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bs_128_conf/.hydra/config.yaml

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+data:
+  dataname: motionfix
+  _target_: src.data.motionfix.MotionFixDataModule
+  debug: ${debug}
+  datapath: ${path.data}/motionfix-dataset/motionfix.pth.tar
+  smplh_path: ${path.data}/body_models
+  smplh_path_dbg: ${path.minidata}/body_models
+  load_with_rot: true
+  load_splits:
+  - train
+  - val
+  - test
+  proportion: 1.0
+  text_augment: false
+  batch_size: ${machine.batch_size}
+  num_workers: ${machine.num_workers}
+  rot_repr: 6d
+  preproc:
+    stats_file: ${path.deps}/stats/statistics_${data.dataname}.npy
+    split_seed: 0
+    calculate_minmax: true
+    generate_joint_files: true
+    use_cuda: true
+    n_body_joints: 22
+    norm_type: std
+  framerate: 30
+  sampler: ${sampler}
+  load_feats:
+  - body_transl_delta_pelv
+  - body_orient_xy
+  - z_orient_delta
+  - body_pose
+  - body_joints_local_wo_z_rot
+  progress_bar: true
+model:
+  modelname: basic_clip
+  _target_: src.model.base_diffusion.MD
+  latent_dim: 512
+  ff_size: 2048
+  num_layers: 8
+  num_head: 8
+  droupout: 0.1
+  activation: gelu
+  render_vids_every_n_epochs: 100
+  num_vids_to_render: 2
+  lr_scheduler: null
+  zero_len_source: false
+  old_way: false
+  statistics_path: ${statistics_path}
+  norm_type: standardize
+  diff_params:
+    num_inference_timesteps: 200
+    num_train_timesteps: 200
+    prob_uncondp: 0.05
+    prob_drop_text: 0.05
+    prob_drop_motion: 0.05
+    guidance_scale_text: 2.5
+    guidance_scale_motion: 2.0
+    noise_schedule: squaredcos_cap_v2
+    predict_type: sample
+  motion_condition: source
+  source_encoder: null
+  condition: text
+  smpl_path: ${data.smplh_path}
+  copy_target: false
+  nfeats: 135
+  dim_per_feat:
+  - 135
+  input_feats:
+  - body_transl_delta_pelv
+  - body_orient_xy
+  - z_orient_delta
+  - body_pose
+  - body_joints_local_wo_z_rot
+  pad_inputs: false
+  loss_func_pos: mse
+  loss_func_feats: mse
+  path:
+    deps: ${code_path:./deps}
+    data: ${code_path:./data}
+    minidata: ${code_path:./minidata}
+    code_dir: ${code_path:}
+    working_dir: ${working_path:""}
+    minilog: ${code_path:./miniexperiments}
+  train_scheduler:
+    _target_: diffusers.DDPMScheduler
+    num_train_timesteps: 1000
+    beta_start: 0.00085
+    beta_end: 0.012
+    beta_schedule: squaredcos_cap_v2
+    variance_type: fixed_small
+    clip_sample: false
+    prediction_type: sample
+  infer_scheduler:
+    _target_: diffusers.DDPMScheduler
+    num_train_timesteps: 1000
+    beta_start: 0.00085
+    beta_end: 0.012
+    beta_schedule: squaredcos_cap_v2
+    variance_type: fixed_small
+    clip_sample: false
+    prediction_type: sample
+  denoiser:
+    _target_: src.model.tmed_denoiser.TMED_denoiser
+    text_encoded_dim: 768
+    ff_size: 1024
+    num_layers: 8
+    num_heads: 4
+    dropout: 0.1
+    activation: gelu
+    condition: ${model.condition}
+    motion_condition: ${model.motion_condition}
+    latent_dim: ${model.latent_dim}
+    nfeats: ${model.nfeats}
+    use_sep: true
+    pred_delta_motion: false
+  text_encoder:
+    _target_: src.model.textencoder.clip_encoder.ClipTextEncoder
+    finetune: false
+    last_hidden_state: true
+    modelpath: ${path.deps}/clip-vit-large-patch14
+  motion_condition_encoder:
+    name: actor_encoder
