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medimageinsight/config.yaml

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+##################
+# Trainer settings
+##################
+
+
+TASK: UniCLTask
+
+NAME: 'Example Eval Configuration'
+SAVE_TIMER_LOG: true
+
+# TUTORIAL STEP 1: CHOOSE SAVE DIR
+SAVE_DIR: ''
+LOG_EVERY: 10
+LOGLEVEL_OVERRIDE: INFO
+LOG_GPU_MEM: true
+RESUME: False
+RESET_DATA_LOADER: false
+
+FP16: true
+ZERO_STAGE: 0
+DEEPSPEED: false
+# ZERO_STAGE: 1
+AMP: PYTORCH
+# USE_APEX_DDP: false
+# USE_APEX_AMP: false
+# USE_HIT: false
+
+FIND_UNUSED_PARAMETERS: false
+
+SAVE_PER_OPTIM_STEPS: 500
+EVAL_PER_OPTIM_STEPS: 250
+EVAL_AT_START: False
+# SAVE_PER_UPDATE_NUM: -1
+# EVAL_PER_UPDATE_NUM: 0 # 0: do evaluation when saving checkpoint, -1: don't do evaluation
+
+NO_AUTO_LR_SCALING: true
+GRAD_CLIPPING: 1.0 #0.07
+
+SET_SAMPLER_EPOCH: true
+
+DONT_LOAD_MODEL: true
+
+user_dir: "./MainzVision" # lower case due to it is used in mainz as such
+
+##################
+# Task settings
+##################
+
+
+
+VERBOSE: true
+WORKERS: 6
+PIN_MEMORY: true
+IMAGE_ENCODER:
+  NAME: davit_v1
+  NUM_CLASSES: 0
+  #IMAGE_SIZE: [384, 384]
+  IMAGE_SIZE: [480, 480]
+  LOAD_PRETRAINED: true
+  PRETRAINED: ''
+  PRETRAINED_LAYERS: '*'
+  IMAGE_MEAN: [0.485, 0.456, 0.406]
+  IMAGE_STD: [0.229, 0.224, 0.225]
+  SPEC:
+    DROP_RATE: 0.1
+    DROP_PATH_RATE: 0.2
+    PATCH_SIZE: [7, 3, 3, 3]
+    PATCH_STRIDE: [4, 2, 2, 2]
+    PATCH_PADDING: [3, 1, 1, 1]
+    PATCH_PRENORM: [false, true, true, true]
+    DIM_EMBED: [256, 512, 1024, 2048]
+    NUM_HEADS: [8, 16, 32, 64]
+    NUM_GROUPS: [8, 16, 32, 64]
+    DEPTHS: [1, 1, 9, 1]
+    WINDOW_SIZE: 12
+    ENABLE_CHECKPOINT: true
+
+LANG_ENCODER:
+  NAME: transformer
+  LOAD_PRETRAINED: false
+  PRETRAINED: ''
+  PRETRAINED_LAYERS: '*'
+  TOKENIZER: clip
+  CONTEXT_LENGTH: 77
+  WIDTH: 1024
+  HEADS: 16
+  LAYERS: 16
+  AUTOGRESSIVE: false
+
+UNICL_MODEL:
+  DIM_PROJECTION: 1024
+  GATHER_TENSORS: true
+  LOAD_PRETRAINED: true
+
+  # TUTORIAL STEP 2: CHOOSE MODEL PATH
+  PRETRAINED: ''
+
+  PRETRAINED_LAYERS: '*'
+
+AUG:
+  MIXUP_PROB: 0.0
+  MIXUP: 0.8
+  MIXCUT: 1.0
+  MIXCUT_MINMAX: []
+  MIXUP_SWITCH_PROB: 0.5
+  MIXUP_MODE: 'batch'
+  SCALE: [0.8, 1.0]
+  RATIO: [0.75, 1.3333333]
+  INTERPOLATION: 'bicubic'
+  TORCHVISION_AUG:
+    AUTO_AUGMENT: ta_wide
+    RE_PROB: 0.25
+    HFLIP: 0.0
+    VFLIP: 0.0
+
+LOSS:
+  LOSS: UniCL
+DATASET:
+  DATASET: 'image_text_pairs_v2'
+  TEXT_FORMAT: 'json'
+  ROOT: ''
+  TRAIN_SET: 'mimic_cxr_v2-chestxray14-chexpertv4-irma2009_v2-rsnaboneage-mura-bingmedicalfewshot'
+  DATA_FORMAT: 'tsv'
+  SAMPLER: 'default'
+  LOADER: 'default'
+  TOKEN_FILE: ''
+  #PROMPT_ENGINEERING: False
+  #SAMPLER: 'chunk'
+  #LOADER: 'azcopy'
+  #TOKEN_FILE: 'cliptrainingpairs.txt'
+  #TEST_SET: 'MarsAtrain'
+
+
+# TUTORIAL STEP 3: CHOOSE ALL BELOW EVAL PATHS (THESE ARE ALL OPTIONAL EXTRA EVALS)
+# Note how one eval is ZIP format and the other is TSV format.
+
+
+
+
+EVALDATASET_LTCXR_S100_N100_TEXT_CLASSIFIER:
+  TEXT_FORMAT: json
+  FORMAT: 'zip'
+  SPLIT: 'NIH-CXR-LT'
+  ZIP_FILE: ''
+  ZIP_MAP_FILE: ''
+  LABEL_FILE: ''
+  IMAGE_TSV: ''
+  TEXT_TSV: ''
+  CWEIGHT_FILE: ''
+  ZS_MODE: 2
+  ZS_WEIGHT: 1.0
+  KNN: 100
+#  CLASSIFICATION_SETS: ['NIH-CXR-LT']
+#  NUM_CLASSES: [20]
+
+
+
+
+# TUTORIAL STEP 4: SET THE DEFAULT ZEROSHOT EVAL (THIS IS THE MANDATORY EVAL)
+
+ZEROSHOT_EVAL_DATASET:
+  FORMAT: 'zip'
+  SPLIT: 'NIH-CXR-LT'
+  ZIP_FILE: ''
+  ZIP_MAP_FILE: ''
+  LABEL_FILE: ''
+
+
+
+EVALUATION_SPLITS: ['cls-zeroshot-eval']
+TEST:
+  BATCH_SIZE_PER_GPU: 8
+  MODEL_FILE: ''
+  CENTER_CROP: false
+TRAIN:
+  BATCH_SIZE_TOTAL: 1024
+  BATCH_SIZE_PER_GPU: 16
+
+  SHUFFLE: true
+
+WEIGHT_SMOOTHING:
+  decay: 0.999
+  use_cpu: False
+  eval_smoothed_weight: True
+
+START_LEARNING_RATE: 0.00001
+# MAX_NUM_EPOCHS: 2
+MAX_NUM_EPOCHS: 100
+OPTIMIZER: AdamW # adam
+OPTIMIZER_PARAMS:
+  weight_decay: 0.2 #0.1
+CUSTOMIZED_PARAMS_CONF:
+  NO_WEIGHT_DECAY_MODULES: ['dw', 'norm']
+  WEIGHT_DECAY_PATTERNS:
+    "\\.bias$": 0.0
+    "logit_scale": 0.0
+    "positional_embedding": 0.0
+    "token_embedding": 0.0
+
+
+
+LR_SCHEDULER: TimmScheduler
+LR_SCHEDULER_PARAMS:
+  sched: cosine
+  warmup_steps: 5
+  warmup_lr: 0.000000001
+  min_lr: 0.000000001
+
+# GRADIENT_ACCUMULATE_STEP will be updated by:
+# BATCH_SIZE_TOTAL // (BATCH_SIZE_PER_GPU * world_size)
+GRADIENT_ACCUMULATE_STEP: -1

