remove all runs due to results being not useful (error in loss function)

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/0/.hydra/config.yaml

@@ -1,66 +0,0 @@
-original_work_dir: ${hydra:runtime.cwd}
-data_dir: ${original_work_dir}/data
-print_config: true
-ignore_warnings: true
-train: true
-test: true
-seed: null
-name: focus150_optuna
-datamodule:
-  _target_: src.datamodules.focus_datamodule.FocusDataModule
-  data_dir: ${data_dir}/focus150
-  csv_file: ${data_dir}/focus150/metadata.csv
-  batch_size: 32
-  train_val_test_split_percentage:
-  - 0.7
-  - 0.15
-  - 0.15
-  num_workers: 0
-  pin_memory: false
-model:
-  _target_: src.models.focus_module.FocusLitModule
-  input_size: 67500
-  lin1_size: 128
-  lin2_size: 32
-  lin3_size: 32
-  output_size: 1
-  lr: 0.04099159968275264
-  weight_decay: 0.0005
-callbacks:
-  model_checkpoint:
-    _target_: pytorch_lightning.callbacks.ModelCheckpoint
-    monitor: val/mae
-    mode: min
-    save_top_k: 1
-    save_last: true
-    verbose: false
-    dirpath: checkpoints/
-    filename: epoch_{epoch:03d}
-    auto_insert_metric_name: false
-  early_stopping:
-    _target_: pytorch_lightning.callbacks.EarlyStopping
-    monitor: val/mae
-    mode: min
-    patience: 100
-    min_delta: 0
-  model_summary:
-    _target_: pytorch_lightning.callbacks.RichModelSummary
-    max_depth: -1
-  rich_progress_bar:
-    _target_: pytorch_lightning.callbacks.RichProgressBar
-logger:
-  tensorboard:
-    _target_: pytorch_lightning.loggers.tensorboard.TensorBoardLogger
-    save_dir: tensorboard/
-    name: null
-    version: ${name}
-    log_graph: false
-    default_hp_metric: true
-    prefix: ''
-trainer:
-  _target_: pytorch_lightning.Trainer
-  gpus: 1
-  min_epochs: 1
-  max_epochs: 100
-  resume_from_checkpoint: null
-optimized_metric: val/mae_best

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/0/.hydra/hydra.yaml

@@ -1,232 +0,0 @@
-hydra:
-  run:
-    dir: logs/experiments/runs/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
-  sweep:
-    dir: logs/experiments/multiruns/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
-    subdir: ${hydra.job.num}
-  launcher:
-    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
-  sweeper:
-    sampler:
-      _target_: optuna.samplers.TPESampler
-      seed: 12345
-      consider_prior: true
-      prior_weight: 1.0
-      consider_magic_clip: true
-      consider_endpoints: false
-      n_startup_trials: 10
-      n_ei_candidates: 24
-      multivariate: false
-      warn_independent_sampling: true
-    _target_: hydra_plugins.hydra_optuna_sweeper.optuna_sweeper.OptunaSweeper
-    direction: minimize
-    storage: null
-    study_name: focus150_hyperparameter_search
-    n_trials: 25
-    n_jobs: 1
-    search_space:
-      datamodule.batch_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-      model.lr:
-        type: float
-        low: 0.0001
-        high: 0.2
-      model.lin1_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-      model.lin2_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-      model.lin3_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-  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'
-    handlers:
-      console:
-        class: logging.StreamHandler
-        formatter: colorlog
-        stream: ext://sys.stdout
-    root:
-      level: INFO
-      handlers:
-      - console
-    disable_existing_loggers: false
-  job_logging:
-    version: 1
-    formatters:
-      simple:
-        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)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'
-        log_colors:
-          DEBUG: purple
-          INFO: green
-          WARNING: yellow
-          ERROR: red
-          CRITICAL: red
-    handlers:
-      console:
-        class: logging.StreamHandler
-        formatter: colorlog
-        stream: ext://sys.stdout
-      file:
-        class: logging.FileHandler
-        formatter: simple
-        filename: ${hydra.job.name}.log
-    root:
-      level: INFO
-      handlers:
-      - console
-      - file
-    disable_existing_loggers: false
-  env: {}
-  searchpath: []
-  callbacks: {}
-  output_subdir: .hydra
-  overrides:
-    hydra: []
-    task:
-    - datamodule.batch_size=32
-    - model.lr=0.04099159968275264
-    - model.lin1_size=128
-    - model.lin2_size=32
-    - model.lin3_size=32
-    - hparams_search=focus150_optuna
-  job:
-    name: train
-    override_dirname: datamodule.batch_size=32,hparams_search=focus150_optuna,model.lin1_size=128,model.lin2_size=32,model.lin3_size=32,model.lr=0.04099159968275264
-    id: '0'
-    num: 0
-    config_name: train.yaml
-    env_set: {}
-    env_copy: []
-    config:
-      override_dirname:
-        kv_sep: '='
-        item_sep: ','
-        exclude_keys: []
-  runtime:
-    version: 1.1.1
-    cwd: /usr/src/app
-    config_sources:
-    - path: hydra.conf
-      schema: pkg
-      provider: hydra
-    - path: /usr/src/app/configs
-      schema: file
-      provider: main
-    - path: hydra_plugins.hydra_colorlog.conf
-      schema: pkg
-      provider: hydra-colorlog
-    - path: ''
-      schema: structured
-      provider: schema
-    choices:
-      local: default.yaml
-      hparams_search: focus150_optuna
-      debug: null
-      experiment: null
-      log_dir: default.yaml
-      trainer: long.yaml
-      logger: tensorboard
-      callbacks: default.yaml
-      model: focus150.yaml
-      datamodule: focus150.yaml
-      hydra/env: default
-      hydra/callbacks: null
-      hydra/job_logging: colorlog
-      hydra/hydra_logging: colorlog
-      hydra/hydra_help: default
-      hydra/help: default
-      hydra/sweeper: optuna
-      hydra/sweeper/sampler: tpe
-      hydra/launcher: basic
-      hydra/output: default
-  verbose: false

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/0/.hydra/overrides.yaml

@@ -1,6 +0,0 @@
-- datamodule.batch_size=32
-- model.lr=0.04099159968275264
-- model.lin1_size=128
-- model.lin2_size=32
-- model.lin3_size=32
-- hparams_search=focus150_optuna

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/0/tensorboard/focus150_optuna/events.out.tfevents.1646393430.e02c2cd1d8ab.1.0

@@ -1,3 +0,0 @@
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-oid sha256:d6afc0f43b3c1bd7933f2a0e2d56b93f74680505b96c42a15f8970c35864b322
-size 36391

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/0/tensorboard/focus150_optuna/events.out.tfevents.1646393675.e02c2cd1d8ab.1.1

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:c7356d4d877d5517b1738d3fbb03153b84e6a6c09d506bbabbdffcebca279aba
-size 179

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/0/tensorboard/focus150_optuna/hparams.yaml

@@ -1,52 +0,0 @@
-trainer:
-  _target_: pytorch_lightning.Trainer
-  gpus: 1
-  min_epochs: 1
-  max_epochs: 100
-  resume_from_checkpoint: null
-model:
-  _target_: src.models.focus_module.FocusLitModule
-  input_size: 67500
-  lin1_size: 128
-  lin2_size: 32
-  lin3_size: 32
-  output_size: 1
-  lr: 0.04099159968275264
-  weight_decay: 0.0005
-datamodule:
-  _target_: src.datamodules.focus_datamodule.FocusDataModule
-  data_dir: /usr/src/app/data/focus150
-  csv_file: /usr/src/app/data/focus150/metadata.csv
-  batch_size: 32
-  train_val_test_split_percentage:
-  - 0.7
-  - 0.15
-  - 0.15
-  num_workers: 0
-  pin_memory: false
-seed: null
-callbacks:
-  model_checkpoint:
-    _target_: pytorch_lightning.callbacks.ModelCheckpoint
-    monitor: val/mae
-    mode: min
-    save_top_k: 1
-    save_last: true
-    verbose: false
-    dirpath: checkpoints/
-    filename: epoch_{epoch:03d}
-    auto_insert_metric_name: false
-  early_stopping:
-    _target_: pytorch_lightning.callbacks.EarlyStopping
-    monitor: val/mae
-    mode: min
-    patience: 100
-    min_delta: 0
-  model_summary:
-    _target_: pytorch_lightning.callbacks.RichModelSummary
-    max_depth: -1
-  rich_progress_bar:
-    _target_: pytorch_lightning.callbacks.RichProgressBar
-model/params/total: 8645729
-model/params/trainable: 8645729
-model/params/non_trainable: 0

