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

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

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

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

@@ -1,232 +0,0 @@
-hydra:
- run:
- dir: logs/experiments/runs/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
- sweep:
- dir: logs/experiments/multiruns/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
- subdir: ${hydra.job.num}
- launcher:
- _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
- sweeper:
- sampler:
- _target_: optuna.samplers.TPESampler
- seed: 12345
- consider_prior: true
- prior_weight: 1.0
- consider_magic_clip: true
- consider_endpoints: false
- n_startup_trials: 10
- n_ei_candidates: 24
- multivariate: false
- warn_independent_sampling: true
- _target_: hydra_plugins.hydra_optuna_sweeper.optuna_sweeper.OptunaSweeper
- direction: minimize
- storage: null
- study_name: focus150_hyperparameter_search
- n_trials: 25
- n_jobs: 1
- search_space:
- datamodule.batch_size:
- type: categorical
- choices:
- - 32
- - 64
- - 128
- model.lr:
- type: float
- low: 0.0001
- high: 0.2
- model.lin1_size:
- type: categorical
- choices:
- - 32
- - 64
- - 128
- - 256
- - 512
- - 1024
- - 2048
- model.lin2_size:
- type: categorical
- choices:
- - 32
- - 64
- - 128
- - 256
- - 512
- - 1024
- - 2048
- model.lin3_size:
- type: categorical
- choices:
- - 32
- - 64
- - 128
- - 256
- - 512
- - 1024
- - 2048
- help:
- app_name: ${hydra.job.name}
- header: '${hydra.help.app_name} is powered by Hydra.
-
- '
- footer: 'Powered by Hydra (https://hydra.cc)
-
- Use --hydra-help to view Hydra specific help
-
- '
- template: '${hydra.help.header}
-
- == Configuration groups ==
-
- Compose your configuration from those groups (group=option)
-
-
- $APP_CONFIG_GROUPS
-
-
- == Config ==
-
- Override anything in the config (foo.bar=value)
-
-
- $CONFIG
-
-
- ${hydra.help.footer}
-
- '
- hydra_help:
- template: 'Hydra (${hydra.runtime.version})
-
- See https://hydra.cc for more info.
-
-
- == Flags ==
-
- $FLAGS_HELP
-
-
- == Configuration groups ==
-
- Compose your configuration from those groups (For example, append hydra/job_logging=disabled
- to command line)
-
-
- $HYDRA_CONFIG_GROUPS
-
-
- Use ''--cfg hydra'' to Show the Hydra config.
-
- '
- hydra_help: ???
- hydra_logging:
- version: 1
- formatters:
- colorlog:
- (): colorlog.ColoredFormatter
- format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
- handlers:
- console:
- class: logging.StreamHandler
- formatter: colorlog
- stream: ext://sys.stdout
- root:
- level: INFO
- handlers:
- - console
- disable_existing_loggers: false
- job_logging:
- version: 1
- formatters:
- simple:
- format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
- colorlog:
- (): colorlog.ColoredFormatter
- format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
- - %(message)s'
- log_colors:
- DEBUG: purple
- INFO: green
- WARNING: yellow
- ERROR: red
- CRITICAL: red
- handlers:
- console:
- class: logging.StreamHandler
- formatter: colorlog
- stream: ext://sys.stdout
- file:
- class: logging.FileHandler
- formatter: simple
- filename: ${hydra.job.name}.log
- root:
- level: INFO
- handlers:
- - console
- - file
- disable_existing_loggers: false
- env: {}
- searchpath: []
- callbacks: {}
- output_subdir: .hydra
- overrides:
- hydra: []
- task:
- - datamodule.batch_size=32
- - model.lr=0.04099159968275264
- - model.lin1_size=128
- - model.lin2_size=32
- - model.lin3_size=32
- - hparams_search=focus150_optuna
- job:
- name: train
- override_dirname: datamodule.batch_size=32,hparams_search=focus150_optuna,model.lin1_size=128,model.lin2_size=32,model.lin3_size=32,model.lr=0.04099159968275264
- id: '0'
- num: 0
- config_name: train.yaml
- env_set: {}
- env_copy: []
- config:
- override_dirname:
- kv_sep: '='
- item_sep: ','
- exclude_keys: []
- runtime:
- version: 1.1.1
- cwd: /usr/src/app
- config_sources:
- - path: hydra.conf
- schema: pkg
- provider: hydra
- - path: /usr/src/app/configs
- schema: file
- provider: main
- - path: hydra_plugins.hydra_colorlog.conf
- schema: pkg
- provider: hydra-colorlog
- - path: ''
- schema: structured
- provider: schema
- choices:
- local: default.yaml
- hparams_search: focus150_optuna
- debug: null
- experiment: null
- log_dir: default.yaml
- trainer: long.yaml
- logger: tensorboard
- callbacks: default.yaml
- model: focus150.yaml
- datamodule: focus150.yaml
- hydra/env: default
- hydra/callbacks: null
- hydra/job_logging: colorlog
- hydra/hydra_logging: colorlog
- hydra/hydra_help: default
- hydra/help: default
- hydra/sweeper: optuna
- hydra/sweeper/sampler: tpe
- hydra/launcher: basic
- hydra/output: default
- verbose: false