+    _target_: src.model.motionencoder.ActorAgnosticEncoder
+    latent_dim: ${model.latent_dim}
+    ff_size: ${model.ff_size}
+    num_layers: ${model.num_layers}
+    num_head: ${model.num_head}
+    droupout: ${model.droupout}
+    activation: ${model.activation}
+    nfeats: ${model.nfeats}
+  losses:
+    _target_: src.model.losses.MLDLosses
+    lmd_rfeats_recons: 1.0
+    lmd_jfeats_recons: 1.0
+    predict_epsilon: false
+    modelname: ${model.modelname}
+    lmd_latent: 1.0e-05
+    lmd_kl: 1.0e-05
+    lmd_prior: 0.0
+    lmd_recons: 1.0
+    lmd_gen: 1.0
+    fuse: concat
+    loss_on_both: true
+    loss_on_jfeats: false
+    ablation_no_kl_combine: false
+    ablation_no_kl_gaussian: false
+    ablation_no_motionencoder: false
+  optim:
+    _target_: torch.optim.AdamW
+    lr: 0.0001
+    lr_final: 1.0e-06
+    t_warmup: 150
+  func_recons:
+    _target_: src.model.losses.recons.Recons
+  func_latent:
+    _target_: src.model.losses.recons.Recons
+  func_kl:
+    _target_: src.model.losses.KLLoss
+machine:
+  name: server
+  batch_size: 128
+  smpl_batch_size: 64
+  num_workers: 8
+trainer:
+  strategy: auto
+  benchmark: true
+  max_epochs: 1001
+  accelerator: gpu
+  log_every_n_steps: 40
+  deterministic: false
+  detect_anomaly: false
+  enable_progress_bar: true
+  check_val_every_n_epoch: 100
+  limit_train_batches: 1.0
+  limit_val_batches: 1.0
+  num_sanity_val_steps: 0
+  precision: 32
+sampler:
+  _target_: src.data.sampling.FrameSampler
+  request_frames: 300
+  sampling: conseq
+  sampling_step: 1
+  threshold_reject: 0.75
+  max_len: 600
+  min_len: 15
+logger:
+  logger_name: wandb
+  name: ${experiment}-${run_id}
+  save_dir: wandb
+  project: ${project}
+  group: null
+  tags: null
+  notes: null
+  offline: false
+  resume: false
+  save_code: false
+  log_model: false
+callback:
+  last_ckpt:
+    _target_: pytorch_lightning.callbacks.ModelCheckpoint
+    dirpath: ${path.working_dir}/checkpoints
+    filename: latest-{epoch}
+    every_n_epochs: 1
+    save_top_k: 1
+    save_last: true
+  latest_ckpt:
+    _target_: pytorch_lightning.callbacks.ModelCheckpoint
+    dirpath: ${path.working_dir}/checkpoints
+    filename: latest-{epoch}
+    monitor: step
+    mode: max
+    every_n_epochs: 100
+    save_top_k: -1
+    save_last: false
+  progress:
+    _target_: src.callback.ProgressLogger
+  render:
+    _target_: src.callback.RenderCallback
+    every_n_epochs: 50
+    num_workers: ${machine.num_workers}
+    save_last: true
+    nvids_to_save: 3
+    bm_path: ${path.data}
+    modelname: ${model.modelname}
+  lr_logging:
+    _target_: pytorch_lightning.callbacks.LearningRateMonitor
+    logging_interval: epoch
+path:
+  deps: ${code_path:./deps}
+  data: ${code_path:./data}
+  minidata: ${code_path:./minidata}
+  code_dir: ${code_path:}
+  working_dir: ${working_path:""}
+  minilog: ${code_path:./miniexperiments}
+debug: false
+expdir: ${get_expdir:${debug}}
+experiment: final-model
+project: tuning-exps
+seed: 42
+logger_level: INFO
+run_id: bs128_ld512_ts200_big_model
+resume: null
+resume_ckpt_name: null
+renderer: pyrender
+watch_model: false
+log_freq: 1000
+log: all
+devices: 1
+ftune: null
+ftune_ckpt_name: last
+ftune_ckpt_path: ${get_last_checkpoint:${ftune},${ftune_ckpt_name}}
+statistics_file: statistics_${data.dataname}${get_debug:${debug}}.npy
+statistics_path: ${path.deps}/stats/${statistics_file}