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/1/.hydra/config.yaml

@@ -1,66 +0,0 @@
-original_work_dir: ${hydra:runtime.cwd}
-data_dir: ${original_work_dir}/data
-print_config: true
-ignore_warnings: true
-train: true
-test: true
-seed: null
-name: focus150_optuna
-datamodule:
-  _target_: src.datamodules.focus_datamodule.FocusDataModule
-  data_dir: ${data_dir}/focus150
-  csv_file: ${data_dir}/focus150/metadata.csv
-  batch_size: 64
-  train_val_test_split_percentage:
-  - 0.7
-  - 0.15
-  - 0.15
-  num_workers: 0
-  pin_memory: false
-model:
-  _target_: src.models.focus_module.FocusLitModule
-  input_size: 67500
-  lin1_size: 256
-  lin2_size: 128
-  lin3_size: 1024
-  output_size: 1
-  lr: 0.15818542131777294
-  weight_decay: 0.0005
-callbacks:
-  model_checkpoint:
-    _target_: pytorch_lightning.callbacks.ModelCheckpoint
-    monitor: val/mae
-    mode: min
-    save_top_k: 1
-    save_last: true
-    verbose: false
-    dirpath: checkpoints/
-    filename: epoch_{epoch:03d}
-    auto_insert_metric_name: false
-  early_stopping:
-    _target_: pytorch_lightning.callbacks.EarlyStopping
-    monitor: val/mae
-    mode: min
-    patience: 100
-    min_delta: 0
-  model_summary:
-    _target_: pytorch_lightning.callbacks.RichModelSummary
-    max_depth: -1
-  rich_progress_bar:
-    _target_: pytorch_lightning.callbacks.RichProgressBar
-logger:
-  tensorboard:
-    _target_: pytorch_lightning.loggers.tensorboard.TensorBoardLogger
-    save_dir: tensorboard/
-    name: null
-    version: ${name}
-    log_graph: false
-    default_hp_metric: true
-    prefix: ''
-trainer:
-  _target_: pytorch_lightning.Trainer
-  gpus: 1
-  min_epochs: 1
-  max_epochs: 100
-  resume_from_checkpoint: null
-optimized_metric: val/mae_best

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/1/.hydra/hydra.yaml

@@ -1,232 +0,0 @@
-hydra:
-  run:
-    dir: logs/experiments/runs/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
-  sweep:
-    dir: logs/experiments/multiruns/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
-    subdir: ${hydra.job.num}
-  launcher:
-    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
-  sweeper:
-    sampler:
-      _target_: optuna.samplers.TPESampler
-      seed: 12345
-      consider_prior: true
-      prior_weight: 1.0
-      consider_magic_clip: true
-      consider_endpoints: false
-      n_startup_trials: 10
-      n_ei_candidates: 24
-      multivariate: false
-      warn_independent_sampling: true
-    _target_: hydra_plugins.hydra_optuna_sweeper.optuna_sweeper.OptunaSweeper
-    direction: minimize
-    storage: null
-    study_name: focus150_hyperparameter_search
-    n_trials: 25
-    n_jobs: 1
-    search_space:
-      datamodule.batch_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-      model.lr:
-        type: float
-        low: 0.0001
-        high: 0.2
-      model.lin1_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-      model.lin2_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-      model.lin3_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-  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'
-    handlers:
-      console:
-        class: logging.StreamHandler
-        formatter: colorlog
-        stream: ext://sys.stdout
-    root:
-      level: INFO
-      handlers:
-      - console
-    disable_existing_loggers: false
-  job_logging:
-    version: 1
-    formatters:
-      simple:
-        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)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'
-        log_colors:
-          DEBUG: purple
-          INFO: green
-          WARNING: yellow
-          ERROR: red
-          CRITICAL: red
-    handlers:
-      console:
-        class: logging.StreamHandler
-        formatter: colorlog
-        stream: ext://sys.stdout
-      file:
-        class: logging.FileHandler
-        formatter: simple
-        filename: ${hydra.job.name}.log
-    root:
-      level: INFO
-      handlers:
-      - console
-      - file
-    disable_existing_loggers: false
-  env: {}
-  searchpath: []
-  callbacks: {}
-  output_subdir: .hydra
-  overrides:
-    hydra: []
-    task:
-    - datamodule.batch_size=64
-    - model.lr=0.15818542131777294
-    - model.lin1_size=256
-    - model.lin2_size=128
-    - model.lin3_size=1024
-    - hparams_search=focus150_optuna
-  job:
-    name: train
-    override_dirname: datamodule.batch_size=64,hparams_search=focus150_optuna,model.lin1_size=256,model.lin2_size=128,model.lin3_size=1024,model.lr=0.15818542131777294
-    id: '1'
-    num: 1
-    config_name: train.yaml
-    env_set: {}
-    env_copy: []
-    config:
-      override_dirname:
-        kv_sep: '='
-        item_sep: ','
-        exclude_keys: []
-  runtime:
-    version: 1.1.1
-    cwd: /usr/src/app
-    config_sources:
-    - path: hydra.conf
-      schema: pkg
-      provider: hydra
-    - path: /usr/src/app/configs
-      schema: file
-      provider: main
-    - path: hydra_plugins.hydra_colorlog.conf
-      schema: pkg
-      provider: hydra-colorlog
-    - path: ''
-      schema: structured
-      provider: schema
-    choices:
-      local: default.yaml
-      hparams_search: focus150_optuna
-      debug: null
-      experiment: null
-      log_dir: default.yaml
-      trainer: long.yaml
-      logger: tensorboard
-      callbacks: default.yaml
-      model: focus150.yaml
-      datamodule: focus150.yaml
-      hydra/env: default
-      hydra/callbacks: null
-      hydra/job_logging: colorlog
-      hydra/hydra_logging: colorlog
-      hydra/hydra_help: default
-      hydra/help: default
-      hydra/sweeper: optuna
-      hydra/sweeper/sampler: tpe
-      hydra/launcher: basic
-      hydra/output: default
-  verbose: false

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/1/.hydra/overrides.yaml

@@ -1,6 +0,0 @@
-- datamodule.batch_size=64
-- model.lr=0.15818542131777294
-- model.lin1_size=256
-- model.lin2_size=128
-- model.lin3_size=1024
-- hparams_search=focus150_optuna

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/1/tensorboard/focus150_optuna/events.out.tfevents.1646393676.e02c2cd1d8ab.1.2

@@ -1,3 +0,0 @@
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@@ -1,3 +0,0 @@
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logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/1/tensorboard/focus150_optuna/hparams.yaml

@@ -1,52 +0,0 @@
-trainer:
-  _target_: pytorch_lightning.Trainer
-  gpus: 1
-  min_epochs: 1
-  max_epochs: 100
-  resume_from_checkpoint: null
-model:
-  _target_: src.models.focus_module.FocusLitModule
-  input_size: 67500
-  lin1_size: 256
-  lin2_size: 128
-  lin3_size: 1024
-  output_size: 1
-  lr: 0.15818542131777294
-  weight_decay: 0.0005
-datamodule:
-  _target_: src.datamodules.focus_datamodule.FocusDataModule
-  data_dir: /usr/src/app/data/focus150
-  csv_file: /usr/src/app/data/focus150/metadata.csv
-  batch_size: 64
-  train_val_test_split_percentage:
-  - 0.7
-  - 0.15
-  - 0.15
-  num_workers: 0
-  pin_memory: false
-seed: null
-callbacks:
-  model_checkpoint:
-    _target_: pytorch_lightning.callbacks.ModelCheckpoint
-    monitor: val/mae
-    mode: min
-    save_top_k: 1
-    save_last: true
-    verbose: false
-    dirpath: checkpoints/
-    filename: epoch_{epoch:03d}
-    auto_insert_metric_name: false
-  early_stopping:
-    _target_: pytorch_lightning.callbacks.EarlyStopping
-    monitor: val/mae
-    mode: min
-    patience: 100
-    min_delta: 0
-  model_summary:
-    _target_: pytorch_lightning.callbacks.RichModelSummary
-    max_depth: -1
-  rich_progress_bar:
-    _target_: pytorch_lightning.callbacks.RichProgressBar
-model/params/total: 17449089
-model/params/trainable: 17449089
-model/params/non_trainable: 0

