diff --git a/configs/experiment/focusLiteNN_150.yaml b/configs/experiment/focusLiteNN_150.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..46154a435b33c1a65dd5c1c37bf5b220b5bbf456
--- /dev/null
+++ b/configs/experiment/focusLiteNN_150.yaml
@@ -0,0 +1,33 @@
+# @package _global_
+
+# to execute this experiment run:
+# python train.py experiment=example
+
+defaults:
+  - override /datamodule: focus150.yaml
+  - override /model: focusLiteNN.yaml
+  - override /callbacks: default.yaml
+  - override /logger: many_loggers
+  - override /trainer: default.yaml
+
+# all parameters below will be merged with parameters from default configurations set above
+# this allows you to overwrite only specified parameters
+
+# name of the run determines folder name in logs
+name: "focusLiteNN_150"
+seed: 12345
+
+trainer:
+  min_epochs: 1
+  max_epochs: 100
+
+model:
+  pre_trained: False
+  num_channel: 3
+  lr: 0.001
+  weight_decay: 0.0005
+
+datamodule:
+  batch_size: 128
+  augmentation: True
+  
\ No newline at end of file
diff --git a/configs/model/focusLiteNN.yaml b/configs/model/focusLiteNN.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..8cdab21f25fa6191eab5da2913ba40df106c051b
--- /dev/null
+++ b/configs/model/focusLiteNN.yaml
@@ -0,0 +1,6 @@
+_target_: src.models.focus_litenn_module.FocusLiteNNLitModule
+
+pre_trained: false
+num_channel: 3
+lr: 0.001
+weight_decay: 0.0005
diff --git a/logs/experiments/runs/focusLiteNN_150/2022-04-19_11-59-02/.hydra/config.yaml b/logs/experiments/runs/focusLiteNN_150/2022-04-19_11-59-02/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..85a8adff02137a3dd87d26ed0155ec2fd261c0c7
--- /dev/null
+++ b/logs/experiments/runs/focusLiteNN_150/2022-04-19_11-59-02/.hydra/config.yaml
@@ -0,0 +1,74 @@
+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: focusLiteNN_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
+  augmentation: true
+model:
+  _target_: src.models.focus_litenn_module.FocusLiteNNLitModule
+  pre_trained: false
+  num_channel: 3
+  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: ${name}
+    log_graph: false
+    default_hp_metric: true
+    prefix: ''
+trainer:
+  _target_: pytorch_lightning.Trainer
+  gpus: 1
+  min_epochs: 1
+  max_epochs: 100
+  resume_from_checkpoint: null
diff --git a/logs/experiments/runs/focusLiteNN_150/2022-04-19_11-59-02/.hydra/hydra.yaml b/logs/experiments/runs/focusLiteNN_150/2022-04-19_11-59-02/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..ed2b6dac5ea24a0dd78ae9f2260e2e62c6230962
--- /dev/null
+++ b/logs/experiments/runs/focusLiteNN_150/2022-04-19_11-59-02/.hydra/hydra.yaml
@@ -0,0 +1,170 @@
+hydra:
+  run:
+    dir: logs/experiments/runs/${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=focusLiteNN_150
+  job:
+    name: train
+    override_dirname: experiment=focusLiteNN_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: focusLiteNN_150
+      log_dir: default.yaml
+      trainer: default.yaml
+      logger: many_loggers
+      callbacks: default.yaml
+      model: focusLiteNN.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
diff --git a/logs/experiments/runs/focusLiteNN_150/2022-04-19_11-59-02/.hydra/overrides.yaml b/logs/experiments/runs/focusLiteNN_150/2022-04-19_11-59-02/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..1df451192835356f01efc7ac827b26d102c72a4b
--- /dev/null
+++ b/logs/experiments/runs/focusLiteNN_150/2022-04-19_11-59-02/.hydra/overrides.yaml
@@ -0,0 +1 @@
+- experiment=focusLiteNN_150
diff --git a/logs/experiments/runs/focusLiteNN_150/2022-04-19_11-59-02/checkpoints/epoch_098.ckpt b/logs/experiments/runs/focusLiteNN_150/2022-04-19_11-59-02/checkpoints/epoch_098.ckpt
new file mode 100644
index 0000000000000000000000000000000000000000..2b818aba6b68e59af72978cd53fab5714cc688fa
--- /dev/null
+++ b/logs/experiments/runs/focusLiteNN_150/2022-04-19_11-59-02/checkpoints/epoch_098.ckpt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8f2ac4fe3043efeebfbb040689885a3da39ba864a572dedb74b876ae2c74a914
+size 12795
diff --git a/logs/experiments/runs/focusLiteNN_150/2022-04-19_11-59-02/checkpoints/last.ckpt b/logs/experiments/runs/focusLiteNN_150/2022-04-19_11-59-02/checkpoints/last.ckpt
new file mode 100644
index 0000000000000000000000000000000000000000..aec4faa3715843be22a3313eee4a354c013fc0cb
--- /dev/null
+++ b/logs/experiments/runs/focusLiteNN_150/2022-04-19_11-59-02/checkpoints/last.ckpt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:36a17a32ec58b3fae1e9466d6d89dcf01b22779161708ffbbf73f9ead475515a
+size 12795
