Adam_1 not found in checkpoint

本文解决了一个在使用预训练模型继续训练时遇到的Adam_1notfoundincheckpoint错误。通过GitHub上的解决方案,介绍了如何使用optimistic_restore函数来适配不同模型的参数,确保训练过程的顺利进行。

今天训练网上的代码,目前想基于他们训练好的代码,restore ckpt文件的参数以后,再接着训练。

但是加载完数据以后,报错为

Adam_1 not found in checkpoint

经过查找,应该是他们训练好的模型,没有存这些参数,经过查找方法,在GitHub上找到了答案,具体就是在checkpoint里找到所有的参数,和model文件里面的匹配,匹配上就用,匹配不上就算了。

def optimistic_restore(session, save_file):
	reader = tf.train.NewCheckpointReader(save_file)
	saved_shapes = reader.get_variable_to_shape_map()
	var_names = sorted([(var.name, var.name.split(':')[0]) for var in tf.global_variables()
			if var.name.split(':')[0] in saved_shapes])
	restore_vars = []
        name2var = dict(zip(map(lambda x:x.name.split(':')[0], tf.global_variables()), tf.global_variables()))
	with tf.variable_scope('', reuse=True):
		for var_name, saved_var_name in var_names:
			curr_var = name2var[saved_var_name]
			var_shape = curr_var.get_shape().as_list()
			if var_shape == saved_shapes[saved_var_name]:
				restore_vars.append(curr_var)
				saver = tf.train.Saver(restore_vars) #只加载checkpoint有参数的
				saver.restore(session, save_file)
YQS2774128819@LAPTOP-U47PLV6B MINGW64 /d/CoOp-main/CoOp (main) $ bash scripts/coop/main.sh caltech101 rn50_ep50 end 16 1 False Setting fixed seed: 1 *************** ** Arguments ** *************** backbone: config_file: configs/trainers/CoOp/rn50_ep50.yaml dataset_config_file: configs/datasets/caltech101.yaml eval_only: False head: load_epoch: None model_dir: no_train: False opts: ['TRAINER.COOP.N_CTX', '16', 'TRAINER.COOP.CSC', 'False', 'TRAINER.COOP.CLASS_TOKEN_POSITION', 'end', 'DATASET.NUM_SHOTS', '1'] output_dir: output/caltech101/CoOp/rn50_ep50_1shots/nctx16_cscFalse_ctpend/seed1 resume: root: D:/software/Git/path/to/datasets seed: 1 source_domains: None target_domains: None trainer: CoOp 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: 32 N_DOMAIN: 0 N_INS: 16 SAMPLER: RandomSampler DATASET: ALL_AS_UNLABELED: False CIFAR_C_LEVEL: 1 CIFAR_C_TYPE: NAME: Caltech101 NUM_LABELED: -1 NUM_SHOTS: 1 ROOT: D:/software/Git/path/to/datasets 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 RRCROP_SCALE: (0.08, 1.0) SIZE: (224, 224) TRANSFORMS: ('random_resized_crop', 'random_flip', 'normalize') MODEL: BACKBONE: NAME: RN50 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: 0.002 LR_SCHEDULER: cosine MAX_EPOCH: 50 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/caltech101/CoOp/rn50_ep50_1shots/nctx16_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: 5 TRAINER: CDAC: CLASS_LR_MULTI: 10 P_THRESH: 0.95 RAMPUP_COEF: 30 RAMPUP_ITRS: 1000 STRONG_TRANSFORMS: () TOPK_MATCH: 5 COCOOP: CTX_INIT: N_CTX: 16 PREC: fp16 COOP: CLASS_TOKEN_POSITION: end CSC: False CTX_INIT: N_CTX: 16 PREC: fp16 CROSSGRAD: ALPHA_D: 0.5 ALPHA_F: 0.5 EPS_D: 1.0 EPS_F: 1.0 DAEL: CONF_THRE: 0.95 STRONG_TRANSFORMS: () WEIGHT_U: 0.5 DAELDG: 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 DOMAINMIX: ALPHA: 1.0 BETA: 1.0 TYPE: crossdomain ENTMIN: LMDA: 0.001 FIXMATCH: CONF_THRE: 0.95 STRONG_TRANSFORMS: () WEIGHT_U: 1.0 M3SDA: LMDA: 0.5 N_STEP_F: 4 MCD: N_STEP_F: 4 MEANTEACHER: 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: CoOp 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+cpu Is debug build: False CUDA used to build PyTorch: Could not collect ROCM used to