add hyperparameter tuning experiment with more data for focus

logs/experiments/multiruns/focus150_optuna/2022-03-09_09-28-19/0/.hydra/config.yaml

@@ -0,0 +1,66 @@
+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/2022-03-09_09-28-19/0/.hydra/hydra.yaml

@@ -0,0 +1,232 @@
+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/2022-03-09_09-28-19/0/.hydra/overrides.yaml

@@ -0,0 +1,6 @@
+- 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/2022-03-09_09-28-19/0/checkpoints/epoch_006.ckpt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9dbad499e4e8e4b49bb49ddbbab2069d7c62870437af1426c2e041813c7ac873
+size 103767494

logs/experiments/multiruns/focus150_optuna/2022-03-09_09-28-19/0/checkpoints/last.ckpt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b85244acd45ff138a3bc546bec9d862e565e69721fa949ed92747061aced2ffe
+size 103767494

logs/experiments/multiruns/focus150_optuna/2022-03-09_09-28-19/0/tensorboard/focus150_optuna/events.out.tfevents.1646818102.36d13a512e74.1.0

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+oid sha256:1d42f548c740696417c0ed022456c72825c930a20d0f4d639927d59a1a9ee185
+size 36440

logs/experiments/multiruns/focus150_optuna/2022-03-09_09-28-19/0/tensorboard/focus150_optuna/events.out.tfevents.1646818619.36d13a512e74.1.1

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ae7d078dd7233ae6bc21c95e466a74e5c6f8a61ffc58592ca40ad85b7bd22e19
+size 179

logs/experiments/multiruns/focus150_optuna/2022-03-09_09-28-19/0/tensorboard/focus150_optuna/hparams.yaml

@@ -0,0 +1,52 @@
+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/2022-03-09_09-28-19/1/.hydra/config.yaml

@@ -0,0 +1,66 @@
+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/2022-03-09_09-28-19/1/.hydra/hydra.yaml

@@ -0,0 +1,232 @@
+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/2022-03-09_09-28-19/1/.hydra/overrides.yaml

@@ -0,0 +1,6 @@
+- 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/2022-03-09_09-28-19/1/checkpoints/epoch_060.ckpt

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logs/experiments/multiruns/focus150_optuna/2022-03-09_09-28-19/1/tensorboard/focus150_optuna/events.out.tfevents.1646819320.36d13a512e74.1.3

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logs/experiments/multiruns/focus150_optuna/2022-03-09_09-28-19/1/tensorboard/focus150_optuna/hparams.yaml

@@ -0,0 +1,52 @@
+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/2022-03-09_09-28-19/10/.hydra/config.yaml

@@ -0,0 +1,66 @@
+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/2022-03-09_09-28-19/10/.hydra/hydra.yaml

@@ -0,0 +1,232 @@
+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=0.07148210917089061
+    - 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/2022-03-09_09-28-19/10/.hydra/overrides.yaml

@@ -0,0 +1,6 @@
+- 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/2022-03-09_09-28-19/10/checkpoints/epoch_006.ckpt

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+size 419515270

logs/experiments/multiruns/focus150_optuna/2022-03-09_09-28-19/10/checkpoints/last.ckpt

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+size 419515334

logs/experiments/multiruns/focus150_optuna/2022-03-09_09-28-19/10/tensorboard/focus150_optuna/events.out.tfevents.1646829822.36d13a512e74.1.20

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+size 36391

logs/experiments/multiruns/focus150_optuna/2022-03-09_09-28-19/10/tensorboard/focus150_optuna/events.out.tfevents.1646830970.36d13a512e74.1.21

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+size 176

logs/experiments/multiruns/focus150_optuna/2022-03-09_09-28-19/10/tensorboard/focus150_optuna/hparams.yaml

@@ -0,0 +1,52 @@
+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/2022-03-09_09-28-19/11/.hydra/config.yaml

@@ -0,0 +1,66 @@
+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: 256
+  lin2_size: 512
+  lin3_size: 512
+  output_size: 1
+  lr: 0.0033092554782795935
+  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/2022-03-09_09-28-19/11/.hydra/hydra.yaml

@@ -0,0 +1,232 @@
+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=0.0033092554782795935
+    - model.lin1_size=256
+    - model.lin2_size=512
+    - model.lin3_size=512
+    - hparams_search=focus150_optuna
+  job:
+    name: train
+    override_dirname: datamodule.batch_size=32,hparams_search=focus150_optuna,model.lin1_size=256,model.lin2_size=512,model.lin3_size=512,model.lr=0.0033092554782795935
+    id: '11'
+    num: 11
+    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/2022-03-09_09-28-19/11/.hydra/overrides.yaml