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/10/.hydra/config.yaml

@@ -1,66 +0,0 @@
-original_work_dir: ${hydra:runtime.cwd}
-data_dir: ${original_work_dir}/data
-print_config: true
-ignore_warnings: true
-train: true
-test: true
-seed: null
-name: focus150_optuna
-datamodule:
-  _target_: src.datamodules.focus_datamodule.FocusDataModule
-  data_dir: ${data_dir}/focus150
-  csv_file: ${data_dir}/focus150/metadata.csv
-  batch_size: 128
-  train_val_test_split_percentage:
-  - 0.7
-  - 0.15
-  - 0.15
-  num_workers: 0
-  pin_memory: false
-model:
-  _target_: src.models.focus_module.FocusLitModule
-  input_size: 67500
-  lin1_size: 512
-  lin2_size: 512
-  lin3_size: 256
-  output_size: 1
-  lr: 0.07148210917089061
-  weight_decay: 0.0005
-callbacks:
-  model_checkpoint:
-    _target_: pytorch_lightning.callbacks.ModelCheckpoint
-    monitor: val/mae
-    mode: min
-    save_top_k: 1
-    save_last: true
-    verbose: false
-    dirpath: checkpoints/
-    filename: epoch_{epoch:03d}
-    auto_insert_metric_name: false
-  early_stopping:
-    _target_: pytorch_lightning.callbacks.EarlyStopping
-    monitor: val/mae
-    mode: min
-    patience: 100
-    min_delta: 0
-  model_summary:
-    _target_: pytorch_lightning.callbacks.RichModelSummary
-    max_depth: -1
-  rich_progress_bar:
-    _target_: pytorch_lightning.callbacks.RichProgressBar
-logger:
-  tensorboard:
-    _target_: pytorch_lightning.loggers.tensorboard.TensorBoardLogger
-    save_dir: tensorboard/
-    name: null
-    version: ${name}
-    log_graph: false
-    default_hp_metric: true
-    prefix: ''
-trainer:
-  _target_: pytorch_lightning.Trainer
-  gpus: 1
-  min_epochs: 1
-  max_epochs: 100
-  resume_from_checkpoint: null
-optimized_metric: val/mae_best

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/10/.hydra/hydra.yaml

@@ -1,232 +0,0 @@
-hydra:
-  run:
-    dir: logs/experiments/runs/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
-  sweep:
-    dir: logs/experiments/multiruns/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
-    subdir: ${hydra.job.num}
-  launcher:
-    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
-  sweeper:
-    sampler:
-      _target_: optuna.samplers.TPESampler
-      seed: 12345
-      consider_prior: true
-      prior_weight: 1.0
-      consider_magic_clip: true
-      consider_endpoints: false
-      n_startup_trials: 10
-      n_ei_candidates: 24
-      multivariate: false
-      warn_independent_sampling: true
-    _target_: hydra_plugins.hydra_optuna_sweeper.optuna_sweeper.OptunaSweeper
-    direction: minimize
-    storage: null
-    study_name: focus150_hyperparameter_search
-    n_trials: 25
-    n_jobs: 1
-    search_space:
-      datamodule.batch_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-      model.lr:
-        type: float
-        low: 0.0001
-        high: 0.2
-      model.lin1_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-      model.lin2_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-      model.lin3_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-  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'
-    handlers:
-      console:
-        class: logging.StreamHandler
-        formatter: colorlog
-        stream: ext://sys.stdout
-    root:
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-      handlers:
-      - console
-    disable_existing_loggers: false
-  job_logging:
-    version: 1
-    formatters:
-      simple:
-        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)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'
-        log_colors:
-          DEBUG: purple
-          INFO: green
-          WARNING: yellow
-          ERROR: red
-          CRITICAL: red
-    handlers:
-      console:
-        class: logging.StreamHandler
-        formatter: colorlog
-        stream: ext://sys.stdout
-      file:
-        class: logging.FileHandler
-        formatter: simple
-        filename: ${hydra.job.name}.log
-    root:
-      level: INFO
-      handlers:
-      - console
-      - file
-    disable_existing_loggers: false
-  env: {}
-  searchpath: []
-  callbacks: {}
-  output_subdir: .hydra
-  overrides:
-    hydra: []
-    task:
-    - datamodule.batch_size=128
-    - model.lr=0.07148210917089061
-    - model.lin1_size=512
-    - model.lin2_size=512
-    - model.lin3_size=256
-    - hparams_search=focus150_optuna
-  job:
-    name: train
-    override_dirname: datamodule.batch_size=128,hparams_search=focus150_optuna,model.lin1_size=512,model.lin2_size=512,model.lin3_size=256,model.lr=0.07148210917089061
-    id: '10'
-    num: 10
-    config_name: train.yaml
-    env_set: {}
-    env_copy: []
-    config:
-      override_dirname:
-        kv_sep: '='
-        item_sep: ','
-        exclude_keys: []
-  runtime:
-    version: 1.1.1
-    cwd: /usr/src/app
-    config_sources:
-    - path: hydra.conf
-      schema: pkg
-      provider: hydra
-    - path: /usr/src/app/configs
-      schema: file
-      provider: main
-    - path: hydra_plugins.hydra_colorlog.conf
-      schema: pkg
-      provider: hydra-colorlog
-    - path: ''
-      schema: structured
-      provider: schema
-    choices:
-      local: default.yaml
-      hparams_search: focus150_optuna
-      debug: null
-      experiment: null
-      log_dir: default.yaml
-      trainer: long.yaml
-      logger: tensorboard
-      callbacks: default.yaml
-      model: focus150.yaml
-      datamodule: focus150.yaml
-      hydra/env: default
-      hydra/callbacks: null
-      hydra/job_logging: colorlog
-      hydra/hydra_logging: colorlog
-      hydra/hydra_help: default
-      hydra/help: default
-      hydra/sweeper: optuna
-      hydra/sweeper/sampler: tpe
-      hydra/launcher: basic
-      hydra/output: default
-  verbose: false

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/10/.hydra/overrides.yaml

@@ -1,6 +0,0 @@
-- datamodule.batch_size=128
-- model.lr=0.07148210917089061
-- model.lin1_size=512
-- model.lin2_size=512
-- model.lin3_size=256
-- hparams_search=focus150_optuna

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/10/tensorboard/focus150_optuna/events.out.tfevents.1646399561.e02c2cd1d8ab.1.19

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logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/10/tensorboard/focus150_optuna/hparams.yaml

@@ -1,52 +0,0 @@
-trainer:
-  _target_: pytorch_lightning.Trainer
-  gpus: 1
-  min_epochs: 1
-  max_epochs: 100
-  resume_from_checkpoint: null
-model:
-  _target_: src.models.focus_module.FocusLitModule
-  input_size: 67500
-  lin1_size: 512
-  lin2_size: 512
-  lin3_size: 256
-  output_size: 1
-  lr: 0.07148210917089061
-  weight_decay: 0.0005
-datamodule:
-  _target_: src.datamodules.focus_datamodule.FocusDataModule
-  data_dir: /usr/src/app/data/focus150
-  csv_file: /usr/src/app/data/focus150/metadata.csv
-  batch_size: 128
-  train_val_test_split_percentage:
-  - 0.7
-  - 0.15
-  - 0.15
-  num_workers: 0
-  pin_memory: false
-seed: null
-callbacks:
-  model_checkpoint:
-    _target_: pytorch_lightning.callbacks.ModelCheckpoint
-    monitor: val/mae
-    mode: min
-    save_top_k: 1
-    save_last: true
-    verbose: false
-    dirpath: checkpoints/
-    filename: epoch_{epoch:03d}
-    auto_insert_metric_name: false
-  early_stopping:
-    _target_: pytorch_lightning.callbacks.EarlyStopping
-    monitor: val/mae
-    mode: min
-    patience: 100
-    min_delta: 0
-  model_summary:
-    _target_: pytorch_lightning.callbacks.RichModelSummary
-    max_depth: -1
-  rich_progress_bar:
-    _target_: pytorch_lightning.callbacks.RichProgressBar
-model/params/total: 34957313
-model/params/trainable: 34957313
-model/params/non_trainable: 0

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/11/.hydra/config.yaml

@@ -1,66 +0,0 @@
-original_work_dir: ${hydra:runtime.cwd}
-data_dir: ${original_work_dir}/data
-print_config: true
-ignore_warnings: true
-train: true
-test: true
-seed: null
-name: focus150_optuna
-datamodule:
-  _target_: src.datamodules.focus_datamodule.FocusDataModule
-  data_dir: ${data_dir}/focus150
-  csv_file: ${data_dir}/focus150/metadata.csv
-  batch_size: 64
-  train_val_test_split_percentage:
-  - 0.7
-  - 0.15
-  - 0.15
-  num_workers: 0
-  pin_memory: false
-model:
-  _target_: src.models.focus_module.FocusLitModule
-  input_size: 67500
-  lin1_size: 32
-  lin2_size: 256
-  lin3_size: 128
-  output_size: 1
-  lr: 0.11779269530261958
-  weight_decay: 0.0005
-callbacks:
-  model_checkpoint:
-    _target_: pytorch_lightning.callbacks.ModelCheckpoint
-    monitor: val/mae
-    mode: min
-    save_top_k: 1
-    save_last: true
-    verbose: false
-    dirpath: checkpoints/
-    filename: epoch_{epoch:03d}
-    auto_insert_metric_name: false
-  early_stopping:
-    _target_: pytorch_lightning.callbacks.EarlyStopping
-    monitor: val/mae
-    mode: min
-    patience: 100
-    min_delta: 0
-  model_summary:
-    _target_: pytorch_lightning.callbacks.RichModelSummary
-    max_depth: -1
-  rich_progress_bar:
-    _target_: pytorch_lightning.callbacks.RichProgressBar
-logger:
-  tensorboard:
-    _target_: pytorch_lightning.loggers.tensorboard.TensorBoardLogger
-    save_dir: tensorboard/
-    name: null
-    version: ${name}
-    log_graph: false
-    default_hp_metric: true
-    prefix: ''
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-  _target_: pytorch_lightning.Trainer
-  gpus: 1
-  min_epochs: 1
-  max_epochs: 100
-  resume_from_checkpoint: null
-optimized_metric: val/mae_best

