ran hyperparameter search wfor cnn with relu and batchnorm

configs/hparams_search/focusConvReLU_MSE_150.yaml

@@ -0,0 +1,73 @@
+# @package _global_
+
+# example hyperparameter optimization of some experiment with Optuna:
+# python train.py -m hparams_search=mnist_optuna experiment=example
+
+defaults:
+  - override /datamodule: focus150.yaml
+  - override /model: focusConvReLU_150.yaml
+  - override /hydra/sweeper: optuna
+
+# choose metric which will be optimized by Optuna
+# make sure this is the correct name of some metric logged in lightning module!
+optimized_metric: "val/mae_best"
+
+name: "focusConvReLU_MSE_150_hyperparameter_search"
+
+# here we define Optuna hyperparameter search
+# it optimizes for value returned from function with @hydra.main decorator
+# docs: https://hydra.cc/docs/next/plugins/optuna_sweeper
+hydra:
+  sweeper:
+    _target_: hydra_plugins.hydra_optuna_sweeper.optuna_sweeper.OptunaSweeper
+
+    # storage URL to persist optimization results
+    # for example, you can use SQLite if you set 'sqlite:///example.db'
+    storage: null
+
+    # name of the study to persist optimization results
+    study_name: focusConvReLU_MSE_150_hyperparameter_search
+
+    # number of parallel workers
+    n_jobs: 1
+
+    # 'minimize' or 'maximize' the objective
+    direction: minimize
+
+    # total number of runs that will be executed
+    n_trials: 20
+
+    # choose Optuna hyperparameter sampler
+    # docs: https://optuna.readthedocs.io/en/stable/reference/samplers.html
+    sampler:
+      _target_: optuna.samplers.TPESampler
+      seed: 12345
+      n_startup_trials: 10 # number of random sampling runs before optimization starts
+
+    # define range of hyperparameters
+    search_space:
+      datamodule.batch_size:
+        type: categorical
+        choices: [64]
+      model.lr:
+        type: float
+        low: 0.0001
+        high: 0.01
+      model.conv1_size:
+        type: categorical
+        choices: [3, 5, 7]
+      model.conv1_channels:
+        type: categorical
+        choices: [3, 6, 9]
+      model.conv2_size:
+        type: categorical
+        choices: [3, 5, 7]
+      model.conv2_channels:
+        type: categorical
+        choices: [3, 6, 9]
+      model.lin1_size:
+        type: categorical
+        choices: [16, 32, 72, 128]
+      model.lin2_size:
+        type: categorical
+        choices: [16, 32, 72, 128]

logs/experiments/multiruns/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/0/.hydra/config.yaml

@@ -0,0 +1,81 @@
+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: focusConvReLU_MSE_150_hyperparameter_search
+datamodule:
+  _target_: src.datamodules.focus_datamodule.FocusDataModule
+  data_dir: ${data_dir}/focus150
+  csv_train_file: ${data_dir}/focus150/train_metadata.csv
+  csv_val_file: ${data_dir}/focus150/validation_metadata.csv
+  csv_test_file: ${data_dir}/focus150/test_metadata.csv
+  batch_size: 64
+  num_workers: 0
+  pin_memory: false
+model:
+  _target_: src.models.focus_conv_module.FocusConvReLULitModule
+  image_size: 150
+  pool_size: 2
+  conv1_size: 3
+  conv1_channels: 9
+  conv2_size: 5
+  conv2_channels: 6
+  lin1_size: 128
+  lin2_size: 32
+  output_size: 1
+  lr: 0.009303199318889763
+  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:
+  csv:
+    _target_: pytorch_lightning.loggers.csv_logs.CSVLogger
+    save_dir: .
+    name: csv/
+    prefix: ''
+  mlflow:
+    _target_: pytorch_lightning.loggers.mlflow.MLFlowLogger
+    experiment_name: ${name}
+    tracking_uri: ${original_work_dir}/logs/mlflow/mlruns
+    tags: null
+    save_dir: ./mlruns
+    prefix: ''
+    artifact_location: null
+  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/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/0/.hydra/hydra.yaml

