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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: False
-
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: 2
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
-
NAME: mscoco_caption
DATASETS:
TRAIN: 'ImageTextPairDataset'
# VAL: 'ImageTextPairDataset'
# TEST: 'ImageTextPairDataset'
TASK_TYPE: 'image_caption'
DATASET_NAME: 'MSCOCO'
TARGET_SET: ['Vocab_Word']
DATALOADER:
TRAIN_BATCH_SIZE: 64
TEST_BATCH_SIZE: 32
NUM_WORKERS: 4
FEATS_FOLDER: 'open_source_dataset/mscoco_dataset/coco_origin'
ANNO_FOLDER: 'open_source_dataset/mscoco_dataset/new_annotations'
S3_PATH: 's3://coco/'
SEQ_PER_SAMPLE: 1
CACHE_MODE: True
CIRCULAR_CACHE_MODE: False
ZIP_MODE: False
CACHE_ORIGIN_IMAGE: False
RANDOM_CAPTION: False
AS_NUMPY_AS_POSSIBLE: False
SAMPLING_WEIGHT: 1.0
TRANSFORM: 'clip_transforms'
RANDOM_MASK: True
MODEL:
MAX_SEQ_LEN: 50
EVAL_MAX_SEQ_LEN: 21
TEMP_NAME: logit_scale_caption
LOSSES:
NAMES: ['CrossEntropy', 'Accuracy']
LOSS_WEIGHT: 0.33333
REDUCTION: 'mean'
DECODE_STRATEGY:
NAME: 'CaptionBeamSearcherV3'
BEAM_SIZE: 2
# LEN_PENALTY: 1.0
INFERENCE:
NAME: 'COCOEvaler'
VOCAB: 'CLIP'
ID_KEY: 'image_id'
VALUE: 'caption'
VAL_ANNFILE: 'open_source_dataset/mscoco_dataset/new_annotations/captions_val5k.json'
TEST_ANNFILE: 'open_source_dataset/mscoco_dataset/new_annotations/captions_test5k.json'
GENERATION_MODE: True
-
NAME: yfcc_caption
DATASETS:
TRAIN: 'ImageTextPairDataset'
TASK_TYPE: 'image_caption'
DATASET_NAME: 'YFCC'
TARGET_SET: ['Vocab_Word']
DATALOADER:
TRAIN_BATCH_SIZE: 64
TEST_BATCH_SIZE: 32
NUM_WORKERS: 2
S3_ANNO_FOLDER: 'cluster2:s3://yfcc'
ANNO_FOLDER: 'open_source_dataset/yfcc'
ANNO_FILENAME: 'yfcc100m_subset_available_untokenized.json'
FEATS_FOLDER: 'open_source_dataset/yfcc/'
S3_PATH: 'cluster2:s3://yfcc/'
SEQ_PER_SAMPLE: 1
SAMPLER: NodeDistributed
CACHE_MODE: True
CIRCULAR_CACHE_MODE: False
ZIP_MODE: False
CACHE_ORIGIN_IMAGE: False
RANDOM_CAPTION: True
AS_NUMPY_AS_POSSIBLE: False
SAMPLING_WEIGHT: 1.0
TRANSFORM: 'clip_transforms'
MODEL:
MAX_SEQ_LEN: 50
TEMP_NAME: logit_scale_caption
LOSSES:
NAMES: ['CrossEntropy', 'Accuracy']
LOSS_WEIGHT: 1.0
REDUCTION: 'mean'
INFERENCE:
VOCAB: 'CLIP'
GENERATION_MODE: False
-
NAME: cc12m_caption
DATASETS:
TRAIN: 'ImageTextPairDataset'
TASK_TYPE: 'image_caption'
DATASET_NAME: 'CC12M'
TARGET_SET: ['Vocab_Word']
DATALOADER:
TRAIN_BATCH_SIZE: 64
TEST_BATCH_SIZE: 32
NUM_WORKERS: 2
S3_ANNO_FOLDER: 's3://cc12m/'
ANNO_FOLDER: 'open_source_dataset/c12m/'
ANNO_FILENAME: 'train_available.json'
FEATS_FOLDER: 'open_source_dataset/c12m/'
S3_PATH: 's3://cc12m/'