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

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

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

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:d6afc0f43b3c1bd7933f2a0e2d56b93f74680505b96c42a15f8970c35864b322
-size 36391

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

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

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

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

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

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

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

@@ -1,232 +0,0 @@
-hydra:
- run:
- dir: logs/experiments/runs/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
- sweep:
- dir: logs/experiments/multiruns/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
- subdir: ${hydra.job.num}
- launcher:
- _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
- sweeper:
- sampler:
- _target_: optuna.samplers.TPESampler
- seed: 12345
- consider_prior: true
- prior_weight: 1.0
- consider_magic_clip: true
- consider_endpoints: false
- n_startup_trials: 10
- n_ei_candidates: 24
- multivariate: false
- warn_independent_sampling: true
- _target_: hydra_plugins.hydra_optuna_sweeper.optuna_sweeper.OptunaSweeper
- direction: minimize
- storage: null
- study_name: focus150_hyperparameter_search
- n_trials: 25
- n_jobs: 1
- search_space:
- datamodule.batch_size:
- type: categorical
- choices:
- - 32
- - 64
- - 128
- model.lr:
- type: float
- low: 0.0001
- high: 0.2
- model.lin1_size:
- type: categorical
- choices:
- - 32
- - 64
- - 128
- - 256
- - 512
- - 1024
- - 2048
- model.lin2_size:
- type: categorical
- choices:
- - 32
- - 64
- - 128
- - 256
- - 512
- - 1024
- - 2048
- model.lin3_size:
- type: categorical
- choices:
- - 32
- - 64
- - 128
- - 256
- - 512
- - 1024
- - 2048
- help:
- app_name: ${hydra.job.name}
- header: '${hydra.help.app_name} is powered by Hydra.
-
- '
- footer: 'Powered by Hydra (https://hydra.cc)
-
- Use --hydra-help to view Hydra specific help
-
- '
- template: '${hydra.help.header}
-
- == Configuration groups ==
-
- Compose your configuration from those groups (group=option)
-
-
- $APP_CONFIG_GROUPS
-
-
- == Config ==
-
- Override anything in the config (foo.bar=value)
-
-
- $CONFIG
-
-
- ${hydra.help.footer}
-
- '
- hydra_help:
- template: 'Hydra (${hydra.runtime.version})
-
- See https://hydra.cc for more info.
-
-
- == Flags ==
-
- $FLAGS_HELP
-
-
- == Configuration groups ==
-
- Compose your configuration from those groups (For example, append hydra/job_logging=disabled
- to command line)
-
-
- $HYDRA_CONFIG_GROUPS
-
-
- Use ''--cfg hydra'' to Show the Hydra config.
-
- '
- hydra_help: ???
- hydra_logging:
- version: 1
- formatters:
- colorlog:
- (): colorlog.ColoredFormatter
- format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
- handlers:
- console:
- class: logging.StreamHandler
- formatter: colorlog
- stream: ext://sys.stdout
- root:
- level: INFO
- handlers:
- - console
- disable_existing_loggers: false
- job_logging:
- version: 1
- formatters:
- simple:
- format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
- colorlog:
- (): colorlog.ColoredFormatter
- format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
- - %(message)s'
- log_colors:
- DEBUG: purple
- INFO: green
- WARNING: yellow
- ERROR: red
- CRITICAL: red
- handlers:
- console:
- class: logging.StreamHandler
- formatter: colorlog
- stream: ext://sys.stdout
- file:
- class: logging.FileHandler
- formatter: simple
- filename: ${hydra.job.name}.log
- root:
- level: INFO
- handlers:
- - console
- - file
- disable_existing_loggers: false
- env: {}
- searchpath: []
- callbacks: {}
- output_subdir: .hydra
- overrides:
- hydra: []
- task:
- - datamodule.batch_size=64
- - model.lr=0.15818542131777294
- - model.lin1_size=256
- - model.lin2_size=128
- - model.lin3_size=1024
- - hparams_search=focus150_optuna
- job:
- name: train
- override_dirname: datamodule.batch_size=64,hparams_search=focus150_optuna,model.lin1_size=256,model.lin2_size=128,model.lin3_size=1024,model.lr=0.15818542131777294
- id: '1'
- num: 1
- config_name: train.yaml
- env_set: {}
- env_copy: []
- config:
- override_dirname:
- kv_sep: '='
- item_sep: ','
- exclude_keys: []
- runtime:
- version: 1.1.1
- cwd: /usr/src/app
- config_sources:
- - path: hydra.conf
- schema: pkg
- provider: hydra
- - path: /usr/src/app/configs
- schema: file
- provider: main
- - path: hydra_plugins.hydra_colorlog.conf
- schema: pkg
- provider: hydra-colorlog
- - path: ''
- schema: structured
- provider: schema
- choices:
- local: default.yaml
- hparams_search: focus150_optuna
- debug: null
- experiment: null
- log_dir: default.yaml
- trainer: long.yaml
- logger: tensorboard
- callbacks: default.yaml
- model: focus150.yaml
- datamodule: focus150.yaml
- hydra/env: default
- hydra/callbacks: null
- hydra/job_logging: colorlog
- hydra/hydra_logging: colorlog
- hydra/hydra_help: default
- hydra/help: default
- hydra/sweeper: optuna
- hydra/sweeper/sampler: tpe
- hydra/launcher: basic
- hydra/output: default
- verbose: false