@@ -0,0 +1,241 @@
+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: focusConvReLU_MSE_150_hyperparameter_search
+    n_trials: 20
+    n_jobs: 1
+    search_space:
+      datamodule.batch_size:
+        type: categorical
+        choices:
+        - 64
+      model.lr:
+        type: float
+        low: 0.0001
+        high: 0.01
+      model.conv1_size:
+        type: categorical
+        choices:
+        - 3
+        - 5
+        - 7
+      model.conv1_channels:
+        type: categorical
+        choices:
+        - 3
+        - 6
+        - 9
+      model.conv2_size:
+        type: categorical
+        choices:
+        - 3
+        - 5
+        - 7
+      model.conv2_channels:
+        type: categorical
+        choices:
+        - 3
+        - 6
+        - 9
+      model.lin1_size:
+        type: categorical
+        choices:
+        - 16
+        - 32
+        - 72
+        - 128
+      model.lin2_size:
+        type: categorical
+        choices:
+        - 16
+        - 32
+        - 72
+        - 128
+  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=0.009303199318889763
+    - model.conv1_size=3
+    - model.conv1_channels=9
+    - model.conv2_size=5
+    - model.conv2_channels=6
+    - model.lin1_size=128
+    - model.lin2_size=32
+    - hparams_search=focusConvReLU_MSE_150.yaml
+  job:
+    name: train
+    override_dirname: datamodule.batch_size=64,hparams_search=focusConvReLU_MSE_150.yaml,model.conv1_channels=9,model.conv1_size=3,model.conv2_channels=6,model.conv2_size=5,model.lin1_size=128,model.lin2_size=32,model.lr=0.009303199318889763
+    id: '0'
+    num: 0
+    config_name: train.yaml
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.1.2
+    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: focusConvReLU_MSE_150.yaml
+      debug: null
+      experiment: null
+      log_dir: default.yaml
+      trainer: long.yaml
+      logger: many_loggers
+      callbacks: default.yaml
+      model: focusConvReLU_150.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/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/0/.hydra/overrides.yaml

@@ -0,0 +1,9 @@
+- datamodule.batch_size=64
+- model.lr=0.009303199318889763
+- model.conv1_size=3
+- model.conv1_channels=9
+- model.conv2_size=5
+- model.conv2_channels=6
+- model.lin1_size=128
+- model.lin2_size=32
+- hparams_search=focusConvReLU_MSE_150.yaml

logs/experiments/multiruns/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/0/checkpoints/epoch_058.ckpt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:bc054c2c7bacae09ee0f244f68be43290e82dbb6f095f4339c54ff40b51804c5
+size 10162063

logs/experiments/multiruns/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/0/checkpoints/last.ckpt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:435acb158e8550d70a9c3403f45e2032b373603e2ccfff999814be356d8990f6
+size 10162063

logs/experiments/multiruns/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/0/csv/version_0/hparams.yaml

@@ -0,0 +1,54 @@
+trainer:
+  _target_: pytorch_lightning.Trainer
+  gpus: 1
+  min_epochs: 1
+  max_epochs: 100
+  resume_from_checkpoint: null
+model:
+  _target_: src.models.focus_conv_module.FocusConvReLULitModule
+  image_size: 150
+  pool_size: 2
+  conv1_size: 3
+  conv1_channels: 9
+  conv2_size: 5
+  conv2_channels: 6
+  lin1_size: 128
+  lin2_size: 32
+  output_size: 1
+  lr: 0.009303199318889763
+  weight_decay: 0.0005
+datamodule:
+  _target_: src.datamodules.focus_datamodule.FocusDataModule
+  data_dir: /usr/src/app/data/focus150
+  csv_train_file: /usr/src/app/data/focus150/train_metadata.csv
+  csv_val_file: /usr/src/app/data/focus150/validation_metadata.csv
+  csv_test_file: /usr/src/app/data/focus150/test_metadata.csv
+  batch_size: 64
+  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: 845303
+model/params/trainable: 845303
+model/params/non_trainable: 0

logs/experiments/multiruns/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/0/csv/version_0/metrics.csv

