta 0:01:45	loss 1.0303 (1.0303)	acc 50.0000 (50.0000)	lr 2.460729e-03
+epoch [10/100][2/2]	time 0.071 (0.326)	data 0.002 (0.252)	eta 0:00:58	loss 1.4134 (1.2219)	acc 50.0000 (50.0000)	lr 2.450367e-03
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+epoch [73/100][1/2]	time 0.554 (0.554)	data 0.481 (0.481)	eta 0:00:30	loss 0.2245 (0.2245)	acc 100.0000 (100.0000)	lr 4.838662e-04
+epoch [73/100][2/2]	time 0.070 (0.312)	data 0.001 (0.241)	eta 0:00:16	loss 0.3338 (0.2792)	acc 100.0000 (100.0000)	lr 4.532200e-04
+epoch [74/100][1/2]	time 0.579 (0.579)	data 0.502 (0.502)	eta 0:00:30	loss 0.4033 (0.4033)	acc 100.0000 (100.0000)	lr 4.532200e-04
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+epoch [81/100][1/2]	time 0.571 (0.571)	data 0.498 (0.498)	eta 0:00:22	loss 0.6499 (0.6499)	acc 50.0000 (50.0000)	lr 2.623062e-04
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+epoch [84/100][1/2]	time 0.589 (0.589)	data 0.516 (0.516)	eta 0:00:19	loss 0.8054 (0.8054)	acc 75.0000 (75.0000)	lr 1.945901e-04
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+epoch [97/100][2/2]	time 0.071 (0.321)	data 0.001 (0.249)	eta 0:00:01	loss 1.2018 (0.8240)	acc 75.0000 (75.0000)	lr 9.856623e-06
+epoch [98/100][1/2]	time 0.583 (0.583)	data 0.510 (0.510)	eta 0:00:02	loss 0.9827 (0.9827)	acc 50.0000 (50.0000)	lr 9.856623e-06
+epoch [98/100][2/2]	time 0.071 (0.327)	data 0.001 (0.256)	eta 0:00:01	loss 0.2828 (0.6328)	acc 100.0000 (75.0000)	lr 5.547544e-06
+epoch [99/100][1/2]	time 0.588 (0.588)	data 0.515 (0.515)	eta 0:00:01	loss 1.5345 (1.5345)	acc 50.0000 (50.0000)	lr 5.547544e-06
+epoch [99/100][2/2]	time 0.073 (0.331)	data 0.003 (0.259)	eta 0:00:00	loss 0.8281 (1.1813)	acc 75.0000 (62.5000)	lr 2.466589e-06
+epoch [100/100][1/2]	time 0.578 (0.578)	data 0.500 (0.500)	eta 0:00:00	loss 0.8067 (0.8067)	acc 75.0000 (75.0000)	lr 2.466589e-06
+epoch [100/100][2/2]	time 0.071 (0.324)	data 0.001 (0.251)	eta 0:00:00	loss 1.0039 (0.9053)	acc 50.0000 (62.5000)	lr 6.167995e-07
+Checkpoint saved to "output_reproduce/lungcolon/shots_2/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1/prompt_learner/model.pth.tar-100"
+Finished training
+Do evaluation on test set
+=> result
+* total: 7,500
+* correct: 5,867
+* accuracy: 78.23%
+* error: 21.77%
+* macro_f1: 77.96%
+Elapsed: 0:01:39

few_shot/lungcolon/shots_2/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1/prompt_learner/checkpoint

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+size 1132531909

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few_shot/lungcolon/shots_2/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/log.txt