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

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

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

@@ -1,3 +0,0 @@
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logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/1/tensorboard/focus150_optuna/events.out.tfevents.1646394071.e02c2cd1d8ab.1.3

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

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

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

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

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

@@ -1,232 +0,0 @@
-hydra:
- run:
- dir: logs/experiments/runs/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
- sweep:
- dir: logs/experiments/multiruns/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
- subdir: ${hydra.job.num}
- launcher:
- _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
- sweeper:
- sampler:
- _target_: optuna.samplers.TPESampler
- seed: 12345
- consider_prior: true
- prior_weight: 1.0
- consider_magic_clip: true
- consider_endpoints: false
- n_startup_trials: 10
- n_ei_candidates: 24
- multivariate: false
- warn_independent_sampling: true
- _target_: hydra_plugins.hydra_optuna_sweeper.optuna_sweeper.OptunaSweeper
- direction: minimize
- storage: null
- study_name: focus150_hyperparameter_search
- n_trials: 25
- n_jobs: 1
- search_space:
- datamodule.batch_size:
- type: categorical
- choices:
- - 32
- - 64
- - 128
- model.lr:
- type: float
- low: 0.0001
- high: 0.2
- model.lin1_size:
- type: categorical
- choices:
- - 32
- - 64
- - 128
- - 256
- - 512
- - 1024
- - 2048
- model.lin2_size:
- type: categorical
- choices:
- - 32
- - 64
- - 128
- - 256
- - 512
- - 1024
- - 2048
- model.lin3_size:
- type: categorical
- choices:
- - 32
- - 64
- - 128
- - 256
- - 512
- - 1024
- - 2048
- help:
- app_name: ${hydra.job.name}
- header: '${hydra.help.app_name} is powered by Hydra.
-
- '
- footer: 'Powered by Hydra (https://hydra.cc)
-
- Use --hydra-help to view Hydra specific help
-
- '
- template: '${hydra.help.header}
-
- == Configuration groups ==
-
- Compose your configuration from those groups (group=option)
-
-
- $APP_CONFIG_GROUPS
-
-
- == Config ==
-
- Override anything in the config (foo.bar=value)
-
-
- $CONFIG
-
-
- ${hydra.help.footer}
-
- '
- hydra_help:
- template: 'Hydra (${hydra.runtime.version})
-
- See https://hydra.cc for more info.
-
-
- == Flags ==
-
- $FLAGS_HELP
-
-
- == Configuration groups ==
-
- Compose your configuration from those groups (For example, append hydra/job_logging=disabled
- to command line)
-
-
- $HYDRA_CONFIG_GROUPS
-
-
- Use ''--cfg hydra'' to Show the Hydra config.
-
- '
- hydra_help: ???
- hydra_logging:
- version: 1
- formatters:
- colorlog:
- (): colorlog.ColoredFormatter
- format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
- handlers:
- console:
- class: logging.StreamHandler
- formatter: colorlog
- stream: ext://sys.stdout
- root:
- 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:
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- kv_sep: '='
- item_sep: ','
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- runtime:
- version: 1.1.1
- cwd: /usr/src/app
- config_sources:
- - path: hydra.conf
- schema: pkg
- provider: hydra
- - path: /usr/src/app/configs
- schema: file
- provider: main
- - path: hydra_plugins.hydra_colorlog.conf
- schema: pkg
- provider: hydra-colorlog
- - path: ''
- schema: structured
- provider: schema
- choices:
- local: default.yaml
- hparams_search: focus150_optuna
- debug: null
- experiment: null
- log_dir: default.yaml
- trainer: long.yaml
- logger: tensorboard
- callbacks: default.yaml
- model: focus150.yaml
- datamodule: focus150.yaml
- hydra/env: default
- hydra/callbacks: null
- hydra/job_logging: colorlog
- hydra/hydra_logging: colorlog
- hydra/hydra_help: default
- hydra/help: default
- hydra/sweeper: optuna
- hydra/sweeper/sampler: tpe
- hydra/launcher: basic
- hydra/output: default
- verbose: false