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logs/experiments/multiruns/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/0/tensorboard/focusConvReLU_MSE_150_hyperparameter_search/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_conv_module.FocusConvReLULitModule
+  image_size: 150
+  pool_size: 2
+  conv1_size: 3
+  conv1_channels: 9
+  conv2_size: 5
+  conv2_channels: 6
+  lin1_size: 128
+  lin2_size: 32
+  output_size: 1
+  lr: 0.009303199318889763
+  weight_decay: 0.0005
+datamodule:
+  _target_: src.datamodules.focus_datamodule.FocusDataModule
+  data_dir: /usr/src/app/data/focus150
+  csv_train_file: /usr/src/app/data/focus150/train_metadata.csv
+  csv_val_file: /usr/src/app/data/focus150/validation_metadata.csv
+  csv_test_file: /usr/src/app/data/focus150/test_metadata.csv
+  batch_size: 64
+  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: 845303
+model/params/trainable: 845303
+model/params/non_trainable: 0

logs/experiments/multiruns/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/1/.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: focusConvReLU_MSE_150_hyperparameter_search
+datamodule:
+  _target_: src.datamodules.focus_datamodule.FocusDataModule
+  data_dir: ${data_dir}/focus150
+  csv_train_file: ${data_dir}/focus150/train_metadata.csv
+  csv_val_file: ${data_dir}/focus150/validation_metadata.csv
+  csv_test_file: ${data_dir}/focus150/test_metadata.csv
+  batch_size: 64
+  num_workers: 0
+  pin_memory: false
+model:
+  _target_: src.models.focus_conv_module.FocusConvReLULitModule
+  image_size: 150
+  pool_size: 2
+  conv1_size: 3
+  conv1_channels: 6
+  conv2_size: 3
+  conv2_channels: 6
+  lin1_size: 72
+  lin2_size: 16
+  output_size: 1
+  lr: 0.007202790846042897
+  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:
+  csv:
+    _target_: pytorch_lightning.loggers.csv_logs.CSVLogger
+    save_dir: .
+    name: csv/
+    prefix: ''
+  mlflow:
+    _target_: pytorch_lightning.loggers.mlflow.MLFlowLogger
+    experiment_name: ${name}
+    tracking_uri: ${original_work_dir}/logs/mlflow/mlruns
+    tags: null
+    save_dir: ./mlruns
+    prefix: ''
+    artifact_location: null
+  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/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/1/.hydra/hydra.yaml

@@ -0,0 +1,241 @@
+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: focusConvReLU_MSE_150_hyperparameter_search
+    n_trials: 20
+    n_jobs: 1
+    search_space:
+      datamodule.batch_size:
+        type: categorical
+        choices:
+        - 64
+      model.lr:
+        type: float
+        low: 0.0001
+        high: 0.01
+      model.conv1_size:
+        type: categorical
+        choices:
+        - 3
+        - 5
+        - 7
+      model.conv1_channels:
+        type: categorical
+        choices:
+        - 3
+        - 6
+        - 9
+      model.conv2_size:
+        type: categorical
+        choices:
+        - 3
+        - 5
+        - 7
+      model.conv2_channels:
+        type: categorical
+        choices:
+        - 3
+        - 6
+        - 9
+      model.lin1_size:
+        type: categorical
+        choices:
+        - 16
+        - 32
+        - 72
+        - 128
+      model.lin2_size:
+        type: categorical
+        choices:
+        - 16
+        - 32
+        - 72
+        - 128
+  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'
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+          INFO: green
+          WARNING: yellow
+          ERROR: red
+          CRITICAL: red
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+        formatter: colorlog
+        stream: ext://sys.stdout
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+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
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+  callbacks: {}
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+    - model.conv1_channels=6
+    - model.conv2_size=3
+    - model.conv2_channels=6
+    - model.lin1_size=72
+    - model.lin2_size=16
+    - hparams_search=focusConvReLU_MSE_150.yaml
+  job:
+    name: train
+    override_dirname: datamodule.batch_size=64,hparams_search=focusConvReLU_MSE_150.yaml,model.conv1_channels=6,model.conv1_size=3,model.conv2_channels=6,model.conv2_size=3,model.lin1_size=72,model.lin2_size=16,model.lr=0.007202790846042897
+    id: '1'
+    num: 1
+    config_name: train.yaml
+    env_set: {}
+    env_copy: []
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+    - 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: focusConvReLU_MSE_150.yaml
+      debug: null
+      experiment: null
+      log_dir: default.yaml
+      trainer: long.yaml
+      logger: many_loggers
+      callbacks: default.yaml
+      model: focusConvReLU_150.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/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/1/.hydra/overrides.yaml