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+***************
+** Arguments **
+***************
+backbone: 
+config_file: configs/trainers/BiomedCoOp_BiomedCLIP/few_shot/lungcolon.yaml
+dataset_config_file: configs/datasets/lungcolon.yaml
+eval_only: False
+head: 
+load_epoch: None
+model_dir: 
+no_train: False
+opts: ['TRAINER.BIOMEDCOOP.N_CTX', '4', 'TRAINER.BIOMEDCOOP.CSC', 'False', 'TRAINER.BIOMEDCOOP.CLASS_TOKEN_POSITION', 'end', 'DATASET.NUM_SHOTS', '2']
+output_dir: output_reproduce/lungcolon/shots_2/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2
+resume: 
+root: DATA
+seed: 2
+source_domains: None
+target_domains: None
+trainer: BiomedCoOp_BiomedCLIP
+transforms: None
+************
+** Config **
+************
+DATALOADER:
+  K_TRANSFORMS: 1
+  NUM_WORKERS: 8
+  RETURN_IMG0: False
+  TEST:
+    BATCH_SIZE: 100
+    SAMPLER: SequentialSampler
+  TRAIN_U:
+    BATCH_SIZE: 32
+    N_DOMAIN: 0
+    N_INS: 16
+    SAME_AS_X: True
+    SAMPLER: RandomSampler
+  TRAIN_X:
+    BATCH_SIZE: 4
+    N_DOMAIN: 0
+    N_INS: 16
+    SAMPLER: RandomSampler
+DATASET:
+  ALL_AS_UNLABELED: False
+  CIFAR_C_LEVEL: 1
+  CIFAR_C_TYPE: 
+  NAME: LungColon
+  NUM_LABELED: -1
+  NUM_SHOTS: 2
+  ROOT: DATA
+  SOURCE_DOMAINS: ()
+  STL10_FOLD: -1
+  SUBSAMPLE_CLASSES: all
+  TARGET_DOMAINS: ()
+  VAL_PERCENT: 0.1
+INPUT:
+  COLORJITTER_B: 0.4
+  COLORJITTER_C: 0.4
+  COLORJITTER_H: 0.1
+  COLORJITTER_S: 0.4
+  CROP_PADDING: 4
+  CUTOUT_LEN: 16
+  CUTOUT_N: 1
+  GB_K: 21
+  GB_P: 0.5
+  GN_MEAN: 0.0
+  GN_STD: 0.15
+  INTERPOLATION: bicubic
+  NO_TRANSFORM: False
+  PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
+  PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
+  RANDAUGMENT_M: 10
+  RANDAUGMENT_N: 2
+  RGS_P: 0.2
+  SIZE: (224, 224)
+  TRANSFORMS: ('random_resized_crop', 'normalize')
+MODEL:
+  BACKBONE:
+    NAME: ViT-B/16
+    PRETRAINED: True
+  HEAD:
+    ACTIVATION: relu
+    BN: True
+    DROPOUT: 0.0
+    HIDDEN_LAYERS: ()
+    NAME: 
+  INIT_WEIGHTS: 
+OPTIM:
+  ADAM_BETA1: 0.9
+  ADAM_BETA2: 0.999
+  BASE_LR_MULT: 0.1
+  GAMMA: 0.1
+  LR: 0.0025
+  LR_SCHEDULER: cosine
+  MAX_EPOCH: 100
+  MOMENTUM: 0.9
+  NAME: sgd
+  NEW_LAYERS: ()
+  RMSPROP_ALPHA: 0.99
+  SGD_DAMPNING: 0
+  SGD_NESTEROV: False
+  STAGED_LR: False
+  STEPSIZE: (-1,)
+  WARMUP_CONS_LR: 1e-05
+  WARMUP_EPOCH: 1
+  WARMUP_MIN_LR: 1e-05
+  WARMUP_RECOUNT: True
+  WARMUP_TYPE: constant
+  WEIGHT_DECAY: 0.0005
+OUTPUT_DIR: output_reproduce/lungcolon/shots_2/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2
+RESUME: 
+SEED: 2
+TEST:
+  COMPUTE_CMAT: False
+  EVALUATOR: Classification
+  FINAL_MODEL: last_step
+  NO_TEST: False
+  PER_CLASS_RESULT: False
+  SPLIT: test
+TRAIN:
+  CHECKPOINT_FREQ: 0
+  COUNT_ITER: train_x
+  PRINT_FREQ: 20
+TRAINER:
+  BIOMEDCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    KDSP_LAMBDA: 0.5
+    N_CTX: 4
+    N_PROMPTS: 50
+    PREC: fp32
+    SCCM_LAMBDA: 0.5
+    TAU: 1.5
+  CG:
+    ALPHA_D: 0.5
+    ALPHA_F: 0.5
+    EPS_D: 1.0
+    EPS_F: 1.0
+  COCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: 
+    N_CTX: 4
+    PREC: fp32
+  COOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: 
+    N_CTX: 4
+    PREC: fp32
+  DAEL:
+    CONF_THRE: 0.95
+    STRONG_TRANSFORMS: ()
+    WEIGHT_U: 0.5
+  DDAIG:
+    ALPHA: 0.5
+    CLAMP: False
+    CLAMP_MAX: 1.0
+    CLAMP_MIN: -1.0
+    G_ARCH: 
+    LMDA: 0.3
+    WARMUP: 0
+  ENTMIN:
+    LMDA: 0.001
+  FIXMATCH:
+    CONF_THRE: 0.95
+    STRONG_TRANSFORMS: ()
+    WEIGHT_U: 1.0
+  KGCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    N_CTX: 4
+    PREC: fp32
+    W: 1.0
+  M3SDA:
+    LMDA: 0.5
+    N_STEP_F: 4
+  MCD:
+    N_STEP_F: 4
+  MEANTEA:
+    EMA_ALPHA: 0.999
+    RAMPUP: 5
+    WEIGHT_U: 1.0
+  MIXMATCH:
+    MIXUP_BETA: 0.75
+    RAMPUP: 20000
+    TEMP: 2.0
+    WEIGHT_U: 100.0
+  MME:
+    LMDA: 0.1
+  NAME: BiomedCoOp_BiomedCLIP
+  PROGRAD:
+    ALPHA: 0.0
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    GM: False
+    LAMBDA: 1.0
+    NAME: 
+    N_CTX: 4
+    PREC: fp32
+    T: 1.0
+  SE:
+    CONF_THRE: 0.95
+    EMA_ALPHA: 0.999
+    RAMPUP: 300
+USE_CUDA: True
+VERBOSE: True
+VERSION: 1
+Collecting env info ...
+** System info **
+PyTorch version: 2.0.1+cu118
+Is debug build: False
+CUDA used to build PyTorch: 11.8
+ROCM used to build PyTorch: N/A
+
+OS: Ubuntu 22.04.5 LTS (x86_64)
+GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
+Clang version: Could not collect
+CMake version: version 3.25.0
+Libc version: glibc-2.35
+
+Python version: 3.10.15 (main, Oct  3 2024, 07:27:34) [GCC 11.2.0] (64-bit runtime)
+Python platform: Linux-5.15.0-134-generic-x86_64-with-glibc2.35
+Is CUDA available: True
+CUDA runtime version: 12.8.61
+CUDA_MODULE_LOADING set to: LAZY
+GPU models and configuration: 
+GPU 0: NVIDIA A100-SXM4-40GB
+GPU 1: NVIDIA A100-SXM4-40GB
+GPU 2: NVIDIA A100-SXM4-40GB
+GPU 3: NVIDIA A100-SXM4-40GB
+
+Nvidia driver version: 570.124.06
+cuDNN version: Could not collect
+HIP runtime version: N/A
+MIOpen runtime version: N/A
+Is XNNPACK available: True
+
+CPU:
+Architecture:                         x86_64
+CPU op-mode(s):                       32-bit, 64-bit
+Address sizes:                        43 bits physical, 48 bits virtual
+Byte Order:                           Little Endian
+CPU(s):                               128
+On-line CPU(s) list:                  0-127
+Vendor ID:                            AuthenticAMD
+Model name:                           AMD EPYC 7502 32-Core Processor
+CPU family:                           23
+Model:                                49
+Thread(s) per core:                   2
+Core(s) per socket:                   32
+Socket(s):                            2
+Stepping:                             0
+Frequency boost:                      enabled
+CPU max MHz:                          2500.0000
+CPU min MHz:                          1500.0000
+BogoMIPS:                             4999.71
+Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl umip rdpid overflow_recov succor smca sme sev sev_es
+Virtualization:                       AMD-V
+L1d cache:                            2 MiB (64 instances)
+L1i cache:                            2 MiB (64 instances)
+L2 cache:                             32 MiB (64 instances)
+L3 cache:                             256 MiB (16 instances)
+NUMA node(s):                         2
+NUMA node0 CPU(s):                    0-31,64-95
+NUMA node1 CPU(s):                    32-63,96-127
+Vulnerability Gather data sampling:   Not affected
+Vulnerability Itlb multihit:          Not affected
+Vulnerability L1tf:                   Not affected
+Vulnerability Mds:                    Not affected
+Vulnerability Meltdown:               Not affected
+Vulnerability Mmio stale data:        Not affected
+Vulnerability Reg file data sampling: Not affected
+Vulnerability Retbleed:               Mitigation; untrained return thunk; SMT enabled with STIBP protection
+Vulnerability Spec rstack overflow:   Mitigation; safe RET
+Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl and seccomp
+Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
+Vulnerability Spectre v2:             Mitigation; Retpolines; IBPB conditional; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
+Vulnerability Srbds:                  Not affected
+Vulnerability Tsx async abort:        Not affected
+
+Versions of relevant libraries:
+[pip3] numpy==1.26.3
+[pip3] torch==2.0.1+cu118
+[pip3] torchvision==0.15.2+cu118
+[conda] numpy                     1.26.3                   pypi_0    pypi
+[conda] torch                     2.0.1+cu118              pypi_0    pypi
+[conda] torchvision               0.15.2+cu118             pypi_0    pypi
+        Pillow (10.2.0)
+
+Loading trainer: BiomedCoOp_BiomedCLIP
+Loading dataset: LungColon
+Reading split from /data/t_kol/BiomedCoOp/DATA/LungColon/split_LungColon.json
+Loading preprocessed few-shot data from /data/t_kol/BiomedCoOp/DATA/LungColon/split_fewshot/shot_2-seed_2.pkl
+Building transform_train
++ random resized crop (size=(224, 224))
++ to torch tensor of range [0, 1]
++ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
+Building transform_test
++ resize the smaller edge to 224
++ 224x224 center crop
++ to torch tensor of range [0, 1]
++ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
+***** Dataset statistics *****
+  Dataset: LungColon
+  # classes: 5
+  # train_x: 10
+  # val: 10
+  # test: 7,500
+Loading BiomedCLIP (backbone: ViT-B/16)
+Building custom CLIP
+Initial text context: "a photo of a"
+Number of context words (tokens) for Language prompting: 4
+Turning off gradients in both the image and the text encoder
+Parameters to be updated: {'prompt_learner.ctx'}
+Parameters count: 1
+Loading evaluator: Classification
+Trainer built successfully.
+No checkpoint found, train from scratch
+Initializing summary writer for tensorboard with log_dir=output_reproduce/lungcolon/shots_2/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/tensorboard
+epoch [1/100][1/2]	time 0.691 (0.691)	data 0.348 (0.348)	eta 0:02:17	loss 2.9936 (2.9936)	acc 25.0000 (25.0000)	lr 1.000000e-05
+epoch [1/100][2/2]	time 0.072 (0.382)	data 0.003 (0.176)	eta 0:01:15	loss 1.2405 (2.1170)	acc 50.0000 (37.5000)	lr 2.500000e-03
+epoch [2/100][1/2]	time 0.526 (0.526)	data 0.448 (0.448)	eta 0:01:43	loss 1.1785 (1.1785)	acc 50.0000 (50.0000)	lr 2.500000e-03