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

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

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

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

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

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

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

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

@@ -1,232 +0,0 @@
-hydra:
- run:
- dir: logs/experiments/runs/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
- sweep:
- dir: logs/experiments/multiruns/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
- subdir: ${hydra.job.num}
- launcher:
- _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
- sweeper:
- sampler:
- _target_: optuna.samplers.TPESampler
- seed: 12345
- consider_prior: true
- prior_weight: 1.0
- consider_magic_clip: true
- consider_endpoints: false
- n_startup_trials: 10
- n_ei_candidates: 24
- multivariate: false
- warn_independent_sampling: true
- _target_: hydra_plugins.hydra_optuna_sweeper.optuna_sweeper.OptunaSweeper
- direction: minimize
- storage: null
- study_name: focus150_hyperparameter_search
- n_trials: 25
- n_jobs: 1
- search_space:
- datamodule.batch_size:
- type: categorical
- choices:
- - 32
- - 64
- - 128
- model.lr:
- type: float
- low: 0.0001
- high: 0.2
- model.lin1_size:
- type: categorical
- choices:
- - 32
- - 64
- - 128
- - 256
- - 512
- - 1024
- - 2048
- model.lin2_size:
- type: categorical
- choices:
- - 32
- - 64
- - 128
- - 256
- - 512
- - 1024
- - 2048
- model.lin3_size:
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- choices:
- - 32
- - 64
- - 128
- - 256
- - 512
- - 1024
- - 2048
- help:
- app_name: ${hydra.job.name}
- header: '${hydra.help.app_name} is powered by Hydra.
-
- '
- footer: 'Powered by Hydra (https://hydra.cc)
-
- Use --hydra-help to view Hydra specific help
-
- '
- template: '${hydra.help.header}
-
- == Configuration groups ==
-
- Compose your configuration from those groups (group=option)
-
-
- $APP_CONFIG_GROUPS
-
-
- == Config ==
-
- Override anything in the config (foo.bar=value)
-
-
- $CONFIG
-
-
- ${hydra.help.footer}
-
- '
- hydra_help:
- template: 'Hydra (${hydra.runtime.version})
-
- See https://hydra.cc for more info.
-
-
- == Flags ==
-
- $FLAGS_HELP
-
-
- == Configuration groups ==
-
- Compose your configuration from those groups (For example, append hydra/job_logging=disabled
- to command line)
-
-
- $HYDRA_CONFIG_GROUPS
-
-
- Use ''--cfg hydra'' to Show the Hydra config.
-
- '
- hydra_help: ???
- hydra_logging:
- version: 1
- formatters:
- colorlog:
- (): colorlog.ColoredFormatter
- format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
- handlers:
- console:
- class: logging.StreamHandler
- formatter: colorlog
- stream: ext://sys.stdout
- root:
- level: INFO
- handlers:
- - console
- disable_existing_loggers: false
- 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=0.11779269530261958
- - model.lin1_size=32
- - model.lin2_size=256
- - model.lin3_size=128
- - hparams_search=focus150_optuna
- job:
- name: train
- override_dirname: datamodule.batch_size=64,hparams_search=focus150_optuna,model.lin1_size=32,model.lin2_size=256,model.lin3_size=128,model.lr=0.11779269530261958
- id: '11'
- num: 11
- config_name: train.yaml
- env_set: {}
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- config:
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- kv_sep: '='
- item_sep: ','
- exclude_keys: []
- runtime:
- version: 1.1.1
- cwd: /usr/src/app
- config_sources:
- - path: hydra.conf
- schema: pkg
- provider: hydra
- - path: /usr/src/app/configs
- schema: file
- provider: main
- - path: hydra_plugins.hydra_colorlog.conf
- schema: pkg
- provider: hydra-colorlog
- - path: ''
- schema: structured
- provider: schema
- choices:
- local: default.yaml
- hparams_search: focus150_optuna
- debug: null
- experiment: null
- log_dir: default.yaml
- trainer: long.yaml
- logger: tensorboard
- callbacks: default.yaml
- model: focus150.yaml
- datamodule: focus150.yaml
- hydra/env: default
- hydra/callbacks: null
- hydra/job_logging: colorlog
- hydra/hydra_logging: colorlog
- hydra/hydra_help: default
- hydra/help: default
- hydra/sweeper: optuna
- hydra/sweeper/sampler: tpe
- hydra/launcher: basic
- hydra/output: default
- verbose: false