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+- model.lr=0.007202790846042897
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+- model.conv2_size=3
+- model.conv2_channels=6
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+- model.lin2_size=16
+- hparams_search=focusConvReLU_MSE_150.yaml

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logs/experiments/multiruns/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/1/csv/version_0/hparams.yaml

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+    verbose: false
+    dirpath: checkpoints/
+    filename: epoch_{epoch:03d}
+    auto_insert_metric_name: false
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+    min_delta: 0
+  model_summary:
+    _target_: pytorch_lightning.callbacks.RichModelSummary
+    max_depth: -1
+  rich_progress_bar:
+    _target_: pytorch_lightning.callbacks.RichProgressBar
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+model/params/trainable: 502143
+model/params/non_trainable: 0

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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_conv_module.FocusConvReLULitModule
+  image_size: 150
+  pool_size: 2
+  conv1_size: 3
+  conv1_channels: 6
+  conv2_size: 3
+  conv2_channels: 6
+  lin1_size: 72
+  lin2_size: 16
+  output_size: 1
+  lr: 0.007202790846042897
+  weight_decay: 0.0005
+datamodule:
+  _target_: src.datamodules.focus_datamodule.FocusDataModule
+  data_dir: /usr/src/app/data/focus150
+  csv_train_file: /usr/src/app/data/focus150/train_metadata.csv
+  csv_val_file: /usr/src/app/data/focus150/validation_metadata.csv
+  csv_test_file: /usr/src/app/data/focus150/test_metadata.csv
+  batch_size: 64
+  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: 502143
+model/params/trainable: 502143
+model/params/non_trainable: 0