bs_128_conf/.hydra/hydra.yaml

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+hydra:
+  run:
+    dir: ${expdir}/${project}/${experiment}/${run_id}/
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+        datefmt: '%d/%m/%y %H:%M:%S'
+    handlers:
+      console:
+        class: rich.logging.RichHandler
+        formatter: colorlog
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    filters:
+      onlyimportant:
+        (): src.tools.logging.LevelsFilter
+        levels:
+        - CRITICAL
+        - ERROR
+        - WARNING
+      noimportant:
+        (): src.tools.logging.LevelsFilter
+        levels:
+        - INFO
+        - DEBUG
+        - NOTSET
+    formatters:
+      verysimple:
+        format: '%(message)s'
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+        datefmt: '%d/%m/%y %H:%M:%S'
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        datefmt: '%d/%m/%y %H:%M:%S'
+      log_colors:
+        DEBUG: purple
+        INFO: green
+        WARNING: yellow
+        ERROR: red
+        CRITICAL: red
+    handlers:
+      console:
+        class: rich.logging.RichHandler
+        formatter: verysimple
+        rich_tracebacks: true
+      file_out:
+        class: logging.FileHandler
+        formatter: simple
+        filename: logs.out
+        filters:
+        - noimportant
+      file_err:
+        class: logging.FileHandler
+        formatter: simple
+        filename: logs.err
+        filters:
+        - onlyimportant
+    root:
+      level: ${logger_level}
+      handlers:
+      - console
+      - file_out
+      - file_err
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - run_id=bs128_ld512_ts200_big_model
+    - trainer.strategy=auto
+    - devices=1
+    - machine.num_workers=8
+    - experiment=final-model
+    - machine.batch_size=128
+    - model.diff_params.num_train_timesteps=200
+    - model.latent_dim=512
+    - model.ff_size=2048
+    - model.num_layers=8
+    - model.num_head=8
+  job:
+    name: train
+    chdir: true
+    override_dirname: devices=1,experiment=final-model,machine.batch_size=128,machine.num_workers=8,model.diff_params.num_train_timesteps=200,model.ff_size=2048,model.latent_dim=512,model.num_head=8,model.num_layers=8,run_id=bs128_ld512_ts200_big_model,trainer.strategy=auto
+    id: ???
+    num: ???
+    config_name: train
+    env_set:
+      PYOPENGL_PLATFORM: egl
+      HYDRA_FULL_ERROR: '1'
+      WANDB__SERVICE_WAIT: '300'
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.2'
+    cwd: /lustre/home/nathanasiou/projects/tgm
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /lustre/home/nathanasiou/projects/tgm/configs
+      schema: file
+      provider: main
+    - path: hydra_plugins.hydra_colorlog.conf
+      schema: pkg
+      provider: hydra-colorlog
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /lustre/home/nathanasiou/projects/tgm/experiments/tuning-exps/final-model/bs128_ld512_ts200_big_model
+    choices:
+      callback: base
+      logger: wandb
+      sampler: variable_conseq
+      trainer: base
+      machine: server
+      model: basic_clip
+      model/optim: adamw
+      model/losses: basic
+      model/motion_condition_encoder: actor
+      model/text_encoder: clipenc
+      model/denoiser: denoiser
+      model/infer_scheduler: ddpm
+      model/train_scheduler: ddpm
+      data: motionfix
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: rich
+      hydra/hydra_logging: rich
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

bs_128_conf/.hydra/overrides.yaml

@@ -0,0 +1,11 @@
+- run_id=bs128_ld512_ts200_big_model
+- trainer.strategy=auto
+- devices=1
+- machine.num_workers=8
+- experiment=final-model
+- machine.batch_size=128
+- model.diff_params.num_train_timesteps=200
+- model.latent_dim=512
+- model.ff_size=2048
+- model.num_layers=8
+- model.num_head=8