+epoch [2/100][2/2]	time 0.073 (0.300)	data 0.004 (0.226)	eta 0:00:58	loss 2.2615 (1.7200)	acc 50.0000 (50.0000)	lr 2.499383e-03
+epoch [3/100][1/2]	time 0.511 (0.511)	data 0.437 (0.437)	eta 0:01:39	loss 1.9699 (1.9699)	acc 75.0000 (75.0000)	lr 2.499383e-03
+epoch [3/100][2/2]	time 0.071 (0.291)	data 0.001 (0.219)	eta 0:00:56	loss 0.6276 (1.2987)	acc 75.0000 (75.0000)	lr 2.497533e-03
+epoch [4/100][1/2]	time 0.541 (0.541)	data 0.468 (0.468)	eta 0:01:44	loss 2.1344 (2.1344)	acc 50.0000 (50.0000)	lr 2.497533e-03
+epoch [4/100][2/2]	time 0.071 (0.306)	data 0.001 (0.235)	eta 0:00:58	loss 2.0207 (2.0776)	acc 25.0000 (37.5000)	lr 2.494452e-03
+epoch [5/100][1/2]	time 0.527 (0.527)	data 0.454 (0.454)	eta 0:01:40	loss 2.2613 (2.2613)	acc 75.0000 (75.0000)	lr 2.494452e-03
+epoch [5/100][2/2]	time 0.073 (0.300)	data 0.003 (0.228)	eta 0:00:56	loss 1.8776 (2.0695)	acc 25.0000 (50.0000)	lr 2.490143e-03
+epoch [6/100][1/2]	time 0.517 (0.517)	data 0.443 (0.443)	eta 0:01:37	loss 1.3058 (1.3058)	acc 50.0000 (50.0000)	lr 2.490143e-03
+epoch [6/100][2/2]	time 0.070 (0.294)	data 0.001 (0.222)	eta 0:00:55	loss 0.4528 (0.8793)	acc 75.0000 (62.5000)	lr 2.484610e-03
+epoch [7/100][1/2]	time 0.495 (0.495)	data 0.423 (0.423)	eta 0:01:32	loss 2.1565 (2.1565)	acc 25.0000 (25.0000)	lr 2.484610e-03
+epoch [7/100][2/2]	time 0.070 (0.283)	data 0.001 (0.212)	eta 0:00:52	loss 2.6939 (2.4252)	acc 0.0000 (12.5000)	lr 2.477859e-03
+epoch [8/100][1/2]	time 0.534 (0.534)	data 0.460 (0.460)	eta 0:01:38	loss 0.8506 (0.8506)	acc 75.0000 (75.0000)	lr 2.477859e-03
+epoch [8/100][2/2]	time 0.071 (0.302)	data 0.001 (0.231)	eta 0:00:55	loss 0.6398 (0.7452)	acc 75.0000 (75.0000)	lr 2.469896e-03
+epoch [9/100][1/2]	time 0.535 (0.535)	data 0.455 (0.455)	eta 0:01:37	loss 0.7410 (0.7410)	acc 75.0000 (75.0000)	lr 2.469896e-03
+epoch [9/100][2/2]	time 0.072 (0.303)	data 0.002 (0.229)	eta 0:00:55	loss 0.5797 (0.6603)	acc 75.0000 (75.0000)	lr 2.460729e-03
+epoch [10/100][1/2]	time 0.543 (0.543)	data 0.469 (0.469)	eta 0:01:38	loss 0.3382 (0.3382)	acc 100.0000 (100.0000)	lr 2.460729e-03
+epoch [10/100][2/2]	time 0.073 (0.308)	data 0.003 (0.236)	eta 0:00:55	loss 1.6866 (1.0124)	acc 75.0000 (87.5000)	lr 2.450367e-03
+epoch [11/100][1/2]	time 0.629 (0.629)	data 0.551 (0.551)	eta 0:01:52	loss 0.1350 (0.1350)	acc 100.0000 (100.0000)	lr 2.450367e-03
+epoch [11/100][2/2]	time 0.071 (0.350)	data 0.001 (0.276)	eta 0:01:02	loss 1.2119 (0.6734)	acc 25.0000 (62.5000)	lr 2.438821e-03
+epoch [12/100][1/2]	time 0.608 (0.608)	data 0.532 (0.532)	eta 0:01:47	loss 0.3384 (0.3384)	acc 100.0000 (100.0000)	lr 2.438821e-03
+epoch [12/100][2/2]	time 0.074 (0.341)	data 0.003 (0.268)	eta 0:01:00	loss 0.5159 (0.4272)	acc 75.0000 (87.5000)	lr 2.426101e-03
+epoch [13/100][1/2]	time 0.633 (0.633)	data 0.554 (0.554)	eta 0:01:50	loss 0.4977 (0.4977)	acc 75.0000 (75.0000)	lr 2.426101e-03
+epoch [13/100][2/2]	time 0.072 (0.352)	data 0.002 (0.278)	eta 0:01:01	loss 1.0393 (0.7685)	acc 75.0000 (75.0000)	lr 2.412221e-03
+epoch [14/100][1/2]	time 0.585 (0.585)	data 0.508 (0.508)	eta 0:01:41	loss 0.3634 (0.3634)	acc 100.0000 (100.0000)	lr 2.412221e-03
+epoch [14/100][2/2]	time 0.071 (0.328)	data 0.001 (0.255)	eta 0:00:56	loss 1.6100 (0.9867)	acc 50.0000 (75.0000)	lr 2.397193e-03
+epoch [15/100][1/2]	time 0.551 (0.551)	data 0.475 (0.475)	eta 0:01:34	loss 0.5381 (0.5381)	acc 75.0000 (75.0000)	lr 2.397193e-03
+epoch [15/100][2/2]	time 0.073 (0.312)	data 0.003 (0.239)	eta 0:00:53	loss 0.3037 (0.4209)	acc 100.0000 (87.5000)	lr 2.381034e-03
+epoch [16/100][1/2]	time 0.555 (0.555)	data 0.482 (0.482)	eta 0:01:33	loss 1.8096 (1.8096)	acc 25.0000 (25.0000)	lr 2.381034e-03
+epoch [16/100][2/2]	time 0.074 (0.314)	data 0.003 (0.243)	eta 0:00:52	loss 0.4819 (1.1458)	acc 75.0000 (50.0000)	lr 2.363758e-03
+epoch [17/100][1/2]	time 0.553 (0.553)	data 0.475 (0.475)	eta 0:01:32	loss 0.2755 (0.2755)	acc 100.0000 (100.0000)	lr 2.363758e-03
+epoch [17/100][2/2]	time 0.071 (0.312)	data 0.001 (0.238)	eta 0:00:51	loss 0.4599 (0.3677)	acc 100.0000 (100.0000)	lr 2.345383e-03
+epoch [18/100][1/2]	time 0.555 (0.555)	data 0.481 (0.481)	eta 0:01:31	loss 0.2270 (0.2270)	acc 100.0000 (100.0000)	lr 2.345383e-03
+epoch [18/100][2/2]	time 0.073 (0.314)	data 0.003 (0.242)	eta 0:00:51	loss 0.7831 (0.5050)	acc 50.0000 (75.0000)	lr 2.325928e-03
+epoch [19/100][1/2]	time 0.521 (0.521)	data 0.448 (0.448)	eta 0:01:24	loss 0.3094 (0.3094)	acc 75.0000 (75.0000)	lr 2.325928e-03
+epoch [19/100][2/2]	time 0.072 (0.297)	data 0.003 (0.225)	eta 0:00:48	loss 0.2435 (0.2764)	acc 100.0000 (87.5000)	lr 2.305410e-03
+epoch [20/100][1/2]	time 0.547 (0.547)	data 0.473 (0.473)	eta 0:01:28	loss 0.8609 (0.8609)	acc 50.0000 (50.0000)	lr 2.305410e-03
+epoch [20/100][2/2]	time 0.074 (0.310)	data 0.003 (0.238)	eta 0:00:49	loss 2.3157 (1.5883)	acc 50.0000 (50.0000)	lr 2.283851e-03
+epoch [21/100][1/2]	time 0.547 (0.547)	data 0.473 (0.473)	eta 0:01:26	loss 0.4376 (0.4376)	acc 75.0000 (75.0000)	lr 2.283851e-03
+epoch [21/100][2/2]	time 0.074 (0.310)	data 0.003 (0.238)	eta 0:00:48	loss 0.2913 (0.3645)	acc 100.0000 (87.5000)	lr 2.261271e-03
+epoch [22/100][1/2]	time 0.537 (0.537)	data 0.465 (0.465)	eta 0:01:24	loss 0.4047 (0.4047)	acc 100.0000 (100.0000)	lr 2.261271e-03
+epoch [22/100][2/2]	time 0.073 (0.305)	data 0.003 (0.234)	eta 0:00:47	loss 0.4509 (0.4278)	acc 50.0000 (75.0000)	lr 2.237694e-03
+epoch [23/100][1/2]	time 0.515 (0.515)	data 0.441 (0.441)	eta 0:01:19	loss 0.3605 (0.3605)	acc 100.0000 (100.0000)	lr 2.237694e-03
+epoch [23/100][2/2]	time 0.073 (0.294)	data 0.003 (0.222)	eta 0:00:45	loss 0.2312 (0.2959)	acc 100.0000 (100.0000)	lr 2.213142e-03
+epoch [24/100][1/2]	time 0.550 (0.550)	data 0.479 (0.479)	eta 0:01:24	loss 0.5600 (0.5600)	acc 100.0000 (100.0000)	lr 2.213142e-03
+epoch [24/100][2/2]	time 0.072 (0.311)	data 0.003 (0.241)	eta 0:00:47	loss 1.1371 (0.8486)	acc 75.0000 (87.5000)	lr 2.187639e-03
+epoch [25/100][1/2]	time 0.540 (0.540)	data 0.468 (0.468)	eta 0:01:21	loss 0.8191 (0.8191)	acc 50.0000 (50.0000)	lr 2.187639e-03
+epoch [25/100][2/2]	time 0.070 (0.305)	data 0.001 (0.234)	eta 0:00:45	loss 0.3364 (0.5777)	acc 100.0000 (75.0000)	lr 2.161211e-03
+epoch [26/100][1/2]	time 0.519 (0.519)	data 0.446 (0.446)	eta 0:01:17	loss 0.5858 (0.5858)	acc 75.0000 (75.0000)	lr 2.161211e-03
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+epoch [27/100][1/2]	time 0.513 (0.513)	data 0.440 (0.440)	eta 0:01:15	loss 0.2024 (0.2024)	acc 100.0000 (100.0000)	lr 2.133883e-03
+epoch [27/100][2/2]	time 0.071 (0.292)	data 0.002 (0.221)	eta 0:00:42	loss 0.3104 (0.2564)	acc 100.0000 (100.0000)	lr 2.105684e-03
+epoch [28/100][1/2]	time 0.514 (0.514)	data 0.441 (0.441)	eta 0:01:14	loss 0.6750 (0.6750)	acc 75.0000 (75.0000)	lr 2.105684e-03
+epoch [28/100][2/2]	time 0.072 (0.293)	data 0.003 (0.222)	eta 0:00:42	loss 0.6476 (0.6613)	acc 75.0000 (75.0000)	lr 2.076640e-03
+epoch [29/100][1/2]	time 0.497 (0.497)	data 0.424 (0.424)	eta 0:01:11	loss 0.3394 (0.3394)	acc 100.0000 (100.0000)	lr 2.076640e-03
+epoch [29/100][2/2]	time 0.072 (0.285)	data 0.003 (0.213)	eta 0:00:40	loss 0.4330 (0.3862)	acc 75.0000 (87.5000)	lr 2.046780e-03
+epoch [30/100][1/2]	time 0.518 (0.518)	data 0.445 (0.445)	eta 0:01:13	loss 0.7155 (0.7155)	acc 75.0000 (75.0000)	lr 2.046780e-03
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+epoch [40/100][1/2]	time 0.527 (0.527)	data 0.454 (0.454)	eta 0:01:03	loss 0.7648 (0.7648)	acc 75.0000 (75.0000)	lr 1.710156e-03
+epoch [40/100][2/2]	time 0.071 (0.299)	data 0.001 (0.227)	eta 0:00:35	loss 0.5363 (0.6505)	acc 75.0000 (75.0000)	lr 1.673422e-03
+epoch [41/100][1/2]	time 0.500 (0.500)	data 0.427 (0.427)	eta 0:00:59	loss 0.3283 (0.3283)	acc 100.0000 (100.0000)	lr 1.673422e-03
+epoch [41/100][2/2]	time 0.071 (0.286)	data 0.002 (0.214)	eta 0:00:33	loss 0.2892 (0.3087)	acc 100.0000 (100.0000)	lr 1.636271e-03
+epoch [42/100][1/2]	time 0.510 (0.510)	data 0.438 (0.438)	eta 0:00:59	loss 0.0790 (0.0790)	acc 100.0000 (100.0000)	lr 1.636271e-03
+epoch [42/100][2/2]	time 0.073 (0.292)	data 0.003 (0.221)	eta 0:00:33	loss 0.9120 (0.4955)	acc 75.0000 (87.5000)	lr 1.598739e-03
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+epoch [99/100][1/2]	time 0.539 (0.539)	data 0.465 (0.465)	eta 0:00:01	loss 0.3760 (0.3760)	acc 100.0000 (100.0000)	lr 5.547544e-06
+epoch [99/100][2/2]	time 0.072 (0.305)	data 0.003 (0.234)	eta 0:00:00	loss 0.4353 (0.4057)	acc 75.0000 (87.5000)	lr 2.466589e-06
+epoch [100/100][1/2]	time 0.524 (0.524)	data 0.451 (0.451)	eta 0:00:00	loss 0.3598 (0.3598)	acc 75.0000 (75.0000)	lr 2.466589e-06
+epoch [100/100][2/2]	time 0.071 (0.298)	data 0.001 (0.226)	eta 0:00:00	loss 0.2205 (0.2901)	acc 100.0000 (87.5000)	lr 6.167995e-07
+Checkpoint saved to "output_reproduce/lungcolon/shots_2/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/prompt_learner/model.pth.tar-100"
+Finished training
+Do evaluation on test set
+=> result
+* total: 7,500
+* correct: 5,630
+* accuracy: 75.07%
+* error: 24.93%
+* macro_f1: 73.82%
+Elapsed: 0:01:33

few_shot/lungcolon/shots_2/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/prompt_learner/checkpoint

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few_shot/lungcolon/shots_2/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/tensorboard/events.out.tfevents.1742384993.impactlab-server.2677372.0

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few_shot/lungcolon/shots_2/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/log.txt