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/11/.hydra/hydra.yaml

@@ -1,232 +0,0 @@
-hydra:
-  run:
-    dir: logs/experiments/runs/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
-  sweep:
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-    subdir: ${hydra.job.num}
-  launcher:
-    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
-  sweeper:
-    sampler:
-      _target_: optuna.samplers.TPESampler
-      seed: 12345
-      consider_prior: true
-      prior_weight: 1.0
-      consider_magic_clip: true
-      consider_endpoints: false
-      n_startup_trials: 10
-      n_ei_candidates: 24
-      multivariate: false
-      warn_independent_sampling: true
-    _target_: hydra_plugins.hydra_optuna_sweeper.optuna_sweeper.OptunaSweeper
-    direction: minimize
-    storage: null
-    study_name: focus150_hyperparameter_search
-    n_trials: 25
-    n_jobs: 1
-    search_space:
-      datamodule.batch_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-      model.lr:
-        type: float
-        low: 0.0001
-        high: 0.2
-      model.lin1_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-      model.lin2_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-      model.lin3_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-  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'
-    handlers:
-      console:
-        class: logging.StreamHandler
-        formatter: colorlog
-        stream: ext://sys.stdout
-    root:
-      level: INFO
-      handlers:
-      - console
-    disable_existing_loggers: false
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-    version: 1
-    formatters:
-      simple:
-        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)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'
-        log_colors:
-          DEBUG: purple
-          INFO: green
-          WARNING: yellow
-          ERROR: red
-          CRITICAL: red
-    handlers:
-      console:
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-        formatter: colorlog
-        stream: ext://sys.stdout
-      file:
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-        formatter: simple
-        filename: ${hydra.job.name}.log
-    root:
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-      - console
-      - file
-    disable_existing_loggers: false
-  env: {}
-  searchpath: []
-  callbacks: {}
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-  overrides:
-    hydra: []
-    task:
-    - datamodule.batch_size=64
-    - model.lr=0.11779269530261958
-    - model.lin1_size=32
-    - model.lin2_size=256
-    - model.lin3_size=128
-    - hparams_search=focus150_optuna
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-    name: train
-    override_dirname: datamodule.batch_size=64,hparams_search=focus150_optuna,model.lin1_size=32,model.lin2_size=256,model.lin3_size=128,model.lr=0.11779269530261958
-    id: '11'
-    num: 11
-    config_name: train.yaml
-    env_set: {}
-    env_copy: []
-    config:
-      override_dirname:
-        kv_sep: '='
-        item_sep: ','
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-  runtime:
-    version: 1.1.1
-    cwd: /usr/src/app
-    config_sources:
-    - path: hydra.conf
-      schema: pkg
-      provider: hydra
-    - path: /usr/src/app/configs
-      schema: file
-      provider: main
-    - path: hydra_plugins.hydra_colorlog.conf
-      schema: pkg
-      provider: hydra-colorlog
-    - path: ''
-      schema: structured
-      provider: schema
-    choices:
-      local: default.yaml
-      hparams_search: focus150_optuna
-      debug: null
-      experiment: null
-      log_dir: default.yaml
-      trainer: long.yaml
-      logger: tensorboard
-      callbacks: default.yaml
-      model: focus150.yaml
-      datamodule: focus150.yaml
-      hydra/env: default
-      hydra/callbacks: null
-      hydra/job_logging: colorlog
-      hydra/hydra_logging: colorlog
-      hydra/hydra_help: default
-      hydra/help: default
-      hydra/sweeper: optuna
-      hydra/sweeper/sampler: tpe
-      hydra/launcher: basic
-      hydra/output: default
-  verbose: false

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/11/.hydra/overrides.yaml

@@ -1,6 +0,0 @@
-- datamodule.batch_size=64
-- model.lr=0.11779269530261958
-- model.lin1_size=32
-- model.lin2_size=256
-- model.lin3_size=128
-- hparams_search=focus150_optuna

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/11/tensorboard/focus150_optuna/events.out.tfevents.1646400251.e02c2cd1d8ab.1.21

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logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/11/tensorboard/focus150_optuna/hparams.yaml

@@ -1,52 +0,0 @@
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-  _target_: pytorch_lightning.Trainer
-  gpus: 1
-  min_epochs: 1
-  max_epochs: 100
-  resume_from_checkpoint: null
-model:
-  _target_: src.models.focus_module.FocusLitModule
-  input_size: 67500
-  lin1_size: 32
-  lin2_size: 256
-  lin3_size: 128
-  output_size: 1
-  lr: 0.11779269530261958
-  weight_decay: 0.0005
-datamodule:
-  _target_: src.datamodules.focus_datamodule.FocusDataModule
-  data_dir: /usr/src/app/data/focus150
-  csv_file: /usr/src/app/data/focus150/metadata.csv
-  batch_size: 64
-  train_val_test_split_percentage:
-  - 0.7
-  - 0.15
-  - 0.15
-  num_workers: 0
-  pin_memory: false
-seed: null
-callbacks:
-  model_checkpoint:
-    _target_: pytorch_lightning.callbacks.ModelCheckpoint
-    monitor: val/mae
-    mode: min
-    save_top_k: 1
-    save_last: true
-    verbose: false
-    dirpath: checkpoints/
-    filename: epoch_{epoch:03d}
-    auto_insert_metric_name: false
-  early_stopping:
-    _target_: pytorch_lightning.callbacks.EarlyStopping
-    monitor: val/mae
-    mode: min
-    patience: 100
-    min_delta: 0
-  model_summary:
-    _target_: pytorch_lightning.callbacks.RichModelSummary
-    max_depth: -1
-  rich_progress_bar:
-    _target_: pytorch_lightning.callbacks.RichProgressBar
-model/params/total: 2202337
-model/params/trainable: 2202337
-model/params/non_trainable: 0

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/12/.hydra/config.yaml

@@ -1,66 +0,0 @@
-original_work_dir: ${hydra:runtime.cwd}
-data_dir: ${original_work_dir}/data
-print_config: true
-ignore_warnings: true
-train: true
-test: true
-seed: null
-name: focus150_optuna
-datamodule:
-  _target_: src.datamodules.focus_datamodule.FocusDataModule
-  data_dir: ${data_dir}/focus150
-  csv_file: ${data_dir}/focus150/metadata.csv
-  batch_size: 64
-  train_val_test_split_percentage:
-  - 0.7
-  - 0.15
-  - 0.15
-  num_workers: 0
-  pin_memory: false
-model:
-  _target_: src.models.focus_module.FocusLitModule
-  input_size: 67500
-  lin1_size: 32
-  lin2_size: 256
-  lin3_size: 128
-  output_size: 1
-  lr: 0.13355237942960652
-  weight_decay: 0.0005
-callbacks:
-  model_checkpoint:
-    _target_: pytorch_lightning.callbacks.ModelCheckpoint
-    monitor: val/mae
-    mode: min
-    save_top_k: 1
-    save_last: true
-    verbose: false
-    dirpath: checkpoints/
-    filename: epoch_{epoch:03d}
-    auto_insert_metric_name: false
-  early_stopping:
-    _target_: pytorch_lightning.callbacks.EarlyStopping
-    monitor: val/mae
-    mode: min
-    patience: 100
-    min_delta: 0
-  model_summary:
-    _target_: pytorch_lightning.callbacks.RichModelSummary
-    max_depth: -1
-  rich_progress_bar:
-    _target_: pytorch_lightning.callbacks.RichProgressBar
-logger:
-  tensorboard:
-    _target_: pytorch_lightning.loggers.tensorboard.TensorBoardLogger
-    save_dir: tensorboard/
-    name: null
-    version: ${name}
-    log_graph: false
-    default_hp_metric: true
-    prefix: ''
-trainer:
-  _target_: pytorch_lightning.Trainer
-  gpus: 1
-  min_epochs: 1
-  max_epochs: 100
-  resume_from_checkpoint: null
-optimized_metric: val/mae_best