build PyTorch: N/A OS: Microsoft Windows 10 家庭中文版 GCC version: Could not collect Clang version: Could not collect CMake version: Could not collect Libc version: N/A Python version: 3.8.20 (default, Oct 3 2024, 15:19:54) [MSC v.1929 64 bit (AMD64)] (64-bit runtime) Python platform: Windows-10-10.0.19045-SP0 Is CUDA available: False CUDA runtime version: Could not collect CUDA_MODULE_LOADING set to: N/A GPU models and configuration: GPU 0: NVIDIA GeForce MX450 Nvidia driver version: 517.47 cuDNN version: Could not collect HIP runtime version: N/A MIOpen runtime version: N/A Is XNNPACK available: True CPU: Architecture=9 CurrentClockSpeed=2419 DeviceID=CPU0 Family=205 L2CacheSize=5120 L2CacheSpeed= Manufacturer=GenuineIntel MaxClockSpeed=2419 Name=11th Gen Intel(R) Core(TM) i5-1135G7 @ 2.40GHz ProcessorType=3 Revision= Versions of relevant libraries: [pip3] numpy==1.24.4 [pip3] torch==2.0.1 [pip3] torchaudio==2.0.2 [pip3] torchvision==0.15.2 [conda] numpy 1.24.4 pypi_0 pypi [conda] torch 2.0.1 pypi_0 pypi [conda] torchaudio 2.0.2 pypi_0 pypi [conda] torchvision 0.15.2 pypi_0 pypi Pillow (10.4.0) Loading trainer: CoOp Loading dataset: Caltech101 Reading split from D:\software\Git\path\to\datasets\caltech-101\split_zhou_Caltech101.json Loading preprocessed few-shot data from D:\software\Git\path\to\datasets\caltech-101\split_fewshot\shot_1-seed_1.pkl Building transform_train + random resized crop (size=(224, 224), scale=(0.08, 1.0)) + random flip + 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 Caltech101 # classes 100 # train_x 100 # val 100 # test 2,465 --------- ---------- Loading CLIP (backbone: RN50) Building custom CLIP Initializing a generic context Initial context: "X X X X X X X X X X X X X X X X" Number of context words (tokens): 16 Turning off gradients in both the image and the text encoder Loading evaluator: Classification No checkpoint found, train from scratch Initialize tensorboard (log_dir=output/caltech101/CoOp/rn50_ep50_1shots/nctx16_cscFalse_ctpend/seed1\tensorboard) Traceback (most recent call last): File "train.py", line 207, in <module> main(args) File "train.py", line 150, in main trainer.train() File "d:\coop-main\dassl.pytorch\dassl\engine\trainer.py", line 386, in train super().train(self.start_epoch, self.max_epoch) File "d:\coop-main\dassl.pytorch\dassl\engine\trainer.py", line 250, in train self.run_epoch() File "d:\coop-main\dassl.pytorch\dassl\engine\trainer.py", line 594, in run_epoch for self.batch_idx, batch in enumerate(self.train_loader_x): File "D:\Anaconda\envs\dassl\lib\site-packages\torch\utils\data\dataloader.py", line 633, in __next__ data = self._next_data() File "D:\Anaconda\envs\dassl\lib\site-packages\torch\utils\data\dataloader.py", line 1345, in _next_data return self._process_data(data) File "D:\Anaconda\envs\dassl\lib\site-packages\torch\utils\data\dataloader.py", line 1371, in _process_data data.reraise() File "D:\Anaconda\envs\dassl\lib\site-packages\torch\_utils.py", line 644, in reraise raise exception FileNotFoundError: Caught FileNotFoundError in DataLoader worker process 0. Original Traceback (most recent call last): File "D:\Anaconda\envs\dassl\lib\site-packages\torch\utils\data\_utils\worker.py", line 308, in _worker_loop data = fetcher.fetch(index) File "D:\Anaconda\envs\dassl\lib\site-packages\torch\utils\data\_utils\fetch.py", line 51, in fetch data = [self.dataset[idx] for idx in possibly_batched_index] File "D:\Anaconda\envs\dassl\lib\site-packages\torch\utils\data\_utils\fetch.py", line 51, in <listcomp> data = [self.dataset[idx] for idx in possibly_batched_index] File "d:\coop-main\dassl.pytorch\dassl\data\data_manager.py", line 230, in __getitem__ img0 = read_image(item.impath) File "d:\coop-main\dassl.pytorch\dassl\utils\tools.py", line 120, in read_image return Image.open(path).convert("RGB") File "D:\Anaconda\envs\dassl\lib\site-packages\PIL\Image.py", line 3431, in open fp = builtins.open(filename, "rb") FileNotFoundError: [Errno 2] No such file or directory: 'C:\\Users\\Administrator\\Desktop\\DATA\\caltech-101\\101_ObjectCategories\\umbrella\\image_0040.jpg' Setting fixed seed: 2 *************** ** Arguments ** *************** backbone: config_file: configs/trainers/CoOp/rn50_ep50.yaml dataset_config_file: configs/datasets/caltech101.yaml eval_only: False head: load_epoch: None model_dir: no_train: False opts: ['TRAINER.COOP.N_CTX', '16', 'TRAINER.COOP.CSC', 'False', 'TRAINER.COOP.CLASS_TOKEN_POSITION', 'end', 'DATASET.NUM_SHOTS', '1'] output_dir: output/caltech101/CoOp/rn50_ep50_1shots/nctx16_cscFalse_ctpend/seed2 resume: root: D:/software/Git/path/to/datasets seed: 2 source_domains: None target_domains: None trainer: CoOp 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: 32 N_DOMAIN: 0 N_INS: 16 SAMPLER: RandomSampler DATASET: ALL_AS_UNLABELED: False CIFAR_C_LEVEL: 1 CIFAR_C_TYPE: NAME: Caltech101 NUM_LABELED: -1 NUM_SHOTS: 1 ROOT: D:/software/Git/path/to/datasets 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 RRCROP_SCALE: (0.08, 1.0) SIZE: (224, 224) TRANSFORMS: ('random_resized_crop', 'random_flip', 'normalize') MODEL: BACKBONE: NAME: RN50 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: 0.002 LR_SCHEDULER: cosine MAX_EPOCH: 50 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/caltech101/CoOp/rn50_ep50_1shots/nctx16_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: 5 TRAINER: CDAC: CLASS_LR_MULTI: 10 P_THRESH: 0.95 RAMPUP_COEF: 30 RAMPUP_ITRS: 1000 STRONG_TRANSFORMS: () TOPK_MATCH: 5 COCOOP: CTX_INIT: N_CTX: 16 PREC: fp16 COOP: CLASS_TOKEN_POSITION: end CSC: False CTX_INIT: N_CTX: 16 PREC: fp16 CROSSGRAD: ALPHA_D: 0.5 ALPHA_F: 0.5 EPS_D: 1.0 EPS_F: 1.0 DAEL: CONF_THRE: 0.95 STRONG_TRANSFORMS: () WEIGHT_U: 0.5 DAELDG: 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 DOMAINMIX: ALPHA: 1.0 BETA: 1.0 TYPE: crossdomain ENTMIN: LMDA: 0.001 FIXMATCH: CONF_THRE: 0.95 STRONG_TRANSFORMS: () WEIGHT_U: 1.0 M3SDA: LMDA: 0.5 N_STEP_F: 4 MCD: N_STEP_F: 4 MEANTEACHER: 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: CoOp 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+cpu Is debug build: False CUDA used to build PyTorch: Could not collect ROCM used to build PyTorch: N/A OS: Microsoft Windows 10 家庭中文版 GCC version: Could not collect Clang version: Could not collect CMake version: Could not collect Libc version: N/A Python version: 3.8.20 (default, Oct 3 2024, 15:19:54) [MSC v.1929 64 bit (AMD64)] (64-bit runtime) Python platform: Windows-10-10.0.19045-SP0 Is CUDA available: False CUDA runtime version: Could not collect CUDA_MODULE_LOADING set to: N/A GPU models and configuration: GPU 0: NVIDIA GeForce MX450 Nvidia driver version: 517.47 cuDNN version: Could not collect HIP runtime version: N/A MIOpen runtime version: N/A Is XNNPACK available: True CPU: Architecture=9 CurrentClockSpeed=2419 DeviceID=CPU0 Family=205 L2CacheSize=5120 L2CacheSpeed= Manufacturer=GenuineIntel MaxClockSpeed=2419 Name=11th Gen Intel(R) Core(TM) i5-1135G7 @ 2.40GHz ProcessorType=3 Revision= Versions of relevant libraries: [pip3] numpy==1.24.4 [pip3] torch==2.0.1 [pip3] torchaudio==2.0.2 [pip3] torchvision==0.15.2 [conda] numpy 1.24.4 pypi_0 pypi [conda] torch 2.0.1 pypi_0 pypi [conda] torchaudio 2.0.2 pypi_0 pypi [conda] torchvision 0.15.2 pypi_0 pypi Pillow (10.4.0) Loading trainer: CoOp Loading dataset: Caltech101 Reading split from D:\software\Git\path\to\datasets\caltech-101\split_zhou_Caltech101.json Loading preprocessed few-shot data from D:\software\Git\path\to\datasets\caltech-101\split_fewshot\shot_1-seed_2.pkl Building transform_train + random resized crop (size=(224, 224), scale=(0.08, 1.0)) + random flip + 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 Caltech101 # classes 100 # train_x 100 # val 100 # test 2,465 --------- ---------- Loading CLIP (backbone: RN50) Building custom CLIP Initializing a generic context Initial context: "X X X X X X X X X X X X X X X X" Number of context words (tokens): 16 Turning off gradients in both the image and the text encoder Loading evaluator: Classification No checkpoint found, train from scratch Initialize tensorboard (log_dir=output/caltech101/CoOp/rn50_ep50_1shots/nctx16_cscFalse_ctpend/seed2\tensorboard) Traceback (most recent call last): File "train.py", line 207, in <module> main(args) File "train.py", line 150, in main trainer.train() File "d:\coop-main\dassl.pytorch\dassl\engine\trainer.py", line 386, in train super().train(self.start_epoch, self.max_epoch) File "d:\coop-main\dassl.pytorch\dassl\engine\trainer.py", line 250, in train self.run_epoch() File "d:\coop-main\dassl.pytorch\dassl\engine\trainer.py", line 594, in run_epoch for self.batch_idx, batch in enumerate(self.train_loader_x): File "D:\Anaconda\envs\dassl\lib\site-packages\torch\utils\data\dataloader.py", line 633, in __next__ data = self._next_data() File "D:\Anaconda\envs\dassl\lib\site-packages\torch\utils\data\dataloader.py", line 1345, in _next_data return self._process_data(data) File "D:\Anaconda\envs\dassl\lib\site-packages\torch\utils\data\dataloader.py", line 1371, in _process_data data.reraise() File "D:\Anaconda\envs\dassl\lib\site-packages\torch\_utils.py", line 644, in reraise raise exception FileNotFoundError: Caught FileNotFoundError in DataLoader worker process 0. Original Traceback (most recent call last): File "D:\Anaconda\envs\dassl\lib\site-packages\torch\utils\data\_utils\worker.py", line 308, in _worker_loop data = fetcher.fetch(index) File "D:\Anaconda\envs\dassl\lib\site-packages\torch\utils\data\_utils\fetch.py", line 51, in fetch data = [self.dataset[idx] for idx in possibly_batched_index] File "D:\Anaconda\envs\dassl\lib\site-packages\torch\utils\data\_utils\fetch.py", line 51, in <listcomp> data = [self.dataset[idx] for idx in possibly_batched_index] File "d:\coop-main\dassl.pytorch\dassl\data\data_manager.py", line 230, in __getitem__ img0 = read_image(item.impath) File "d:\coop-main\dassl.pytorch\dassl\utils\tools.py", line 