logs/experiments/multiruns/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/10/.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: focusConvReLU_MSE_150_hyperparameter_search
+datamodule:
+  _target_: src.datamodules.focus_datamodule.FocusDataModule
+  data_dir: ${data_dir}/focus150
+  csv_train_file: ${data_dir}/focus150/train_metadata.csv
+  csv_val_file: ${data_dir}/focus150/validation_metadata.csv
+  csv_test_file: ${data_dir}/focus150/test_metadata.csv
+  batch_size: 64
+  num_workers: 0
+  pin_memory: false
+model:
+  _target_: src.models.focus_conv_module.FocusConvReLULitModule
+  image_size: 150
+  pool_size: 2
+  conv1_size: 5
+  conv1_channels: 6
+  conv2_size: 7
+  conv2_channels: 9
+  lin1_size: 32
+  lin2_size: 72
+  output_size: 1
+  lr: 0.00036397175769800963
+  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:
+  csv:
+    _target_: pytorch_lightning.loggers.csv_logs.CSVLogger
+    save_dir: .
+    name: csv/
+    prefix: ''
+  mlflow:
+    _target_: pytorch_lightning.loggers.mlflow.MLFlowLogger
+    experiment_name: ${name}
+    tracking_uri: ${original_work_dir}/logs/mlflow/mlruns
+    tags: null
+    save_dir: ./mlruns
+    prefix: ''
+    artifact_location: null
+  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/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/10/.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: focusConvReLU_MSE_150_hyperparameter_search
+    n_trials: 20
+    n_jobs: 1
+    search_space:
+      datamodule.batch_size:
+        type: categorical
+        choices:
+        - 64
+      model.lr:
+        type: float
+        low: 0.0001
+        high: 0.01
+      model.conv1_size:
+        type: categorical
+        choices:
+        - 3
+        - 5
+        - 7
+      model.conv1_channels:
+        type: categorical
+        choices:
+        - 3
+        - 6
+        - 9
+      model.conv2_size:
+        type: categorical
+        choices:
+        - 3
+        - 5
+        - 7
+      model.conv2_channels:
+        type: categorical
+        choices:
+        - 3
+        - 6
+        - 9
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+        type: categorical
+        choices:
+        - 16
+        - 32
+        - 72
+        - 128
+      model.lin2_size:
+        type: categorical
+        choices:
+        - 16
+        - 32
+        - 72
+        - 128
+  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
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+      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=0.00036397175769800963
+    - model.conv1_size=5
+    - model.conv1_channels=6
+    - model.conv2_size=7
+    - model.conv2_channels=9
+    - model.lin1_size=32
+    - model.lin2_size=72
+    - hparams_search=focusConvReLU_MSE_150.yaml
+  job:
+    name: train
+    override_dirname: datamodule.batch_size=64,hparams_search=focusConvReLU_MSE_150.yaml,model.conv1_channels=6,model.conv1_size=5,model.conv2_channels=9,model.conv2_size=7,model.lin1_size=32,model.lin2_size=72,model.lr=0.00036397175769800963
+    id: '10'
+    num: 10
+    config_name: train.yaml
+    env_set: {}
+    env_copy: []
+    config:
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+        item_sep: ','
+        exclude_keys: []
+  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: focusConvReLU_MSE_150.yaml
+      debug: null
+      experiment: null
+      log_dir: default.yaml
+      trainer: long.yaml
+      logger: many_loggers
+      callbacks: default.yaml
+      model: focusConvReLU_150.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/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/10/.hydra/overrides.yaml

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+- model.lr=0.00036397175769800963
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+- model.conv2_size=7
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+- model.lin2_size=72
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+  data_dir: /usr/src/app/data/focus150
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logs/experiments/multiruns/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/11/.hydra/config.yaml

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+name: focusConvReLU_MSE_150_hyperparameter_search
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+  csv_val_file: ${data_dir}/focus150/validation_metadata.csv
+  csv_test_file: ${data_dir}/focus150/test_metadata.csv
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+    dirpath: checkpoints/
+    filename: epoch_{epoch:03d}
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+    _target_: pytorch_lightning.loggers.csv_logs.CSVLogger
+    save_dir: .
+    name: csv/
+    prefix: ''
+  mlflow:
+    _target_: pytorch_lightning.loggers.mlflow.MLFlowLogger
+    experiment_name: ${name}
+    tracking_uri: ${original_work_dir}/logs/mlflow/mlruns
+    tags: null
+    save_dir: ./mlruns
+    prefix: ''
+    artifact_location: null
+  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/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/11/.hydra/hydra.yaml

@@ -0,0 +1,241 @@
+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: focusConvReLU_MSE_150_hyperparameter_search
+    n_trials: 20
+    n_jobs: 1
+    search_space:
+      datamodule.batch_size:
+        type: categorical
+        choices:
+        - 64
+      model.lr:
+        type: float
+        low: 0.0001
+        high: 0.01
+      model.conv1_size:
+        type: categorical
+        choices:
+        - 3
+        - 5
+        - 7
+      model.conv1_channels:
+        type: categorical
+        choices:
+        - 3
+        - 6
+        - 9
+      model.conv2_size:
+        type: categorical
+        choices:
+        - 3
+        - 5
+        - 7
+      model.conv2_channels:
+        type: categorical
+        choices:
+        - 3
+        - 6
+        - 9
+      model.lin1_size:
+        type: categorical
+        choices:
+        - 16
+        - 32
+        - 72
+        - 128
+      model.lin2_size:
+        type: categorical
+        choices:
+        - 16
+        - 32
+        - 72
+        - 128
+  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=0.00017488815901394057
+    - model.conv1_size=5
+    - model.conv1_channels=6
+    - model.conv2_size=7
+    - model.conv2_channels=9
+    - model.lin1_size=32
+    - model.lin2_size=72
+    - hparams_search=focusConvReLU_MSE_150.yaml
+  job:
+    name: train
+    override_dirname: datamodule.batch_size=64,hparams_search=focusConvReLU_MSE_150.yaml,model.conv1_channels=6,model.conv1_size=5,model.conv2_channels=9,model.conv2_size=7,model.lin1_size=32,model.lin2_size=72,model.lr=0.00017488815901394057
+    id: '11'
+    num: 11
+    config_name: train.yaml
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.1.2
+    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: focusConvReLU_MSE_150.yaml
+      debug: null
+      experiment: null
+      log_dir: default.yaml
+      trainer: long.yaml
+      logger: many_loggers
+      callbacks: default.yaml
+      model: focusConvReLU_150.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/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/11/.hydra/overrides.yaml