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

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

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

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

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

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

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

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

@@ -1,232 +0,0 @@
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- 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: ${hydra.job.num}
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- n_ei_candidates: 24
- multivariate: false
- warn_independent_sampling: true
- _target_: hydra_plugins.hydra_optuna_sweeper.optuna_sweeper.OptunaSweeper
- direction: minimize
- storage: null
- study_name: focus150_hyperparameter_search
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- n_jobs: 1
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- - 64
- - 128
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- high: 0.2
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- - 256
- - 512
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- - 512
- - 1024
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- header: '${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 ==
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-
-
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- Use ''--cfg hydra'' to Show the Hydra config.
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- - %(message)s'
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- stream: ext://sys.stdout
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- - model.lin2_size=256
- - model.lin3_size=128
- - hparams_search=focus150_optuna
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- id: '12'
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- - path: hydra_plugins.hydra_colorlog.conf
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- schema: structured
- provider: schema
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- hparams_search: focus150_optuna
- debug: null
- experiment: null
- log_dir: default.yaml
- trainer: long.yaml
- logger: tensorboard
- callbacks: default.yaml
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- datamodule: focus150.yaml
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- hydra/callbacks: null
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- hydra/help: default
- hydra/sweeper: optuna
- hydra/sweeper/sampler: tpe
- hydra/launcher: basic
- hydra/output: default
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logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/12/.hydra/overrides.yaml

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

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

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

@@ -1,52 +0,0 @@
-trainer:
- _target_: pytorch_lightning.Trainer
- gpus: 1
- min_epochs: 1
- max_epochs: 100
- resume_from_checkpoint: null
-model:
- _target_: src.models.focus_module.FocusLitModule
- input_size: 67500
- lin1_size: 32
- lin2_size: 256
- lin3_size: 128
- output_size: 1
- lr: 0.13355237942960652
- weight_decay: 0.0005
-datamodule:
- _target_: src.datamodules.focus_datamodule.FocusDataModule
- data_dir: /usr/src/app/data/focus150
- csv_file: /usr/src/app/data/focus150/metadata.csv
- batch_size: 64
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- num_workers: 0
- pin_memory: false
-seed: null
-callbacks:
- model_checkpoint:
- _target_: pytorch_lightning.callbacks.ModelCheckpoint
- monitor: val/mae
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- save_last: true
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- 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:
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-model/params/total: 2202337
-model/params/trainable: 2202337
-model/params/non_trainable: 0

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

@@ -1,66 +0,0 @@
-original_work_dir: ${hydra:runtime.cwd}
-data_dir: ${original_work_dir}/data
-print_config: true
-ignore_warnings: true
-train: true
-test: true
-seed: null
-name: focus150_optuna
-datamodule:
- _target_: src.datamodules.focus_datamodule.FocusDataModule
- data_dir: ${data_dir}/focus150
- csv_file: ${data_dir}/focus150/metadata.csv
- batch_size: 128
- train_val_test_split_percentage:
- - 0.7
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- - 0.15
- num_workers: 0
- pin_memory: false
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- _target_: src.models.focus_module.FocusLitModule
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- lin3_size: 2048
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- monitor: val/mae
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- save_last: true
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- dirpath: checkpoints/
- filename: epoch_{epoch:03d}
- auto_insert_metric_name: false
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- _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
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- min_epochs: 1
- max_epochs: 100
- resume_from_checkpoint: null
-optimized_metric: val/mae_best

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

@@ -1,232 +0,0 @@
-hydra:
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- dir: logs/experiments/runs/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
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- n_ei_candidates: 24
- multivariate: false
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- _target_: hydra_plugins.hydra_optuna_sweeper.optuna_sweeper.OptunaSweeper
- direction: minimize
- storage: null
- study_name: focus150_hyperparameter_search
- n_trials: 25
- n_jobs: 1
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- type: categorical
- choices:
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- model.lr:
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- high: 0.2
- model.lin1_size:
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- help:
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- header: '${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
-
-
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-
-
- $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:
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- formatter: colorlog
- stream: ext://sys.stdout
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- 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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- - model.lin2_size=512
- - model.lin3_size=2048
- - hparams_search=focus150_optuna
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- override_dirname: datamodule.batch_size=128,hparams_search=focus150_optuna,model.lin1_size=32,model.lin2_size=512,model.lin3_size=2048,model.lr=0.07220274494059103
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- provider: main
- - path: hydra_plugins.hydra_colorlog.conf
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- provider: hydra-colorlog
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- provider: schema
- choices:
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- 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
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- hydra/sweeper: optuna
- hydra/sweeper/sampler: tpe
- hydra/launcher: basic
- hydra/output: default
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logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/13/.hydra/overrides.yaml

