285 lines
6.6 KiB
YAML
285 lines
6.6 KiB
YAML
ENV:
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BACKEND: nccl
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META:
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VERSION: 'SD2.1'
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DESCRIPTION: "Stable Diffusion v2.1"
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IS_DEFAULT: False
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IS_SHARE: True
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INFERENCE_PARAS:
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INFERENCE_BATCH_SIZE: 1
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INFERENCE_PREFIX: ""
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DEFAULT_SAMPLER: "ddim"
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DEFAULT_SAMPLE_STEPS: 40
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INFERENCE_N_PROMPT: ""
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RESOLUTION: [768, 768]
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PARAS:
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-
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TRAIN_BATCH_SIZE: 2
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TRAIN_PREFIX: ""
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TRAIN_N_PROMPT: ""
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RESOLUTION: [768, 768]
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MEMORY: 29000
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EPOCHS: 50
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SAVE_INTERVAL: 25
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EPSEC: 0.818
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LEARNING_RATE: 0.0001
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IS_DEFAULT: False
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TUNER: FULL
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-
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TRAIN_BATCH_SIZE: 2
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TRAIN_PREFIX: ""
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TRAIN_N_PROMPT: ""
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RESOLUTION: [768, 768]
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MEMORY: 29000
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EPOCHS: 50
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SAVE_INTERVAL: 25
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EPSEC: 0.818
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LEARNING_RATE: 0.0001
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IS_DEFAULT: False
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TUNER: LORA
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-
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TRAIN_BATCH_SIZE: 2
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TRAIN_PREFIX: ""
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TRAIN_N_PROMPT: ""
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RESOLUTION: [768, 768]
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MEMORY: 29000
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EPOCHS: 200
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SAVE_INTERVAL: 25
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EPSEC: 0.818
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LEARNING_RATE: 0.0001
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IS_DEFAULT: True
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TUNER: SCE
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TUNERS:
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LORA:
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-
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NAME: SwiftLoRA
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R: 256
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LORA_ALPHA: 256
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LORA_DROPOUT: 0.0
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BIAS: "none"
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TARGET_MODULES: "model.*(to_q|to_k|to_v|to_out.0|net.0.proj|net.2)$"
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SCE:
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-
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NAME: SwiftSCETuning
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DIMS: [1280, 1280, 1280, 1280, 1280, 640, 640, 640, 320, 320, 320, 320]
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DOWN_RATIO: 1.0
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TARGET_MODULES: model.lsc_identity\.\d+$
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TUNER_MODE: identity
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SOLVER:
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NAME: LatentDiffusionSolver
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RESUME_FROM:
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LOAD_MODEL_ONLY: True
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USE_FSDP: False
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SHARDING_STRATEGY:
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USE_AMP: True
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DTYPE: float16
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CHANNELS_LAST: True
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MAX_STEPS: 1000
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MAX_EPOCHS: -1
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NUM_FOLDS: 1
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ACCU_STEP: 1
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EVAL_INTERVAL: -1
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#
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WORK_DIR:
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LOG_FILE: std_log.txt
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#
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FILE_SYSTEM:
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NAME: "ModelscopeFs"
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TEMP_DIR: "./cache/data"
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#
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FREEZE:
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#
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TUNER:
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#
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MODEL:
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NAME: LatentDiffusion
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PARAMETERIZATION: v
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TIMESTEPS: 1000
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MIN_SNR_GAMMA:
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ZERO_TERMINAL_SNR: False
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PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-2-1@v2-1_768-ema-pruned.safetensors
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IGNORE_KEYS: [ ]
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SCALE_FACTOR: 0.18215
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SIZE_FACTOR: 8
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# DEFAULT_N_PROMPT: 'lowres, error, worst quality, low quality, jpeg artifacts, ugly, duplicate, morbid, mutilated, out of frame, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, mutation, deformed, blurry, dehydrated, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature'
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DEFAULT_N_PROMPT:
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SCHEDULE_ARGS:
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"NAME": "scaled_linear"
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"BETA_MIN": 0.00085
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"BETA_MAX": 0.012
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USE_EMA: False
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#
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DIFFUSION_MODEL:
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NAME: DiffusionUNet
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IN_CHANNELS: 4
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OUT_CHANNELS: 4
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MODEL_CHANNELS: 320
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NUM_HEADS_CHANNELS: 64
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NUM_RES_BLOCKS: 2
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ATTENTION_RESOLUTIONS: [ 4, 2, 1 ]
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CHANNEL_MULT: [ 1, 2, 4, 4 ]
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CONV_RESAMPLE: True
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DIMS: 2
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USE_CHECKPOINT: False
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USE_SCALE_SHIFT_NORM: False
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RESBLOCK_UPDOWN: False
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USE_SPATIAL_TRANSFORMER: True
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TRANSFORMER_DEPTH: 1
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CONTEXT_DIM: 1024
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DISABLE_MIDDLE_SELF_ATTN: False
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USE_LINEAR_IN_TRANSFORMER: True
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PRETRAINED_MODEL:
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#
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FIRST_STAGE_MODEL:
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NAME: AutoencoderKL
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EMBED_DIM: 4
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PRETRAINED_MODEL:
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IGNORE_KEYS: [ ]
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BATCH_SIZE: 4
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#
