run fc models hyperparameter tuning again on MSE model

configs/hparams_search/{focusMAE_150_optuna.yaml → focusMSE_150_optuna.yaml}

@@ -12,7 +12,7 @@ defaults:
 # make sure this is the correct name of some metric logged in lightning module!
 optimized_metric: "val/mae_best"
 
-name: "focusMAE_150_hyperparameter_search"
+name: "focusMSE_150_hyperparameter_search"
 
 # here we define Optuna hyperparameter search
 # it optimizes for value returned from function with @hydra.main decorator
@@ -35,7 +35,7 @@ hydra:
  direction: minimize
 
  # total number of runs that will be executed
- n_trials: 25
+ n_trials: 20
 
  # choose Optuna hyperparameter sampler
  # docs: https://optuna.readthedocs.io/en/stable/reference/samplers.html

configs/model/focus150.yaml

@@ -1,4 +1,4 @@
-_target_: src.models.focus_module.FocusLitModule
+_target_: src.models.focus_module.FocusMSELitModule
 
 input_size: 67500
 lin1_size: 256

logs/experiments/multiruns/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/0/.hydra/config.yaml

@@ -0,0 +1,77 @@
+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: focusMSE_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_module.FocusMSELitModule
+ input_size: 67500
+ lin1_size: 512
+ lin2_size: 512
+ lin3_size: 1024
+ output_size: 1
+ lr: 0.03686537045425119
+ 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/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/0/.hydra/hydra.yaml

@@ -0,0 +1,225 @@
+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: focusMAE_150_hyperparameter_search
+ n_trials: 20
+ n_jobs: 1
+ search_space:
+ datamodule.batch_size:
+ type: categorical
+ choices:
+ - 64
+ - 128
+ model.lr:
+ type: float
+ low: 0.0001
+ high: 0.2
+ model.lin1_size:
+ type: categorical
+ choices:
+ - 64
+ - 128
+ - 256
+ - 512
+ - 1024
+ model.lin2_size:
+ type: categorical
+ choices:
+ - 64
+ - 128
+ - 256
+ - 512
+ - 1024
+ model.lin3_size:
+ type: categorical
+ choices:
+ - 64
+ - 128
+ - 256
+ - 512
+ - 1024
+ 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=0.03686537045425119
+ - model.lin1_size=512
+ - model.lin2_size=512
+ - model.lin3_size=1024
+ - hparams_search=focusMSE_150_optuna.yaml
+ job:
+ name: train
+ override_dirname: datamodule.batch_size=64,hparams_search=focusMSE_150_optuna.yaml,model.lin1_size=512,model.lin2_size=512,model.lin3_size=1024,model.lr=0.03686537045425119
+ 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: focusMSE_150_optuna.yaml
+ debug: null
+ experiment: null
+ log_dir: default.yaml
+ trainer: long.yaml
+ logger: many_loggers
+ 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/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/0/.hydra/overrides.yaml

@@ -0,0 +1,6 @@
+- datamodule.batch_size=64
+- model.lr=0.03686537045425119
+- model.lin1_size=512
+- model.lin2_size=512
+- model.lin3_size=1024
+- hparams_search=focusMSE_150_optuna.yaml

logs/experiments/multiruns/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/0/checkpoints/epoch_085.ckpt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0d1a67b4da401a35ee406ad6561f4174a114de6526bee3b873b5d92ba0a1fdbb
+size 424279302

logs/experiments/multiruns/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/0/checkpoints/last.ckpt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2f8026d168a4cd95f76889a1b00f191fa5f6d69af2cd941fb628eb5c8f27f2e1
+size 424279302

logs/experiments/multiruns/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/0/csv/version_0/hparams.yaml

@@ -0,0 +1,50 @@
+trainer:
+ _target_: pytorch_lightning.Trainer
+ gpus: 1
+ min_epochs: 1
+ max_epochs: 100
+ resume_from_checkpoint: null
+model:
+ _target_: src.models.focus_module.FocusMSELitModule
+ input_size: 67500
+ lin1_size: 512
+ lin2_size: 512
+ lin3_size: 1024
+ output_size: 1
+ lr: 0.03686537045425119
+ 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: 35353601
+model/params/trainable: 35353601
+model/params/non_trainable: 0

logs/experiments/multiruns/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/0/csv/version_0/metrics.csv