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

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

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

@@ -1,52 +0,0 @@
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- _target_: pytorch_lightning.Trainer
- gpus: 1
- min_epochs: 1
- max_epochs: 100
- resume_from_checkpoint: null
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- _target_: src.models.focus_module.FocusLitModule
- input_size: 67500
- lin1_size: 32
- lin2_size: 512
- lin3_size: 2048
- output_size: 1
- lr: 0.07220274494059103
- weight_decay: 0.0005
-datamodule:
- _target_: src.datamodules.focus_datamodule.FocusDataModule
- data_dir: /usr/src/app/data/focus150
- csv_file: /usr/src/app/data/focus150/metadata.csv
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-seed: null
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- model_checkpoint:
- _target_: pytorch_lightning.callbacks.ModelCheckpoint
- monitor: val/mae
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- verbose: false
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- patience: 100
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-model/params/trainable: 3234785
-model/params/non_trainable: 0

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

@@ -1,66 +0,0 @@
-original_work_dir: ${hydra:runtime.cwd}
-data_dir: ${original_work_dir}/data
-print_config: true
-ignore_warnings: true
-train: true
-test: true
-seed: null
-name: focus150_optuna
-datamodule:
- _target_: src.datamodules.focus_datamodule.FocusDataModule
- data_dir: ${data_dir}/focus150
- csv_file: ${data_dir}/focus150/metadata.csv
- batch_size: 128
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- - 0.7
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- pin_memory: false
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- _target_: src.models.focus_module.FocusLitModule
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- _target_: pytorch_lightning.callbacks.ModelCheckpoint
- monitor: val/mae
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- save_last: true
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- dirpath: checkpoints/
- filename: epoch_{epoch:03d}
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- _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
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- _target_: pytorch_lightning.callbacks.RichProgressBar
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- _target_: pytorch_lightning.loggers.tensorboard.TensorBoardLogger
- save_dir: tensorboard/
- name: null
- version: ${name}
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logs/experiments/multiruns/focus150_optuna/2022-03-04_11-30-27/14/.hydra/hydra.yaml

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- _target_: hydra_plugins.hydra_optuna_sweeper.optuna_sweeper.OptunaSweeper
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- high: 0.2
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- 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})
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- See https://hydra.cc for more info.
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- == 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=0.08335231197967785
- - model.lin1_size=2048
- - model.lin2_size=512
- - model.lin3_size=128
- - hparams_search=focus150_optuna
- job:
- name: train
- override_dirname: datamodule.batch_size=128,hparams_search=focus150_optuna,model.lin1_size=2048,model.lin2_size=512,model.lin3_size=128,model.lr=0.08335231197967785
- id: '14'
- num: 14
- config_name: train.yaml
- env_set: {}
- env_copy: []
- config:
- override_dirname:
- kv_sep: '='
- item_sep: ','
- exclude_keys: []
- runtime:
- version: 1.1.1
- cwd: /usr/src/app
- config_sources:
- - path: hydra.conf
- schema: pkg
- provider: hydra
- - path: /usr/src/app/configs
- schema: file
- provider: main
- - path: hydra_plugins.hydra_colorlog.conf
- schema: pkg
- provider: hydra-colorlog
- - path: ''
- schema: structured
- provider: schema
- choices:
- local: default.yaml
- hparams_search: focus150_optuna
- debug: null
- experiment: null
- log_dir: default.yaml
- trainer: long.yaml
- logger: tensorboard
- callbacks: default.yaml
- model: focus150.yaml
- datamodule: focus150.yaml
- hydra/env: default
- hydra/callbacks: null
- hydra/job_logging: colorlog
- hydra/hydra_logging: colorlog
- hydra/hydra_help: default
- hydra/help: default
- hydra/sweeper: optuna
- hydra/sweeper/sampler: tpe
- hydra/launcher: basic
- hydra/output: default
- verbose: false