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+- datamodule.batch_size=64
+- model.lr=0.00017488815901394057
+- model.conv1_size=5
+- model.conv1_channels=6
+- model.conv2_size=7
+- model.conv2_channels=9
+- model.lin1_size=32
+- model.lin2_size=72
+- hparams_search=focusConvReLU_MSE_150.yaml

logs/experiments/multiruns/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/11/checkpoints/epoch_096.ckpt

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logs/experiments/multiruns/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/11/checkpoints/last.ckpt

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+size 4072399

logs/experiments/multiruns/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/11/csv/version_0/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_conv_module.FocusConvReLULitModule
+  image_size: 150
+  pool_size: 2
+  conv1_size: 5
+  conv1_channels: 6
+  conv2_size: 7
+  conv2_channels: 9
+  lin1_size: 32
+  lin2_size: 72
+  output_size: 1
+  lr: 0.00017488815901394057
+  weight_decay: 0.0005
+datamodule:
+  _target_: src.datamodules.focus_datamodule.FocusDataModule
+  data_dir: /usr/src/app/data/focus150
+  csv_train_file: /usr/src/app/data/focus150/train_metadata.csv
+  csv_val_file: /usr/src/app/data/focus150/validation_metadata.csv
+  csv_test_file: /usr/src/app/data/focus150/test_metadata.csv
+  batch_size: 64
+  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: 337848
+model/params/trainable: 337848
+model/params/non_trainable: 0

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logs/experiments/multiruns/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/11/tensorboard/focusConvReLU_MSE_150_hyperparameter_search/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_conv_module.FocusConvReLULitModule
+  image_size: 150
+  pool_size: 2
+  conv1_size: 5
+  conv1_channels: 6
+  conv2_size: 7
+  conv2_channels: 9
+  lin1_size: 32
+  lin2_size: 72
+  output_size: 1
+  lr: 0.00017488815901394057
+  weight_decay: 0.0005
+datamodule:
+  _target_: src.datamodules.focus_datamodule.FocusDataModule
+  data_dir: /usr/src/app/data/focus150
+  csv_train_file: /usr/src/app/data/focus150/train_metadata.csv
+  csv_val_file: /usr/src/app/data/focus150/validation_metadata.csv
+  csv_test_file: /usr/src/app/data/focus150/test_metadata.csv
+  batch_size: 64
+  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: 337848
+model/params/trainable: 337848
+model/params/non_trainable: 0