@@ -0,0 +1,532 @@
+***************
+** Arguments **
+***************
+backbone: 
+config_file: configs/trainers/BiomedCoOp_BiomedCLIP/few_shot/lungcolon.yaml
+dataset_config_file: configs/datasets/lungcolon.yaml
+eval_only: False
+head: 
+load_epoch: None
+model_dir: 
+no_train: False
+opts: ['TRAINER.BIOMEDCOOP.N_CTX', '4', 'TRAINER.BIOMEDCOOP.CSC', 'False', 'TRAINER.BIOMEDCOOP.CLASS_TOKEN_POSITION', 'end', 'DATASET.NUM_SHOTS', '2']
+output_dir: output_reproduce/lungcolon/shots_2/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3
+resume: 
+root: DATA
+seed: 3
+source_domains: None
+target_domains: None
+trainer: BiomedCoOp_BiomedCLIP
+transforms: None
+************
+** Config **
+************
+DATALOADER:
+  K_TRANSFORMS: 1
+  NUM_WORKERS: 8
+  RETURN_IMG0: False
+  TEST:
+    BATCH_SIZE: 100
+    SAMPLER: SequentialSampler
+  TRAIN_U:
+    BATCH_SIZE: 32
+    N_DOMAIN: 0
+    N_INS: 16
+    SAME_AS_X: True
+    SAMPLER: RandomSampler
+  TRAIN_X:
+    BATCH_SIZE: 4
+    N_DOMAIN: 0
+    N_INS: 16
+    SAMPLER: RandomSampler
+DATASET:
+  ALL_AS_UNLABELED: False
+  CIFAR_C_LEVEL: 1
+  CIFAR_C_TYPE: 
+  NAME: LungColon
+  NUM_LABELED: -1
+  NUM_SHOTS: 2
+  ROOT: DATA
+  SOURCE_DOMAINS: ()
+  STL10_FOLD: -1
+  SUBSAMPLE_CLASSES: all
+  TARGET_DOMAINS: ()
+  VAL_PERCENT: 0.1
+INPUT:
+  COLORJITTER_B: 0.4
+  COLORJITTER_C: 0.4
+  COLORJITTER_H: 0.1
+  COLORJITTER_S: 0.4
+  CROP_PADDING: 4
+  CUTOUT_LEN: 16
+  CUTOUT_N: 1
+  GB_K: 21
+  GB_P: 0.5
+  GN_MEAN: 0.0
+  GN_STD: 0.15
+  INTERPOLATION: bicubic
+  NO_TRANSFORM: False
+  PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
+  PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
+  RANDAUGMENT_M: 10
+  RANDAUGMENT_N: 2
+  RGS_P: 0.2
+  SIZE: (224, 224)
+  TRANSFORMS: ('random_resized_crop', 'normalize')
+MODEL:
+  BACKBONE:
+    NAME: ViT-B/16
+    PRETRAINED: True
+  HEAD:
+    ACTIVATION: relu
+    BN: True
+    DROPOUT: 0.0
+    HIDDEN_LAYERS: ()
+    NAME: 
+  INIT_WEIGHTS: 
+OPTIM:
+  ADAM_BETA1: 0.9
+  ADAM_BETA2: 0.999
+  BASE_LR_MULT: 0.1
+  GAMMA: 0.1
+  LR: 0.0025
+  LR_SCHEDULER: cosine
+  MAX_EPOCH: 100
+  MOMENTUM: 0.9
+  NAME: sgd
+  NEW_LAYERS: ()
+  RMSPROP_ALPHA: 0.99
+  SGD_DAMPNING: 0
+  SGD_NESTEROV: False
+  STAGED_LR: False
+  STEPSIZE: (-1,)
+  WARMUP_CONS_LR: 1e-05
+  WARMUP_EPOCH: 1
+  WARMUP_MIN_LR: 1e-05
+  WARMUP_RECOUNT: True
+  WARMUP_TYPE: constant
+  WEIGHT_DECAY: 0.0005
+OUTPUT_DIR: output_reproduce/lungcolon/shots_2/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3
+RESUME: 
+SEED: 3
+TEST:
+  COMPUTE_CMAT: False
+  EVALUATOR: Classification
+  FINAL_MODEL: last_step
+  NO_TEST: False
+  PER_CLASS_RESULT: False
+  SPLIT: test
+TRAIN:
+  CHECKPOINT_FREQ: 0
+  COUNT_ITER: train_x
+  PRINT_FREQ: 20
+TRAINER:
+  BIOMEDCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    KDSP_LAMBDA: 0.5
+    N_CTX: 4
+    N_PROMPTS: 50
+    PREC: fp32
+    SCCM_LAMBDA: 0.5
+    TAU: 1.5
+  CG:
+    ALPHA_D: 0.5
+    ALPHA_F: 0.5
+    EPS_D: 1.0
+    EPS_F: 1.0
+  COCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: 
+    N_CTX: 4
+    PREC: fp32
+  COOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: 
+    N_CTX: 4
+    PREC: fp32
+  DAEL:
+    CONF_THRE: 0.95
+    STRONG_TRANSFORMS: ()
+    WEIGHT_U: 0.5
+  DDAIG:
+    ALPHA: 0.5
+    CLAMP: False
+    CLAMP_MAX: 1.0
+    CLAMP_MIN: -1.0
+    G_ARCH: 
+    LMDA: 0.3
+    WARMUP: 0
+  ENTMIN:
+    LMDA: 0.001
+  FIXMATCH:
+    CONF_THRE: 0.95
+    STRONG_TRANSFORMS: ()
+    WEIGHT_U: 1.0
+  KGCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    N_CTX: 4
+    PREC: fp32
+    W: 1.0
+  M3SDA:
+    LMDA: 0.5
+    N_STEP_F: 4
+  MCD:
+    N_STEP_F: 4
+  MEANTEA:
+    EMA_ALPHA: 0.999
+    RAMPUP: 5
+    WEIGHT_U: 1.0
+  MIXMATCH:
+    MIXUP_BETA: 0.75
+    RAMPUP: 20000
+    TEMP: 2.0
+    WEIGHT_U: 100.0
+  MME:
+    LMDA: 0.1
+  NAME: BiomedCoOp_BiomedCLIP
+  PROGRAD:
+    ALPHA: 0.0
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    GM: False
+    LAMBDA: 1.0
+    NAME: 
+    N_CTX: 4
+    PREC: fp32
+    T: 1.0
+  SE:
+    CONF_THRE: 0.95
+    EMA_ALPHA: 0.999
+    RAMPUP: 300
+USE_CUDA: True
+VERBOSE: True
+VERSION: 1
+Collecting env info ...
+** System info **
+PyTorch version: 2.0.1+cu118
+Is debug build: False
+CUDA used to build PyTorch: 11.8
+ROCM used to build PyTorch: N/A
+
+OS: Ubuntu 22.04.5 LTS (x86_64)
+GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
+Clang version: Could not collect
+CMake version: version 3.25.0
+Libc version: glibc-2.35
+
+Python version: 3.10.15 (main, Oct  3 2024, 07:27:34) [GCC 11.2.0] (64-bit runtime)
+Python platform: Linux-5.15.0-134-generic-x86_64-with-glibc2.35
+Is CUDA available: True
+CUDA runtime version: 12.8.61
+CUDA_MODULE_LOADING set to: LAZY
+GPU models and configuration: 
+GPU 0: NVIDIA A100-SXM4-40GB
+GPU 1: NVIDIA A100-SXM4-40GB
+GPU 2: NVIDIA A100-SXM4-40GB
+GPU 3: NVIDIA A100-SXM4-40GB
+
+Nvidia driver version: 570.124.06
+cuDNN version: Could not collect
+HIP runtime version: N/A
+MIOpen runtime version: N/A
+Is XNNPACK available: True
+
+CPU:
+Architecture:                         x86_64
+CPU op-mode(s):                       32-bit, 64-bit
+Address sizes:                        43 bits physical, 48 bits virtual
+Byte Order:                           Little Endian
+CPU(s):                               128
+On-line CPU(s) list:                  0-127
+Vendor ID:                            AuthenticAMD
+Model name:                           AMD EPYC 7502 32-Core Processor
+CPU family:                           23
+Model:                                49
+Thread(s) per core:                   2
+Core(s) per socket:                   32
+Socket(s):                            2
+Stepping:                             0
+Frequency boost:                      enabled
+CPU max MHz:                          2500.0000
+CPU min MHz:                          1500.0000
+BogoMIPS:                             4999.71
+Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl umip rdpid overflow_recov succor smca sme sev sev_es
+Virtualization:                       AMD-V
+L1d cache:                            2 MiB (64 instances)
+L1i cache:                            2 MiB (64 instances)
+L2 cache:                             32 MiB (64 instances)
+L3 cache:                             256 MiB (16 instances)
+NUMA node(s):                         2
+NUMA node0 CPU(s):                    0-31,64-95
+NUMA node1 CPU(s):                    32-63,96-127
+Vulnerability Gather data sampling:   Not affected
+Vulnerability Itlb multihit:          Not affected
+Vulnerability L1tf:                   Not affected
+Vulnerability Mds:                    Not affected
+Vulnerability Meltdown:               Not affected
+Vulnerability Mmio stale data:        Not affected
+Vulnerability Reg file data sampling: Not affected
+Vulnerability Retbleed:               Mitigation; untrained return thunk; SMT enabled with STIBP protection
+Vulnerability Spec rstack overflow:   Mitigation; safe RET
+Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl and seccomp
+Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
+Vulnerability Spectre v2:             Mitigation; Retpolines; IBPB conditional; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
+Vulnerability Srbds:                  Not affected
+Vulnerability Tsx async abort:        Not affected
+
+Versions of relevant libraries:
+[pip3] numpy==1.26.3
+[pip3] torch==2.0.1+cu118
+[pip3] torchvision==0.15.2+cu118
+[conda] numpy                     1.26.3                   pypi_0    pypi
+[conda] torch                     2.0.1+cu118              pypi_0    pypi
+[conda] torchvision               0.15.2+cu118             pypi_0    pypi
+        Pillow (10.2.0)
+
+Loading trainer: BiomedCoOp_BiomedCLIP
+Loading dataset: LungColon
+Reading split from /data/t_kol/BiomedCoOp/DATA/LungColon/split_LungColon.json
+Loading preprocessed few-shot data from /data/t_kol/BiomedCoOp/DATA/LungColon/split_fewshot/shot_2-seed_3.pkl
+Building transform_train
++ random resized crop (size=(224, 224))
++ to torch tensor of range [0, 1]
++ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
+Building transform_test
++ resize the smaller edge to 224
++ 224x224 center crop
++ to torch tensor of range [0, 1]
++ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
+***** Dataset statistics *****
+  Dataset: LungColon
+  # classes: 5
+  # train_x: 10
+  # val: 10
+  # test: 7,500
+Loading BiomedCLIP (backbone: ViT-B/16)
+Building custom CLIP
+Initial text context: "a photo of a"
+Number of context words (tokens) for Language prompting: 4
+Turning off gradients in both the image and the text encoder
+Parameters to be updated: {'prompt_learner.ctx'}
+Parameters count: 1
+Loading evaluator: Classification
+Trainer built successfully.
+No checkpoint found, train from scratch
+Initializing summary writer for tensorboard with log_dir=output_reproduce/lungcolon/shots_2/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/tensorboard
+epoch [1/100][1/2]	time 0.722 (0.722)	data 0.367 (0.367)	eta 0:02:23	loss 1.3275 (1.3275)	acc 50.0000 (50.0000)	lr 1.000000e-05
+epoch [1/100][2/2]	time 0.073 (0.398)	data 0.003 (0.185)	eta 0:01:18	loss 1.2012 (1.2644)	acc 50.0000 (50.0000)	lr 2.500000e-03
+epoch [2/100][1/2]	time 0.542 (0.542)	data 0.452 (0.452)	eta 0:01:46	loss 0.8581 (0.8581)	acc 75.0000 (75.0000)	lr 2.500000e-03
+epoch [2/100][2/2]	time 0.088 (0.315)	data 0.003 (0.228)	eta 0:01:01	loss 2.1479 (1.5030)	acc 50.0000 (62.5000)	lr 2.499383e-03
+epoch [3/100][1/2]	time 0.546 (0.546)	data 0.473 (0.473)	eta 0:01:46	loss 1.9104 (1.9104)	acc 25.0000 (25.0000)	lr 2.499383e-03
+epoch [3/100][2/2]	time 0.072 (0.309)	data 0.002 (0.238)	eta 0:00:59	loss 0.9192 (1.4148)	acc 50.0000 (37.5000)	lr 2.497533e-03
+epoch [4/100][1/2]	time 0.555 (0.555)	data 0.481 (0.481)	eta 0:01:47	loss 2.5336 (2.5336)	acc 25.0000 (25.0000)	lr 2.497533e-03
+epoch [4/100][2/2]	time 0.071 (0.313)	data 0.001 (0.241)	eta 0:01:00	loss 0.4756 (1.5046)	acc 75.0000 (50.0000)	lr 2.494452e-03
+epoch [5/100][1/2]	time 0.543 (0.543)	data 0.470 (0.470)	eta 0:01:43	loss 1.4873 (1.4873)	acc 50.0000 (50.0000)	lr 2.494452e-03
+epoch [5/100][2/2]	time 0.071 (0.307)	data 0.001 (0.236)	eta 0:00:58	loss 1.0186 (1.2530)	acc 75.0000 (62.5000)	lr 2.490143e-03
+epoch [6/100][1/2]	time 0.538 (0.538)	data 0.465 (0.465)	eta 0:01:41	loss 0.9770 (0.9770)	acc 75.0000 (75.0000)	lr 2.490143e-03
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+epoch [7/100][1/2]	time 0.540 (0.540)	data 0.467 (0.467)	eta 0:01:41	loss 1.1659 (1.1659)	acc 75.0000 (75.0000)	lr 2.484610e-03
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+epoch [8/100][1/2]	time 0.558 (0.558)	data 0.485 (0.485)	eta 0:01:43	loss 1.6377 (1.6377)	acc 50.0000 (50.0000)	lr 2.477859e-03
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+epoch [9/100][1/2]	time 0.556 (0.556)	data 0.478 (0.478)	eta 0:01:41	loss 0.4215 (0.4215)	acc 75.0000 (75.0000)	lr 2.469896e-03
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+epoch [10/100][2/2]	time 0.071 (0.301)	data 0.001 (0.230)	eta 0:00:54	loss 1.2787 (1.0710)	acc 50.0000 (62.5000)	lr 2.450367e-03
+epoch [11/100][1/2]	time 0.526 (0.526)	data 0.452 (0.452)	eta 0:01:34	loss 0.4059 (0.4059)	acc 100.0000 (100.0000)	lr 2.450367e-03
+epoch [11/100][2/2]	time 0.072 (0.299)	data 0.003 (0.228)	eta 0:00:53	loss 0.1992 (0.3025)	acc 100.0000 (100.0000)	lr 2.438821e-03
+epoch [12/100][1/2]	time 0.544 (0.544)	data 0.471 (0.471)	eta 0:01:36	loss 4.1453 (4.1453)	acc 25.0000 (25.0000)	lr 2.438821e-03
+epoch [12/100][2/2]	time 0.073 (0.308)	data 0.003 (0.237)	eta 0:00:54	loss 0.2832 (2.2143)	acc 75.0000 (50.0000)	lr 2.426101e-03
+epoch [13/100][1/2]	time 0.527 (0.527)	data 0.454 (0.454)	eta 0:01:32	loss 0.5763 (0.5763)	acc 100.0000 (100.0000)	lr 2.426101e-03
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+epoch [14/100][1/2]	time 0.553 (0.553)	data 0.476 (0.476)	eta 0:01:35	loss 1.7620 (1.7620)	acc 50.0000 (50.0000)	lr 2.412221e-03
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+epoch [75/100][1/2]	time 0.538 (0.538)	data 0.464 (0.464)	eta 0:00:27	loss 0.6957 (0.6957)	acc 75.0000 (75.0000)	lr 4.233602e-04
+epoch [75/100][2/2]	time 0.071 (0.304)	data 0.001 (0.233)	eta 0:00:15	loss 0.1981 (0.4469)	acc 100.0000 (87.5000)	lr 3.943161e-04
+epoch [76/100][1/2]	time 0.557 (0.557)	data 0.479 (0.479)	eta 0:00:27	loss 0.4250 (0.4250)	acc 100.0000 (100.0000)	lr 3.943161e-04
+epoch [76/100][2/2]	time 0.071 (0.314)	data 0.002 (0.240)	eta 0:00:15	loss 0.2967 (0.3609)	acc 75.0000 (87.5000)	lr 3.661165e-04
+epoch [77/100][1/2]	time 0.562 (0.562)	data 0.488 (0.488)	eta 0:00:26	loss 0.7686 (0.7686)	acc 75.0000 (75.0000)	lr 3.661165e-04
+epoch [77/100][2/2]	time 0.071 (0.316)	data 0.001 (0.245)	eta 0:00:14	loss 0.9156 (0.8421)	acc 75.0000 (75.0000)	lr 3.387892e-04
+epoch [78/100][1/2]	time 0.539 (0.539)	data 0.460 (0.460)	eta 0:00:24	loss 0.7813 (0.7813)	acc 75.0000 (75.0000)	lr 3.387892e-04
+epoch [78/100][2/2]	time 0.071 (0.305)	data 0.001 (0.230)	eta 0:00:13	loss 0.1979 (0.4896)	acc 100.0000 (87.5000)	lr 3.123612e-04
+epoch [79/100][1/2]	time 0.513 (0.513)	data 0.440 (0.440)	eta 0:00:22	loss 0.3761 (0.3761)	acc 75.0000 (75.0000)	lr 3.123612e-04
+epoch [79/100][2/2]	time 0.072 (0.292)	data 0.003 (0.221)	eta 0:00:12	loss 0.4203 (0.3982)	acc 75.0000 (75.0000)	lr 2.868584e-04
+epoch [80/100][1/2]	time 0.549 (0.549)	data 0.475 (0.475)	eta 0:00:22	loss 0.4518 (0.4518)	acc 75.0000 (75.0000)	lr 2.868584e-04
+epoch [80/100][2/2]	time 0.073 (0.311)	data 0.003 (0.239)	eta 0:00:12	loss 0.7638 (0.6078)	acc 75.0000 (75.0000)	lr 2.623062e-04
+epoch [81/100][1/2]	time 0.565 (0.565)	data 0.491 (0.491)	eta 0:00:22	loss 0.1725 (0.1725)	acc 100.0000 (100.0000)	lr 2.623062e-04
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+epoch [82/100][1/2]	time 0.531 (0.531)	data 0.459 (0.459)	eta 0:00:19	loss 0.2874 (0.2874)	acc 100.0000 (100.0000)	lr 2.387288e-04
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+epoch [83/100][2/2]	time 0.070 (0.309)	data 0.001 (0.238)	eta 0:00:10	loss 0.3685 (0.4712)	acc 75.0000 (75.0000)	lr 1.945901e-04
+epoch [84/100][1/2]	time 0.560 (0.560)	data 0.482 (0.482)	eta 0:00:18	loss 0.3491 (0.3491)	acc 100.0000 (100.0000)	lr 1.945901e-04
+epoch [84/100][2/2]	time 0.071 (0.316)	data 0.001 (0.242)	eta 0:00:10	loss 0.6857 (0.5174)	acc 75.0000 (87.5000)	lr 1.740725e-04
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+epoch [86/100][2/2]	time 0.070 (0.313)	data 0.001 (0.242)	eta 0:00:08	loss 0.5286 (0.4195)	acc 75.0000 (87.5000)	lr 1.362418e-04
+epoch [87/100][1/2]	time 0.526 (0.526)	data 0.453 (0.453)	eta 0:00:14	loss 1.3172 (1.3172)	acc 75.0000 (75.0000)	lr 1.362418e-04
+epoch [87/100][2/2]	time 0.072 (0.299)	data 0.002 (0.228)	eta 0:00:07	loss 0.1937 (0.7554)	acc 100.0000 (87.5000)	lr 1.189662e-04
+epoch [88/100][1/2]	time 0.545 (0.545)	data 0.472 (0.472)	eta 0:00:13	loss 0.5908 (0.5908)	acc 75.0000 (75.0000)	lr 1.189662e-04
+epoch [88/100][2/2]	time 0.072 (0.308)	data 0.002 (0.237)	eta 0:00:07	loss 0.2388 (0.4148)	acc 100.0000 (87.5000)	lr 1.028067e-04
+epoch [89/100][1/2]	time 0.537 (0.537)	data 0.464 (0.464)	eta 0:00:12	loss 0.5447 (0.5447)	acc 75.0000 (75.0000)	lr 1.028067e-04
+epoch [89/100][2/2]	time 0.072 (0.305)	data 0.003 (0.233)	eta 0:00:06	loss 0.1362 (0.3405)	acc 100.0000 (87.5000)	lr 8.777939e-05
+epoch [90/100][1/2]	time 0.538 (0.538)	data 0.465 (0.465)	eta 0:00:11	loss 0.5484 (0.5484)	acc 75.0000 (75.0000)	lr 8.777939e-05
+epoch [90/100][2/2]	time 0.070 (0.304)	data 0.001 (0.233)	eta 0:00:06	loss 0.1406 (0.3445)	acc 100.0000 (87.5000)	lr 7.389904e-05
+epoch [91/100][1/2]	time 0.561 (0.561)	data 0.488 (0.488)	eta 0:00:10	loss 0.4752 (0.4752)	acc 75.0000 (75.0000)	lr 7.389904e-05
+epoch [91/100][2/2]	time 0.070 (0.316)	data 0.001 (0.244)	eta 0:00:05	loss 0.3163 (0.3957)	acc 100.0000 (87.5000)	lr 6.117935e-05
+epoch [92/100][1/2]	time 0.559 (0.559)	data 0.481 (0.481)	eta 0:00:09	loss 0.2712 (0.2712)	acc 100.0000 (100.0000)	lr 6.117935e-05
+epoch [92/100][2/2]	time 0.071 (0.315)	data 0.001 (0.241)	eta 0:00:05	loss 0.1991 (0.2352)	acc 100.0000 (100.0000)	lr 4.963289e-05
+epoch [93/100][1/2]	time 0.557 (0.557)	data 0.484 (0.484)	eta 0:00:08	loss 0.1938 (0.1938)	acc 100.0000 (100.0000)	lr 4.963289e-05
+epoch [93/100][2/2]	time 0.071 (0.314)	data 0.001 (0.242)	eta 0:00:04	loss 0.2899 (0.2419)	acc 100.0000 (100.0000)	lr 3.927105e-05
+epoch [94/100][1/2]	time 0.539 (0.539)	data 0.467 (0.467)	eta 0:00:07	loss 0.2409 (0.2409)	acc 100.0000 (100.0000)	lr 3.927105e-05
+epoch [94/100][2/2]	time 0.071 (0.305)	data 0.001 (0.234)	eta 0:00:03	loss 0.1815 (0.2112)	acc 100.0000 (100.0000)	lr 3.010405e-05
+epoch [95/100][1/2]	time 0.554 (0.554)	data 0.481 (0.481)	eta 0:00:06	loss 0.6418 (0.6418)	acc 50.0000 (50.0000)	lr 3.010405e-05
+epoch [95/100][2/2]	time 0.072 (0.313)	data 0.003 (0.242)	eta 0:00:03	loss 0.3513 (0.4965)	acc 100.0000 (75.0000)	lr 2.214094e-05
+epoch [96/100][1/2]	time 0.546 (0.546)	data 0.473 (0.473)	eta 0:00:04	loss 0.2993 (0.2993)	acc 75.0000 (75.0000)	lr 2.214094e-05
+epoch [96/100][2/2]	time 0.072 (0.309)	data 0.003 (0.238)	eta 0:00:02	loss 0.3028 (0.3010)	acc 100.0000 (87.5000)	lr 1.538957e-05
+epoch [97/100][1/2]	time 0.556 (0.556)	data 0.479 (0.479)	eta 0:00:03	loss 1.3971 (1.3971)	acc 50.0000 (50.0000)	lr 1.538957e-05
+epoch [97/100][2/2]	time 0.071 (0.313)	data 0.001 (0.240)	eta 0:00:01	loss 0.3504 (0.8738)	acc 75.0000 (62.5000)	lr 9.856623e-06
+epoch [98/100][1/2]	time 0.527 (0.527)	data 0.455 (0.455)	eta 0:00:02	loss 0.1856 (0.1856)	acc 100.0000 (100.0000)	lr 9.856623e-06
+epoch [98/100][2/2]	time 0.072 (0.299)	data 0.003 (0.229)	eta 0:00:01	loss 0.8603 (0.5229)	acc 50.0000 (75.0000)	lr 5.547544e-06
+epoch [99/100][1/2]	time 0.545 (0.545)	data 0.472 (0.472)	eta 0:00:01	loss 0.6929 (0.6929)	acc 50.0000 (50.0000)	lr 5.547544e-06
+epoch [99/100][2/2]	time 0.071 (0.308)	data 0.001 (0.236)	eta 0:00:00	loss 0.5094 (0.6012)	acc 75.0000 (62.5000)	lr 2.466589e-06
+epoch [100/100][1/2]	time 0.518 (0.518)	data 0.444 (0.444)	eta 0:00:00	loss 0.1092 (0.1092)	acc 100.0000 (100.0000)	lr 2.466589e-06
+epoch [100/100][2/2]	time 0.074 (0.296)	data 0.003 (0.224)	eta 0:00:00	loss 0.5488 (0.3290)	acc 100.0000 (100.0000)	lr 6.167995e-07
+Checkpoint saved to "output_reproduce/lungcolon/shots_2/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/prompt_learner/model.pth.tar-100"
+Finished training
+Do evaluation on test set
+=> result
+* total: 7,500
+* correct: 5,993
+* accuracy: 79.91%
+* error: 20.09%
+* macro_f1: 79.53%
+Elapsed: 0:01:34