@@ -0,0 +1,202 @@
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logs/experiments/multiruns/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/0/tensorboard/focusMSE_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_module.FocusMSELitModule
+ input_size: 67500
+ lin1_size: 512
+ lin2_size: 512
+ lin3_size: 1024
+ output_size: 1
+ lr: 0.03686537045425119
+ 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: 35353601
+model/params/trainable: 35353601
+model/params/non_trainable: 0

logs/experiments/multiruns/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/1/.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: focusMSE_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_module.FocusMSELitModule
+ input_size: 67500
+ lin1_size: 1024
+ lin2_size: 64
+ lin3_size: 128
+ output_size: 1
+ lr: 0.12853081804637867
+ 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/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/1/.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: focusMAE_150_hyperparameter_search
+ n_trials: 20
+ n_jobs: 1
+ search_space:
+ datamodule.batch_size:
+ type: categorical
+ choices:
+ - 64
+ - 128
+ model.lr:
+ type: float
+ low: 0.0001
+ high: 0.2
+ model.lin1_size:
+ type: categorical
+ choices:
+ - 64
+ - 128
+ - 256
+ - 512
+ - 1024
+ model.lin2_size:
+ type: categorical
+ choices:
+ - 64
+ - 128
+ - 256
+ - 512
+ - 1024
+ model.lin3_size:
+ type: categorical
+ choices:
+ - 64
+ - 128
+ - 256
+ - 512
+ - 1024
+ 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=0.12853081804637867
+ - model.lin1_size=1024
+ - model.lin2_size=64
+ - model.lin3_size=128
+ - hparams_search=focusMSE_150_optuna.yaml
+ job:
+ name: train
+ override_dirname: datamodule.batch_size=64,hparams_search=focusMSE_150_optuna.yaml,model.lin1_size=1024,model.lin2_size=64,model.lin3_size=128,model.lr=0.12853081804637867
+ id: '1'
+ num: 1
+ config_name: train.yaml
+ env_set: {}
+ env_copy: []
+ config:
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+ 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: focusMSE_150_optuna.yaml
+ debug: null
+ experiment: null
+ log_dir: default.yaml
+ trainer: long.yaml
+ logger: many_loggers
+ 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/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/1/.hydra/overrides.yaml

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+- model.lr=0.12853081804637867
+- model.lin1_size=1024
+- model.lin2_size=64
+- model.lin3_size=128
+- hparams_search=focusMSE_150_optuna.yaml

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+trainer:
+ _target_: pytorch_lightning.Trainer
+ gpus: 1
+ min_epochs: 1
+ max_epochs: 100
+ resume_from_checkpoint: null
+model:
+ _target_: src.models.focus_module.FocusMSELitModule
+ input_size: 67500
+ lin1_size: 1024
+ lin2_size: 64
+ lin3_size: 128
+ output_size: 1
+ lr: 0.12853081804637867
+ 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:
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+ _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: 69197505
+model/params/trainable: 69197505
+model/params/non_trainable: 0

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+ gpus: 1
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+ _target_: src.models.focus_module.FocusMSELitModule
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+ data_dir: /usr/src/app/data/focus150
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+ csv_val_file: /usr/src/app/data/focus150/validation_metadata.csv
+ csv_test_file: /usr/src/app/data/focus150/test_metadata.csv
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+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: 69197505
+model/params/trainable: 69197505
+model/params/non_trainable: 0

logs/experiments/multiruns/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/10/.hydra/config.yaml

@@ -0,0 +1,77 @@
+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: focusMSE_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_module.FocusMSELitModule
+ input_size: 67500
+ lin1_size: 512
+ lin2_size: 128
+ lin3_size: 64
+ output_size: 1
+ lr: 0.02282695974132741
+ 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/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/10/.hydra/hydra.yaml