120, in read_image return Image.open(path).convert("RGB") File "D:\Anaconda\envs\dassl\lib\site-packages\PIL\Image.py", line 3431, in open fp = builtins.open(filename, "rb") FileNotFoundError: [Errno 2] No such file or directory: 'C:\\Users\\Administrator\\Desktop\\DATA\\caltech-101\\101_ObjectCategories\\stop_sign\\image_0014.jpg' Setting fixed seed: 3 *************** ** Arguments ** *************** backbone: config_file: configs/trainers/CoOp/rn50_ep50.yaml dataset_config_file: configs/datasets/caltech101.yaml eval_only: False head: load_epoch: None model_dir: no_train: False opts: ['TRAINER.COOP.N_CTX', '16', 'TRAINER.COOP.CSC', 'False', 'TRAINER.COOP.CLASS_TOKEN_POSITION', 'end', 'DATASET.NUM_SHOTS', '1'] output_dir: output/caltech101/CoOp/rn50_ep50_1shots/nctx16_cscFalse_ctpend/seed3 resume: root: D:/software/Git/path/to/datasets seed: 3 source_domains: None target_domains: None trainer: CoOp 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: 32 N_DOMAIN: 0 N_INS: 16 SAMPLER: RandomSampler DATASET: ALL_AS_UNLABELED: False CIFAR_C_LEVEL: 1 CIFAR_C_TYPE: NAME: Caltech101 NUM_LABELED: -1 NUM_SHOTS: 1 ROOT: D:/software/Git/path/to/datasets 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 RRCROP_SCALE: (0.08, 1.0) SIZE: (224, 224) TRANSFORMS: ('random_resized_crop', 'random_flip', 'normalize') MODEL: BACKBONE: NAME: RN50 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: 0.002 LR_SCHEDULER: cosine MAX_EPOCH: 50 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/caltech101/CoOp/rn50_ep50_1shots/nctx16_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: 5 TRAINER: CDAC: CLASS_LR_MULTI: 10 P_THRESH: 0.95 RAMPUP_COEF: 30 RAMPUP_ITRS: 1000 STRONG_TRANSFORMS: () TOPK_MATCH: 5 COCOOP: CTX_INIT: N_CTX: 16 PREC: fp16 COOP: CLASS_TOKEN_POSITION: end CSC: False CTX_INIT: N_CTX: 16 PREC: fp16 CROSSGRAD: ALPHA_D: 0.5 ALPHA_F: 0.5 EPS_D: 1.0 EPS_F: 1.0 DAEL: CONF_THRE: 0.95 STRONG_TRANSFORMS: () WEIGHT_U: 0.5 DAELDG: 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 DOMAINMIX: ALPHA: 1.0 BETA: 1.0 TYPE: crossdomain ENTMIN: LMDA: 0.001 FIXMATCH: CONF_THRE: 0.95 STRONG_TRANSFORMS: () WEIGHT_U: 1.0 M3SDA: LMDA: 0.5 N_STEP_F: 4 MCD: N_STEP_F: 4 MEANTEACHER: 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: CoOp 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+cpu Is debug build: False CUDA used to build PyTorch: Could not collect ROCM used to build PyTorch: N/A OS: Microsoft Windows 10 家庭中文版 GCC version: Could not collect Clang version: Could not collect CMake version: Could not collect Libc version: N/A Python version: 3.8.20 (default, Oct 3 2024, 15:19:54) [MSC v.1929 64 bit (AMD64)] (64-bit runtime) Python platform: Windows-10-10.0.19045-SP0 Is CUDA available: False CUDA runtime version: Could not collect CUDA_MODULE_LOADING set to: N/A GPU models and configuration: GPU 0: NVIDIA GeForce MX450 Nvidia driver version: 517.47 cuDNN version: Could not collect HIP runtime version: N/A MIOpen runtime version: N/A Is XNNPACK available: True CPU: Architecture=9 CurrentClockSpeed=2419 DeviceID=CPU0 Family=205 L2CacheSize=5120 L2CacheSpeed= Manufacturer=GenuineIntel MaxClockSpeed=2419 Name=11th Gen Intel(R) Core(TM) i5-1135G7 @ 2.40GHz ProcessorType=3 Revision= Versions of relevant libraries: [pip3] numpy==1.24.4 [pip3] torch==2.0.1 [pip3] torchaudio==2.0.2 [pip3] torchvision==0.15.2 [conda] numpy 1.24.4 pypi_0 pypi [conda] torch 2.0.1 pypi_0 pypi [conda] torchaudio 2.0.2 pypi_0 pypi [conda] torchvision 0.15.2 pypi_0 pypi Pillow (10.4.0) Loading trainer: CoOp Loading dataset: Caltech101 Reading split from D:\software\Git\path\to\datasets\caltech-101\split_zhou_Caltech101.json Loading preprocessed few-shot data from D:\software\Git\path\to\datasets\caltech-101\split_fewshot\shot_1-seed_3.pkl Building transform_train + random resized crop (size=(224, 224), scale=(0.08, 1.0)) + random flip + 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 Caltech101 # classes 100 # train_x 100 # val 100 # test 2,465 --------- ---------- Loading CLIP (backbone: RN50) Building custom CLIP Initializing a generic context Initial context: "X X X X X X X X X X X X X X X X" Number of context words (tokens): 16 Turning off gradients in both the image and the text encoder Loading evaluator: Classification No checkpoint found, train from scratch Initialize tensorboard (log_dir=output/caltech101/CoOp/rn50_ep50_1shots/nctx16_cscFalse_ctpend/seed3\tensorboard) Traceback (most recent call last): File "train.py", line 207, in <module> main(args) File "train.py", line 150, in main trainer.train() File "d:\coop-main\dassl.pytorch\dassl\engine\trainer.py", line 386, in train super().train(self.start_epoch, self.max_epoch) File "d:\coop-main\dassl.pytorch\dassl\engine\trainer.py", line 250, in train self.run_epoch() File "d:\coop-main\dassl.pytorch\dassl\engine\trainer.py", line 594, in run_epoch for self.batch_idx, batch in enumerate(self.train_loader_x): File "D:\Anaconda\envs\dassl\lib\site-packages\torch\utils\data\dataloader.py", line 633, in __next__ data = self._next_data() File "D:\Anaconda\envs\dassl\lib\site-packages\torch\utils\data\dataloader.py", line 1345, in _next_data return self._process_data(data) File "D:\Anaconda\envs\dassl\lib\site-packages\torch\utils\data\dataloader.py", line 1371, in _process_data data.reraise() File "D:\Anaconda\envs\dassl\lib\site-packages\torch\_utils.py", line 644, in reraise raise exception FileNotFoundError: Caught FileNotFoundError in DataLoader worker process 0. Original Traceback (most recent call last): File "D:\Anaconda\envs\dassl\lib\site-packages\torch\utils\data\_utils\worker.py", line 308, in _worker_loop data = fetcher.fetch(index) File "D:\Anaconda\envs\dassl\lib\site-packages\torch\utils\data\_utils\fetch.py", line 51, in fetch data = [self.dataset[idx] for idx in possibly_batched_index] File "D:\Anaconda\envs\dassl\lib\site-packages\torch\utils\data\_utils\fetch.py", line 51, in <listcomp> data = [self.dataset[idx] for idx in possibly_batched_index] File "d:\coop-main\dassl.pytorch\dassl\data\data_manager.py", line 230, in __getitem__ img0 = read_image(item.impath) File "d:\coop-main\dassl.pytorch\dassl\utils\tools.py", line 120, in read_image return Image.open(path).convert("RGB") File "D:\Anaconda\envs\dassl\lib\site-packages\PIL\Image.py", line 3431, in open fp = builtins.open(filename, "rb") FileNotFoundError: [Errno 2] No such file or directory: 'C:\\Users\\Administrator\\Desktop\\DATA\\caltech-101\\101_ObjectCategories\\headphone\\image_0016.jpg' (dassl) 这是为什么
最新发布
09-17
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