SEQ_PER_SAMPLE: 1
SAMPLER: NodeDistributed
CACHE_MODE: True
CIRCULAR_CACHE_MODE: False
ZIP_MODE: False
CACHE_ORIGIN_IMAGE: False
RANDOM_CAPTION: False
AS_NUMPY_AS_POSSIBLE: False
SAMPLING_WEIGHT: 1.0
TRANSFORM: 'clip_transforms'
MODEL:
MAX_SEQ_LEN: 50
TEMP_NAME: logit_scale_caption
LOSSES:
NAMES: ['CrossEntropy', 'Accuracy']
LOSS_WEIGHT: 1.0
REDUCTION: 'mean'
INFERENCE:
VOCAB: 'CLIP'
GENERATION_MODE: False
-
NAME: cc3m_caption
DATASETS:
TRAIN: 'ImageTextPairDataset'
TASK_TYPE: 'image_caption'
DATASET_NAME: 'CC3M'
TARGET_SET: ['Vocab_Word']
DATALOADER:
TRAIN_BATCH_SIZE: 64
TEST_BATCH_SIZE: 32
NUM_WORKERS: 2
S3_ANNO_FOLDER: 's3://cc3m/'
ANNO_FOLDER: 'open_source_dataset/cc3m/'
ANNO_FILENAME: 'train_spacy.json'
FEATS_FOLDER: 'open_source_dataset/cc3m/'
S3_PATH: 's3://cc3m/'
SEQ_PER_SAMPLE: 1
SAMPLER: NodeDistributed
CACHE_MODE: True
CIRCULAR_CACHE_MODE: False
ZIP_MODE: False
CACHE_ORIGIN_IMAGE: False
RANDOM_CAPTION: False
AS_NUMPY_AS_POSSIBLE: False
SAMPLING_WEIGHT: 1.0
TRANSFORM: 'clip_transforms'
MODEL:
MAX_SEQ_LEN: 50
TEMP_NAME: logit_scale_caption
LOSSES:
NAMES: ['CrossEntropy', 'Accuracy']
LOSS_WEIGHT: 1.0
REDUCTION: 'mean'
INFERENCE:
VOCAB: 'CLIP'
GENERATION_MODE: False
-
NAME: sbu_caption
DATASETS:
TRAIN: 'ImageTextPairDataset'
TASK_TYPE: 'image_caption'
DATASET_NAME: 'SBU'
TARGET_SET: ['Vocab_Word']
DATALOADER:
TRAIN_BATCH_SIZE: 64
TEST_BATCH_SIZE: 32
NUM_WORKERS: 1
S3_ANNO_FOLDER: 's3://SBU/annotations'
ANNO_FOLDER: 'open_source_dataset/sbucaption/annotations'
ANNO_FILENAME: 'subcaption.json'
FEATS_FOLDER: 'open_source_dataset/sbucaption/'
S3_PATH: 's3://SBU/images'
SEQ_PER_SAMPLE: 1
SAMPLER: NodeDistributed
CACHE_MODE: True
CIRCULAR_CACHE_MODE: False
ZIP_MODE: False
CACHE_ORIGIN_IMAGE: False
RANDOM_CAPTION: False
AS_NUMPY_AS_POSSIBLE: False
SAMPLING_WEIGHT: 1.0
TRANSFORM: 'clip_transforms'
MODEL:
MAX_SEQ_LEN: 50
TEMP_NAME: logit_scale_caption
LOSSES:
NAMES: ['CrossEntropy', 'Accuracy']
LOSS_WEIGHT: 1.0
REDUCTION: 'mean'
INFERENCE:
VOCAB: 'CLIP'
GENERATION_MODE: False
-
NAME: vg_caption
DATASETS:
TRAIN: 'ImageTextPairDataset'
TASK_TYPE: 'image_caption'
DATASET_NAME: 'VG'
TARGET_SET: ['Vocab_Word']
DATALOADER:
TRAIN_BATCH_SIZE: 64
TEST_BATCH_SIZE: 32
NUM_WORKERS: 2
FEATS_FOLDER: 'open_source_dataset/visual_genome/images'
ANNO_FOLDER: 'open_source_dataset/visual_genome/annotations'
S3_PATH: 's3://visual_genome/images'
ANNO_FILENAME: 'vg_captions_128filter.json'
SEQ_PER_SAMPLE: 1
CACHE_MODE: True
CIRCULAR_CACHE_MODE: False
ZIP_MODE: False
CACHE_ORIGIN_IMAGE: False
RANDOM_CAPTION: False
AS_NUMPY_AS_POSSIBLE: False