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/12/.hydra/hydra.yaml

@@ -1,232 +0,0 @@
-hydra:
-  run:
-    dir: logs/experiments/runs/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
-  sweep:
-    dir: logs/experiments/multiruns/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
-    subdir: ${hydra.job.num}
-  launcher:
-    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
-  sweeper:
-    sampler:
-      _target_: optuna.samplers.TPESampler
-      seed: 12345
-      consider_prior: true
-      prior_weight: 1.0
-      consider_magic_clip: true
-      consider_endpoints: false
-      n_startup_trials: 10
-      n_ei_candidates: 24
-      multivariate: false
-      warn_independent_sampling: true
-    _target_: hydra_plugins.hydra_optuna_sweeper.optuna_sweeper.OptunaSweeper
-    direction: minimize
-    storage: null
-    study_name: focus150_hyperparameter_search
-    n_trials: 25
-    n_jobs: 1
-    search_space:
-      datamodule.batch_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-      model.lr:
-        type: float
-        low: 0.0001
-        high: 0.2
-      model.lin1_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-      model.lin2_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-      model.lin3_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-  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'
-    handlers:
-      console:
-        class: logging.StreamHandler
-        formatter: colorlog
-        stream: ext://sys.stdout
-    root:
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-      - console
-    disable_existing_loggers: false
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-    formatters:
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-        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)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'
-        log_colors:
-          DEBUG: purple
-          INFO: green
-          WARNING: yellow
-          ERROR: red
-          CRITICAL: red
-    handlers:
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-        formatter: colorlog
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-        formatter: simple
-        filename: ${hydra.job.name}.log
-    root:
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-      - file
-    disable_existing_loggers: false
-  env: {}
-  searchpath: []
-  callbacks: {}
-  output_subdir: .hydra
-  overrides:
-    hydra: []
-    task:
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-    - model.lr=0.13355237942960652
-    - model.lin1_size=32
-    - model.lin2_size=256
-    - model.lin3_size=128
-    - hparams_search=focus150_optuna
-  job:
-    name: train
-    override_dirname: datamodule.batch_size=64,hparams_search=focus150_optuna,model.lin1_size=32,model.lin2_size=256,model.lin3_size=128,model.lr=0.13355237942960652
-    id: '12'
-    num: 12
-    config_name: train.yaml
-    env_set: {}
-    env_copy: []
-    config:
-      override_dirname:
-        kv_sep: '='
-        item_sep: ','
-        exclude_keys: []
-  runtime:
-    version: 1.1.1
-    cwd: /usr/src/app
-    config_sources:
-    - path: hydra.conf
-      schema: pkg
-      provider: hydra
-    - path: /usr/src/app/configs
-      schema: file
-      provider: main
-    - path: hydra_plugins.hydra_colorlog.conf
-      schema: pkg
-      provider: hydra-colorlog
-    - path: ''
-      schema: structured
-      provider: schema
-    choices:
-      local: default.yaml
-      hparams_search: focus150_optuna
-      debug: null
-      experiment: null
-      log_dir: default.yaml
-      trainer: long.yaml
-      logger: tensorboard
-      callbacks: default.yaml
-      model: focus150.yaml
-      datamodule: focus150.yaml
-      hydra/env: default
-      hydra/callbacks: null
-      hydra/job_logging: colorlog
-      hydra/hydra_logging: colorlog
-      hydra/hydra_help: default
-      hydra/help: default
-      hydra/sweeper: optuna
-      hydra/sweeper/sampler: tpe
-      hydra/launcher: basic
-      hydra/output: default
-  verbose: false

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/12/.hydra/overrides.yaml

@@ -1,6 +0,0 @@
-- datamodule.batch_size=64
-- model.lr=0.13355237942960652
-- model.lin1_size=32
-- model.lin2_size=256
-- model.lin3_size=128
-- hparams_search=focus150_optuna

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/12/tensorboard/focus150_optuna/events.out.tfevents.1646400341.e02c2cd1d8ab.1.23

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logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/12/tensorboard/focus150_optuna/hparams.yaml

@@ -1,52 +0,0 @@
-trainer:
-  _target_: pytorch_lightning.Trainer
-  gpus: 1
-  min_epochs: 1
-  max_epochs: 100
-  resume_from_checkpoint: null
-model:
-  _target_: src.models.focus_module.FocusLitModule
-  input_size: 67500
-  lin1_size: 32
-  lin2_size: 256
-  lin3_size: 128
-  output_size: 1
-  lr: 0.13355237942960652
-  weight_decay: 0.0005
-datamodule:
-  _target_: src.datamodules.focus_datamodule.FocusDataModule
-  data_dir: /usr/src/app/data/focus150
-  csv_file: /usr/src/app/data/focus150/metadata.csv
-  batch_size: 64
-  train_val_test_split_percentage:
-  - 0.7
-  - 0.15
-  - 0.15
-  num_workers: 0
-  pin_memory: false
-seed: null
-callbacks:
-  model_checkpoint:
-    _target_: pytorch_lightning.callbacks.ModelCheckpoint
-    monitor: val/mae
-    mode: min
-    save_top_k: 1
-    save_last: true
-    verbose: false
-    dirpath: checkpoints/
-    filename: epoch_{epoch:03d}
-    auto_insert_metric_name: false
-  early_stopping:
-    _target_: pytorch_lightning.callbacks.EarlyStopping
-    monitor: val/mae
-    mode: min
-    patience: 100
-    min_delta: 0
-  model_summary:
-    _target_: pytorch_lightning.callbacks.RichModelSummary
-    max_depth: -1
-  rich_progress_bar:
-    _target_: pytorch_lightning.callbacks.RichProgressBar
-model/params/total: 2202337
-model/params/trainable: 2202337
-model/params/non_trainable: 0

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/13/.hydra/config.yaml

@@ -1,66 +0,0 @@
-original_work_dir: ${hydra:runtime.cwd}
-data_dir: ${original_work_dir}/data
-print_config: true
-ignore_warnings: true
-train: true
-test: true
-seed: null
-name: focus150_optuna
-datamodule:
-  _target_: src.datamodules.focus_datamodule.FocusDataModule
-  data_dir: ${data_dir}/focus150
-  csv_file: ${data_dir}/focus150/metadata.csv
-  batch_size: 128
-  train_val_test_split_percentage:
-  - 0.7
-  - 0.15
-  - 0.15
-  num_workers: 0
-  pin_memory: false
-model:
-  _target_: src.models.focus_module.FocusLitModule
-  input_size: 67500
-  lin1_size: 32
-  lin2_size: 512
-  lin3_size: 2048
-  output_size: 1
-  lr: 0.07220274494059103
-  weight_decay: 0.0005
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-  model_checkpoint:
-    _target_: pytorch_lightning.callbacks.ModelCheckpoint
-    monitor: val/mae
-    mode: min
-    save_top_k: 1
-    save_last: true
-    verbose: false
-    dirpath: checkpoints/
-    filename: epoch_{epoch:03d}
-    auto_insert_metric_name: false
-  early_stopping:
-    _target_: pytorch_lightning.callbacks.EarlyStopping
-    monitor: val/mae
-    mode: min
-    patience: 100
-    min_delta: 0
-  model_summary:
-    _target_: pytorch_lightning.callbacks.RichModelSummary
-    max_depth: -1
-  rich_progress_bar:
-    _target_: pytorch_lightning.callbacks.RichProgressBar
-logger:
-  tensorboard:
-    _target_: pytorch_lightning.loggers.tensorboard.TensorBoardLogger
-    save_dir: tensorboard/
-    name: null
-    version: ${name}
-    log_graph: false
-    default_hp_metric: true
-    prefix: ''
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-  _target_: pytorch_lightning.Trainer
-  gpus: 1
-  min_epochs: 1
-  max_epochs: 100
-  resume_from_checkpoint: null
-optimized_metric: val/mae_best