diff --git a/logs/experiments/runs/focusLiteNN_150/2022-04-19_11-59-02/csv/version_0/hparams.yaml b/logs/experiments/runs/focusLiteNN_150/2022-04-19_11-59-02/csv/version_0/hparams.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..9c890d702e84c9a8ccc39e140817bda440722a45
--- /dev/null
+++ b/logs/experiments/runs/focusLiteNN_150/2022-04-19_11-59-02/csv/version_0/hparams.yaml
@@ -0,0 +1,48 @@
+trainer:
+  _target_: pytorch_lightning.Trainer
+  gpus: 1
+  min_epochs: 1
+  max_epochs: 100
+  resume_from_checkpoint: null
+model:
+  _target_: src.models.focus_litenn_module.FocusLiteNNLitModule
+  pre_trained: false
+  num_channel: 3
+  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
+  augmentation: true
+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: 448
+model/params/trainable: 448
+model/params/non_trainable: 0
diff --git a/logs/experiments/runs/focusLiteNN_150/2022-04-19_11-59-02/csv/version_0/metrics.csv b/logs/experiments/runs/focusLiteNN_150/2022-04-19_11-59-02/csv/version_0/metrics.csv
new file mode 100644
index 0000000000000000000000000000000000000000..3ab9f1af700a9bea6a985c84c75530b7b64342a9
--- /dev/null
+++ b/logs/experiments/runs/focusLiteNN_150/2022-04-19_11-59-02/csv/version_0/metrics.csv
@@ -0,0 +1,202 @@
+val/loss,val/mae,val/mae_best,epoch,step,train/loss,train/mae,test/loss,test/mae
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+    filename: epoch_{epoch:03d}
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diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/metrics/val/mae_best b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/metrics/val/mae_best
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diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/callbacks/early_stopping/_target_ b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/callbacks/early_stopping/_target_
new file mode 100644
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@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/callbacks/early_stopping/min_delta b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/callbacks/early_stopping/min_delta
new file mode 100644
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diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/callbacks/early_stopping/mode b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/callbacks/early_stopping/mode
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diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/callbacks/early_stopping/monitor b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/callbacks/early_stopping/monitor
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diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/callbacks/early_stopping/patience b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/callbacks/early_stopping/patience
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diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/callbacks/model_checkpoint/_target_ b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/callbacks/model_checkpoint/_target_
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diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/callbacks/model_checkpoint/auto_insert_metric_name b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/callbacks/model_checkpoint/auto_insert_metric_name
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diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/callbacks/model_checkpoint/dirpath b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/callbacks/model_checkpoint/dirpath
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diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/callbacks/model_checkpoint/filename b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/callbacks/model_checkpoint/filename
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diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/callbacks/model_checkpoint/monitor b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/callbacks/model_checkpoint/monitor
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diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/callbacks/model_summary/_target_ b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/callbacks/model_summary/_target_
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--- /dev/null
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@@ -0,0 +1 @@
+128
\ No newline at end of file
diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/datamodule/csv_test_file b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/datamodule/csv_test_file
new file mode 100644
index 0000000000000000000000000000000000000000..69910129138d6d6714086863ffa853b10503abc6
--- /dev/null
+++ b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/datamodule/csv_test_file