SAMPLING_WEIGHT: 1.0
TRANSFORM: 'clip_transforms'
MODEL:
MAX_SEQ_LEN: 30
TEMP_NAME: logit_scale_caption
LOSSES:
NAMES: ['CrossEntropy', 'Accuracy']
LOSS_WEIGHT: 1.0
REDUCTION: 'mean'
INFERENCE:
VOCAB: 'CLIP'
GENERATION_MODE: True
-
NAME: mscoco_retrieve
DATASETS:
TRAIN: 'ImageTextPairDataset'
# TEST: 'ImageTextPairDataset'
TASK_TYPE: 'image_retrieval'
DATASET_NAME: 'MSCOCO'
DATALOADER:
TRAIN_BATCH_SIZE: 100
TEST_BATCH_SIZE: 32
NUM_WORKERS: 1
FEATS_FOLDER: 'open_source_dataset/mscoco_dataset/coco_origin'
ANNO_FOLDER: 'open_source_dataset/mscoco_dataset/new_annotations'
S3_PATH: 's3://coco/'
SEQ_PER_SAMPLE: 1
CACHE_MODE: True
CIRCULAR_CACHE_MODE: False
ZIP_MODE: False
CACHE_ORIGIN_IMAGE: False
RANDOM_CAPTION: False
AS_NUMPY_AS_POSSIBLE: False
SAMPLING_WEIGHT: 1.0
TRANSFORM: 'clip_transforms'
MODEL:
MAX_SEQ_LEN: 50
TEMP_NAME: logit_scale_retrieve
LOSSES:
NAMES: ['LabelSmoothingCrossEntropy', 'Accuracy']
LABELSMOOTHING: 0.1
LOSS_WEIGHT: 1.0
REDUCTION: 'mean'
INFERENCE:
VOCAB: 'CLIP'
ID_KEY: 'image_id'
VALUE: 'caption'
NAME: 'RetrievalEvaler'
VAL_ANNFILE: 'open_source_dataset/flickr30k/all_data_final_val_set0_2014.jsonline'
TEST_ANNFILE: 'open_source_dataset/flickr30k/all_data_final_test_set0_2014.jsonline'
GENERATION_MODE: False
-
NAME: yfcc_retrieve
DATASETS:
TRAIN: 'ImageTextPairDataset'
TASK_TYPE: 'image_retrieval'
DATASET_NAME: 'YFCC'
DATALOADER:
TRAIN_BATCH_SIZE: 64
TEST_BATCH_SIZE: 32
NUM_WORKERS: 2
S3_ANNO_FOLDER: 'cluster2:s3://yfcc'
ANNO_FOLDER: 'open_source_dataset/yfcc'
ANNO_FILENAME: 'yfcc100m_subset_available_untokenized.json'
FEATS_FOLDER: 'open_source_dataset/yfcc/'
S3_PATH: 'cluster2:s3://yfcc/'
SAMPLER: NodeDistributed
CACHE_MODE: True
CIRCULAR_CACHE_MODE: False
ZIP_MODE: False
CACHE_ORIGIN_IMAGE: False
RANDOM_CAPTION: True
AS_NUMPY_AS_POSSIBLE: False
SAMPLING_WEIGHT: 1.0
TRANSFORM: 'clip_transforms'
MODEL:
MAX_SEQ_LEN: 50
TEMP_NAME: logit_scale_retrieve
LOSSES:
NAMES: ['LabelSmoothingCrossEntropy', 'Accuracy']
LABELSMOOTHING: 0.1
LOSS_WEIGHT: 0.5
REDUCTION: 'mean'
INFERENCE:
VOCAB: 'CLIP'
GENERATION_MODE: False
-
NAME: cc12m_retrieve
DATASETS:
TRAIN: 'ImageTextPairDataset'
TASK_TYPE: 'image_retrieval'
DATASET_NAME: 'CC12M'
DATALOADER:
TRAIN_BATCH_SIZE: 64
TEST_BATCH_SIZE: 32
NUM_WORKERS: 2
S3_ANNO_FOLDER: 's3://cc12m/'
ANNO_FOLDER: 'open_source_dataset/c12m/'
ANNO_FILENAME: 'train_available.json'
FEATS_FOLDER: 'open_source_dataset/c12m/'
S3_PATH: 's3://cc12m/'
SAMPLER: NodeDistributed
CACHE_MODE: True
CIRCULAR_CACHE_MODE: False
ZIP_MODE: False
CACHE_ORIGIN_IMAGE: False
RANDOM_CAPTION: False
AS_NUMPY_AS_POSSIBLE: False