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/13/.hydra/hydra.yaml

@@ -1,232 +0,0 @@
-hydra:
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-    dir: logs/experiments/runs/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
-  sweep:
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-    subdir: ${hydra.job.num}
-  launcher:
-    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
-  sweeper:
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-      _target_: optuna.samplers.TPESampler
-      seed: 12345
-      consider_prior: true
-      prior_weight: 1.0
-      consider_magic_clip: true
-      consider_endpoints: false
-      n_startup_trials: 10
-      n_ei_candidates: 24
-      multivariate: false
-      warn_independent_sampling: true
-    _target_: hydra_plugins.hydra_optuna_sweeper.optuna_sweeper.OptunaSweeper
-    direction: minimize
-    storage: null
-    study_name: focus150_hyperparameter_search
-    n_trials: 25
-    n_jobs: 1
-    search_space:
-      datamodule.batch_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-      model.lr:
-        type: float
-        low: 0.0001
-        high: 0.2
-      model.lin1_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-      model.lin2_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-      model.lin3_size:
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-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-  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'
-    handlers:
-      console:
-        class: logging.StreamHandler
-        formatter: colorlog
-        stream: ext://sys.stdout
-    root:
-      level: INFO
-      handlers:
-      - console
-    disable_existing_loggers: false
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-    formatters:
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-        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)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'
-        log_colors:
-          DEBUG: purple
-          INFO: green
-          WARNING: yellow
-          ERROR: red
-          CRITICAL: red
-    handlers:
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-        formatter: colorlog
-        stream: ext://sys.stdout
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-    root:
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-  env: {}
-  searchpath: []
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-    hydra: []
-    task:
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-    - model.lr=0.07220274494059103
-    - model.lin1_size=32
-    - model.lin2_size=512
-    - model.lin3_size=2048
-    - hparams_search=focus150_optuna
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-    id: '13'
-    num: 13
-    config_name: train.yaml
-    env_set: {}
-    env_copy: []
-    config:
-      override_dirname:
-        kv_sep: '='
-        item_sep: ','
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-  runtime:
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-    cwd: /usr/src/app
-    config_sources:
-    - path: hydra.conf
-      schema: pkg
-      provider: hydra
-    - path: /usr/src/app/configs
-      schema: file
-      provider: main
-    - path: hydra_plugins.hydra_colorlog.conf
-      schema: pkg
-      provider: hydra-colorlog
-    - path: ''
-      schema: structured
-      provider: schema
-    choices:
-      local: default.yaml
-      hparams_search: focus150_optuna
-      debug: null
-      experiment: null
-      log_dir: default.yaml
-      trainer: long.yaml
-      logger: tensorboard
-      callbacks: default.yaml
-      model: focus150.yaml
-      datamodule: focus150.yaml
-      hydra/env: default
-      hydra/callbacks: null
-      hydra/job_logging: colorlog
-      hydra/hydra_logging: colorlog
-      hydra/hydra_help: default
-      hydra/help: default
-      hydra/sweeper: optuna
-      hydra/sweeper/sampler: tpe
-      hydra/launcher: basic
-      hydra/output: default
-  verbose: false

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/13/.hydra/overrides.yaml

@@ -1,6 +0,0 @@
-- datamodule.batch_size=128
-- model.lr=0.07220274494059103
-- model.lin1_size=32
-- model.lin2_size=512
-- model.lin3_size=2048
-- hparams_search=focus150_optuna

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/13/tensorboard/focus150_optuna/events.out.tfevents.1646400436.e02c2cd1d8ab.1.25

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logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/13/tensorboard/focus150_optuna/hparams.yaml

@@ -1,52 +0,0 @@
-trainer:
-  _target_: pytorch_lightning.Trainer
-  gpus: 1
-  min_epochs: 1
-  max_epochs: 100
-  resume_from_checkpoint: null
-model:
-  _target_: src.models.focus_module.FocusLitModule
-  input_size: 67500
-  lin1_size: 32
-  lin2_size: 512
-  lin3_size: 2048
-  output_size: 1
-  lr: 0.07220274494059103
-  weight_decay: 0.0005
-datamodule:
-  _target_: src.datamodules.focus_datamodule.FocusDataModule
-  data_dir: /usr/src/app/data/focus150
-  csv_file: /usr/src/app/data/focus150/metadata.csv
-  batch_size: 128
-  train_val_test_split_percentage:
-  - 0.7
-  - 0.15
-  - 0.15
-  num_workers: 0
-  pin_memory: false
-seed: null
-callbacks:
-  model_checkpoint:
-    _target_: pytorch_lightning.callbacks.ModelCheckpoint
-    monitor: val/mae
-    mode: min
-    save_top_k: 1
-    save_last: true
-    verbose: false
-    dirpath: checkpoints/
-    filename: epoch_{epoch:03d}
-    auto_insert_metric_name: false
-  early_stopping:
-    _target_: pytorch_lightning.callbacks.EarlyStopping
-    monitor: val/mae
-    mode: min
-    patience: 100
-    min_delta: 0
-  model_summary:
-    _target_: pytorch_lightning.callbacks.RichModelSummary
-    max_depth: -1
-  rich_progress_bar:
-    _target_: pytorch_lightning.callbacks.RichProgressBar
-model/params/total: 3234785
-model/params/trainable: 3234785
-model/params/non_trainable: 0

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/14/.hydra/config.yaml

@@ -1,66 +0,0 @@
-original_work_dir: ${hydra:runtime.cwd}
-data_dir: ${original_work_dir}/data
-print_config: true
-ignore_warnings: true
-train: true
-test: true
-seed: null
-name: focus150_optuna
-datamodule:
-  _target_: src.datamodules.focus_datamodule.FocusDataModule
-  data_dir: ${data_dir}/focus150
-  csv_file: ${data_dir}/focus150/metadata.csv
-  batch_size: 128
-  train_val_test_split_percentage:
-  - 0.7
-  - 0.15
-  - 0.15
-  num_workers: 0
-  pin_memory: false
-model:
-  _target_: src.models.focus_module.FocusLitModule
-  input_size: 67500
-  lin1_size: 2048
-  lin2_size: 512
-  lin3_size: 128
-  output_size: 1
-  lr: 0.08335231197967785
-  weight_decay: 0.0005
-callbacks:
-  model_checkpoint:
-    _target_: pytorch_lightning.callbacks.ModelCheckpoint
-    monitor: val/mae
-    mode: min
-    save_top_k: 1
-    save_last: true
-    verbose: false
-    dirpath: checkpoints/
-    filename: epoch_{epoch:03d}
-    auto_insert_metric_name: false
-  early_stopping:
-    _target_: pytorch_lightning.callbacks.EarlyStopping
-    monitor: val/mae
-    mode: min
-    patience: 100
-    min_delta: 0
-  model_summary:
-    _target_: pytorch_lightning.callbacks.RichModelSummary
-    max_depth: -1
-  rich_progress_bar:
-    _target_: pytorch_lightning.callbacks.RichProgressBar
-logger:
-  tensorboard:
-    _target_: pytorch_lightning.loggers.tensorboard.TensorBoardLogger
-    save_dir: tensorboard/
-    name: null
-    version: ${name}
-    log_graph: false
-    default_hp_metric: true
-    prefix: ''
-trainer:
-  _target_: pytorch_lightning.Trainer
-  gpus: 1
-  min_epochs: 1
-  max_epochs: 100
-  resume_from_checkpoint: null
-optimized_metric: val/mae_best

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/14/.hydra/hydra.yaml

@@ -1,232 +0,0 @@
-hydra:
-  run:
-    dir: logs/experiments/runs/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
-  sweep:
-    dir: logs/experiments/multiruns/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
-    subdir: ${hydra.job.num}
-  launcher:
-    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
-  sweeper:
-    sampler:
-      _target_: optuna.samplers.TPESampler
-      seed: 12345
-      consider_prior: true
-      prior_weight: 1.0
-      consider_magic_clip: true
-      consider_endpoints: false
-      n_startup_trials: 10
-      n_ei_candidates: 24
-      multivariate: false
-      warn_independent_sampling: true
-    _target_: hydra_plugins.hydra_optuna_sweeper.optuna_sweeper.OptunaSweeper
-    direction: minimize
-    storage: null
-    study_name: focus150_hyperparameter_search
-    n_trials: 25
-    n_jobs: 1
-    search_space:
-      datamodule.batch_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-      model.lr:
-        type: float
-        low: 0.0001
-        high: 0.2
-      model.lin1_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-      model.lin2_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-      model.lin3_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-  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'
-    handlers:
-      console:
-        class: logging.StreamHandler
-        formatter: colorlog
-        stream: ext://sys.stdout
-    root:
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-      handlers:
-      - console
-    disable_existing_loggers: false
-  job_logging:
-    version: 1
-    formatters:
-      simple:
-        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)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'
-        log_colors:
-          DEBUG: purple
-          INFO: green
-          WARNING: yellow
-          ERROR: red
-          CRITICAL: red
-    handlers:
-      console:
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-        formatter: colorlog
-        stream: ext://sys.stdout
-      file:
-        class: logging.FileHandler
-        formatter: simple
-        filename: ${hydra.job.name}.log
-    root:
-      level: INFO
-      handlers:
-      - console
-      - file
-    disable_existing_loggers: false
-  env: {}
-  searchpath: []
-  callbacks: {}
-  output_subdir: .hydra
-  overrides:
-    hydra: []
-    task:
-    - datamodule.batch_size=128
-    - model.lr=0.08335231197967785
-    - model.lin1_size=2048
-    - model.lin2_size=512
-    - model.lin3_size=128
-    - hparams_search=focus150_optuna
-  job:
-    name: train
-    override_dirname: datamodule.batch_size=128,hparams_search=focus150_optuna,model.lin1_size=2048,model.lin2_size=512,model.lin3_size=128,model.lr=0.08335231197967785
-    id: '14'
-    num: 14
-    config_name: train.yaml
-    env_set: {}
-    env_copy: []
-    config:
-      override_dirname:
-        kv_sep: '='
-        item_sep: ','
-        exclude_keys: []
-  runtime:
-    version: 1.1.1
-    cwd: /usr/src/app
-    config_sources:
-    - path: hydra.conf
-      schema: pkg
-      provider: hydra
-    - path: /usr/src/app/configs
-      schema: file
-      provider: main
-    - path: hydra_plugins.hydra_colorlog.conf
-      schema: pkg
-      provider: hydra-colorlog
-    - path: ''
-      schema: structured
-      provider: schema
-    choices:
-      local: default.yaml
-      hparams_search: focus150_optuna
-      debug: null
-      experiment: null
-      log_dir: default.yaml
-      trainer: long.yaml
-      logger: tensorboard
-      callbacks: default.yaml
-      model: focus150.yaml
-      datamodule: focus150.yaml
-      hydra/env: default
-      hydra/callbacks: null
-      hydra/job_logging: colorlog
-      hydra/hydra_logging: colorlog
-      hydra/hydra_help: default
-      hydra/help: default
-      hydra/sweeper: optuna
-      hydra/sweeper/sampler: tpe
-      hydra/launcher: basic
-      hydra/output: default
-  verbose: false