@@ -0,0 +1 @@
+/usr/src/app/data/focus150/test_metadata.csv
\ No newline at end of file
diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/datamodule/csv_train_file b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/datamodule/csv_train_file
new file mode 100644
index 0000000000000000000000000000000000000000..6a397043cbb33603a2180ffea75f9c81916274ec
--- /dev/null
+++ b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/datamodule/csv_train_file
@@ -0,0 +1 @@
+/usr/src/app/data/focus150/train_metadata.csv
\ No newline at end of file
diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/datamodule/csv_val_file b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/datamodule/csv_val_file
new file mode 100644
index 0000000000000000000000000000000000000000..2a4ead115d4267a7d21708c8c9bb5c051bf4d3d4
--- /dev/null
+++ b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/datamodule/csv_val_file
@@ -0,0 +1 @@
+/usr/src/app/data/focus150/validation_metadata.csv
\ No newline at end of file
diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/datamodule/data_dir b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/datamodule/data_dir
new file mode 100644
index 0000000000000000000000000000000000000000..b815b619ac8a58b21b05404aa1ebc935578e6539
--- /dev/null
+++ b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/datamodule/data_dir
@@ -0,0 +1 @@
+/usr/src/app/data/focus150
\ No newline at end of file
diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/datamodule/num_workers b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/datamodule/num_workers
new file mode 100644
index 0000000000000000000000000000000000000000..c227083464fb9af8955c90d2924774ee50abb547
--- /dev/null
+++ b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/datamodule/num_workers
@@ -0,0 +1 @@
+0
\ No newline at end of file
diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/datamodule/pin_memory b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/datamodule/pin_memory
new file mode 100644
index 0000000000000000000000000000000000000000..c1f22fbc23bb6ee67824843d6685826db10313d3
--- /dev/null
+++ b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/datamodule/pin_memory
@@ -0,0 +1 @@
+False
\ No newline at end of file
diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/model/_target_ b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/model/_target_
new file mode 100644
index 0000000000000000000000000000000000000000..dc5c2e671cb8adff47a5b22cf0e8fa881150962b
--- /dev/null
+++ b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/model/_target_
@@ -0,0 +1 @@
+src.models.focus_litenn_module.FocusLiteNNLitModule
\ No newline at end of file
diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/model/lr b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/model/lr
new file mode 100644
index 0000000000000000000000000000000000000000..eb5a1db868251c6a5c775b49efde91a5ec3205df
--- /dev/null
+++ b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/model/lr
@@ -0,0 +1 @@
+0.001
\ No newline at end of file
diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/model/num_channel b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/model/num_channel
new file mode 100644
index 0000000000000000000000000000000000000000..e440e5c842586965a7fb77deda2eca68612b1f53
--- /dev/null
+++ b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/model/num_channel
@@ -0,0 +1 @@
+3
\ No newline at end of file
diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/model/params/non_trainable b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/model/params/non_trainable
new file mode 100644
index 0000000000000000000000000000000000000000..c227083464fb9af8955c90d2924774ee50abb547
--- /dev/null
+++ b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/model/params/non_trainable
@@ -0,0 +1 @@
+0
\ No newline at end of file
diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/model/params/total b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/model/params/total
new file mode 100644
index 0000000000000000000000000000000000000000..2415c065944e9ce572ac4d79cc79e621e9dee039
--- /dev/null
+++ b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/model/params/total
@@ -0,0 +1 @@
+448
\ No newline at end of file
diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/model/params/trainable b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/model/params/trainable
new file mode 100644
index 0000000000000000000000000000000000000000..2415c065944e9ce572ac4d79cc79e621e9dee039
--- /dev/null
+++ b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/model/params/trainable