few_shot/lungcolon/shots_2/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/prompt_learner/checkpoint

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few_shot/lungcolon/shots_2/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/tensorboard/events.out.tfevents.1742385103.impactlab-server.2775922.0

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few_shot/lungcolon/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1/log.txt

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+***************
+** Arguments **
+***************
+backbone: 
+config_file: configs/trainers/BiomedCoOp_BiomedCLIP/few_shot/lungcolon.yaml
+dataset_config_file: configs/datasets/lungcolon.yaml
+eval_only: False
+head: 
+load_epoch: None
+model_dir: 
+no_train: False
+opts: ['TRAINER.BIOMEDCOOP.N_CTX', '4', 'TRAINER.BIOMEDCOOP.CSC', 'False', 'TRAINER.BIOMEDCOOP.CLASS_TOKEN_POSITION', 'end', 'DATASET.NUM_SHOTS', '4']
+output_dir: output_reproduce/lungcolon/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1
+resume: 
+root: DATA
+seed: 1
+source_domains: None
+target_domains: None
+trainer: BiomedCoOp_BiomedCLIP
+transforms: None
+************
+** Config **
+************
+DATALOADER:
+  K_TRANSFORMS: 1
+  NUM_WORKERS: 8
+  RETURN_IMG0: False
+  TEST:
+    BATCH_SIZE: 100
+    SAMPLER: SequentialSampler
+  TRAIN_U:
+    BATCH_SIZE: 32
+    N_DOMAIN: 0
+    N_INS: 16
+    SAME_AS_X: True
+    SAMPLER: RandomSampler
+  TRAIN_X:
+    BATCH_SIZE: 4
+    N_DOMAIN: 0
+    N_INS: 16
+    SAMPLER: RandomSampler
+DATASET:
+  ALL_AS_UNLABELED: False
+  CIFAR_C_LEVEL: 1
+  CIFAR_C_TYPE: 
+  NAME: LungColon
+  NUM_LABELED: -1
+  NUM_SHOTS: 4
+  ROOT: DATA
+  SOURCE_DOMAINS: ()
+  STL10_FOLD: -1
+  SUBSAMPLE_CLASSES: all
+  TARGET_DOMAINS: ()
+  VAL_PERCENT: 0.1
+INPUT:
+  COLORJITTER_B: 0.4
+  COLORJITTER_C: 0.4
+  COLORJITTER_H: 0.1
+  COLORJITTER_S: 0.4
+  CROP_PADDING: 4
+  CUTOUT_LEN: 16
+  CUTOUT_N: 1
+  GB_K: 21
+  GB_P: 0.5
+  GN_MEAN: 0.0
+  GN_STD: 0.15
+  INTERPOLATION: bicubic
+  NO_TRANSFORM: False
+  PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
+  PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
+  RANDAUGMENT_M: 10
+  RANDAUGMENT_N: 2
+  RGS_P: 0.2
+  SIZE: (224, 224)
+  TRANSFORMS: ('random_resized_crop', 'normalize')
+MODEL:
+  BACKBONE:
+    NAME: ViT-B/16
+    PRETRAINED: True
+  HEAD:
+    ACTIVATION: relu
+    BN: True
+    DROPOUT: 0.0
+    HIDDEN_LAYERS: ()
+    NAME: 
+  INIT_WEIGHTS: 
+OPTIM:
+  ADAM_BETA1: 0.9
+  ADAM_BETA2: 0.999
+  BASE_LR_MULT: 0.1
+  GAMMA: 0.1
+  LR: 0.0025
+  LR_SCHEDULER: cosine
+  MAX_EPOCH: 100
+  MOMENTUM: 0.9
+  NAME: sgd
+  NEW_LAYERS: ()
+  RMSPROP_ALPHA: 0.99
+  SGD_DAMPNING: 0
+  SGD_NESTEROV: False
+  STAGED_LR: False
+  STEPSIZE: (-1,)
+  WARMUP_CONS_LR: 1e-05
+  WARMUP_EPOCH: 1
+  WARMUP_MIN_LR: 1e-05
+  WARMUP_RECOUNT: True
+  WARMUP_TYPE: constant
+  WEIGHT_DECAY: 0.0005
+OUTPUT_DIR: output_reproduce/lungcolon/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1
+RESUME: 
+SEED: 1
+TEST:
+  COMPUTE_CMAT: False
+  EVALUATOR: Classification
+  FINAL_MODEL: last_step
+  NO_TEST: False
+  PER_CLASS_RESULT: False
+  SPLIT: test
+TRAIN:
+  CHECKPOINT_FREQ: 0
+  COUNT_ITER: train_x
+  PRINT_FREQ: 20
+TRAINER:
+  BIOMEDCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    KDSP_LAMBDA: 0.5
+    N_CTX: 4
+    N_PROMPTS: 50
+    PREC: fp32
+    SCCM_LAMBDA: 0.5
+    TAU: 1.5
+  CG:
+    ALPHA_D: 0.5
+    ALPHA_F: 0.5
+    EPS_D: 1.0
+    EPS_F: 1.0
+  COCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: 
+    N_CTX: 4
+    PREC: fp32
+  COOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: 
+    N_CTX: 4
+    PREC: fp32
+  DAEL:
+    CONF_THRE: 0.95
+    STRONG_TRANSFORMS: ()
+    WEIGHT_U: 0.5
+  DDAIG:
+    ALPHA: 0.5
+    CLAMP: False
+    CLAMP_MAX: 1.0
+    CLAMP_MIN: -1.0
+    G_ARCH: 
+    LMDA: 0.3
+    WARMUP: 0
+  ENTMIN:
+    LMDA: 0.001
+  FIXMATCH:
+    CONF_THRE: 0.95
+    STRONG_TRANSFORMS: ()
+    WEIGHT_U: 1.0
+  KGCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    N_CTX: 4
+    PREC: fp32
+    W: 1.0
+  M3SDA:
+    LMDA: 0.5
+    N_STEP_F: 4
+  MCD:
+    N_STEP_F: 4
+  MEANTEA:
+    EMA_ALPHA: 0.999
+    RAMPUP: 5
+    WEIGHT_U: 1.0
+  MIXMATCH:
+    MIXUP_BETA: 0.75
+    RAMPUP: 20000
+    TEMP: 2.0
+    WEIGHT_U: 100.0
+  MME:
+    LMDA: 0.1
+  NAME: BiomedCoOp_BiomedCLIP
+  PROGRAD:
+    ALPHA: 0.0
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    GM: False
+    LAMBDA: 1.0
+    NAME: 
+    N_CTX: 4
+    PREC: fp32
+    T: 1.0
+  SE:
+    CONF_THRE: 0.95
+    EMA_ALPHA: 0.999
+    RAMPUP: 300
+USE_CUDA: True
+VERBOSE: True
+VERSION: 1
+Collecting env info ...
+** System info **
+PyTorch version: 2.0.1+cu118
+Is debug build: False
+CUDA used to build PyTorch: 11.8
+ROCM used to build PyTorch: N/A
+
+OS: Ubuntu 22.04.5 LTS (x86_64)
+GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
+Clang version: Could not collect
+CMake version: version 3.25.0
+Libc version: glibc-2.35
+
+Python version: 3.10.15 (main, Oct  3 2024, 07:27:34) [GCC 11.2.0] (64-bit runtime)
+Python platform: Linux-5.15.0-134-generic-x86_64-with-glibc2.35
+Is CUDA available: True
+CUDA runtime version: 12.8.61
+CUDA_MODULE_LOADING set to: LAZY
+GPU models and configuration: 
+GPU 0: NVIDIA A100-SXM4-40GB
+GPU 1: NVIDIA A100-SXM4-40GB
+GPU 2: NVIDIA A100-SXM4-40GB
+GPU 3: NVIDIA A100-SXM4-40GB
+
+Nvidia driver version: 570.124.06
+cuDNN version: Could not collect
+HIP runtime version: N/A
+MIOpen runtime version: N/A
+Is XNNPACK available: True
+
+CPU:
+Architecture:                         x86_64
+CPU op-mode(s):                       32-bit, 64-bit
+Address sizes:                        43 bits physical, 48 bits virtual
+Byte Order:                           Little Endian
+CPU(s):                               128
+On-line CPU(s) list:                  0-127
+Vendor ID:                            AuthenticAMD
+Model name:                           AMD EPYC 7502 32-Core Processor
+CPU family:                           23
+Model:                                49
+Thread(s) per core:                   2
+Core(s) per socket:                   32
+Socket(s):                            2
+Stepping:                             0
+Frequency boost:                      enabled
+CPU max MHz:                          2500.0000
+CPU min MHz:                          1500.0000
+BogoMIPS:                             4999.71
+Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl umip rdpid overflow_recov succor smca sme sev sev_es
+Virtualization:                       AMD-V
+L1d cache:                            2 MiB (64 instances)
+L1i cache:                            2 MiB (64 instances)
+L2 cache:                             32 MiB (64 instances)
+L3 cache:                             256 MiB (16 instances)
+NUMA node(s):                         2
+NUMA node0 CPU(s):                    0-31,64-95
+NUMA node1 CPU(s):                    32-63,96-127
+Vulnerability Gather data sampling:   Not affected
+Vulnerability Itlb multihit:          Not affected
+Vulnerability L1tf:                   Not affected
+Vulnerability Mds:                    Not affected
+Vulnerability Meltdown:               Not affected
+Vulnerability Mmio stale data:        Not affected
+Vulnerability Reg file data sampling: Not affected
+Vulnerability Retbleed:               Mitigation; untrained return thunk; SMT enabled with STIBP protection
+Vulnerability Spec rstack overflow:   Mitigation; safe RET
+Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl and seccomp
+Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
+Vulnerability Spectre v2:             Mitigation; Retpolines; IBPB conditional; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
+Vulnerability Srbds:                  Not affected
+Vulnerability Tsx async abort:        Not affected
+
+Versions of relevant libraries:
+[pip3] numpy==1.26.3
+[pip3] torch==2.0.1+cu118
+[pip3] torchvision==0.15.2+cu118
+[conda] numpy                     1.26.3                   pypi_0    pypi
+[conda] torch                     2.0.1+cu118              pypi_0    pypi
+[conda] torchvision               0.15.2+cu118             pypi_0    pypi
+        Pillow (10.2.0)
+
+Loading trainer: BiomedCoOp_BiomedCLIP
+Loading dataset: LungColon
+Reading split from /data/t_kol/BiomedCoOp/DATA/LungColon/split_LungColon.json
+Loading preprocessed few-shot data from /data/t_kol/BiomedCoOp/DATA/LungColon/split_fewshot/shot_4-seed_1.pkl
+Building transform_train
++ random resized crop (size=(224, 224))
++ to torch tensor of range [0, 1]
++ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
+Building transform_test
++ resize the smaller edge to 224
++ 224x224 center crop
++ to torch tensor of range [0, 1]
++ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
+***** Dataset statistics *****
+  Dataset: LungColon
+  # classes: 5
+  # train_x: 20
+  # val: 20
+  # test: 7,500
+Loading BiomedCLIP (backbone: ViT-B/16)
+Building custom CLIP
+Initial text context: "a photo of a"
+Number of context words (tokens) for Language prompting: 4
+Turning off gradients in both the image and the text encoder
+Parameters to be updated: {'prompt_learner.ctx'}
+Parameters count: 1
+Loading evaluator: Classification
+Trainer built successfully.
+No checkpoint found, train from scratch
+Initializing summary writer for tensorboard with log_dir=output_reproduce/lungcolon/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1/tensorboard
+epoch [1/100][1/5]	time 0.707 (0.707)	data 0.362 (0.362)	eta 0:05:52	loss 3.5880 (3.5880)	acc 25.0000 (25.0000)	lr 1.000000e-05
+epoch [1/100][2/5]	time 0.071 (0.389)	data 0.001 (0.181)	eta 0:03:13	loss 0.9768 (2.2824)	acc 50.0000 (37.5000)	lr 1.000000e-05
+epoch [1/100][3/5]	time 0.070 (0.283)	data 0.001 (0.121)	eta 0:02:20	loss 2.8168 (2.4605)	acc 25.0000 (33.3333)	lr 1.000000e-05
+epoch [1/100][4/5]	time 0.070 (0.229)	data 0.001 (0.091)	eta 0:01:53	loss 3.0481 (2.6074)	acc 25.0000 (31.2500)	lr 1.000000e-05
+epoch [1/100][5/5]	time 0.070 (0.198)	data 0.001 (0.073)	eta 0:01:37	loss 2.1774 (2.5214)	acc 50.0000 (35.0000)	lr 2.500000e-03
+epoch [2/100][1/5]	time 0.525 (0.525)	data 0.453 (0.453)	eta 0:04:19	loss 2.6695 (2.6695)	acc 50.0000 (50.0000)	lr 2.500000e-03
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+epoch [2/100][5/5]	time 0.070 (0.161)	data 0.001 (0.092)	eta 0:01:19	loss 4.1020 (2.3545)	acc 0.0000 (45.0000)	lr 2.499383e-03
+epoch [3/100][1/5]	time 0.486 (0.486)	data 0.413 (0.413)	eta 0:03:57	loss 1.5642 (1.5642)	acc 75.0000 (75.0000)	lr 2.499383e-03
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+epoch [7/100][3/5]	time 0.070 (0.227)	data 0.001 (0.155)	eta 0:01:46	loss 0.6659 (1.4880)	acc 50.0000 (58.3333)	lr 2.484610e-03
+epoch [7/100][4/5]	time 0.070 (0.188)	data 0.001 (0.116)	eta 0:01:27	loss 1.4087 (1.4682)	acc 25.0000 (50.0000)	lr 2.484610e-03
+epoch [7/100][5/5]	time 0.070 (0.165)	data 0.001 (0.093)	eta 0:01:16	loss 0.8312 (1.3408)	acc 75.0000 (55.0000)	lr 2.477859e-03
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+epoch [8/100][2/5]	time 0.070 (0.292)	data 0.001 (0.222)	eta 0:02:15	loss 1.5701 (1.4291)	acc 75.0000 (62.5000)	lr 2.477859e-03
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+epoch [100/100][1/5]	time 0.504 (0.504)	data 0.431 (0.431)	eta 0:00:02	loss 0.6323 (0.6323)	acc 100.0000 (100.0000)	lr 2.466589e-06
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+epoch [100/100][4/5]	time 0.073 (0.180)	data 0.003 (0.109)	eta 0:00:00	loss 0.1031 (0.3510)	acc 100.0000 (100.0000)	lr 2.466589e-06
+epoch [100/100][5/5]	time 0.072 (0.158)	data 0.003 (0.088)	eta 0:00:00	loss 0.2565 (0.3321)	acc 100.0000 (100.0000)	lr 6.167995e-07
+Checkpoint saved to "output_reproduce/lungcolon/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1/prompt_learner/model.pth.tar-100"
+Finished training
+Do evaluation on test set
+=> result
+* total: 7,500
+* correct: 6,251
+* accuracy: 83.35%
+* error: 16.65%
+* macro_f1: 82.88%
+Elapsed: 0:01:54

few_shot/lungcolon/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1/prompt_learner/checkpoint

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few_shot/lungcolon/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed1/prompt_learner/model.pth.tar-100

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+size 1132531909

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few_shot/lungcolon/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/log.txt