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/14/.hydra/overrides.yaml

@@ -1,6 +0,0 @@
-- datamodule.batch_size=128
-- model.lr=0.08335231197967785
-- model.lin1_size=2048
-- model.lin2_size=512
-- model.lin3_size=128
-- hparams_search=focus150_optuna

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/14/tensorboard/focus150_optuna/events.out.tfevents.1646400570.e02c2cd1d8ab.1.27

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logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/14/tensorboard/focus150_optuna/hparams.yaml

@@ -1,52 +0,0 @@
-trainer:
-  _target_: pytorch_lightning.Trainer
-  gpus: 1
-  min_epochs: 1
-  max_epochs: 100
-  resume_from_checkpoint: null
-model:
-  _target_: src.models.focus_module.FocusLitModule
-  input_size: 67500
-  lin1_size: 2048
-  lin2_size: 512
-  lin3_size: 128
-  output_size: 1
-  lr: 0.08335231197967785
-  weight_decay: 0.0005
-datamodule:
-  _target_: src.datamodules.focus_datamodule.FocusDataModule
-  data_dir: /usr/src/app/data/focus150
-  csv_file: /usr/src/app/data/focus150/metadata.csv
-  batch_size: 128
-  train_val_test_split_percentage:
-  - 0.7
-  - 0.15
-  - 0.15
-  num_workers: 0
-  pin_memory: false
-seed: null
-callbacks:
-  model_checkpoint:
-    _target_: pytorch_lightning.callbacks.ModelCheckpoint
-    monitor: val/mae
-    mode: min
-    save_top_k: 1
-    save_last: true
-    verbose: false
-    dirpath: checkpoints/
-    filename: epoch_{epoch:03d}
-    auto_insert_metric_name: false
-  early_stopping:
-    _target_: pytorch_lightning.callbacks.EarlyStopping
-    monitor: val/mae
-    mode: min
-    patience: 100
-    min_delta: 0
-  model_summary:
-    _target_: pytorch_lightning.callbacks.RichModelSummary
-    max_depth: -1
-  rich_progress_bar:
-    _target_: pytorch_lightning.callbacks.RichProgressBar
-model/params/total: 139362305
-model/params/trainable: 139362305
-model/params/non_trainable: 0

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/15/.hydra/config.yaml

@@ -1,66 +0,0 @@
-original_work_dir: ${hydra:runtime.cwd}
-data_dir: ${original_work_dir}/data
-print_config: true
-ignore_warnings: true
-train: true
-test: true
-seed: null
-name: focus150_optuna
-datamodule:
-  _target_: src.datamodules.focus_datamodule.FocusDataModule
-  data_dir: ${data_dir}/focus150
-  csv_file: ${data_dir}/focus150/metadata.csv
-  batch_size: 64
-  train_val_test_split_percentage:
-  - 0.7
-  - 0.15
-  - 0.15
-  num_workers: 0
-  pin_memory: false
-model:
-  _target_: src.models.focus_module.FocusLitModule
-  input_size: 67500
-  lin1_size: 64
-  lin2_size: 256
-  lin3_size: 128
-  output_size: 1
-  lr: 0.04131276528182434
-  weight_decay: 0.0005
-callbacks:
-  model_checkpoint:
-    _target_: pytorch_lightning.callbacks.ModelCheckpoint
-    monitor: val/mae
-    mode: min
-    save_top_k: 1
-    save_last: true
-    verbose: false
-    dirpath: checkpoints/
-    filename: epoch_{epoch:03d}
-    auto_insert_metric_name: false
-  early_stopping:
-    _target_: pytorch_lightning.callbacks.EarlyStopping
-    monitor: val/mae
-    mode: min
-    patience: 100
-    min_delta: 0
-  model_summary:
-    _target_: pytorch_lightning.callbacks.RichModelSummary
-    max_depth: -1
-  rich_progress_bar:
-    _target_: pytorch_lightning.callbacks.RichProgressBar
-logger:
-  tensorboard:
-    _target_: pytorch_lightning.loggers.tensorboard.TensorBoardLogger
-    save_dir: tensorboard/
-    name: null
-    version: ${name}
-    log_graph: false
-    default_hp_metric: true
-    prefix: ''
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-  _target_: pytorch_lightning.Trainer
-  gpus: 1
-  min_epochs: 1
-  max_epochs: 100
-  resume_from_checkpoint: null
-optimized_metric: val/mae_best

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/15/.hydra/hydra.yaml

@@ -1,232 +0,0 @@
-hydra:
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-    dir: logs/experiments/runs/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
-  sweep:
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-    subdir: ${hydra.job.num}
-  launcher:
-    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
-  sweeper:
-    sampler:
-      _target_: optuna.samplers.TPESampler
-      seed: 12345
-      consider_prior: true
-      prior_weight: 1.0
-      consider_magic_clip: true
-      consider_endpoints: false
-      n_startup_trials: 10
-      n_ei_candidates: 24
-      multivariate: false
-      warn_independent_sampling: true
-    _target_: hydra_plugins.hydra_optuna_sweeper.optuna_sweeper.OptunaSweeper
-    direction: minimize
-    storage: null
-    study_name: focus150_hyperparameter_search
-    n_trials: 25
-    n_jobs: 1
-    search_space:
-      datamodule.batch_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-      model.lr:
-        type: float
-        low: 0.0001
-        high: 0.2
-      model.lin1_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-      model.lin2_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-      model.lin3_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-  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'
-    handlers:
-      console:
-        class: logging.StreamHandler
-        formatter: colorlog
-        stream: ext://sys.stdout
-    root:
-      level: INFO
-      handlers:
-      - console
-    disable_existing_loggers: false
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-    version: 1
-    formatters:
-      simple:
-        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)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'
-        log_colors:
-          DEBUG: purple
-          INFO: green
-          WARNING: yellow
-          ERROR: red
-          CRITICAL: red
-    handlers:
-      console:
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-        formatter: colorlog
-        stream: ext://sys.stdout
-      file:
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-        formatter: simple
-        filename: ${hydra.job.name}.log
-    root:
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-      - console
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-    disable_existing_loggers: false
-  env: {}
-  searchpath: []
-  callbacks: {}
-  output_subdir: .hydra
-  overrides:
-    hydra: []
-    task:
-    - datamodule.batch_size=64
-    - model.lr=0.04131276528182434
-    - model.lin1_size=64
-    - model.lin2_size=256
-    - model.lin3_size=128
-    - hparams_search=focus150_optuna
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-    name: train
-    override_dirname: datamodule.batch_size=64,hparams_search=focus150_optuna,model.lin1_size=64,model.lin2_size=256,model.lin3_size=128,model.lr=0.04131276528182434
-    id: '15'
-    num: 15
-    config_name: train.yaml
-    env_set: {}
-    env_copy: []
-    config:
-      override_dirname:
-        kv_sep: '='
-        item_sep: ','
-        exclude_keys: []
-  runtime:
-    version: 1.1.1
-    cwd: /usr/src/app
-    config_sources:
-    - path: hydra.conf
-      schema: pkg
-      provider: hydra
-    - path: /usr/src/app/configs
-      schema: file
-      provider: main
-    - path: hydra_plugins.hydra_colorlog.conf
-      schema: pkg
-      provider: hydra-colorlog
-    - path: ''
-      schema: structured
-      provider: schema
-    choices:
-      local: default.yaml
-      hparams_search: focus150_optuna
-      debug: null
-      experiment: null
-      log_dir: default.yaml
-      trainer: long.yaml
-      logger: tensorboard
-      callbacks: default.yaml
-      model: focus150.yaml
-      datamodule: focus150.yaml
-      hydra/env: default
-      hydra/callbacks: null
-      hydra/job_logging: colorlog
-      hydra/hydra_logging: colorlog
-      hydra/hydra_help: default
-      hydra/help: default
-      hydra/sweeper: optuna
-      hydra/sweeper/sampler: tpe
-      hydra/launcher: basic
-      hydra/output: default
-  verbose: false