@@ -0,0 +1 @@
+448
\ No newline at end of file
diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/model/pre_trained b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/model/pre_trained
new file mode 100644
index 0000000000000000000000000000000000000000..c1f22fbc23bb6ee67824843d6685826db10313d3
--- /dev/null
+++ b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/model/pre_trained
@@ -0,0 +1 @@
+False
\ No newline at end of file
diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/model/weight_decay b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/model/weight_decay
new file mode 100644
index 0000000000000000000000000000000000000000..752f26d69b0a2d03af05585d38e9e9cdd94d78ea
--- /dev/null
+++ b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/model/weight_decay
@@ -0,0 +1 @@
+0.0005
\ No newline at end of file
diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/seed b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/seed
new file mode 100644
index 0000000000000000000000000000000000000000..bd41cba781d8349272bf3eb92568285b411c027c
--- /dev/null
+++ b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/seed
@@ -0,0 +1 @@
+12345
\ No newline at end of file
diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/trainer/_target_ b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/trainer/_target_
new file mode 100644
index 0000000000000000000000000000000000000000..6b23728d56f799f2fedf10e2776b353c78e47498
--- /dev/null
+++ b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/trainer/_target_
@@ -0,0 +1 @@
+pytorch_lightning.Trainer
\ No newline at end of file
diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/trainer/gpus b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/trainer/gpus
new file mode 100644
index 0000000000000000000000000000000000000000..56a6051ca2b02b04ef92d5150c9ef600403cb1de
--- /dev/null
+++ b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/trainer/gpus
@@ -0,0 +1 @@
+1
\ No newline at end of file
diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/trainer/max_epochs b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/trainer/max_epochs
new file mode 100644
index 0000000000000000000000000000000000000000..105d7d9ad3afc7bb78a0dec4d829880831605dfb
--- /dev/null
+++ b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/trainer/max_epochs
@@ -0,0 +1 @@
+100
\ No newline at end of file
diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/trainer/min_epochs b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/trainer/min_epochs
new file mode 100644
index 0000000000000000000000000000000000000000..56a6051ca2b02b04ef92d5150c9ef600403cb1de
--- /dev/null
+++ b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/trainer/min_epochs
@@ -0,0 +1 @@
+1
\ No newline at end of file
diff --git a/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/trainer/resume_from_checkpoint b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/trainer/resume_from_checkpoint
new file mode 100644
index 0000000000000000000000000000000000000000..4af18322e32f3dd19579c80e26e4a306ad11e049
--- /dev/null
+++ b/logs/mlflow/mlruns/7/fa455b82340e485db4128038d25f385a/params/trainer/resume_from_checkpoint
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/logs/mlflow/mlruns/7/meta.yaml b/logs/mlflow/mlruns/7/meta.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..babff6bf1780001503e312bde30ffaa334884759
--- /dev/null
+++ b/logs/mlflow/mlruns/7/meta.yaml
@@ -0,0 +1,4 @@
+artifact_location: /usr/src/app/logs/mlflow/mlruns/7
+experiment_id: '7'
+lifecycle_stage: active
+name: focusLiteNN_150
diff --git a/src/models/focus_litenn_module.py b/src/models/focus_litenn_module.py
new file mode 100644
index 0000000000000000000000000000000000000000..85feb0226e0b9af2183e0561fd7490a5cc3dd4a9
--- /dev/null
+++ b/src/models/focus_litenn_module.py
@@ -0,0 +1,208 @@
+import math
+from typing import Any, List
+
+import torch
+import torch.nn.functional as F
+from torch import nn
+from pytorch_lightning import LightningModule
+from torchmetrics import MaxMetric, MeanAbsoluteError, MinMetric
+from torchmetrics.classification.accuracy import Accuracy
+import torchvision.models as models
+
+
+class FocusLiteNN(nn.Module):
+    """
+    https://github.com/icbcbicc/FocusLiteNN
+    This class is licenced undeer:
+    # The Prosperity Public License 3.0.0
+    Contributor: Zhongling Wang, Mahdi S. Hosseini, Adyn Miles
+    Source Code: https://github.com/icbcbicc/FocusLiteNN
+
+    ## Purpose:
+    This license allows you to use and share this software for noncommercial purposes for free and to try this software for commercial purposes for thirty days.