@@ -0,0 +1,225 @@
+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: focusMAE_150_hyperparameter_search
+ n_trials: 20
+ n_jobs: 1
+ search_space:
+ datamodule.batch_size:
+ type: categorical
+ choices:
+ - 64
+ - 128
+ model.lr:
+ type: float
+ low: 0.0001
+ high: 0.2
+ model.lin1_size:
+ type: categorical
+ choices:
+ - 64
+ - 128
+ - 256
+ - 512
+ - 1024
+ model.lin2_size:
+ type: categorical
+ choices:
+ - 64
+ - 128
+ - 256
+ - 512
+ - 1024
+ model.lin3_size:
+ type: categorical
+ choices:
+ - 64
+ - 128
+ - 256
+ - 512
+ - 1024
+ 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=0.02282695974132741
+ - model.lin1_size=512
+ - model.lin2_size=128
+ - model.lin3_size=64
+ - hparams_search=focusMSE_150_optuna.yaml
+ job:
+ name: train
+ override_dirname: datamodule.batch_size=64,hparams_search=focusMSE_150_optuna.yaml,model.lin1_size=512,model.lin2_size=128,model.lin3_size=64,model.lr=0.02282695974132741
+ id: '10'
+ num: 10
+ config_name: train.yaml
+ env_set: {}
+ env_copy: []
+ config:
+ override_dirname:
+ kv_sep: '='
+ item_sep: ','
+ exclude_keys: []
+ runtime:
+ version: 1.1.2
+ 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: focusMSE_150_optuna.yaml
+ debug: null
+ experiment: null
+ log_dir: default.yaml
+ trainer: long.yaml
+ logger: many_loggers
+ 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/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/10/.hydra/overrides.yaml

@@ -0,0 +1,6 @@
+- datamodule.batch_size=64
+- model.lr=0.02282695974132741
+- model.lin1_size=512
+- model.lin2_size=128
+- model.lin3_size=64
+- hparams_search=focusMSE_150_optuna.yaml

logs/experiments/multiruns/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/10/checkpoints/epoch_043.ckpt

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+size 415656134

logs/experiments/multiruns/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/10/checkpoints/last.ckpt

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+size 415656134

logs/experiments/multiruns/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/10/csv/version_0/hparams.yaml

@@ -0,0 +1,50 @@
+trainer:
+ _target_: pytorch_lightning.Trainer
+ gpus: 1
+ min_epochs: 1
+ max_epochs: 100
+ resume_from_checkpoint: null
+model:
+ _target_: src.models.focus_module.FocusMSELitModule
+ input_size: 67500
+ lin1_size: 512
+ lin2_size: 128
+ lin3_size: 64
+ output_size: 1
+ lr: 0.02282695974132741
+ 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: 34635905
+model/params/trainable: 34635905
+model/params/non_trainable: 0

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logs/experiments/multiruns/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/10/tensorboard/focusMSE_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_module.FocusMSELitModule
+ input_size: 67500
+ lin1_size: 512
+ lin2_size: 128
+ lin3_size: 64
+ output_size: 1
+ lr: 0.02282695974132741
+ 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: 34635905
+model/params/trainable: 34635905
+model/params/non_trainable: 0

logs/experiments/multiruns/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/11/.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: focusMSE_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: 128
+ num_workers: 0
+ pin_memory: false
+model:
+ _target_: src.models.focus_module.FocusMSELitModule
+ input_size: 67500
+ lin1_size: 64
+ lin2_size: 64
+ lin3_size: 1024
+ output_size: 1
+ lr: 0.19688938412353008
+ 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/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/11/.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: focusMAE_150_hyperparameter_search
+ n_trials: 20
+ n_jobs: 1
+ search_space:
+ datamodule.batch_size:
+ type: categorical
+ choices:
+ - 64
+ - 128
+ model.lr:
+ type: float
+ low: 0.0001
+ high: 0.2
+ model.lin1_size:
+ type: categorical
+ choices:
+ - 64
+ - 128
+ - 256
+ - 512
+ - 1024
+ model.lin2_size:
+ type: categorical
+ choices:
+ - 64
+ - 128
+ - 256
+ - 512
+ - 1024
+ model.lin3_size:
+ type: categorical
+ choices:
+ - 64
+ - 128
+ - 256
+ - 512
+ - 1024
+ 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=0.19688938412353008
+ - model.lin1_size=64
+ - model.lin2_size=64
+ - model.lin3_size=1024
+ - hparams_search=focusMSE_150_optuna.yaml
+ job:
+ name: train
+ override_dirname: datamodule.batch_size=128,hparams_search=focusMSE_150_optuna.yaml,model.lin1_size=64,model.lin2_size=64,model.lin3_size=1024,model.lr=0.19688938412353008
+ 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: focusMSE_150_optuna.yaml
+ debug: null
+ experiment: null
+ log_dir: default.yaml
+ trainer: long.yaml
+ logger: many_loggers
+ 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/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/11/.hydra/overrides.yaml