SAMPLING_WEIGHT: 1.0
TRANSFORM: 'clip_transforms'
MODEL:
MAX_SEQ_LEN: 50
TEMP_NAME: logit_scale_retrieve
LOSSES:
NAMES: ['LabelSmoothingCrossEntropy', 'Accuracy']
LABELSMOOTHING: 0.1
LOSS_WEIGHT: 0.5
REDUCTION: 'mean'
INFERENCE:
VOCAB: 'CLIP'
GENERATION_MODE: False
-
NAME: cc3m_retrieve
DATASETS:
TRAIN: 'ImageTextPairDataset'
TASK_TYPE: 'image_retrieval'
DATASET_NAME: 'CC3M'
DATALOADER:
TRAIN_BATCH_SIZE: 64
TEST_BATCH_SIZE: 32
NUM_WORKERS: 2
S3_ANNO_FOLDER: 's3://cc3m/'
ANNO_FOLDER: 'open_source_dataset/cc3m/'
ANNO_FILENAME: 'train_spacy.json'
FEATS_FOLDER: 'open_source_dataset/cc3m/'
S3_PATH: 's3://cc3m/'
SAMPLER: NodeDistributed
CACHE_MODE: True
CIRCULAR_CACHE_MODE: False
ZIP_MODE: False
CACHE_ORIGIN_IMAGE: False
RANDOM_CAPTION: False
AS_NUMPY_AS_POSSIBLE: False
SAMPLING_WEIGHT: 1.0
TRANSFORM: 'clip_transforms'
MODEL:
MAX_SEQ_LEN: 50
TEMP_NAME: logit_scale_retrieve
LOSSES:
NAMES: ['LabelSmoothingCrossEntropy', 'Accuracy']
LABELSMOOTHING: 0.1
LOSS_WEIGHT: 0.5
REDUCTION: 'mean'
INFERENCE:
VOCAB: 'CLIP'
GENERATION_MODE: False
-
NAME: vg_retrieve
DATASETS:
TRAIN: 'ImageTextPairDataset'
TASK_TYPE: 'image_retrieval'
DATASET_NAME: 'VG'
DATALOADER:
TRAIN_BATCH_SIZE: 64
TEST_BATCH_SIZE: 32
NUM_WORKERS: 2
FEATS_FOLDER: 'open_source_dataset/visual_genome/images'
ANNO_FOLDER: 'open_source_dataset/visual_genome/annotations'
S3_PATH: 's3://visual_genome/images'
ANNO_FILENAME: 'vg_captions_128filter.json'
SEQ_PER_SAMPLE: 1
CACHE_MODE: True
CIRCULAR_CACHE_MODE: False
ZIP_MODE: False
CACHE_ORIGIN_IMAGE: False
RANDOM_CAPTION: False
AS_NUMPY_AS_POSSIBLE: False
SAMPLING_WEIGHT: 1.0
TRANSFORM: 'clip_transforms'
MODEL:
MAX_SEQ_LEN: 30
TEMP_NAME: logit_scale_retrieve
LOSSES:
NAMES: ['LabelSmoothingCrossEntropy', 'Accuracy']
LABELSMOOTHING: 0.1
LOSS_WEIGHT: 0.5
REDUCTION: 'mean'
INFERENCE:
VOCAB: 'CLIP'
GENERATION_MODE: False
-
NAME: sbu_retrieve
DATASETS:
TRAIN: 'ImageTextPairDataset'
TASK_TYPE: 'image_retrieval'
DATASET_NAME: 'SBU'
DATALOADER:
TRAIN_BATCH_SIZE: 64
TEST_BATCH_SIZE: 32
NUM_WORKERS: 1
S3_ANNO_FOLDER: 's3://SBU/annotations'
ANNO_FOLDER: 'open_source_dataset/sbucaption/annotations'
ANNO_FILENAME: 'subcaption.json'
FEATS_FOLDER: 'open_source_dataset/sbucaption/'
S3_PATH: 's3://SBU/images'
SAMPLER: NodeDistributed
CACHE_MODE: True
CIRCULAR_CACHE_MODE: False
ZIP_MODE: False
CACHE_ORIGIN_IMAGE: False
RANDOM_CAPTION: False
AS_NUMPY_AS_POSSIBLE: False
SAMPLING_WEIGHT: 1.0
TRANSFORM: 'clip_transforms'
MODEL:
MAX_SEQ_LEN: 50
TEMP_NAME: logit_scale_retrieve
LOSSES:
NAMES: ['LabelSmoothingCrossEntropy', 'Accuracy']
LABELSMOOTHING: 0.1
LOSS_WEIGHT: 0.5
