Upload 3 files
Browse files- config.yaml +188 -0
- model.pth +3 -0
- trunk.pth +3 -0
config.yaml
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seed: 0
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output_dir: output/05_05_2024_20_21_54_727273
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domains: austin_sailor_dataset_converted_externally_to_rlds, stanford_hydra_dataset_converted_externally_to_rlds,
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austin_buds_dataset_converted_externally_to_rlds, austin_sirius_dataset_converted_externally_to_rlds,
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berkeley_mvp_converted_externally_to_rlds, berkeley_rpt_converted_externally_to_rlds,
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iamlab_cmu_pickup_insert_converted_externally_to_rlds, utaustin_mutex, imperialcollege_sawyer_wrist_cam,
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stanford_mask_vit_converted_externally_to_rlds, language_table, kuka, bc_z, robo_net,
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dlr_sara_pour_converted_externally_to_rlds, stanford_robocook_converted_externally_to_rlds,
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cmu_play_fusion, bridge, furniture_bench_dataset_converted_externally_to_rlds, ucsd_pick_and_place_dataset_converted_externally_to_rlds,
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usc_cloth_sim_converted_externally_to_rlds, stanford_kuka_multimodal_dataset_converted_externally_to_rlds,
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roboturk, kaist_nonprehensile_converted_externally_to_rlds, asu_table_top_converted_externally_to_rlds,
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utokyo_xarm_pick_and_place_converted_externally_to_rlds, berkeley_cable_routing,
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droid, uiuc_d3field, robo_set, qut_dexterous_manpulation, nyu_door_opening_surprising_effectiveness,
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nyu_franka_play_dataset_converted_externally_to_rlds, mimic_play, maniskill_dataset_converted_externally_to_rlds,
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columbia_cairlab_pusht_real, conq_hose_manipulation, dlr_edan_shared_control_converted_externally_to_rlds,
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berkeley_gnm_sac_son, berkeley_autolab_ur5, aloha_mobile, agent_aware_affordances
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log_dir: output/05_05_2024_20_21_54_727273
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debug_distributed: false
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wb_tag: default
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wb_cont_run: 2nxmlp81
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log_interval: 10
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script_name: run_resnet_30dataset_traj100000_embed_256_batch2048_800k_language
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save_wb_checkpoint: true
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slurm_job_id: '27155760'
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effective_total_epochs: 100
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effective_batch_size: 256
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epoch_size: 10
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total_num_traj: 0
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total_num_sample: 0
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rank: 0
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gpu: 0
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task_per_gpu: 1
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world_size: 64
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debug_submitit: false
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ngpus: 8
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nodes: 8
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timeout: 4320
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job_dir: logs/
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partition: learnlab
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use_volta32: true
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comment: ''
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resume: logs/
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dist_url: file:///checkpoint/xinleic/experiments/43124ff352a546a8b51d5fb4234b51d8_init
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dist_on_itp: false
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local_rank: 1
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distributed: true
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dist_backend: nccl
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dset_w_temperature: 2.0
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dataset_shuffle: true
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dataset_groups: ''
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nodelist: learnlab,learnfair,scavenge
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fsdp: false
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count_flops: false
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accumuate_gradient_steps: 1
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trunk_acc_gradient_step: 1
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submitit_autoresume: true
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customized_dataset_mixture_file: ''
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trunk_separate_opt: false
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dataset:
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_target_: hpt_pretrain.dataset.traj_dataset.TrajDataset
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horizon: 5
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val_ratio: 0.1
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pad_after: 0
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precompute_feat: true
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image_encoder: resnet
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episode_cnt: 100000
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step_cnt: 10000000
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data_augmentation: false
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use_disk: true
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pad_before: 0
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data_ratio: 1
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action_horizon: 8
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observation_horizon: 4
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dataset_postfix: _traj100000
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dataset_encoder_postfix: _resnet
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use_multiview: false
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normalize_state: true
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use_heldout_dataset: true
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heldout_dataset: false
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regenerate: false
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continue_generate: false
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network:
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_target_: hpt_pretrain.models.policy.Policy
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embed_dim: 256
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num_blocks: 16
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num_heads: 8
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use_modality_embedding: true
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use_domain_embedding: false
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token_postprocessing: mean
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weight_init_style: pytorch
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drop_path: 0.1
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mae_loss_scale: 0.0
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masked_autoencoding: false
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action_horizon: ${dataset.action_horizon}
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stem:
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modalities:
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- image
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- state
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- language
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modality_embed_dim: 256
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normalize_state: ${dataset.normalize_state}
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state_embedding_dim: 1
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image_encoder: ${dataset.image_encoder}
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crossattn_dim_head: 64
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crossattn_heads: 8
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crossattn_modality_dropout: 0.1
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observation_horizon: ${dataset.observation_horizon}
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random_horizon_masking: true
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add_pos_embedding_to_state: false
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num_blocks: 1
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crossattn_latent:
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image: 16
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state: 16
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language: 8
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image:
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_target_: hpt_pretrain.models.policy_stem.MLP
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input_dim: 512
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output_dim: 256
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widths:
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- 128
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num_of_copy: 1
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state:
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_target_: hpt_pretrain.models.policy_stem.MLP
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input_dim: 8
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output_dim: 256
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widths:
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- 128
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language:
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_target_: hpt_pretrain.models.policy_stem.MLP
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input_dim: 768
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output_dim: ${network.embed_dim}
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widths:
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- 128
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head:
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_target_: hpt_pretrain.models.policy_head.MLP
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input_dim: 256
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tanh_end: true
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output_dim: 48
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dropout: true
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widths:
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- 256
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- 128
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dataloader:
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batch_size: 32
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num_workers: 1
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pin_memory: false
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persistent_workers: false
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drop_last: true
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val_dataloader:
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num_workers: 1
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pin_memory: false
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persistent_workers: false
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ddp_dataloader:
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num_workers: 8
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pin_memory: false
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persistent_workers: false
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drop_last: false
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prefetch_factor: 6
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ddp_val_dataloader:
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num_workers: 8
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pin_memory: false
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persistent_workers: false
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drop_last: false
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prefetch_factor: 2
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optimizer:
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_target_: torch.optim.AdamW
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lr: 0.001
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eps: 1.0e-06
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weight_decay: 0.05
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optimizer_misc:
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nontrunk_lr_scale: 0.5
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warmup_lr:
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lr: 1.0e-10
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step: 1000
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train:
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total_epochs: 30000
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total_iters: 800000
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epoch_iters: 1000
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validation_iters: 100
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use_accumulation: false
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pretrained_dir: '05_05_2024_20_21_54_727273'
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max_validation_size: 10
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load_pretrain_trunk_only: false
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freeze_trunk: false
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lr_scheduler:
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_target_: torch.optim.lr_scheduler.CosineAnnealingLR
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T_max: 800000
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eta_min: 1.0e-06
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model.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:76698f5a63dce67bc7b6cb5622781af0c0e3569eaffe459652c3e177afb4c481
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size 379997162
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trunk.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:8b59bf717a7aac851d5a65fb752f4cc957a170f5bb474fc097197be0d9cfa103
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size 50642858
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