bs_64_conf/.hydra/config.yaml

@@ -0,0 +1,254 @@
+data:
+  dataname: motionfix
+  _target_: src.data.motionfix.MotionFixDataModule
+  debug: ${debug}
+  datapath: ${path.data}/motionfix-dataset/motionfix.pth.tar
+  smplh_path: ${path.data}/body_models
+  smplh_path_dbg: ${path.minidata}/body_models
+  load_with_rot: true
+  load_splits:
+  - train
+  - val
+  - test
+  proportion: 1.0
+  text_augment: false
+  batch_size: ${machine.batch_size}
+  num_workers: ${machine.num_workers}
+  rot_repr: 6d
+  preproc:
+    stats_file: ${path.deps}/stats/statistics_${data.dataname}.npy
+    split_seed: 0
+    calculate_minmax: true
+    generate_joint_files: true
+    use_cuda: true
+    n_body_joints: 22
+    norm_type: std
+  framerate: 30
+  sampler: ${sampler}
+  load_feats:
+  - body_transl_delta_pelv
+  - body_orient_xy
+  - z_orient_delta
+  - body_pose
+  - body_joints_local_wo_z_rot
+  progress_bar: true
+model:
+  modelname: basic_clip
+  _target_: src.model.base_diffusion.MD
+  latent_dim: 256
+  ff_size: 1024
+  num_layers: 9
+  num_head: 4
+  droupout: 0.1
+  activation: gelu
+  render_vids_every_n_epochs: 100
+  num_vids_to_render: 2
+  lr_scheduler: null
+  zero_len_source: false
+  old_way: false
+  statistics_path: ${statistics_path}
+  norm_type: standardize
+  diff_params:
+    num_inference_timesteps: 200
+    num_train_timesteps: 200
+    prob_uncondp: 0.05
+    prob_drop_text: 0.05
+    prob_drop_motion: 0.05
+    guidance_scale_text: 2.5
+    guidance_scale_motion: 2.0
+    noise_schedule: squaredcos_cap_v2
+    predict_type: sample
+  motion_condition: source
+  source_encoder: null
+  condition: text
+  smpl_path: ${data.smplh_path}
+  copy_target: false
+  nfeats: 135
+  dim_per_feat:
+  - 135
+  input_feats:
+  - body_transl_delta_pelv
+  - body_orient_xy
+  - z_orient_delta
+  - body_pose
+  - body_joints_local_wo_z_rot
+  pad_inputs: false
+  loss_func_pos: mse
+  loss_func_feats: mse
+  path:
+    deps: ${code_path:./deps}
+    data: ${code_path:./data}
+    minidata: ${code_path:./minidata}
+    code_dir: ${code_path:}
+    working_dir: ${working_path:""}
+    minilog: ${code_path:./miniexperiments}
+  train_scheduler:
+    _target_: diffusers.DDPMScheduler
+    num_train_timesteps: 1000
+    beta_start: 0.00085
+    beta_end: 0.012
+    beta_schedule: squaredcos_cap_v2
+    variance_type: fixed_small
+    clip_sample: false
+    prediction_type: sample
+  infer_scheduler:
+    _target_: diffusers.DDPMScheduler
+    num_train_timesteps: 1000
+    beta_start: 0.00085
+    beta_end: 0.012
+    beta_schedule: squaredcos_cap_v2
+    variance_type: fixed_small
+    clip_sample: false
+    prediction_type: sample
+  denoiser:
+    _target_: src.model.tmed_denoiser.TMED_denoiser
+    text_encoded_dim: 768
+    ff_size: 1024
+    num_layers: 8
+    num_heads: 4
+    dropout: 0.1
+    activation: gelu
+    condition: ${model.condition}
+    motion_condition: ${model.motion_condition}
+    latent_dim: ${model.latent_dim}
+    nfeats: ${model.nfeats}
+    use_sep: true
+    pred_delta_motion: false
+  text_encoder:
+    _target_: src.model.textencoder.clip_encoder.ClipTextEncoder
+    finetune: false
+    last_hidden_state: true
+    modelpath: ${path.deps}/clip-vit-large-patch14
+  motion_condition_encoder:
+    name: actor_encoder
+    _target_: src.model.motionencoder.ActorAgnosticEncoder