REDUCTION: 'mean'
INFERENCE:
VOCAB: 'CLIP'
GENERATION_MODE: False
-
NAME: flickr30k_retrieve
DATASETS:
TRAIN: 'ImageTextPairDataset'
TASK_TYPE: 'image_retrieval'
TEST: 'ImageTextPairDataset'
DATASET_NAME: 'FLICKR'
DATALOADER:
TRAIN_BATCH_SIZE: 128
TEST_BATCH_SIZE: 128
NUM_WORKERS: 2
FEATS_FOLDER: 'open_source_dataset/flickr30k_images/flickr30k_images/flickr30k_images'
ANNO_FOLDER: 'open_source_dataset/flickr30k'
S3_PATH: "s3://open_dataset/flickr30k/flickr30k_images"
SEQ_PER_SAMPLE: 1
CACHE_MODE: True
CIRCULAR_CACHE_MODE: False
ZIP_MODE: False
CACHE_ORIGIN_IMAGE: False
RANDOM_CAPTION: False
AS_NUMPY_AS_POSSIBLE: False
SAMPLING_WEIGHT: 1.0
TRANSFORM: 'clip_transforms'
MODEL:
MAX_SEQ_LEN: 77
TEMP_NAME: logit_scale_retrieve
LOSSES:
NAMES: ['LabelSmoothingCrossEntropy']
LABELSMOOTHING: 0.1
LOSS_WEIGHT: 1.0
REDUCTION: 'mean'
INFERENCE:
VOCAB: 'CLIP'
ID_KEY: 'image_id'
VALUE: 'caption'
NAME: 'RetrievalEvaler'
VAL_ANNFILE: 'open_source_dataset/flickr30k/all_data_final_val_set0_2014.jsonline'
TEST_ANNFILE: 'open_source_dataset/flickr30k/all_data_final_test_set0_2014.jsonline'
GENERATION_MODE: False
-
NAME: flickr30k_caption
DATASETS:
TRAIN: 'ImageTextPairDataset'
TASK_TYPE: 'image_caption'
TEST: 'ImageTextPairDataset'
DATASET_NAME: 'FLICKR'
TARGET_SET: ['Vocab_Word']
DATALOADER:
TRAIN_BATCH_SIZE: 32
TEST_BATCH_SIZE: 8
NUM_WORKERS: 4
FEATS_FOLDER: 'open_source_dataset/flickr30k_images/flickr30k_images/flickr30k_images'
ANNO_FOLDER: 'open_source_dataset/flickr30k'
S3_PATH: "s3://open_dataset/flickr30k/flickr30k_images"
SEQ_PER_SAMPLE: 1
CACHE_MODE: True
CIRCULAR_CACHE_MODE: False
ZIP_MODE: False
CACHE_ORIGIN_IMAGE: False
RANDOM_CAPTION: False
AS_NUMPY_AS_POSSIBLE: False
SAMPLING_WEIGHT: 1.0
TRANSFORM: 'clip_transforms'
TASK_TYPE: caption
# DATA_PERCENTAGE: 0.01
MODEL:
MAX_SEQ_LEN: 21
TEMP_NAME: logit_scale_caption
LOSSES:
NAMES: ['LabelSmoothingCrossEntropy', 'Accuracy']
LABELSMOOTHING: 0.1
LOSS_WEIGHT: 1.0
REDUCTION: 'mean'
DECODE_STRATEGY:
NAME: 'CaptionBeamSearcherV3'
BEAM_SIZE: 2
INFERENCE:
NAME: 'COCOEvaler'
VOCAB: 'CLIP'
ID_KEY: 'image_id'
VALUE: 'caption'
VAL_ANNFILE: 'open_source_dataset/flickr30k/captions_val.json'
TEST_ANNFILE: 'open_source_dataset/flickr30k/captions_test.json'
GENERATION_MODE: True
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: 0.1
NUM_HIDDEN_LAYERS: 1
DROP_PATH_PROB_FIXED: True
UNIFY_QKV: True
MODEL_EMA: False
MODEL_EMA_DECAY: 0.9999
MAEParamsInit: True
POSEMBEDFIX: True
IMG_INPUT_SIZE: 224
PATCH_SIZE: 16
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
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