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+***************
+** Arguments **
+***************
+backbone: 
+config_file: configs/trainers/BiomedCoOp_BiomedCLIP/few_shot/lungcolon.yaml
+dataset_config_file: configs/datasets/lungcolon.yaml
+eval_only: False
+head: 
+load_epoch: None
+model_dir: 
+no_train: False
+opts: ['TRAINER.BIOMEDCOOP.N_CTX', '4', 'TRAINER.BIOMEDCOOP.CSC', 'False', 'TRAINER.BIOMEDCOOP.CLASS_TOKEN_POSITION', 'end', 'DATASET.NUM_SHOTS', '4']
+output_dir: output_reproduce/lungcolon/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2
+resume: 
+root: DATA
+seed: 2
+source_domains: None
+target_domains: None
+trainer: BiomedCoOp_BiomedCLIP
+transforms: None
+************
+** Config **
+************
+DATALOADER:
+  K_TRANSFORMS: 1
+  NUM_WORKERS: 8
+  RETURN_IMG0: False
+  TEST:
+    BATCH_SIZE: 100
+    SAMPLER: SequentialSampler
+  TRAIN_U:
+    BATCH_SIZE: 32
+    N_DOMAIN: 0
+    N_INS: 16
+    SAME_AS_X: True
+    SAMPLER: RandomSampler
+  TRAIN_X:
+    BATCH_SIZE: 4
+    N_DOMAIN: 0
+    N_INS: 16
+    SAMPLER: RandomSampler
+DATASET:
+  ALL_AS_UNLABELED: False
+  CIFAR_C_LEVEL: 1
+  CIFAR_C_TYPE: 
+  NAME: LungColon
+  NUM_LABELED: -1
+  NUM_SHOTS: 4
+  ROOT: DATA
+  SOURCE_DOMAINS: ()
+  STL10_FOLD: -1
+  SUBSAMPLE_CLASSES: all
+  TARGET_DOMAINS: ()
+  VAL_PERCENT: 0.1
+INPUT:
+  COLORJITTER_B: 0.4
+  COLORJITTER_C: 0.4
+  COLORJITTER_H: 0.1
+  COLORJITTER_S: 0.4
+  CROP_PADDING: 4
+  CUTOUT_LEN: 16
+  CUTOUT_N: 1
+  GB_K: 21
+  GB_P: 0.5
+  GN_MEAN: 0.0
+  GN_STD: 0.15
+  INTERPOLATION: bicubic
+  NO_TRANSFORM: False
+  PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
+  PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
+  RANDAUGMENT_M: 10
+  RANDAUGMENT_N: 2
+  RGS_P: 0.2
+  SIZE: (224, 224)
+  TRANSFORMS: ('random_resized_crop', 'normalize')
+MODEL:
+  BACKBONE:
+    NAME: ViT-B/16
+    PRETRAINED: True
+  HEAD:
+    ACTIVATION: relu
+    BN: True
+    DROPOUT: 0.0
+    HIDDEN_LAYERS: ()
+    NAME: 
+  INIT_WEIGHTS: 
+OPTIM:
+  ADAM_BETA1: 0.9
+  ADAM_BETA2: 0.999
+  BASE_LR_MULT: 0.1
+  GAMMA: 0.1
+  LR: 0.0025
+  LR_SCHEDULER: cosine
+  MAX_EPOCH: 100
+  MOMENTUM: 0.9
+  NAME: sgd
+  NEW_LAYERS: ()
+  RMSPROP_ALPHA: 0.99
+  SGD_DAMPNING: 0
+  SGD_NESTEROV: False
+  STAGED_LR: False
+  STEPSIZE: (-1,)
+  WARMUP_CONS_LR: 1e-05
+  WARMUP_EPOCH: 1
+  WARMUP_MIN_LR: 1e-05
+  WARMUP_RECOUNT: True
+  WARMUP_TYPE: constant
+  WEIGHT_DECAY: 0.0005
+OUTPUT_DIR: output_reproduce/lungcolon/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2
+RESUME: 
+SEED: 2
+TEST:
+  COMPUTE_CMAT: False
+  EVALUATOR: Classification
+  FINAL_MODEL: last_step
+  NO_TEST: False
+  PER_CLASS_RESULT: False
+  SPLIT: test
+TRAIN:
+  CHECKPOINT_FREQ: 0
+  COUNT_ITER: train_x
+  PRINT_FREQ: 20
+TRAINER:
+  BIOMEDCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    KDSP_LAMBDA: 0.5
+    N_CTX: 4
+    N_PROMPTS: 50
+    PREC: fp32
+    SCCM_LAMBDA: 0.5
+    TAU: 1.5
+  CG:
+    ALPHA_D: 0.5
+    ALPHA_F: 0.5
+    EPS_D: 1.0
+    EPS_F: 1.0
+  COCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: 
+    N_CTX: 4
+    PREC: fp32
+  COOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: 
+    N_CTX: 4
+    PREC: fp32
+  DAEL:
+    CONF_THRE: 0.95
+    STRONG_TRANSFORMS: ()
+    WEIGHT_U: 0.5
+  DDAIG:
+    ALPHA: 0.5
+    CLAMP: False
+    CLAMP_MAX: 1.0
+    CLAMP_MIN: -1.0
+    G_ARCH: 
+    LMDA: 0.3
+    WARMUP: 0
+  ENTMIN:
+    LMDA: 0.001
+  FIXMATCH:
+    CONF_THRE: 0.95
+    STRONG_TRANSFORMS: ()
+    WEIGHT_U: 1.0
+  KGCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    N_CTX: 4
+    PREC: fp32
+    W: 1.0
+  M3SDA:
+    LMDA: 0.5
+    N_STEP_F: 4
+  MCD:
+    N_STEP_F: 4
+  MEANTEA:
+    EMA_ALPHA: 0.999
+    RAMPUP: 5
+    WEIGHT_U: 1.0
+  MIXMATCH:
+    MIXUP_BETA: 0.75
+    RAMPUP: 20000
+    TEMP: 2.0
+    WEIGHT_U: 100.0
+  MME:
+    LMDA: 0.1
+  NAME: BiomedCoOp_BiomedCLIP
+  PROGRAD:
+    ALPHA: 0.0
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    GM: False
+    LAMBDA: 1.0
+    NAME: 
+    N_CTX: 4
+    PREC: fp32
+    T: 1.0
+  SE:
+    CONF_THRE: 0.95
+    EMA_ALPHA: 0.999
+    RAMPUP: 300
+USE_CUDA: True
+VERBOSE: True
+VERSION: 1
+Collecting env info ...
+** System info **
+PyTorch version: 2.0.1+cu118
+Is debug build: False
+CUDA used to build PyTorch: 11.8
+ROCM used to build PyTorch: N/A
+
+OS: Ubuntu 22.04.5 LTS (x86_64)
+GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
+Clang version: Could not collect
+CMake version: version 3.25.0
+Libc version: glibc-2.35
+
+Python version: 3.10.15 (main, Oct  3 2024, 07:27:34) [GCC 11.2.0] (64-bit runtime)
+Python platform: Linux-5.15.0-134-generic-x86_64-with-glibc2.35
+Is CUDA available: True
+CUDA runtime version: 12.8.61
+CUDA_MODULE_LOADING set to: LAZY
+GPU models and configuration: 
+GPU 0: NVIDIA A100-SXM4-40GB
+GPU 1: NVIDIA A100-SXM4-40GB
+GPU 2: NVIDIA A100-SXM4-40GB
+GPU 3: NVIDIA A100-SXM4-40GB
+
+Nvidia driver version: 570.124.06
+cuDNN version: Could not collect
+HIP runtime version: N/A
+MIOpen runtime version: N/A
+Is XNNPACK available: True
+
+CPU:
+Architecture:                         x86_64
+CPU op-mode(s):                       32-bit, 64-bit
+Address sizes:                        43 bits physical, 48 bits virtual
+Byte Order:                           Little Endian
+CPU(s):                               128
+On-line CPU(s) list:                  0-127
+Vendor ID:                            AuthenticAMD
+Model name:                           AMD EPYC 7502 32-Core Processor
+CPU family:                           23
+Model:                                49
+Thread(s) per core:                   2
+Core(s) per socket:                   32
+Socket(s):                            2
+Stepping:                             0
+Frequency boost:                      enabled
+CPU max MHz:                          2500.0000
+CPU min MHz:                          1500.0000
+BogoMIPS:                             4999.71
+Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl umip rdpid overflow_recov succor smca sme sev sev_es
+Virtualization:                       AMD-V
+L1d cache:                            2 MiB (64 instances)
+L1i cache:                            2 MiB (64 instances)
+L2 cache:                             32 MiB (64 instances)
+L3 cache:                             256 MiB (16 instances)
+NUMA node(s):                         2
+NUMA node0 CPU(s):                    0-31,64-95
+NUMA node1 CPU(s):                    32-63,96-127
+Vulnerability Gather data sampling:   Not affected
+Vulnerability Itlb multihit:          Not affected
+Vulnerability L1tf:                   Not affected
+Vulnerability Mds:                    Not affected
+Vulnerability Meltdown:               Not affected
+Vulnerability Mmio stale data:        Not affected
+Vulnerability Reg file data sampling: Not affected
+Vulnerability Retbleed:               Mitigation; untrained return thunk; SMT enabled with STIBP protection
+Vulnerability Spec rstack overflow:   Mitigation; safe RET
+Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl and seccomp
+Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
+Vulnerability Spectre v2:             Mitigation; Retpolines; IBPB conditional; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
+Vulnerability Srbds:                  Not affected
+Vulnerability Tsx async abort:        Not affected
+
+Versions of relevant libraries:
+[pip3] numpy==1.26.3
+[pip3] torch==2.0.1+cu118
+[pip3] torchvision==0.15.2+cu118
+[conda] numpy                     1.26.3                   pypi_0    pypi
+[conda] torch                     2.0.1+cu118              pypi_0    pypi
+[conda] torchvision               0.15.2+cu118             pypi_0    pypi
+        Pillow (10.2.0)
+
+Loading trainer: BiomedCoOp_BiomedCLIP
+Loading dataset: LungColon
+Reading split from /data/t_kol/BiomedCoOp/DATA/LungColon/split_LungColon.json
+Loading preprocessed few-shot data from /data/t_kol/BiomedCoOp/DATA/LungColon/split_fewshot/shot_4-seed_2.pkl
+Building transform_train
++ random resized crop (size=(224, 224))
++ to torch tensor of range [0, 1]
++ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
+Building transform_test
++ resize the smaller edge to 224
++ 224x224 center crop
++ to torch tensor of range [0, 1]
++ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
+***** Dataset statistics *****
+  Dataset: LungColon
+  # classes: 5
+  # train_x: 20
+  # val: 20
+  # test: 7,500
+Loading BiomedCLIP (backbone: ViT-B/16)
+Building custom CLIP
+Initial text context: "a photo of a"
+Number of context words (tokens) for Language prompting: 4
+Turning off gradients in both the image and the text encoder
+Parameters to be updated: {'prompt_learner.ctx'}
+Parameters count: 1
+Loading evaluator: Classification
+Trainer built successfully.
+No checkpoint found, train from scratch
+Initializing summary writer for tensorboard with log_dir=output_reproduce/lungcolon/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/tensorboard
+epoch [1/100][1/5]	time 0.733 (0.733)	data 0.393 (0.393)	eta 0:06:05	loss 2.0641 (2.0641)	acc 50.0000 (50.0000)	lr 1.000000e-05
+epoch [1/100][2/5]	time 0.071 (0.402)	data 0.001 (0.197)	eta 0:03:20	loss 2.6245 (2.3443)	acc 50.0000 (50.0000)	lr 1.000000e-05
+epoch [1/100][3/5]	time 0.070 (0.291)	data 0.001 (0.132)	eta 0:02:24	loss 1.9509 (2.2131)	acc 25.0000 (41.6667)	lr 1.000000e-05
+epoch [1/100][4/5]	time 0.070 (0.236)	data 0.001 (0.099)	eta 0:01:57	loss 2.1960 (2.2089)	acc 25.0000 (37.5000)	lr 1.000000e-05
+epoch [1/100][5/5]	time 0.070 (0.203)	data 0.001 (0.079)	eta 0:01:40	loss 2.5781 (2.2827)	acc 50.0000 (40.0000)	lr 2.500000e-03
+epoch [2/100][1/5]	time 0.521 (0.521)	data 0.448 (0.448)	eta 0:04:17	loss 4.1272 (4.1272)	acc 25.0000 (25.0000)	lr 2.500000e-03
+epoch [2/100][2/5]	time 0.074 (0.298)	data 0.005 (0.226)	eta 0:02:26	loss 0.5720 (2.3496)	acc 75.0000 (50.0000)	lr 2.500000e-03
+epoch [2/100][3/5]	time 0.070 (0.222)	data 0.001 (0.151)	eta 0:01:49	loss 1.5726 (2.0906)	acc 50.0000 (50.0000)	lr 2.500000e-03
+epoch [2/100][4/5]	time 0.070 (0.184)	data 0.001 (0.114)	eta 0:01:30	loss 0.2460 (1.6294)	acc 100.0000 (62.5000)	lr 2.500000e-03
+epoch [2/100][5/5]	time 0.071 (0.161)	data 0.003 (0.091)	eta 0:01:18	loss 2.0317 (1.7099)	acc 50.0000 (60.0000)	lr 2.499383e-03
+epoch [3/100][1/5]	time 0.555 (0.555)	data 0.477 (0.477)	eta 0:04:31	loss 1.1786 (1.1786)	acc 75.0000 (75.0000)	lr 2.499383e-03
+epoch [3/100][2/5]	time 0.071 (0.313)	data 0.001 (0.239)	eta 0:02:32	loss 1.6821 (1.4304)	acc 50.0000 (62.5000)	lr 2.499383e-03
+epoch [3/100][3/5]	time 0.070 (0.232)	data 0.001 (0.160)	eta 0:01:52	loss 1.2808 (1.3805)	acc 50.0000 (58.3333)	lr 2.499383e-03
+epoch [3/100][4/5]	time 0.072 (0.192)	data 0.003 (0.121)	eta 0:01:33	loss 2.0628 (1.5511)	acc 75.0000 (62.5000)	lr 2.499383e-03
+epoch [3/100][5/5]	time 0.071 (0.168)	data 0.001 (0.097)	eta 0:01:21	loss 0.4879 (1.3384)	acc 75.0000 (65.0000)	lr 2.497533e-03
+epoch [4/100][1/5]	time 0.557 (0.557)	data 0.478 (0.478)	eta 0:04:29	loss 1.5521 (1.5521)	acc 50.0000 (50.0000)	lr 2.497533e-03
+epoch [4/100][2/5]	time 0.071 (0.314)	data 0.001 (0.239)	eta 0:02:31	loss 1.2691 (1.4106)	acc 25.0000 (37.5000)	lr 2.497533e-03
+epoch [4/100][3/5]	time 0.070 (0.233)	data 0.001 (0.160)	eta 0:01:52	loss 1.7685 (1.5299)	acc 50.0000 (41.6667)	lr 2.497533e-03
+epoch [4/100][4/5]	time 0.070 (0.192)	data 0.001 (0.120)	eta 0:01:32	loss 0.9701 (1.3899)	acc 75.0000 (50.0000)	lr 2.497533e-03
+epoch [4/100][5/5]	time 0.073 (0.168)	data 0.003 (0.097)	eta 0:01:20	loss 1.2489 (1.3617)	acc 50.0000 (50.0000)	lr 2.494452e-03
+epoch [5/100][1/5]	time 0.544 (0.544)	data 0.471 (0.471)	eta 0:04:20	loss 1.0558 (1.0558)	acc 75.0000 (75.0000)	lr 2.494452e-03
+epoch [5/100][2/5]	time 0.072 (0.308)	data 0.003 (0.237)	eta 0:02:27	loss 0.5876 (0.8217)	acc 100.0000 (87.5000)	lr 2.494452e-03
+epoch [5/100][3/5]	time 0.071 (0.229)	data 0.001 (0.158)	eta 0:01:49	loss 0.8153 (0.8196)	acc 75.0000 (83.3333)	lr 2.494452e-03
+epoch [5/100][4/5]	time 0.070 (0.189)	data 0.001 (0.119)	eta 0:01:30	loss 0.2963 (0.6887)	acc 100.0000 (87.5000)	lr 2.494452e-03
+epoch [5/100][5/5]	time 0.070 (0.166)	data 0.001 (0.095)	eta 0:01:18	loss 0.6994 (0.6909)	acc 75.0000 (85.0000)	lr 2.490143e-03
+epoch [6/100][1/5]	time 0.522 (0.522)	data 0.449 (0.449)	eta 0:04:07	loss 0.8998 (0.8998)	acc 75.0000 (75.0000)	lr 2.490143e-03
+epoch [6/100][2/5]	time 0.071 (0.296)	data 0.001 (0.225)	eta 0:02:20	loss 1.3429 (1.1214)	acc 25.0000 (50.0000)	lr 2.490143e-03
+epoch [6/100][3/5]	time 0.071 (0.221)	data 0.001 (0.150)	eta 0:01:44	loss 1.5331 (1.2586)	acc 25.0000 (41.6667)	lr 2.490143e-03
+epoch [6/100][4/5]	time 0.072 (0.184)	data 0.003 (0.113)	eta 0:01:26	loss 2.0873 (1.4658)	acc 25.0000 (37.5000)	lr 2.490143e-03
+epoch [6/100][5/5]	time 0.071 (0.161)	data 0.001 (0.091)	eta 0:01:15	loss 1.6728 (1.5072)	acc 25.0000 (35.0000)	lr 2.484610e-03
+epoch [7/100][1/5]	time 0.513 (0.513)	data 0.440 (0.440)	eta 0:04:00	loss 1.8289 (1.8289)	acc 25.0000 (25.0000)	lr 2.484610e-03
+epoch [7/100][2/5]	time 0.073 (0.293)	data 0.004 (0.222)	eta 0:02:17	loss 1.2337 (1.5313)	acc 75.0000 (50.0000)	lr 2.484610e-03
+epoch [7/100][3/5]	time 0.072 (0.219)	data 0.003 (0.149)	eta 0:01:42	loss 1.0278 (1.3635)	acc 75.0000 (58.3333)	lr 2.484610e-03
+epoch [7/100][4/5]	time 0.070 (0.182)	data 0.001 (0.112)	eta 0:01:24	loss 1.4600 (1.3876)	acc 25.0000 (50.0000)	lr 2.484610e-03
+epoch [7/100][5/5]	time 0.072 (0.160)	data 0.003 (0.090)	eta 0:01:14	loss 0.9748 (1.3050)	acc 75.0000 (55.0000)	lr 2.477859e-03
+epoch [8/100][1/5]	time 0.549 (0.549)	data 0.470 (0.470)	eta 0:04:14	loss 0.6401 (0.6401)	acc 75.0000 (75.0000)	lr 2.477859e-03
+epoch [8/100][2/5]	time 0.070 (0.310)	data 0.001 (0.235)	eta 0:02:23	loss 0.4547 (0.5474)	acc 75.0000 (75.0000)	lr 2.477859e-03
+epoch [8/100][3/5]	time 0.070 (0.230)	data 0.001 (0.157)	eta 0:01:46	loss 1.1768 (0.7572)	acc 50.0000 (66.6667)	lr 2.477859e-03
+epoch [8/100][4/5]	time 0.070 (0.190)	data 0.001 (0.118)	eta 0:01:27	loss 0.4605 (0.6830)	acc 100.0000 (75.0000)	lr 2.477859e-03
+epoch [8/100][5/5]	time 0.071 (0.166)	data 0.001 (0.095)	eta 0:01:16	loss 0.5416 (0.6547)	acc 100.0000 (80.0000)	lr 2.469896e-03
+epoch [9/100][1/5]	time 0.527 (0.527)	data 0.454 (0.454)	eta 0:04:02	loss 0.8265 (0.8265)	acc 75.0000 (75.0000)	lr 2.469896e-03
+epoch [9/100][2/5]	time 0.070 (0.299)	data 0.001 (0.228)	eta 0:02:16	loss 0.5024 (0.6644)	acc 75.0000 (75.0000)	lr 2.469896e-03
+epoch [9/100][3/5]	time 0.074 (0.224)	data 0.005 (0.154)	eta 0:01:42	loss 0.4169 (0.5819)	acc 100.0000 (83.3333)	lr 2.469896e-03
+epoch [9/100][4/5]	time 0.070 (0.185)	data 0.001 (0.115)	eta 0:01:24	loss 0.9210 (0.6667)	acc 50.0000 (75.0000)	lr 2.469896e-03
+epoch [9/100][5/5]	time 0.071 (0.162)	data 0.001 (0.093)	eta 0:01:13	loss 0.2442 (0.5822)	acc 100.0000 (80.0000)	lr 2.460729e-03
+epoch [10/100][1/5]	time 0.545 (0.545)	data 0.467 (0.467)	eta 0:04:07	loss 0.5964 (0.5964)	acc 100.0000 (100.0000)	lr 2.460729e-03
+epoch [10/100][2/5]	time 0.073 (0.309)	data 0.003 (0.235)	eta 0:02:19	loss 0.3617 (0.4790)	acc 100.0000 (100.0000)	lr 2.460729e-03
+epoch [10/100][3/5]	time 0.070 (0.229)	data 0.001 (0.157)	eta 0:01:43	loss 1.2908 (0.7496)	acc 25.0000 (75.0000)	lr 2.460729e-03
+epoch [10/100][4/5]	time 0.070 (0.190)	data 0.001 (0.118)	eta 0:01:25	loss 0.3438 (0.6482)	acc 100.0000 (81.2500)	lr 2.460729e-03
+epoch [10/100][5/5]	time 0.070 (0.166)	data 0.001 (0.095)	eta 0:01:14	loss 0.6039 (0.6393)	acc 75.0000 (80.0000)	lr 2.450367e-03
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+epoch [11/100][3/5]	time 0.070 (0.227)	data 0.001 (0.155)	eta 0:01:41	loss 0.8883 (0.5939)	acc 75.0000 (91.6667)	lr 2.450367e-03
+epoch [11/100][4/5]	time 0.074 (0.188)	data 0.004 (0.118)	eta 0:01:24	loss 1.2193 (0.7502)	acc 50.0000 (81.2500)	lr 2.450367e-03
+epoch [11/100][5/5]	time 0.070 (0.165)	data 0.001 (0.094)	eta 0:01:13	loss 0.3127 (0.6627)	acc 100.0000 (85.0000)	lr 2.438821e-03
+epoch [12/100][1/5]	time 0.533 (0.533)	data 0.460 (0.460)	eta 0:03:56	loss 0.3850 (0.3850)	acc 75.0000 (75.0000)	lr 2.438821e-03
+epoch [12/100][2/5]	time 0.070 (0.302)	data 0.001 (0.231)	eta 0:02:13	loss 0.7063 (0.5456)	acc 75.0000 (75.0000)	lr 2.438821e-03
+epoch [12/100][3/5]	time 0.072 (0.225)	data 0.003 (0.155)	eta 0:01:39	loss 0.4273 (0.5062)	acc 75.0000 (75.0000)	lr 2.438821e-03
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+epoch [16/100][4/5]	time 0.072 (0.196)	data 0.003 (0.125)	eta 0:01:22	loss 0.4355 (0.4294)	acc 100.0000 (87.5000)	lr 2.381034e-03
+epoch [16/100][5/5]	time 0.072 (0.171)	data 0.002 (0.100)	eta 0:01:11	loss 0.3973 (0.4230)	acc 100.0000 (90.0000)	lr 2.363758e-03
+epoch [17/100][1/5]	time 0.544 (0.544)	data 0.467 (0.467)	eta 0:03:48	loss 1.1886 (1.1886)	acc 50.0000 (50.0000)	lr 2.363758e-03
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+epoch [17/100][4/5]	time 0.070 (0.189)	data 0.001 (0.118)	eta 0:01:18	loss 0.0968 (0.5392)	acc 100.0000 (81.2500)	lr 2.363758e-03
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+epoch [100/100][5/5]	time 0.071 (0.167)	data 0.001 (0.096)	eta 0:00:00	loss 1.2140 (0.6383)	acc 75.0000 (80.0000)	lr 6.167995e-07
+Checkpoint saved to "output_reproduce/lungcolon/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/prompt_learner/model.pth.tar-100"
+Finished training
+Do evaluation on test set
+=> result
+* total: 7,500
+* correct: 6,523
+* accuracy: 86.97%
+* error: 13.03%
+* macro_f1: 86.63%
+Elapsed: 0:01:56