+
+    ## Agreement
+    In order to receive this license, you have to agree to its rules.  Those rules are both obligations under that agreement and conditions to your license.  Don't do anything with this software that triggers a rule you can't or won't follow.
+
+    ## Notices
+    Make sure everyone who gets a copy of any part of this software from you, with or without changes, also gets the text of this license and the contributor and source code lines above.
+
+    ## Commercial Trial
+    Limit your use of this software for commercial purposes to a thirty-day trial period.  If you use this software for work, your company gets one trial period for all personnel, not one trial per person.
+
+    ## Contributions Back
+    Developing feedback, changes, or additions that you contribute back to the contributor on the terms of a standardized public software license such as [the Blue Oak Model License 1.0.0](https://blueoakcouncil.org/license/1.0.0), [the Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0.html), [the MIT license](https://spdx.org/licenses/MIT.html), or [the two-clause BSD license](https://spdx.org/licenses/BSD-2-Clause.html) doesn't count as use for a commercial purpose.
+
+    ## Personal Uses
+    Personal use for research, experiment, and testing for the benefit of public knowledge, personal study, private entertainment, hobby projects, amateur pursuits, or religious observance, without any anticipated commercial application, doesn't count as use for a commercial purpose.
+
+    ## Noncommercial Organizations
+    Use by any charitable organization, educational institution, public research organization, public safety or health organization, environmental protection organization, or government institution doesn't count as use for a commercial purpose regardless of the source of funding or obligations resulting from the funding.
+
+    ## Defense
+    Don't make any legal claim against anyone accusing this software, with or without changes, alone or with other technology, of infringing any patent.
+
+    ## Copyright
+    The contributor licenses you to do everything with this software that would otherwise infringe their copyright in it.
+
+    ## Patent
+    The contributor licenses you to do everything with this software that would otherwise infringe any patents they can license or become able to license.
+
+    ## Reliability
+    The contributor can't revoke this license.
+
+    ## Excuse
+    You're excused for unknowingly breaking [Notices](#notices) if you take all practical steps to comply within thirty days of learning you broke the rule.
+
+    ## No Liability
+    ***As far as the law allows, this software comes as is, without any warranty or condition, and the contributor won't be liable to anyone for any damages related to this software or this license, under any kind of legal claim.***
+
+    In practice, we found MIN contributes VERY LITTLE to the performance. To achieve
+    extreme simplicity, different from Equation 1 in the paper, we only use MAX as the
+    nonlinear function. All experimental results in the paper are reported based on the
+    model using only MAX.
+    The model (class FocusLiteNNMinMax) using weighted MAX and MIN as the nonlinear function
+    (Equation 1 in paper) has indistinguishable (slightly better) performance compared to the
+    model using only MAX (class FocusLiteNN).
