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checkpoints/mld_miko_finetune_v2/args.yaml
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"# tyro YAML.\n!dataclass:MLDArgs\ndata_args: !dataclass:DataArgs\n body_type: smplx\n\
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\ cfg_path: ./config_files/config_hydra/motion_primitive/mp_h2_f8_r4.yaml\n data_dir:\
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\ ./data/miko_seq_data_zero_male\n dataset: mp_seq_v2\n enforce_gender: male\n\
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\ enforce_zero_beta: 1\n feature_dim: 276\n future_length: 8\n history_length:\
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\ 2\n num_primitive: 4\n prob_static: 0.0\n text_tolerance: 0.0\n weight_scheme:\
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\ text_samp:0.\ndenoiser_args: !dataclass:DenoiserArgs\n diffusion_args: !dataclass:DiffusionArgs\n\
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\ diffusion_steps: 10\n noise_schedule: cosine\n respacing: ''\n sigma_small:\
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\ true\n model_args: !dataclass:DenoiserTransformerArgs\n activation: gelu\n\
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\ clip_dim: 512\n cond_mask_prob: 0.1\n dropout: 0.1\n ff_size: 1024\n\
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\ h_dim: 512\n history_shape: !!python/tuple\n - 2\n - 276\n noise_shape:\
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\ !!python/tuple\n - 1\n - 256\n num_heads: 4\n num_layers: 8\n model_type:\
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\ transformer\n mvae_path: ./mvae/mvae_miko_finetuned_v2/checkpoint_230000.pt\n\
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\ rescale_latent: 1\n train_rollout_history: rollout\n train_rollout_type: full\n\
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device: cuda\nexp_name: mld_miko_finetune_v2\nsave_dir: !!python/object/apply:pathlib.PosixPath\n\
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- mld_denoiser\n- mld_miko_finetune_v2\nseed: 0\ntorch_deterministic: true\ntrack:\
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\ 1\ntrain_args: !dataclass:TrainArgs\n anneal_lr: 1\n batch_size: 128\n ema_decay:\
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\ 0.999\n grad_clip: 1.0\n learning_rate: 0.0001\n log_interval: 1000\n resume_checkpoint:\
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\ ./mld_denoiser/mld_fps_clip_euler/checkpoint_300000.pt\n save_interval: 15000\n\
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\ stage1_steps: 112000\n stage2_steps: 112000\n stage3_steps: 112000\n use_amp:\
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\ 1\n use_predicted_joints: 0\n val_interval: 10000\n weight_feature_rec: 1.0\n\
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\ weight_joints_consistency: 0.0\n weight_joints_delta: 10000.0\n weight_kl:\
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\ 0.0001\n weight_latent_rec: 1.0\n weight_orient_delta: 10000.0\n weight_rec:\
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\ 1.0\n weight_smpl_joints_rec: 0.0\n weight_transl_delta: 10000.0\nwandb_entity:\
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\ interaction\nwandb_project_name: mld_denoiser\n"
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checkpoints/mld_miko_finetune_v2/args_read.yaml
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data_args:
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body_type: smplx
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cfg_path: ./config_files/config_hydra/motion_primitive/mp_h2_f8_r4.yaml
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data_dir: ./data/miko_seq_data_zero_male
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dataset: mp_seq_v2
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enforce_gender: male
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enforce_zero_beta: 1
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feature_dim: 276
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future_length: 8
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history_length: 2
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num_primitive: 4
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prob_static: 0.0
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text_tolerance: 0.0
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weight_scheme: text_samp:0.
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denoiser_args:
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diffusion_args:
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diffusion_steps: 10
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noise_schedule: cosine
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respacing: ''
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sigma_small: true
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model_args:
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activation: gelu
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clip_dim: 512
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cond_mask_prob: 0.1
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dropout: 0.1
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ff_size: 1024
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h_dim: 512
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history_shape: !!python/tuple
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- 2
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- 276
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noise_shape: !!python/tuple
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- 1
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- 256
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num_heads: 4
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num_layers: 8
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model_type: transformer
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mvae_path: ./mvae/mvae_miko_finetuned_v2/checkpoint_230000.pt
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rescale_latent: 1
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train_rollout_history: rollout
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train_rollout_type: full
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device: cuda
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exp_name: mld_miko_finetune_v2
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save_dir: !!python/object/apply:pathlib.PosixPath
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- mld_denoiser
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- mld_miko_finetune_v2
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seed: 0
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torch_deterministic: true
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track: 1
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train_args:
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anneal_lr: 1
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batch_size: 128
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ema_decay: 0.999
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grad_clip: 1.0
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learning_rate: 0.0001
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log_interval: 1000
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resume_checkpoint: ./mld_denoiser/mld_fps_clip_euler/checkpoint_300000.pt
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save_interval: 15000
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stage1_steps: 112000
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stage2_steps: 112000
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stage3_steps: 112000
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use_amp: 1
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use_predicted_joints: 0
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val_interval: 10000
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weight_feature_rec: 1.0
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weight_joints_consistency: 0.0
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weight_joints_delta: 10000.0
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weight_kl: 0.0001
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weight_latent_rec: 1.0
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weight_orient_delta: 10000.0
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weight_rec: 1.0
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weight_smpl_joints_rec: 0.0
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weight_transl_delta: 10000.0
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wandb_entity: interaction
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wandb_project_name: mld_denoiser
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checkpoints/mld_miko_finetune_v2/checkpoint_30000.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:a5ffd5724377b9928f34941179c66581df33d8e809ef667aafb92822c3862c13
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size 82342289
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checkpoints/mld_miko_finetune_v2/checkpoint_336000.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:236042a847e2e365267a8c0d512b36c8b0aa353a30f05c76143c9da091d78246
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size 82342402
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