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+- model.lr=0.19688938412353008
+- model.lin1_size=64
+- model.lin2_size=64
+- model.lin3_size=1024
+- hparams_search=focusMSE_150_optuna.yaml

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+trainer:
+ _target_: pytorch_lightning.Trainer
+ gpus: 1
+ min_epochs: 1
+ max_epochs: 100
+ resume_from_checkpoint: null
+model:
+ _target_: src.models.focus_module.FocusMSELitModule
+ input_size: 67500
+ lin1_size: 64
+ lin2_size: 64
+ lin3_size: 1024
+ output_size: 1
+ lr: 0.19688938412353008
+ 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: 128
+ 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
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+ _target_: pytorch_lightning.callbacks.RichProgressBar
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+ _target_: src.models.focus_module.FocusMSELitModule
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+ csv_val_file: /usr/src/app/data/focus150/validation_metadata.csv
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+model/params/trainable: 4394113
+model/params/non_trainable: 0

logs/experiments/multiruns/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/12/.hydra/config.yaml

@@ -0,0 +1,77 @@
+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: focusMSE_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: 128
+ num_workers: 0
+ pin_memory: false
+model:
+ _target_: src.models.focus_module.FocusMSELitModule
+ input_size: 67500
+ lin1_size: 64
+ lin2_size: 512
+ lin3_size: 1024
+ output_size: 1
+ lr: 0.06633213937592236
+ 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/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/12/.hydra/hydra.yaml

@@ -0,0 +1,225 @@
+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: focusMAE_150_hyperparameter_search
+ n_trials: 20
+ n_jobs: 1
+ search_space:
+ datamodule.batch_size:
+ type: categorical
+ choices:
+ - 64
+ - 128
+ model.lr:
+ type: float
+ low: 0.0001
+ high: 0.2
+ model.lin1_size:
+ type: categorical
+ choices:
+ - 64
+ - 128
+ - 256
+ - 512
+ - 1024
+ model.lin2_size:
+ type: categorical
+ choices:
+ - 64
+ - 128
+ - 256
+ - 512
+ - 1024
+ model.lin3_size:
+ type: categorical
+ choices:
+ - 64
+ - 128
+ - 256
+ - 512
+ - 1024
+ 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=0.06633213937592236
+ - model.lin1_size=64
+ - model.lin2_size=512
+ - model.lin3_size=1024
+ - hparams_search=focusMSE_150_optuna.yaml
+ job:
+ name: train
+ override_dirname: datamodule.batch_size=128,hparams_search=focusMSE_150_optuna.yaml,model.lin1_size=64,model.lin2_size=512,model.lin3_size=1024,model.lr=0.06633213937592236
+ 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: focusMSE_150_optuna.yaml
+ debug: null
+ experiment: null
+ log_dir: default.yaml
+ trainer: long.yaml
+ logger: many_loggers
+ 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/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/12/.hydra/overrides.yaml

@@ -0,0 +1,6 @@
+- datamodule.batch_size=128
+- model.lr=0.06633213937592236
+- model.lin1_size=64
+- model.lin2_size=512
+- model.lin3_size=1024
+- hparams_search=focusMSE_150_optuna.yaml

logs/experiments/multiruns/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/12/checkpoints/epoch_048.ckpt

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+size 58627014

logs/experiments/multiruns/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/12/checkpoints/last.ckpt

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logs/experiments/multiruns/focusMSE_150_hyperparameter_search/2022-05-11_10-16-51/12/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_module.FocusMSELitModule
+ input_size: 67500
+ lin1_size: 64
+ lin2_size: 512
+ lin3_size: 1024
+ output_size: 1
+ lr: 0.06633213937592236
+ 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: 128
+ 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: 4882881
+model/params/trainable: 4882881
+model/params/non_trainable: 0

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