change conv model to use activation function and rerun a training run

logs/experiments/runs/focusConvMSE_150/2022-05-11_07-46-18/.hydra/config.yaml

@@ -0,0 +1,80 @@
+original_work_dir: ${hydra:runtime.cwd}
+data_dir: ${original_work_dir}/data
+print_config: true
+ignore_warnings: true
+train: true
+test: true
+seed: 12345
+name: focusConvMSE_150
+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_conv_module.FocusConvLitModule
+  image_size: 150
+  pool_size: 2
+  conv1_size: 5
+  conv1_channels: 6
+  conv2_size: 5
+  conv2_channels: 16
+  lin1_size: 100
+  lin2_size: 80
+  output_size: 1
+  lr: 0.001
+  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

logs/experiments/runs/focusConvMSE_150/2022-05-11_07-46-18/.hydra/hydra.yaml

@@ -0,0 +1,170 @@
+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:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+  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:
+    - experiment=focusConvMSE_150
+  job:
+    name: train
+    override_dirname: experiment=focusConvMSE_150
+    id: ???
+    num: ???
+    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: null
+      debug: null
+      experiment: focusConvMSE_150
+      log_dir: default.yaml
+      trainer: default.yaml
+      logger: many_loggers
+      callbacks: default.yaml
+      model: focusConv_150.yaml
+      datamodule: focus150.yaml
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: colorlog
+      hydra/hydra_logging: colorlog
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

logs/experiments/runs/focusConvMSE_150/2022-05-11_07-46-18/.hydra/overrides.yaml

@@ -0,0 +1 @@
+- experiment=focusConvMSE_150

logs/experiments/runs/focusConvMSE_150/2022-05-11_07-46-18/checkpoints/epoch_075.ckpt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1388bc7e1659b1d7365261d6b7561f73b08cd759cc24b94028603d9cccfa82d7
+size 22354437

logs/experiments/runs/focusConvMSE_150/2022-05-11_07-46-18/checkpoints/last.ckpt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:28a726f99e423ff51a8a6660f08a299d3bd4d24d038ab02d088118246133fa32
+size 22354437

logs/experiments/runs/focusConvMSE_150/2022-05-11_07-46-18/csv/version_0/hparams.yaml

@@ -0,0 +1,54 @@
+trainer:
+  _target_: pytorch_lightning.Trainer
+  gpus: 1
+  min_epochs: 1
+  max_epochs: 100
+  resume_from_checkpoint: null
+model:
+  _target_: src.models.focus_conv_module.FocusConvLitModule
+  image_size: 150
+  pool_size: 2
+  conv1_size: 5
+  conv1_channels: 6
+  conv2_size: 5
+  conv2_channels: 16
+  lin1_size: 100
+  lin2_size: 80
+  output_size: 1
+  lr: 0.001
+  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: 12345
+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: 1861789
+model/params/trainable: 1861789
+model/params/non_trainable: 0

logs/experiments/runs/focusConvMSE_150/2022-05-11_07-46-18/csv/version_0/metrics.csv

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