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

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

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

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

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

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

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

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

@@ -1,232 +0,0 @@
-hydra:
- run:
- dir: logs/experiments/runs/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
- sweep:
- dir: logs/experiments/multiruns/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
- subdir: ${hydra.job.num}
- launcher:
- _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
- sweeper:
- sampler:
- _target_: optuna.samplers.TPESampler
- seed: 12345
- consider_prior: true
- prior_weight: 1.0
- consider_magic_clip: true
- consider_endpoints: false
- n_startup_trials: 10
- n_ei_candidates: 24
- multivariate: false
- warn_independent_sampling: true
- _target_: hydra_plugins.hydra_optuna_sweeper.optuna_sweeper.OptunaSweeper
- direction: minimize
- storage: null
- study_name: focus150_hyperparameter_search
- n_trials: 25
- n_jobs: 1
- search_space:
- datamodule.batch_size:
- type: categorical
- choices:
- - 32
- - 64
- - 128
- model.lr:
- type: float
- low: 0.0001
- high: 0.2
- model.lin1_size:
- type: categorical
- choices:
- - 32
- - 64
- - 128
- - 256
- - 512
- - 1024
- - 2048
- model.lin2_size:
- type: categorical
- choices:
- - 32
- - 64
- - 128
- - 256
- - 512
- - 1024
- - 2048
- model.lin3_size:
- type: categorical
- choices:
- - 32
- - 64
- - 128
- - 256
- - 512
- - 1024
- - 2048
- help:
- app_name: ${hydra.job.name}
- header: '${hydra.help.app_name} is powered by Hydra.
-
- '
- footer: 'Powered by Hydra (https://hydra.cc)
-
- Use --hydra-help to view Hydra specific help
-
- '
- template: '${hydra.help.header}
-
- == Configuration groups ==
-
- Compose your configuration from those groups (group=option)
-
-
- $APP_CONFIG_GROUPS
-
-
- == Config ==
-
- Override anything in the config (foo.bar=value)
-
-
- $CONFIG
-
-
- ${hydra.help.footer}
-
- '
- hydra_help:
- template: 'Hydra (${hydra.runtime.version})
-
- See https://hydra.cc for more info.
-
-
- == Flags ==
-
- $FLAGS_HELP
-
-
- == Configuration groups ==
-
- Compose your configuration from those groups (For example, append hydra/job_logging=disabled
- to command line)
-
-
- $HYDRA_CONFIG_GROUPS
-
-
- Use ''--cfg hydra'' to Show the Hydra config.
-
- '
- hydra_help: ???
- hydra_logging:
- version: 1
- formatters:
- colorlog:
- (): colorlog.ColoredFormatter
- format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
- handlers:
- console:
- class: logging.StreamHandler
- formatter: colorlog
- stream: ext://sys.stdout
- root:
- level: INFO
- handlers:
- - console
- disable_existing_loggers: false
- job_logging:
- version: 1
- formatters:
- simple:
- format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
- colorlog:
- (): colorlog.ColoredFormatter
- format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
- - %(message)s'
- log_colors:
- DEBUG: purple
- INFO: green
- WARNING: yellow
- ERROR: red
- CRITICAL: red
- handlers:
- console:
- class: logging.StreamHandler
- formatter: colorlog
- stream: ext://sys.stdout
- file:
- class: logging.FileHandler
- formatter: simple
- filename: ${hydra.job.name}.log
- root:
- level: INFO
- handlers:
- - console
- - file
- disable_existing_loggers: false
- env: {}
- searchpath: []
- callbacks: {}
- output_subdir: .hydra
- overrides:
- hydra: []
- task:
- - datamodule.batch_size=64
- - model.lr=0.04131276528182434
- - model.lin1_size=64
- - model.lin2_size=256
- - model.lin3_size=128
- - hparams_search=focus150_optuna
- job:
- name: train
- override_dirname: datamodule.batch_size=64,hparams_search=focus150_optuna,model.lin1_size=64,model.lin2_size=256,model.lin3_size=128,model.lr=0.04131276528182434
- id: '15'
- num: 15
- config_name: train.yaml
- env_set: {}
- env_copy: []
- config:
- override_dirname:
- kv_sep: '='
- item_sep: ','
- exclude_keys: []
- runtime:
- version: 1.1.1
- cwd: /usr/src/app
- config_sources:
- - path: hydra.conf
- schema: pkg
- provider: hydra
- - path: /usr/src/app/configs
- schema: file
- provider: main
- - path: hydra_plugins.hydra_colorlog.conf
- schema: pkg
- provider: hydra-colorlog
- - path: ''
- schema: structured
- provider: schema
- choices:
- local: default.yaml
- hparams_search: focus150_optuna
- debug: null
- experiment: null
- log_dir: default.yaml
- trainer: long.yaml
- logger: tensorboard
- callbacks: default.yaml
- model: focus150.yaml
- datamodule: focus150.yaml
- hydra/env: default
- hydra/callbacks: null
- hydra/job_logging: colorlog
- hydra/hydra_logging: colorlog
- hydra/hydra_help: default
- hydra/help: default
- hydra/sweeper: optuna
- hydra/sweeper/sampler: tpe
- hydra/launcher: basic
- hydra/output: default
- verbose: false

