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_BASE_: "base_model_bert_l12_h192.yaml"
SHARED_TARGETS:
-
NAME: 'ImageNet1k'
SHARED_TARGETS_CFG:
FILE_PATH: 'open_source_dataset/imagenet_class_name_CLIP_with_endoftext.pkl'
DISTRIBUTED: True
# -
# NAME: 'Vocab_Word'
# SHARED_TARGETS_CFG:
# FILE_PATH: 'open_source_dataset/vocabulary_CLIP_with_endoftext.pkl'
# DISTRIBUTED: True
TASKS:
-
NAME: imagenet
DATASETS:
TRAIN: 'ImageNetDataset'
VAL: 'ImageNetDataset'
TASK_TYPE: 'image_classification'
DATASET_NAME: 'ImageNet1k'
TARGET_SET: ['ImageNet1k']
DATALOADER:
TRAIN_BATCH_SIZE: 4
TEST_BATCH_SIZE: 4
NUM_WORKERS: 4
FEATS_FOLDER: 'open_source_dataset/imagenet'
S3_PATH: 'cluster2:s3://imagenet'
ANNO_FOLDER: 'open_source_dataset/imagenet/meta'
SAMPLING_WEIGHT: 1.0
CLASS_NAME_FILE: 'open_source_dataset/imagenet_class_name.pkl'
MIXUP: 0.8
CUTMIX: 1.0
MIXUP_PROB: 1.0
MIXUP_SWITCH_PROB: 0.5
MIXUP_MODE: 'batch'
MIXUP_LABEL_SMOOTHING: 0.1
MODEL:
MAX_SEQ_LEN: -1
LABELS_NUM: 1000
TEMP_NAME: logit_scale_img_cls
LOSSES:
NAMES: ['SoftTargetCrossEntropy', 'Accuracy']
LOSS_WEIGHT: 1.0
REDUCTION: 'mean'
# LOSS_FP32: True
INFERENCE:
NAME: 'ImageNetEvaler'
ID_KEY: 'image_id'
VALUE: 'cls_logits'
VAL_ANNFILE: 'open_source_dataset/imagenet/meta/val.txt'
TEST_ANNFILE: ''
GENERATION_MODE: False
ENGINE:
NAME: 'UnifiedTrainer'
MODEL:
META_ARCHITECTURE: 'MultiTaskTransformerEncoder'
ENCODER: 'UnifiedBertEncoder'
IN_TUNING: True # use IN1k instead of 22k
SHARE_LAYERNORM: True
BERT:
NORMALIZE_DECISION: "BERTPre"
DROP_PATH_PROB: 0.0
DROP_PATH_PROB_FIXED: True
UNIFY_QKV: True
OLD_CHECKPONT: True
MODEL_EMA: False
MODEL_EMA_DECAY: 0.9999
MAEParamsInit: True
POSEMBEDFIX: True
IMG_INPUT_SIZE: 224
PATCH_SIZE: 16
# POSEMBED_SCALE: !!python/object/apply:eval ["160/224"]
# CHECKPOINT_FILETER: False
LAYER_SCALE: True
LAYER_SCALE_INIT: 1e-3
DATALOADER:
USE_WEIGHTED_SAMPLER: True
UNIFIED_DATASET: True
NUM_WORKERS: 16
PADDING_TO_MAX: False # True for debugging or token moe with distributed moe
####################################### Optimizer #######################################
SOLVER:
NAME: 'Adam'
TORCH_OPTIMIZER: True
PARAMS_SEPERATE: True
# PARAMS_GROUP: True
# EPOCH: 1
MAX_ITER: 150000
CHECKPOINT_PERIOD: 5000
EVAL_PERIOD: 500000
BASE_LR: 0.001
BIAS_LR_FACTOR: 1.0
WEIGHT_DECAY: 0.05
WEIGHT_DECAY_NORM: 0.0
WEIGHT_DECAY_BIAS: 0.0
WEIGHT_DECAY_EMBEDDING: 0.0
MOMENTUM: 0.9
DAMPENING: 0.0
NESTEROV: 0.0
BETAS: [0.9, 0.95]
EPS: 1e-6
GRAD_CLIP: 0.1
GRAD_CLIP_TYPE: 'norm'
ACCUM_ITER: 0
AMP_FP16: True
APEX_FP16: False # dangerous
WRITE_PERIOD: 50
MIN_LOSS_SCLE: 2048.0
# BF16: False # True
# ZEROSTAGE: 2
LOSS_SCALE_WINDOW: 200
####################################### lr scheduler #######################################
LR_SCHEDULER:
NAME: 'WarmupCosine'
WARMUP: 5000
MIN_LR: 0.000001
####################################### evaluation #######################################
INFERENCE:
VOCAB: 'CLIP'
ITER_BASED: True
find_unused_parameters: true
# ENCODERS:
# -
# NAME: VisualEncoder
# TYPE: VisualEncoder
# DROP_PATH_PROB: 0.0
# HIDDEN_SIZE: 192
# HIDDEN_DROPOUT_PROB: 0.
# HIDDEN_ACT: "gelu"
# NUM_ATTENTION_HEADS: 3
# INTERMEDIATE_SIZE: 768
# INTERMEDIATE_DROP: 0.
# FFN_DROPOUT_PROB: 0.
# ATTENTION_PROBS_DROPOUT_PROB: 0.
# NUM_HIDDEN_LAYERS: 6
# NUM_GENERATION_LAYERS: 0
# DROP_PATH_PROB_FIXED: True
# -
# NAME: TextEncoder
# TYPE: TextEncoder
# DROP_PATH_PROB: 0.0
# HIDDEN_SIZE: 192
# HIDDEN_DROPOUT_PROB: 0.
# HIDDEN_ACT: "gelu"
# NUM_ATTENTION_HEADS: 3
# INTERMEDIATE_SIZE: 768
# INTERMEDIATE_DROP: 0.
# FFN_DROPOUT_PROB: 0.
# ATTENTION_PROBS_DROPOUT_PROB: 0.
# NUM_HIDDEN_LAYERS: 6
# NUM_GENERATION_LAYERS: 0
# DROP_PATH_PROB_FIXED: True
MOE:
MOE: True
MOE_TYPE: 'attribute'
TAG_Transform: True
ATTRIBUTE_LENGTH: 8
EP_WORLD_SIZE: 1 # tag moe only
NUM_EXPERTS: 8
TOP_K: 2
CAPACITY_FACTOR: 3.0
EVAL_MIN_CAPACITY: 4.0
MIN_CAPACITY: 4
NOISY_GATE_POLICY: 'vmoe'
MOE_PARAM_GROUP: True
MOE_EXPERT_TYPE: 'FFN,SA'
SA_LINEAR_OUT_MOE: True
MOE_EXPERT_LOCATION: 'all' # 'odd'
# MOE_LAYER_START_IDX: 3
# MOE_LAYER_END_IDX: 21
# MOE_LAYER_START_IDX: 18
# MOE_LAYER_END_IDX: 12
BATCH_PRIO: True
USE_TUTEL: True
FFN_SHARE_GATE_DECISION: True
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