few_shot/lungcolon/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/prompt_learner/checkpoint

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few_shot/lungcolon/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/prompt_learner/model.pth.tar-100

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+oid sha256:10c701dd6b993be92b9bdf95bae6fd15c1030a17c0ab346f21ea4ffeb0f8b474
+size 1132531909

few_shot/lungcolon/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed2/tensorboard/events.out.tfevents.1742385347.impactlab-server.2982402.0

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+size 71853

few_shot/lungcolon/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/log.txt

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+***************
+** Arguments **
+***************
+backbone: 
+config_file: configs/trainers/BiomedCoOp_BiomedCLIP/few_shot/lungcolon.yaml
+dataset_config_file: configs/datasets/lungcolon.yaml
+eval_only: False
+head: 
+load_epoch: None
+model_dir: 
+no_train: False
+opts: ['TRAINER.BIOMEDCOOP.N_CTX', '4', 'TRAINER.BIOMEDCOOP.CSC', 'False', 'TRAINER.BIOMEDCOOP.CLASS_TOKEN_POSITION', 'end', 'DATASET.NUM_SHOTS', '4']
+output_dir: output_reproduce/lungcolon/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3
+resume: 
+root: DATA
+seed: 3
+source_domains: None
+target_domains: None
+trainer: BiomedCoOp_BiomedCLIP
+transforms: None
+************
+** Config **
+************
+DATALOADER:
+  K_TRANSFORMS: 1
+  NUM_WORKERS: 8
+  RETURN_IMG0: False
+  TEST:
+    BATCH_SIZE: 100
+    SAMPLER: SequentialSampler
+  TRAIN_U:
+    BATCH_SIZE: 32
+    N_DOMAIN: 0
+    N_INS: 16
+    SAME_AS_X: True
+    SAMPLER: RandomSampler
+  TRAIN_X:
+    BATCH_SIZE: 4
+    N_DOMAIN: 0
+    N_INS: 16
+    SAMPLER: RandomSampler
+DATASET:
+  ALL_AS_UNLABELED: False
+  CIFAR_C_LEVEL: 1
+  CIFAR_C_TYPE: 
+  NAME: LungColon
+  NUM_LABELED: -1
+  NUM_SHOTS: 4
+  ROOT: DATA
+  SOURCE_DOMAINS: ()
+  STL10_FOLD: -1
+  SUBSAMPLE_CLASSES: all
+  TARGET_DOMAINS: ()
+  VAL_PERCENT: 0.1
+INPUT:
+  COLORJITTER_B: 0.4
+  COLORJITTER_C: 0.4
+  COLORJITTER_H: 0.1
+  COLORJITTER_S: 0.4
+  CROP_PADDING: 4
+  CUTOUT_LEN: 16
+  CUTOUT_N: 1
+  GB_K: 21
+  GB_P: 0.5
+  GN_MEAN: 0.0
+  GN_STD: 0.15
+  INTERPOLATION: bicubic
+  NO_TRANSFORM: False
+  PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
+  PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
+  RANDAUGMENT_M: 10
+  RANDAUGMENT_N: 2
+  RGS_P: 0.2
+  SIZE: (224, 224)
+  TRANSFORMS: ('random_resized_crop', 'normalize')
+MODEL:
+  BACKBONE:
+    NAME: ViT-B/16
+    PRETRAINED: True
+  HEAD:
+    ACTIVATION: relu
+    BN: True
+    DROPOUT: 0.0
+    HIDDEN_LAYERS: ()
+    NAME: 
+  INIT_WEIGHTS: 
+OPTIM:
+  ADAM_BETA1: 0.9
+  ADAM_BETA2: 0.999
+  BASE_LR_MULT: 0.1
+  GAMMA: 0.1
+  LR: 0.0025
+  LR_SCHEDULER: cosine
+  MAX_EPOCH: 100
+  MOMENTUM: 0.9
+  NAME: sgd
+  NEW_LAYERS: ()
+  RMSPROP_ALPHA: 0.99
+  SGD_DAMPNING: 0
+  SGD_NESTEROV: False
+  STAGED_LR: False
+  STEPSIZE: (-1,)
+  WARMUP_CONS_LR: 1e-05
+  WARMUP_EPOCH: 1
+  WARMUP_MIN_LR: 1e-05
+  WARMUP_RECOUNT: True
+  WARMUP_TYPE: constant
+  WEIGHT_DECAY: 0.0005
+OUTPUT_DIR: output_reproduce/lungcolon/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3
+RESUME: 
+SEED: 3
+TEST:
+  COMPUTE_CMAT: False
+  EVALUATOR: Classification
+  FINAL_MODEL: last_step
+  NO_TEST: False
+  PER_CLASS_RESULT: False
+  SPLIT: test
+TRAIN:
+  CHECKPOINT_FREQ: 0
+  COUNT_ITER: train_x
+  PRINT_FREQ: 20
+TRAINER:
+  BIOMEDCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    KDSP_LAMBDA: 0.5
+    N_CTX: 4
+    N_PROMPTS: 50
+    PREC: fp32
+    SCCM_LAMBDA: 0.5
+    TAU: 1.5
+  CG:
+    ALPHA_D: 0.5
+    ALPHA_F: 0.5
+    EPS_D: 1.0
+    EPS_F: 1.0
+  COCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: 
+    N_CTX: 4
+    PREC: fp32
+  COOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: 
+    N_CTX: 4
+    PREC: fp32
+  DAEL:
+    CONF_THRE: 0.95
+    STRONG_TRANSFORMS: ()
+    WEIGHT_U: 0.5
+  DDAIG:
+    ALPHA: 0.5
+    CLAMP: False
+    CLAMP_MAX: 1.0
+    CLAMP_MIN: -1.0
+    G_ARCH: 
+    LMDA: 0.3
+    WARMUP: 0
+  ENTMIN:
+    LMDA: 0.001
+  FIXMATCH:
+    CONF_THRE: 0.95
+    STRONG_TRANSFORMS: ()
+    WEIGHT_U: 1.0
+  KGCOOP:
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    N_CTX: 4
+    PREC: fp32
+    W: 1.0
+  M3SDA:
+    LMDA: 0.5
+    N_STEP_F: 4
+  MCD:
+    N_STEP_F: 4
+  MEANTEA:
+    EMA_ALPHA: 0.999
+    RAMPUP: 5
+    WEIGHT_U: 1.0
+  MIXMATCH:
+    MIXUP_BETA: 0.75
+    RAMPUP: 20000
+    TEMP: 2.0
+    WEIGHT_U: 100.0
+  MME:
+    LMDA: 0.1
+  NAME: BiomedCoOp_BiomedCLIP
+  PROGRAD:
+    ALPHA: 0.0
+    CLASS_TOKEN_POSITION: end
+    CSC: False
+    CTX_INIT: a photo of a
+    GM: False
+    LAMBDA: 1.0
+    NAME: 
+    N_CTX: 4
+    PREC: fp32
+    T: 1.0
+  SE:
+    CONF_THRE: 0.95
+    EMA_ALPHA: 0.999
+    RAMPUP: 300
+USE_CUDA: True
+VERBOSE: True
+VERSION: 1
+Collecting env info ...
+** System info **
+PyTorch version: 2.0.1+cu118
+Is debug build: False
+CUDA used to build PyTorch: 11.8
+ROCM used to build PyTorch: N/A
+
+OS: Ubuntu 22.04.5 LTS (x86_64)
+GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
+Clang version: Could not collect
+CMake version: version 3.25.0
+Libc version: glibc-2.35
+
+Python version: 3.10.15 (main, Oct  3 2024, 07:27:34) [GCC 11.2.0] (64-bit runtime)
+Python platform: Linux-5.15.0-134-generic-x86_64-with-glibc2.35
+Is CUDA available: True
+CUDA runtime version: 12.8.61
+CUDA_MODULE_LOADING set to: LAZY
+GPU models and configuration: 
+GPU 0: NVIDIA A100-SXM4-40GB
+GPU 1: NVIDIA A100-SXM4-40GB
+GPU 2: NVIDIA A100-SXM4-40GB
+GPU 3: NVIDIA A100-SXM4-40GB
+
+Nvidia driver version: 570.124.06
+cuDNN version: Could not collect
+HIP runtime version: N/A
+MIOpen runtime version: N/A
+Is XNNPACK available: True
+
+CPU:
+Architecture:                         x86_64
+CPU op-mode(s):                       32-bit, 64-bit
+Address sizes:                        43 bits physical, 48 bits virtual
+Byte Order:                           Little Endian
+CPU(s):                               128
+On-line CPU(s) list:                  0-127
+Vendor ID:                            AuthenticAMD
+Model name:                           AMD EPYC 7502 32-Core Processor
+CPU family:                           23
+Model:                                49
+Thread(s) per core:                   2
+Core(s) per socket:                   32
+Socket(s):                            2
+Stepping:                             0
+Frequency boost:                      enabled
+CPU max MHz:                          2500.0000
+CPU min MHz:                          1500.0000
+BogoMIPS:                             4999.71
+Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl umip rdpid overflow_recov succor smca sme sev sev_es
+Virtualization:                       AMD-V
+L1d cache:                            2 MiB (64 instances)
+L1i cache:                            2 MiB (64 instances)
+L2 cache:                             32 MiB (64 instances)
+L3 cache:                             256 MiB (16 instances)
+NUMA node(s):                         2
+NUMA node0 CPU(s):                    0-31,64-95
+NUMA node1 CPU(s):                    32-63,96-127
+Vulnerability Gather data sampling:   Not affected
+Vulnerability Itlb multihit:          Not affected
+Vulnerability L1tf:                   Not affected
+Vulnerability Mds:                    Not affected
+Vulnerability Meltdown:               Not affected
+Vulnerability Mmio stale data:        Not affected
+Vulnerability Reg file data sampling: Not affected
+Vulnerability Retbleed:               Mitigation; untrained return thunk; SMT enabled with STIBP protection
+Vulnerability Spec rstack overflow:   Mitigation; safe RET
+Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl and seccomp
+Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
+Vulnerability Spectre v2:             Mitigation; Retpolines; IBPB conditional; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
+Vulnerability Srbds:                  Not affected
+Vulnerability Tsx async abort:        Not affected
+
+Versions of relevant libraries:
+[pip3] numpy==1.26.3
+[pip3] torch==2.0.1+cu118
+[pip3] torchvision==0.15.2+cu118
+[conda] numpy                     1.26.3                   pypi_0    pypi
+[conda] torch                     2.0.1+cu118              pypi_0    pypi
+[conda] torchvision               0.15.2+cu118             pypi_0    pypi
+        Pillow (10.2.0)
+
+Loading trainer: BiomedCoOp_BiomedCLIP
+Loading dataset: LungColon
+Reading split from /data/t_kol/BiomedCoOp/DATA/LungColon/split_LungColon.json
+Loading preprocessed few-shot data from /data/t_kol/BiomedCoOp/DATA/LungColon/split_fewshot/shot_4-seed_3.pkl
+Building transform_train
++ random resized crop (size=(224, 224))
++ to torch tensor of range [0, 1]
++ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
+Building transform_test
++ resize the smaller edge to 224
++ 224x224 center crop
++ to torch tensor of range [0, 1]
++ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
+***** Dataset statistics *****
+  Dataset: LungColon
+  # classes: 5
+  # train_x: 20
+  # val: 20
+  # test: 7,500
+Loading BiomedCLIP (backbone: ViT-B/16)
+Building custom CLIP
+Initial text context: "a photo of a"
+Number of context words (tokens) for Language prompting: 4
+Turning off gradients in both the image and the text encoder
+Parameters to be updated: {'prompt_learner.ctx'}
+Parameters count: 1
+Loading evaluator: Classification
+Trainer built successfully.
+No checkpoint found, train from scratch
+Initializing summary writer for tensorboard with log_dir=output_reproduce/lungcolon/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/tensorboard
+epoch [1/100][1/5]	time 0.704 (0.704)	data 0.382 (0.382)	eta 0:05:51	loss 1.9655 (1.9655)	acc 50.0000 (50.0000)	lr 1.000000e-05
+epoch [1/100][2/5]	time 0.072 (0.388)	data 0.003 (0.193)	eta 0:03:13	loss 2.1633 (2.0644)	acc 50.0000 (50.0000)	lr 1.000000e-05