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ENCODER:
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NAME: Encoder
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CH: 128
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OUT_CH: 3
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NUM_RES_BLOCKS: 2
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IN_CHANNELS: 3
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ATTN_RESOLUTIONS: [ ]
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CH_MULT: [ 1, 2, 4, 4 ]
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Z_CHANNELS: 4
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DOUBLE_Z: True
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DROPOUT: 0.0
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RESAMP_WITH_CONV: True
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#
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DECODER:
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NAME: Decoder
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CH: 128
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OUT_CH: 3
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NUM_RES_BLOCKS: 2
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IN_CHANNELS: 3
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ATTN_RESOLUTIONS: [ ]
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CH_MULT: [ 1, 2, 4, 4 ]
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Z_CHANNELS: 4
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DROPOUT: 0.0
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RESAMP_WITH_CONV: True
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GIVE_PRE_END: False
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TANH_OUT: False
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#
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TOKENIZER:
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NAME: OpenClipTokenizer
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LENGTH: 77
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#
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COND_STAGE_MODEL:
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NAME: FrozenOpenCLIPEmbedder
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ARCH: ViT-H-14
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PRETRAINED_MODEL:
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USE_GRAD: False
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LAYER: penultimate
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#
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LOSS:
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NAME: ReconstructLoss
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LOSS_TYPE: l2
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#
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SAMPLE_ARGS:
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SAMPLER: ddim
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SAMPLE_STEPS: 50
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SEED: 2023
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GUIDE_SCALE: 7.5
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GUIDE_RESCALE:
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DISCRETIZATION: trailing
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RUN_TRAIN_N: False
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#
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OPTIMIZER:
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NAME: AdamW
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LEARNING_RATE: 0.064
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BETAS: [ 0.9, 0.999 ]
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EPS: 1e-8
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WEIGHT_DECAY: 1e-2
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AMSGRAD: False
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#
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TRAIN_DATA:
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NAME: ImageTextPairMSDataset
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MODE: train
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MS_DATASET_NAME: style_custom_dataset
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MS_DATASET_NAMESPACE: damo
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MS_DATASET_SUBNAME: 3D
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PROMPT_PREFIX: ""
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MS_DATASET_SPLIT: train
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MS_REMAP_KEYS: { 'Image:FILE': 'Target:FILE' }
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REPLACE_STYLE: False
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PIN_MEMORY: True
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BATCH_SIZE: 1
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NUM_WORKERS: 4
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SAMPLER:
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NAME: LoopSampler
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TRANSFORMS:
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- NAME: LoadImageFromFile
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RGB_ORDER: RGB
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BACKEND: pillow
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- NAME: FlexibleResize
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INTERPOLATION: bilinear
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SIZE: [ 768, 768 ]
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INPUT_KEY: [ 'img' ]
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OUTPUT_KEY: [ 'img' ]
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BACKEND: pillow
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- NAME: FlexibleCenterCrop
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SIZE: [ 768, 768 ]
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INPUT_KEY: [ 'img' ]
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OUTPUT_KEY: [ 'img' ]
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BACKEND: pillow
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- NAME: ImageToTensor
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INPUT_KEY: [ 'img' ]
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OUTPUT_KEY: [ 'img' ]
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BACKEND: pillow
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- NAME: Normalize
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MEAN: [ 0.5, 0.5, 0.5 ]
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STD: [ 0.5, 0.5, 0.5 ]
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INPUT_KEY: [ 'img' ]
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OUTPUT_KEY: [ 'image' ]
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BACKEND: torchvision
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- NAME: Select
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KEYS: [ 'image', 'prompt' ]
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META_KEYS: [ 'data_key' ]
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#
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EVAL_DATA:
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NAME: Text2ImageDataset
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MODE: eval
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PROMPT_FILE:
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PROMPT_DATA: [ "a boy wearing a jacket", "a dog running on the lawn" ]
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IMAGE_SIZE: [ 768, 768 ]
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FIELDS: [ "prompt" ]
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DELIMITER: '#;#'
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PROMPT_PREFIX: ''
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PIN_MEMORY: True
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BATCH_SIZE: 1
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NUM_WORKERS: 4
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TRANSFORMS:
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- NAME: Select
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KEYS: [ 'index', 'prompt' ]
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META_KEYS: [ 'image_size' ]
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#
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TRAIN_HOOKS:
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-
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NAME: BackwardHook
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PRIORITY: 0
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-
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NAME: LogHook
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LOG_INTERVAL: 10
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SHOW_GPU_MEM: True
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-
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NAME: TensorboardLogHook
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-
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NAME: CheckpointHook
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INTERVAL: 10000
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PRIORITY: 200
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SAVE_LAST: True
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SAVE_NAME_PREFIX: 'step'
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#
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EVAL_HOOKS:
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-
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NAME: ProbeDataHook
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PROB_INTERVAL: 100
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SAVE_LAST: True
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SAVE_NAME_PREFIX: 'step'
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SAVE_PROBE_PREFIX: 'image'
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