medimageinsight/language_model/clip_tokenizer_4.16.2/special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<|startoftext|>",
+    "single_word": false,
+    "lstrip": false,
+    "rstrip": false,
+    "normalized": true,
+    "special": false
+  },
+  "eos_token": {
+    "content": "<|endoftext|>",
+    "single_word": false,
+    "lstrip": false,
+    "rstrip": false,
+    "normalized": true,
+    "special": false
+  },
+  "unk_token": {
+    "content": "<|endoftext|>",
+    "single_word": false,
+    "lstrip": false,
+    "rstrip": false,
+    "normalized": true,
+    "special": false
+  },
+  "pad_token": "<|endoftext|>"
+}

medimageinsight/language_model/clip_tokenizer_4.16.2/tokenizer_config.json

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+{
+  "errors": "replace",
+  "unk_token": {
+    "content": "<|endoftext|>",
+    "single_word": false,
+    "lstrip": false,
+    "rstrip": false,
+    "normalized": true,
+    "special": false,
+    "__type": "AddedToken"
+  },
+  "bos_token": {
+    "content": "<|startoftext|>",
+    "single_word": false,
+    "lstrip": false,
+    "rstrip": false,
+    "normalized": true,
+    "special": false,
+    "__type": "AddedToken"
+  },
+  "eos_token": {
+    "content": "<|endoftext|>",
+    "single_word": false,
+    "lstrip": false,
+    "rstrip": false,
+    "normalized": true,
+    "special": false,
+    "__type": "AddedToken"
+  },
+  "pad_token": "<|endoftext|>",
+  "add_prefix_space": false,
+  "do_lower_case": true,
+  "name_or_path": "openai/clip-vit-base-patch32",
+  "model_max_length": 77,
+  "special_tokens_map_file": "/home/ncodella/.cache/huggingface/transformers/18a566598f286c9139f88160c99f84eec492a26bd22738fa9cb44d5b7e0a5c76.cce1206abbad28826f000510f22f354e53e66a97f7c23745a7dfe27609cc07f5",
+  "tokenizer_file": "/home/ncodella/.cache/huggingface/transformers/7811def0c53be25ba790cb67ac785669b508a8d1cf8c912b8ac046c5f08aee68.20428ea8b6821af2719b760af844a371643ff49f255c73285f6ea448e15597fe",
+  "tokenizer_class": "CLIPTokenizer"
+}

medimageinsight/vision_model/medimageinsigt-v1.0.0-001.pt

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+size 2464060700