logs/experiments/multiruns/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/12/.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: focusConvReLU_MSE_150_hyperparameter_search
+datamodule:
+  _target_: src.datamodules.focus_datamodule.FocusDataModule
+  data_dir: ${data_dir}/focus150
+  csv_train_file: ${data_dir}/focus150/train_metadata.csv
+  csv_val_file: ${data_dir}/focus150/validation_metadata.csv
+  csv_test_file: ${data_dir}/focus150/test_metadata.csv
+  batch_size: 64
+  num_workers: 0
+  pin_memory: false
+model:
+  _target_: src.models.focus_conv_module.FocusConvReLULitModule
+  image_size: 150
+  pool_size: 2
+  conv1_size: 5
+  conv1_channels: 6
+  conv2_size: 7
+  conv2_channels: 9
+  lin1_size: 32
+  lin2_size: 72
+  output_size: 1
+  lr: 0.00018632655175274539
+  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:
+  csv:
+    _target_: pytorch_lightning.loggers.csv_logs.CSVLogger
+    save_dir: .
+    name: csv/
+    prefix: ''
+  mlflow:
+    _target_: pytorch_lightning.loggers.mlflow.MLFlowLogger
+    experiment_name: ${name}
+    tracking_uri: ${original_work_dir}/logs/mlflow/mlruns
+    tags: null
+    save_dir: ./mlruns
+    prefix: ''
+    artifact_location: null
+  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/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/12/.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: focusConvReLU_MSE_150_hyperparameter_search
+    n_trials: 20
+    n_jobs: 1
+    search_space:
+      datamodule.batch_size:
+        type: categorical
+        choices:
+        - 64
+      model.lr:
+        type: float
+        low: 0.0001
+        high: 0.01
+      model.conv1_size:
+        type: categorical
+        choices:
+        - 3
+        - 5
+        - 7
+      model.conv1_channels:
+        type: categorical
+        choices:
+        - 3
+        - 6
+        - 9
+      model.conv2_size:
+        type: categorical
+        choices:
+        - 3
+        - 5
+        - 7
+      model.conv2_channels:
+        type: categorical
+        choices:
+        - 3
+        - 6
+        - 9
+      model.lin1_size:
+        type: categorical
+        choices:
+        - 16
+        - 32
+        - 72
+        - 128
+      model.lin2_size:
+        type: categorical
+        choices:
+        - 16
+        - 32
+        - 72
+        - 128
+  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=0.00018632655175274539
+    - model.conv1_size=5
+    - model.conv1_channels=6
+    - model.conv2_size=7
+    - model.conv2_channels=9
+    - model.lin1_size=32
+    - model.lin2_size=72
+    - hparams_search=focusConvReLU_MSE_150.yaml
+  job:
+    name: train
+    override_dirname: datamodule.batch_size=64,hparams_search=focusConvReLU_MSE_150.yaml,model.conv1_channels=6,model.conv1_size=5,model.conv2_channels=9,model.conv2_size=7,model.lin1_size=32,model.lin2_size=72,model.lr=0.00018632655175274539
+    id: '12'
+    num: 12
+    config_name: train.yaml
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.1.2
+    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: focusConvReLU_MSE_150.yaml
+      debug: null
+      experiment: null
+      log_dir: default.yaml
+      trainer: long.yaml
+      logger: many_loggers
+      callbacks: default.yaml
+      model: focusConvReLU_150.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/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/12/.hydra/overrides.yaml

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+- datamodule.batch_size=64
+- model.lr=0.00018632655175274539
+- model.conv1_size=5
+- model.conv1_channels=6
+- model.conv2_size=7
+- model.conv2_channels=9
+- model.lin1_size=32
+- model.lin2_size=72
+- hparams_search=focusConvReLU_MSE_150.yaml

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logs/experiments/multiruns/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/12/csv/version_0/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_conv_module.FocusConvReLULitModule
+  image_size: 150
+  pool_size: 2
+  conv1_size: 5
+  conv1_channels: 6
+  conv2_size: 7
+  conv2_channels: 9
+  lin1_size: 32
+  lin2_size: 72
+  output_size: 1
+  lr: 0.00018632655175274539
+  weight_decay: 0.0005
+datamodule:
+  _target_: src.datamodules.focus_datamodule.FocusDataModule
+  data_dir: /usr/src/app/data/focus150
+  csv_train_file: /usr/src/app/data/focus150/train_metadata.csv
+  csv_val_file: /usr/src/app/data/focus150/validation_metadata.csv
+  csv_test_file: /usr/src/app/data/focus150/test_metadata.csv
+  batch_size: 64
+  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: 337848
+model/params/trainable: 337848
+model/params/non_trainable: 0

logs/experiments/multiruns/focusConvReLU_MSE_150_hyperparameter_search/2022-05-11_14-55-00/12/csv/version_0/metrics.csv

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