+    latent_dim: ${model.latent_dim}
+    ff_size: ${model.ff_size}
+    num_layers: ${model.num_layers}
+    num_head: ${model.num_head}
+    droupout: ${model.droupout}
+    activation: ${model.activation}
+    nfeats: ${model.nfeats}
+  losses:
+    _target_: src.model.losses.MLDLosses
+    lmd_rfeats_recons: 1.0
+    lmd_jfeats_recons: 1.0
+    predict_epsilon: false
+    modelname: ${model.modelname}
+    lmd_latent: 1.0e-05
+    lmd_kl: 1.0e-05
+    lmd_prior: 0.0
+    lmd_recons: 1.0
+    lmd_gen: 1.0
+    fuse: concat
+    loss_on_both: true
+    loss_on_jfeats: false
+    ablation_no_kl_combine: false
+    ablation_no_kl_gaussian: false
+    ablation_no_motionencoder: false
+  optim:
+    _target_: torch.optim.AdamW
+    lr: 0.0001
+    lr_final: 1.0e-06
+    t_warmup: 150
+  func_recons:
+    _target_: src.model.losses.recons.Recons
+  func_latent:
+    _target_: src.model.losses.recons.Recons
+  func_kl:
+    _target_: src.model.losses.KLLoss
+machine:
+  name: server
+  batch_size: 64
+  smpl_batch_size: 64
+  num_workers: 8
+trainer:
+  strategy: auto
+  benchmark: true
+  max_epochs: 1001
+  accelerator: gpu
+  log_every_n_steps: 40
+  deterministic: false
+  detect_anomaly: false
+  enable_progress_bar: true
+  check_val_every_n_epoch: 100
+  limit_train_batches: 1.0
+  limit_val_batches: 1.0
+  num_sanity_val_steps: 0
+  precision: 32
+sampler:
+  _target_: src.data.sampling.FrameSampler
+  request_frames: 300
+  sampling: conseq
+  sampling_step: 1
+  threshold_reject: 0.75
+  max_len: 600
+  min_len: 15
+logger:
+  logger_name: wandb
+  name: ${experiment}-${run_id}
+  save_dir: wandb
+  project: ${project}
+  group: null
+  tags: null
+  notes: null
+  offline: false
+  resume: false
+  save_code: false
+  log_model: false
+callback:
+  last_ckpt:
+    _target_: pytorch_lightning.callbacks.ModelCheckpoint
+    dirpath: ${path.working_dir}/checkpoints
+    filename: latest-{epoch}
+    every_n_epochs: 1
+    save_top_k: 1
+    save_last: true
+  latest_ckpt:
+    _target_: pytorch_lightning.callbacks.ModelCheckpoint
+    dirpath: ${path.working_dir}/checkpoints
+    filename: latest-{epoch}
+    monitor: step
+    mode: max
+    every_n_epochs: 100
+    save_top_k: -1
+    save_last: false
+  progress:
+    _target_: src.callback.ProgressLogger
+  render:
+    _target_: src.callback.RenderCallback
+    every_n_epochs: 50
+    num_workers: ${machine.num_workers}
+    save_last: true
+    nvids_to_save: 3
+    bm_path: ${path.data}
+    modelname: ${model.modelname}
+  lr_logging:
+    _target_: pytorch_lightning.callbacks.LearningRateMonitor
+    logging_interval: epoch
+path:
+  deps: ${code_path:./deps}
+  data: ${code_path:./data}
+  minidata: ${code_path:./minidata}
+  code_dir: ${code_path:}
+  working_dir: ${working_path:""}
+  minilog: ${code_path:./miniexperiments}
+debug: false
+expdir: ${get_expdir:${debug}}
+experiment: final-model
+project: tuning-exps
+seed: 42
+logger_level: INFO
+run_id: bs64_ld512_ts200
+resume: null
+resume_ckpt_name: null
+renderer: pyrender
+watch_model: false
+log_freq: 1000
+log: all
+devices: 1
+ftune: null
+ftune_ckpt_name: last
+ftune_ckpt_path: ${get_last_checkpoint:${ftune},${ftune_ckpt_name}}
+statistics_file: statistics_${data.dataname}${get_debug:${debug}}.npy
+statistics_path: ${path.deps}/stats/${statistics_file}