+epoch [1/100][3/5]	time 0.078 (0.285)	data 0.006 (0.130)	eta 0:02:21	loss 1.2879 (1.8056)	acc 50.0000 (50.0000)	lr 1.000000e-05
+epoch [1/100][4/5]	time 0.071 (0.231)	data 0.001 (0.098)	eta 0:01:54	loss 1.3875 (1.7011)	acc 50.0000 (50.0000)	lr 1.000000e-05
+epoch [1/100][5/5]	time 0.070 (0.199)	data 0.001 (0.079)	eta 0:01:38	loss 4.2097 (2.2028)	acc 0.0000 (40.0000)	lr 2.500000e-03
+epoch [2/100][1/5]	time 0.628 (0.628)	data 0.555 (0.555)	eta 0:05:10	loss 3.0093 (3.0093)	acc 0.0000 (0.0000)	lr 2.500000e-03
+epoch [2/100][2/5]	time 0.074 (0.351)	data 0.005 (0.280)	eta 0:02:52	loss 1.8314 (2.4203)	acc 50.0000 (25.0000)	lr 2.500000e-03
+epoch [2/100][3/5]	time 0.070 (0.257)	data 0.001 (0.187)	eta 0:02:06	loss 1.8030 (2.2145)	acc 50.0000 (33.3333)	lr 2.500000e-03
+epoch [2/100][4/5]	time 0.070 (0.210)	data 0.001 (0.141)	eta 0:01:43	loss 0.3909 (1.7586)	acc 75.0000 (43.7500)	lr 2.500000e-03
+epoch [2/100][5/5]	time 0.070 (0.182)	data 0.001 (0.113)	eta 0:01:29	loss 0.4476 (1.4964)	acc 75.0000 (50.0000)	lr 2.499383e-03
+epoch [3/100][1/5]	time 0.652 (0.652)	data 0.579 (0.579)	eta 0:05:18	loss 1.3157 (1.3157)	acc 25.0000 (25.0000)	lr 2.499383e-03
+epoch [3/100][2/5]	time 0.072 (0.362)	data 0.003 (0.291)	eta 0:02:56	loss 1.4768 (1.3962)	acc 25.0000 (25.0000)	lr 2.499383e-03
+epoch [3/100][3/5]	time 0.073 (0.266)	data 0.003 (0.195)	eta 0:02:09	loss 0.1304 (0.9743)	acc 100.0000 (50.0000)	lr 2.499383e-03
+epoch [3/100][4/5]	time 0.073 (0.217)	data 0.004 (0.147)	eta 0:01:45	loss 0.6171 (0.8850)	acc 75.0000 (56.2500)	lr 2.499383e-03
+epoch [3/100][5/5]	time 0.071 (0.188)	data 0.001 (0.118)	eta 0:01:31	loss 0.9772 (0.9034)	acc 50.0000 (55.0000)	lr 2.497533e-03
+epoch [4/100][1/5]	time 0.598 (0.598)	data 0.525 (0.525)	eta 0:04:49	loss 0.8277 (0.8277)	acc 50.0000 (50.0000)	lr 2.497533e-03
+epoch [4/100][2/5]	time 0.070 (0.334)	data 0.001 (0.263)	eta 0:02:41	loss 0.5762 (0.7020)	acc 75.0000 (62.5000)	lr 2.497533e-03
+epoch [4/100][3/5]	time 0.074 (0.247)	data 0.003 (0.176)	eta 0:01:59	loss 1.1787 (0.8609)	acc 50.0000 (58.3333)	lr 2.497533e-03
+epoch [4/100][4/5]	time 0.074 (0.204)	data 0.004 (0.133)	eta 0:01:38	loss 0.6440 (0.8067)	acc 50.0000 (56.2500)	lr 2.497533e-03
+epoch [4/100][5/5]	time 0.070 (0.177)	data 0.001 (0.107)	eta 0:01:24	loss 0.5386 (0.7530)	acc 75.0000 (60.0000)	lr 2.494452e-03
+epoch [5/100][1/5]	time 0.632 (0.632)	data 0.555 (0.555)	eta 0:05:02	loss 0.4417 (0.4417)	acc 75.0000 (75.0000)	lr 2.494452e-03
+epoch [5/100][2/5]	time 0.071 (0.351)	data 0.001 (0.278)	eta 0:02:47	loss 0.4348 (0.4383)	acc 75.0000 (75.0000)	lr 2.494452e-03
+epoch [5/100][3/5]	time 0.073 (0.258)	data 0.003 (0.186)	eta 0:02:03	loss 0.4555 (0.4440)	acc 75.0000 (75.0000)	lr 2.494452e-03
+epoch [5/100][4/5]	time 0.071 (0.212)	data 0.001 (0.140)	eta 0:01:40	loss 0.5039 (0.4590)	acc 75.0000 (75.0000)	lr 2.494452e-03
+epoch [5/100][5/5]	time 0.071 (0.183)	data 0.001 (0.112)	eta 0:01:27	loss 1.0404 (0.5753)	acc 50.0000 (70.0000)	lr 2.490143e-03
+epoch [6/100][1/5]	time 0.560 (0.560)	data 0.487 (0.487)	eta 0:04:25	loss 0.6440 (0.6440)	acc 50.0000 (50.0000)	lr 2.490143e-03
+epoch [6/100][2/5]	time 0.074 (0.317)	data 0.005 (0.246)	eta 0:02:29	loss 0.7307 (0.6874)	acc 75.0000 (62.5000)	lr 2.490143e-03
+epoch [6/100][3/5]	time 0.070 (0.234)	data 0.001 (0.164)	eta 0:01:50	loss 1.4086 (0.9278)	acc 50.0000 (58.3333)	lr 2.490143e-03
+epoch [6/100][4/5]	time 0.069 (0.193)	data 0.001 (0.123)	eta 0:01:31	loss 2.4698 (1.3133)	acc 0.0000 (43.7500)	lr 2.490143e-03
+epoch [6/100][5/5]	time 0.070 (0.169)	data 0.001 (0.099)	eta 0:01:19	loss 0.2012 (1.0909)	acc 100.0000 (55.0000)	lr 2.484610e-03
+epoch [7/100][1/5]	time 0.567 (0.567)	data 0.494 (0.494)	eta 0:04:25	loss 0.4404 (0.4404)	acc 100.0000 (100.0000)	lr 2.484610e-03
+epoch [7/100][2/5]	time 0.077 (0.322)	data 0.004 (0.249)	eta 0:02:30	loss 1.3666 (0.9035)	acc 25.0000 (62.5000)	lr 2.484610e-03
+epoch [7/100][3/5]	time 0.072 (0.239)	data 0.003 (0.167)	eta 0:01:51	loss 0.5825 (0.7965)	acc 75.0000 (66.6667)	lr 2.484610e-03
+epoch [7/100][4/5]	time 0.070 (0.197)	data 0.001 (0.126)	eta 0:01:31	loss 0.5553 (0.7362)	acc 75.0000 (68.7500)	lr 2.484610e-03
+epoch [7/100][5/5]	time 0.070 (0.171)	data 0.001 (0.101)	eta 0:01:19	loss 0.9677 (0.7825)	acc 50.0000 (65.0000)	lr 2.477859e-03
+epoch [8/100][1/5]	time 0.562 (0.562)	data 0.488 (0.488)	eta 0:04:20	loss 0.6405 (0.6405)	acc 75.0000 (75.0000)	lr 2.477859e-03
+epoch [8/100][2/5]	time 0.071 (0.317)	data 0.001 (0.245)	eta 0:02:26	loss 1.7466 (1.1936)	acc 25.0000 (50.0000)	lr 2.477859e-03
+epoch [8/100][3/5]	time 0.070 (0.235)	data 0.001 (0.163)	eta 0:01:48	loss 2.2723 (1.5532)	acc 50.0000 (50.0000)	lr 2.477859e-03
+epoch [8/100][4/5]	time 0.074 (0.194)	data 0.004 (0.124)	eta 0:01:29	loss 0.0169 (1.1691)	acc 100.0000 (62.5000)	lr 2.477859e-03
+epoch [8/100][5/5]	time 0.070 (0.170)	data 0.001 (0.099)	eta 0:01:17	loss 0.4972 (1.0347)	acc 75.0000 (65.0000)	lr 2.469896e-03
+epoch [9/100][1/5]	time 0.525 (0.525)	data 0.452 (0.452)	eta 0:04:01	loss 0.8488 (0.8488)	acc 50.0000 (50.0000)	lr 2.469896e-03
+epoch [9/100][2/5]	time 0.072 (0.299)	data 0.003 (0.228)	eta 0:02:16	loss 0.5198 (0.6843)	acc 75.0000 (62.5000)	lr 2.469896e-03
+epoch [9/100][3/5]	time 0.072 (0.223)	data 0.003 (0.153)	eta 0:01:41	loss 0.2489 (0.5392)	acc 100.0000 (75.0000)	lr 2.469896e-03
+epoch [9/100][4/5]	time 0.073 (0.186)	data 0.004 (0.115)	eta 0:01:24	loss 1.1001 (0.6794)	acc 50.0000 (68.7500)	lr 2.469896e-03
+epoch [9/100][5/5]	time 0.072 (0.163)	data 0.001 (0.093)	eta 0:01:14	loss 0.1723 (0.5780)	acc 100.0000 (75.0000)	lr 2.460729e-03
+epoch [10/100][1/5]	time 0.583 (0.583)	data 0.506 (0.506)	eta 0:04:24	loss 0.6351 (0.6351)	acc 50.0000 (50.0000)	lr 2.460729e-03
+epoch [10/100][2/5]	time 0.070 (0.327)	data 0.001 (0.253)	eta 0:02:28	loss 0.9306 (0.7829)	acc 50.0000 (50.0000)	lr 2.460729e-03
+epoch [10/100][3/5]	time 0.073 (0.242)	data 0.003 (0.170)	eta 0:01:49	loss 0.7334 (0.7664)	acc 75.0000 (58.3333)	lr 2.460729e-03
+epoch [10/100][4/5]	time 0.070 (0.199)	data 0.001 (0.128)	eta 0:01:29	loss 0.0448 (0.5860)	acc 100.0000 (68.7500)	lr 2.460729e-03
+epoch [10/100][5/5]	time 0.070 (0.173)	data 0.001 (0.102)	eta 0:01:17	loss 0.4007 (0.5489)	acc 100.0000 (75.0000)	lr 2.450367e-03
+epoch [11/100][1/5]	time 0.583 (0.583)	data 0.509 (0.509)	eta 0:04:21	loss 0.6481 (0.6481)	acc 75.0000 (75.0000)	lr 2.450367e-03
+epoch [11/100][2/5]	time 0.071 (0.327)	data 0.001 (0.255)	eta 0:02:26	loss 0.2148 (0.4315)	acc 100.0000 (87.5000)	lr 2.450367e-03
+epoch [11/100][3/5]	time 0.072 (0.242)	data 0.003 (0.171)	eta 0:01:48	loss 0.3020 (0.3883)	acc 75.0000 (83.3333)	lr 2.450367e-03
+epoch [11/100][4/5]	time 0.070 (0.199)	data 0.001 (0.129)	eta 0:01:28	loss 0.8868 (0.5129)	acc 25.0000 (68.7500)	lr 2.450367e-03
+epoch [11/100][5/5]	time 0.070 (0.173)	data 0.001 (0.103)	eta 0:01:17	loss 0.5330 (0.5169)	acc 75.0000 (70.0000)	lr 2.438821e-03
+epoch [12/100][1/5]	time 0.568 (0.568)	data 0.495 (0.495)	eta 0:04:12	loss 1.6014 (1.6014)	acc 50.0000 (50.0000)	lr 2.438821e-03
+epoch [12/100][2/5]	time 0.075 (0.322)	data 0.005 (0.250)	eta 0:02:22	loss 0.4448 (1.0231)	acc 75.0000 (62.5000)	lr 2.438821e-03
+epoch [12/100][3/5]	time 0.071 (0.238)	data 0.001 (0.167)	eta 0:01:45	loss 0.6971 (0.9144)	acc 75.0000 (66.6667)	lr 2.438821e-03
+epoch [12/100][4/5]	time 0.073 (0.197)	data 0.001 (0.126)	eta 0:01:26	loss 0.6833 (0.8567)	acc 100.0000 (75.0000)	lr 2.438821e-03
+epoch [12/100][5/5]	time 0.073 (0.172)	data 0.003 (0.101)	eta 0:01:15	loss 0.1073 (0.7068)	acc 100.0000 (80.0000)	lr 2.426101e-03
+epoch [13/100][1/5]	time 0.555 (0.555)	data 0.476 (0.476)	eta 0:04:03	loss 0.3794 (0.3794)	acc 75.0000 (75.0000)	lr 2.426101e-03
+epoch [13/100][2/5]	time 0.071 (0.313)	data 0.001 (0.239)	eta 0:02:17	loss 0.6891 (0.5342)	acc 75.0000 (75.0000)	lr 2.426101e-03
+epoch [13/100][3/5]	time 0.070 (0.232)	data 0.001 (0.159)	eta 0:01:41	loss 0.7911 (0.6199)	acc 75.0000 (75.0000)	lr 2.426101e-03
+epoch [13/100][4/5]	time 0.071 (0.192)	data 0.001 (0.120)	eta 0:01:23	loss 0.4481 (0.5769)	acc 100.0000 (81.2500)	lr 2.426101e-03
+epoch [13/100][5/5]	time 0.073 (0.168)	data 0.003 (0.096)	eta 0:01:13	loss 0.9439 (0.6503)	acc 75.0000 (80.0000)	lr 2.412221e-03
+epoch [14/100][1/5]	time 0.554 (0.554)	data 0.480 (0.480)	eta 0:04:00	loss 1.0653 (1.0653)	acc 75.0000 (75.0000)	lr 2.412221e-03
+epoch [14/100][2/5]	time 0.073 (0.313)	data 0.004 (0.242)	eta 0:02:15	loss 0.1668 (0.6161)	acc 100.0000 (87.5000)	lr 2.412221e-03
+epoch [14/100][3/5]	time 0.070 (0.232)	data 0.001 (0.162)	eta 0:01:40	loss 0.2175 (0.4832)	acc 100.0000 (91.6667)	lr 2.412221e-03
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+epoch [100/100][1/5]	time 0.570 (0.570)	data 0.492 (0.492)	eta 0:00:02	loss 0.3255 (0.3255)	acc 100.0000 (100.0000)	lr 2.466589e-06
+epoch [100/100][2/5]	time 0.070 (0.320)	data 0.001 (0.247)	eta 0:00:00	loss 0.2800 (0.3028)	acc 100.0000 (100.0000)	lr 2.466589e-06
+epoch [100/100][3/5]	time 0.072 (0.237)	data 0.002 (0.165)	eta 0:00:00	loss 0.5466 (0.3840)	acc 75.0000 (91.6667)	lr 2.466589e-06
+epoch [100/100][4/5]	time 0.070 (0.196)	data 0.001 (0.124)	eta 0:00:00	loss 0.2411 (0.3483)	acc 100.0000 (93.7500)	lr 2.466589e-06
+epoch [100/100][5/5]	time 0.072 (0.171)	data 0.003 (0.100)	eta 0:00:00	loss 0.3319 (0.3450)	acc 100.0000 (95.0000)	lr 6.167995e-07
+Checkpoint saved to "output_reproduce/lungcolon/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/prompt_learner/model.pth.tar-100"
+Finished training
+Do evaluation on test set
+=> result
+* total: 7,500
+* correct: 6,487
+* accuracy: 86.49%
+* error: 13.51%
+* macro_f1: 86.25%
+Elapsed: 0:01:57

few_shot/lungcolon/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/prompt_learner/checkpoint

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few_shot/lungcolon/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/prompt_learner/model.pth.tar-100

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+size 1132531909

few_shot/lungcolon/shots_4/BiomedCoOp_BiomedCLIP/nctx4_cscFalse_ctpend/seed3/tensorboard/events.out.tfevents.1742385480.impactlab-server.3091224.0

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