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/15/.hydra/overrides.yaml

@@ -1,6 +0,0 @@
-- datamodule.batch_size=64
-- model.lr=0.04131276528182434
-- model.lin1_size=64
-- model.lin2_size=256
-- model.lin3_size=128
-- hparams_search=focus150_optuna

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/15/tensorboard/focus150_optuna/events.out.tfevents.1646403524.e02c2cd1d8ab.1.29

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logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/15/tensorboard/focus150_optuna/hparams.yaml

@@ -1,52 +0,0 @@
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-  _target_: pytorch_lightning.Trainer
-  gpus: 1
-  min_epochs: 1
-  max_epochs: 100
-  resume_from_checkpoint: null
-model:
-  _target_: src.models.focus_module.FocusLitModule
-  input_size: 67500
-  lin1_size: 64
-  lin2_size: 256
-  lin3_size: 128
-  output_size: 1
-  lr: 0.04131276528182434
-  weight_decay: 0.0005
-datamodule:
-  _target_: src.datamodules.focus_datamodule.FocusDataModule
-  data_dir: /usr/src/app/data/focus150
-  csv_file: /usr/src/app/data/focus150/metadata.csv
-  batch_size: 64
-  train_val_test_split_percentage:
-  - 0.7
-  - 0.15
-  - 0.15
-  num_workers: 0
-  pin_memory: false
-seed: null
-callbacks:
-  model_checkpoint:
-    _target_: pytorch_lightning.callbacks.ModelCheckpoint
-    monitor: val/mae
-    mode: min
-    save_top_k: 1
-    save_last: true
-    verbose: false
-    dirpath: checkpoints/
-    filename: epoch_{epoch:03d}
-    auto_insert_metric_name: false
-  early_stopping:
-    _target_: pytorch_lightning.callbacks.EarlyStopping
-    monitor: val/mae
-    mode: min
-    patience: 100
-    min_delta: 0
-  model_summary:
-    _target_: pytorch_lightning.callbacks.RichModelSummary
-    max_depth: -1
-  rich_progress_bar:
-    _target_: pytorch_lightning.callbacks.RichProgressBar
-model/params/total: 4370625
-model/params/trainable: 4370625
-model/params/non_trainable: 0

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/16/.hydra/config.yaml

@@ -1,66 +0,0 @@
-original_work_dir: ${hydra:runtime.cwd}
-data_dir: ${original_work_dir}/data
-print_config: true
-ignore_warnings: true
-train: true
-test: true
-seed: null
-name: focus150_optuna
-datamodule:
-  _target_: src.datamodules.focus_datamodule.FocusDataModule
-  data_dir: ${data_dir}/focus150
-  csv_file: ${data_dir}/focus150/metadata.csv
-  batch_size: 128
-  train_val_test_split_percentage:
-  - 0.7
-  - 0.15
-  - 0.15
-  num_workers: 0
-  pin_memory: false
-model:
-  _target_: src.models.focus_module.FocusLitModule
-  input_size: 67500
-  lin1_size: 512
-  lin2_size: 32
-  lin3_size: 2048
-  output_size: 1
-  lr: 0.12875356688119352
-  weight_decay: 0.0005
-callbacks:
-  model_checkpoint:
-    _target_: pytorch_lightning.callbacks.ModelCheckpoint
-    monitor: val/mae
-    mode: min
-    save_top_k: 1
-    save_last: true
-    verbose: false
-    dirpath: checkpoints/
-    filename: epoch_{epoch:03d}
-    auto_insert_metric_name: false
-  early_stopping:
-    _target_: pytorch_lightning.callbacks.EarlyStopping
-    monitor: val/mae
-    mode: min
-    patience: 100
-    min_delta: 0
-  model_summary:
-    _target_: pytorch_lightning.callbacks.RichModelSummary
-    max_depth: -1
-  rich_progress_bar:
-    _target_: pytorch_lightning.callbacks.RichProgressBar
-logger:
-  tensorboard:
-    _target_: pytorch_lightning.loggers.tensorboard.TensorBoardLogger
-    save_dir: tensorboard/
-    name: null
-    version: ${name}
-    log_graph: false
-    default_hp_metric: true
-    prefix: ''
-trainer:
-  _target_: pytorch_lightning.Trainer
-  gpus: 1
-  min_epochs: 1
-  max_epochs: 100
-  resume_from_checkpoint: null
-optimized_metric: val/mae_best

logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/16/.hydra/hydra.yaml

@@ -1,232 +0,0 @@
-hydra:
-  run:
-    dir: logs/experiments/runs/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
-  sweep:
-    dir: logs/experiments/multiruns/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
-    subdir: ${hydra.job.num}
-  launcher:
-    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
-  sweeper:
-    sampler:
-      _target_: optuna.samplers.TPESampler
-      seed: 12345
-      consider_prior: true
-      prior_weight: 1.0
-      consider_magic_clip: true
-      consider_endpoints: false
-      n_startup_trials: 10
-      n_ei_candidates: 24
-      multivariate: false
-      warn_independent_sampling: true
-    _target_: hydra_plugins.hydra_optuna_sweeper.optuna_sweeper.OptunaSweeper
-    direction: minimize
-    storage: null
-    study_name: focus150_hyperparameter_search
-    n_trials: 25
-    n_jobs: 1
-    search_space:
-      datamodule.batch_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-      model.lr:
-        type: float
-        low: 0.0001
-        high: 0.2
-      model.lin1_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-      model.lin2_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-      model.lin3_size:
-        type: categorical
-        choices:
-        - 32
-        - 64
-        - 128
-        - 256
-        - 512
-        - 1024
-        - 2048
-  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'
-    handlers:
-      console:
-        class: logging.StreamHandler
-        formatter: colorlog
-        stream: ext://sys.stdout
-    root:
-      level: INFO
-      handlers:
-      - console
-    disable_existing_loggers: false
-  job_logging:
-    version: 1
-    formatters:
-      simple:
-        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)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'
-        log_colors:
-          DEBUG: purple
-          INFO: green
-          WARNING: yellow
-          ERROR: red
-          CRITICAL: red
-    handlers:
-      console:
-        class: logging.StreamHandler
-        formatter: colorlog
-        stream: ext://sys.stdout
-      file:
-        class: logging.FileHandler
-        formatter: simple
-        filename: ${hydra.job.name}.log
-    root:
-      level: INFO
-      handlers:
-      - console
-      - file
-    disable_existing_loggers: false
-  env: {}
-  searchpath: []
-  callbacks: {}
-  output_subdir: .hydra
-  overrides:
-    hydra: []
-    task:
-    - datamodule.batch_size=128
-    - model.lr=0.12875356688119352
-    - model.lin1_size=512
-    - model.lin2_size=32
-    - model.lin3_size=2048
-    - hparams_search=focus150_optuna
-  job:
-    name: train
-    override_dirname: datamodule.batch_size=128,hparams_search=focus150_optuna,model.lin1_size=512,model.lin2_size=32,model.lin3_size=2048,model.lr=0.12875356688119352
-    id: '16'
-    num: 16
-    config_name: train.yaml
-    env_set: {}
-    env_copy: []
-    config:
-      override_dirname:
-        kv_sep: '='
-        item_sep: ','
-        exclude_keys: []
-  runtime:
-    version: 1.1.1
-    cwd: /usr/src/app
-    config_sources:
-    - path: hydra.conf
-      schema: pkg
-      provider: hydra
-    - path: /usr/src/app/configs
-      schema: file
-      provider: main
-    - path: hydra_plugins.hydra_colorlog.conf
-      schema: pkg
-      provider: hydra-colorlog
-    - path: ''
-      schema: structured
-      provider: schema
-    choices:
-      local: default.yaml
-      hparams_search: focus150_optuna
-      debug: null
-      experiment: null
-      log_dir: default.yaml
-      trainer: long.yaml
-      logger: tensorboard
-      callbacks: default.yaml
-      model: focus150.yaml
-      datamodule: focus150.yaml
-      hydra/env: default
-      hydra/callbacks: null
-      hydra/job_logging: colorlog
-      hydra/hydra_logging: colorlog
-      hydra/hydra_help: default
-      hydra/help: default
-      hydra/sweeper: optuna
-      hydra/sweeper/sampler: tpe
-      hydra/launcher: basic
-      hydra/output: default
-  verbose: false