bs_64_conf/.hydra/hydra.yaml

@@ -0,0 +1,217 @@
+hydra:
+  run:
+    dir: ${expdir}/${project}/${experiment}/${run_id}/
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+        datefmt: '%d/%m/%y %H:%M:%S'
+    handlers:
+      console:
+        class: rich.logging.RichHandler
+        formatter: colorlog
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    filters:
+      onlyimportant:
+        (): src.tools.logging.LevelsFilter
+        levels:
+        - CRITICAL
+        - ERROR
+        - WARNING
+      noimportant:
+        (): src.tools.logging.LevelsFilter
+        levels:
+        - INFO
+        - DEBUG
+        - NOTSET
+    formatters:
+      verysimple:
+        format: '%(message)s'
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+        datefmt: '%d/%m/%y %H:%M:%S'
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        datefmt: '%d/%m/%y %H:%M:%S'
+      log_colors:
+        DEBUG: purple
+        INFO: green
+        WARNING: yellow
+        ERROR: red
+        CRITICAL: red
+    handlers:
+      console:
+        class: rich.logging.RichHandler
+        formatter: verysimple
+        rich_tracebacks: true
+      file_out:
+        class: logging.FileHandler
+        formatter: simple
+        filename: logs.out
+        filters:
+        - noimportant
+      file_err:
+        class: logging.FileHandler
+        formatter: simple
+        filename: logs.err
+        filters:
+        - onlyimportant
+    root:
+      level: ${logger_level}
+      handlers:
+      - console
+      - file_out
+      - file_err
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - run_id=bs64_ld512_ts200
+    - trainer.strategy=auto
+    - devices=1
+    - machine.num_workers=8
+    - experiment=final-model
+    - machine.batch_size=64
+    - model.diff_params.num_train_timesteps=200
+    - model.latent_dim=256
+  job:
+    name: train
+    chdir: true
+    override_dirname: devices=1,experiment=final-model,machine.batch_size=64,machine.num_workers=8,model.diff_params.num_train_timesteps=200,model.latent_dim=256,run_id=bs64_ld512_ts200,trainer.strategy=auto
+    id: ???
+    num: ???
+    config_name: train
+    env_set:
+      WANDB_API_KEY: 90e13be46265667b13415a5e6d248ae91ab399fc
+      PYOPENGL_PLATFORM: egl
+      HYDRA_FULL_ERROR: '1'
+      WANDB__SERVICE_WAIT: '300'
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.2'
+    cwd: /lustre/home/nathanasiou/projects/tgm
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /lustre/home/nathanasiou/projects/tgm/configs
+      schema: file
+      provider: main
+    - path: hydra_plugins.hydra_colorlog.conf
+      schema: pkg
+      provider: hydra-colorlog
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /lustre/home/nathanasiou/projects/tgm/experiments/tuning-exps/final-model/bs64_ld512_ts200
+    choices:
+      callback: base
+      logger: wandb
+      sampler: variable_conseq
+      trainer: base
+      machine: server
+      model: basic_clip
+      model/optim: adamw
+      model/losses: basic
+      model/motion_condition_encoder: actor
+      model/text_encoder: clipenc
+      model/denoiser: denoiser
+      model/infer_scheduler: ddpm
+      model/train_scheduler: ddpm
+      data: motionfix
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: rich
+      hydra/hydra_logging: rich
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

bs_64_conf/.hydra/overrides.yaml

@@ -0,0 +1,8 @@
+- run_id=bs64_ld512_ts200
+- trainer.strategy=auto
+- devices=1
+- machine.num_workers=8
+- experiment=final-model
+- machine.batch_size=64
+- model.diff_params.num_train_timesteps=200
+- model.latent_dim=256