@@ -0,0 +1,6 @@
+- datamodule.batch_size=32
+- model.lr=0.0033092554782795935
+- model.lin1_size=256
+- model.lin2_size=512
+- model.lin3_size=512
+- hparams_search=focus150_optuna

logs/experiments/multiruns/focus150_optuna/2022-03-09_09-28-19/11/checkpoints/epoch_014.ckpt

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logs/experiments/multiruns/focus150_optuna/2022-03-09_09-28-19/11/tensorboard/focus150_optuna/hparams.yaml

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+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: 512
+  lin3_size: 512
+  output_size: 1
+  lr: 0.0033092554782795935
+  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: 17677569
+model/params/trainable: 17677569
+model/params/non_trainable: 0

logs/experiments/multiruns/focus150_optuna/2022-03-09_09-28-19/12/.hydra/config.yaml

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+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: 256
+  lin2_size: 512
+  lin3_size: 2048
+  output_size: 1
+  lr: 0.001406127964835635
+  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/2022-03-09_09-28-19/12/.hydra/hydra.yaml

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+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=0.001406127964835635
+    - model.lin1_size=256
+    - model.lin2_size=512
+    - model.lin3_size=2048
+    - hparams_search=focus150_optuna
+  job:
+    name: train
+    override_dirname: datamodule.batch_size=128,hparams_search=focus150_optuna,model.lin1_size=256,model.lin2_size=512,model.lin3_size=2048,model.lr=0.001406127964835635
+    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/2022-03-09_09-28-19/12/.hydra/overrides.yaml

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+- datamodule.batch_size=128
+- model.lr=0.001406127964835635
+- model.lin1_size=256
+- model.lin2_size=512
+- model.lin3_size=2048
+- hparams_search=focus150_optuna

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logs/experiments/multiruns/focus150_optuna/2022-03-09_09-28-19/12/tensorboard/focus150_optuna/hparams.yaml

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+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: 512
+  lin3_size: 2048
+  output_size: 1
+  lr: 0.001406127964835635
+  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: 18470145
+model/params/trainable: 18470145
+model/params/non_trainable: 0

logs/experiments/multiruns/focus150_optuna/2022-03-09_09-28-19/13/.hydra/config.yaml

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+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: 256
+  lin2_size: 512
+  lin3_size: 2048
+  output_size: 1
+  lr: 0.0545487164887326
+  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/2022-03-09_09-28-19/13/.hydra/hydra.yaml

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+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=0.0545487164887326
+    - model.lin1_size=256
+    - model.lin2_size=512
+    - model.lin3_size=2048
+    - hparams_search=focus150_optuna
+  job:
+    name: train
+    override_dirname: datamodule.batch_size=32,hparams_search=focus150_optuna,model.lin1_size=256,model.lin2_size=512,model.lin3_size=2048,model.lr=0.0545487164887326
+    id: '13'
+    num: 13
+    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/2022-03-09_09-28-19/13/.hydra/overrides.yaml

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+- datamodule.batch_size=32
+- model.lr=0.0545487164887326
+- model.lin1_size=256
+- model.lin2_size=512
+- model.lin3_size=2048
+- hparams_search=focus150_optuna

logs/experiments/multiruns/focus150_optuna/2022-03-09_09-28-19/13/checkpoints/epoch_060.ckpt

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logs/experiments/multiruns/focus150_optuna/2022-03-09_09-28-19/13/tensorboard/focus150_optuna/hparams.yaml

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+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: 512
+  lin3_size: 2048
+  output_size: 1
+  lr: 0.0545487164887326
+  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: 18470145
+model/params/trainable: 18470145
+model/params/non_trainable: 0

logs/experiments/multiruns/focus150_optuna/2022-03-09_09-28-19/14/.hydra/config.yaml

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+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: 128
+  lin2_size: 512
+  lin3_size: 512
+  output_size: 1
+  lr: 0.003892362171048049
+  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/2022-03-09_09-28-19/14/.hydra/hydra.yaml

@@ -0,0 +1,232 @@
+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=0.003892362171048049
+    - model.lin1_size=128
+    - model.lin2_size=512
+    - model.lin3_size=512
+    - hparams_search=focus150_optuna
+  job:
+    name: train
+    override_dirname: datamodule.batch_size=128,hparams_search=focus150_optuna,model.lin1_size=128,model.lin2_size=512,model.lin3_size=512,model.lr=0.003892362171048049
+    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