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

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

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

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

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

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

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

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

@@ -1,232 +0,0 @@
-hydra:
- run:
- dir: logs/experiments/runs/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
- sweep:
- dir: logs/experiments/multiruns/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
- subdir: ${hydra.job.num}
- launcher:
- _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
- sweeper:
- sampler:
- _target_: optuna.samplers.TPESampler
- seed: 12345
- consider_prior: true
- prior_weight: 1.0
- consider_magic_clip: true
- consider_endpoints: false
- n_startup_trials: 10
- n_ei_candidates: 24
- multivariate: false
- warn_independent_sampling: true
- _target_: hydra_plugins.hydra_optuna_sweeper.optuna_sweeper.OptunaSweeper
- direction: minimize
- storage: null
- study_name: focus150_hyperparameter_search
- n_trials: 25
- n_jobs: 1
- search_space:
- datamodule.batch_size:
- type: categorical
- choices:
- - 32
- - 64
- - 128
- model.lr:
- type: float
- low: 0.0001
- high: 0.2
- model.lin1_size:
- type: categorical
- choices:
- - 32
- - 64
- - 128
- - 256
- - 512
- - 1024
- - 2048
- model.lin2_size:
- type: categorical
- choices:
- - 32
- - 64
- - 128
- - 256
- - 512
- - 1024
- - 2048
- model.lin3_size:
- type: categorical
- choices:
- - 32
- - 64
- - 128
- - 256
- - 512
- - 1024
- - 2048
- help:
- app_name: ${hydra.job.name}
- header: '${hydra.help.app_name} is powered by Hydra.
-
- '
- footer: 'Powered by Hydra (https://hydra.cc)
-
- Use --hydra-help to view Hydra specific help
-
- '
- template: '${hydra.help.header}
-
- == Configuration groups ==
-
- Compose your configuration from those groups (group=option)
-
-
- $APP_CONFIG_GROUPS
-
-
- == Config ==
-
- Override anything in the config (foo.bar=value)
-
-
- $CONFIG
-
-
- ${hydra.help.footer}
-
- '
- hydra_help:
- template: 'Hydra (${hydra.runtime.version})
-
- See https://hydra.cc for more info.
-
-
- == Flags ==
-
- $FLAGS_HELP
-
-
- == Configuration groups ==
-
- Compose your configuration from those groups (For example, append hydra/job_logging=disabled
- to command line)
-
-
- $HYDRA_CONFIG_GROUPS
-
-
- Use ''--cfg hydra'' to Show the Hydra config.
-
- '
- hydra_help: ???
- hydra_logging:
- version: 1
- formatters:
- colorlog:
- (): colorlog.ColoredFormatter
- format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
- handlers:
- console:
- class: logging.StreamHandler
- formatter: colorlog
- stream: ext://sys.stdout
- root:
- level: INFO
- handlers:
- - console
- disable_existing_loggers: false
- job_logging:
- version: 1
- formatters:
- simple:
- format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
- colorlog:
- (): colorlog.ColoredFormatter
- format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
- - %(message)s'
- log_colors:
- DEBUG: purple
- INFO: green
- WARNING: yellow
- ERROR: red
- CRITICAL: red
- handlers:
- console:
- class: logging.StreamHandler
- formatter: colorlog
- stream: ext://sys.stdout
- file:
- class: logging.FileHandler
- formatter: simple
- filename: ${hydra.job.name}.log
- root:
- level: INFO
- handlers:
- - console
- - file
- disable_existing_loggers: false
- env: {}
- searchpath: []
- callbacks: {}
- output_subdir: .hydra
- overrides:
- hydra: []
- task:
- - datamodule.batch_size=128
- - model.lr=0.12875356688119352
- - model.lin1_size=512
- - model.lin2_size=32
- - model.lin3_size=2048
- - hparams_search=focus150_optuna
- job:
- name: train
- override_dirname: datamodule.batch_size=128,hparams_search=focus150_optuna,model.lin1_size=512,model.lin2_size=32,model.lin3_size=2048,model.lr=0.12875356688119352
- id: '16'
- num: 16
- config_name: train.yaml
- env_set: {}
- env_copy: []
- config:
- override_dirname:
- kv_sep: '='
- item_sep: ','
- exclude_keys: []
- runtime:
- version: 1.1.1
- cwd: /usr/src/app
- config_sources:
- - path: hydra.conf
- schema: pkg
- provider: hydra
- - path: /usr/src/app/configs
- schema: file
- provider: main
- - path: hydra_plugins.hydra_colorlog.conf
- schema: pkg
- provider: hydra-colorlog
- - path: ''
- schema: structured
- provider: schema
- choices:
- local: default.yaml
- hparams_search: focus150_optuna
- debug: null
- experiment: null
- log_dir: default.yaml
- trainer: long.yaml
- logger: tensorboard
- callbacks: default.yaml
- model: focus150.yaml
- datamodule: focus150.yaml
- hydra/env: default
- hydra/callbacks: null
- hydra/job_logging: colorlog
- hydra/hydra_logging: colorlog
- hydra/hydra_help: default
- hydra/help: default
- hydra/sweeper: optuna
- hydra/sweeper/sampler: tpe
- hydra/launcher: basic
- hydra/output: default
- verbose: false