+    """
+
+    def __init__(self, num_channel=3):
+        super(FocusLiteNN, self).__init__()
+        self.num_channel = num_channel
+        self.conv = nn.Conv2d(3, self.num_channel, 7, stride=5, padding=1)  # 47x47
+        self.maxpool = nn.MaxPool2d(kernel_size=47)
+        if self.num_channel > 1:
+            self.fc = nn.Conv2d(self.num_channel, 1, 1, stride=1, padding=0)
+
+        for m in self.modules():
+            if isinstance(m, nn.Conv2d):
+                n = m.kernel_size[0] * m.kernel_size[1] * m.out_channels
+                m.weight.data.normal_(0, math.sqrt(2.0 / n))
+
+    def forward(self, x):
+        batch_size = x.size()[0]
+
+        x = self.conv(x)
+        x = -self.maxpool(-x)  # minpooling
+        if self.num_channel > 1:
+            x = self.fc(x)
+        x = x.view(batch_size, -1)
+
+        return x
+
+
+"""
+All code below is licenced under the licence of the whole repository
+"""
+
+
+class FocusLiteNNLitModule(LightningModule):
+    def __init__(
+        self,
+        lr: float = 0.001,
+        num_channel: int = 3,
+        pre_trained: bool = False,
+        weight_decay: float = 0.0005,
+    ):
+        super().__init__()
+
+        # this line allows to access init params with 'self.hparams' attribute
+        # it also ensures init params will be stored in ckpt
+        self.save_hyperparameters(logger=False)
+
+        # loss function
+        self.criterion = torch.nn.MSELoss()
+
+        # use separate metric instance for train, val and test step
+        # to ensure a proper reduction over the epoch
+        self.train_mae = MeanAbsoluteError()
+        self.val_mae = MeanAbsoluteError()
+        self.test_mae = MeanAbsoluteError()
+
+        # for logging best so far validation accuracy
+        self.val_mae_best = MinMetric()
+
+        self.num_channel = num_channel
+        self.model = FocusLiteNN(num_channel)
+
+        self.model.maxpool = nn.AdaptiveMaxPool2d(1)
+
+    def forward(self, x):
+        x = self.model(x)
+        return x
+
+    def step(self, batch: Any):
+        x = batch["image"]
+        y = batch["focus_height"]
+        logits = self.forward(x)
+        loss = self.criterion(logits, y.unsqueeze(1))
+        preds = torch.squeeze(logits)
+        return loss, preds, y
+
+    def training_step(self, batch: Any, batch_idx: int):
+        loss, preds, targets = self.step(batch)
+
+        # log train metrics
+        mae = self.train_mae(preds, targets)
+        self.log("train/loss", loss, on_step=False, on_epoch=True, prog_bar=False)
+        self.log("train/mae", mae, on_step=False, on_epoch=True, prog_bar=True)
+
+        # we can return here dict with any tensors
+        # and then read it in some callback or in `training_epoch_end()`` below
+        # remember to always return loss from `training_step()` or else
+        # backpropagation will fail!
+        return {"loss": loss, "preds": preds, "targets": targets}
+
+    def training_epoch_end(self, outputs: List[Any]):
+        # `outputs` is a list of dicts returned from `training_step()`
+        pass
+
+    def validation_step(self, batch: Any, batch_idx: int):
+        loss, preds, targets = self.step(batch)
+
+        # log val metrics
+        mae = self.val_mae(preds, targets)
+        self.log("val/loss", loss, on_step=False, on_epoch=True, prog_bar=False)
+        self.log("val/mae", mae, on_step=False, on_epoch=True, prog_bar=True)
+
+        return {"loss": loss, "preds": preds, "targets": targets}
+
+    def validation_epoch_end(self, outputs: List[Any]):
+        mae = self.val_mae.compute()  # get val accuracy from current epoch
+        self.val_mae_best.update(mae)
+        self.log(
+            "val/mae_best", self.val_mae_best.compute(), on_epoch=True, prog_bar=True
+        )
+
+    def test_step(self, batch: Any, batch_idx: int):
+        loss, preds, targets = self.step(batch)
+
+        # log test metrics
+        mae = self.test_mae(preds, targets)
+        self.log("test/loss", loss, on_step=False, on_epoch=True)
+        self.log("test/mae", mae, on_step=False, on_epoch=True)
+
+    def test_epoch_end(self, outputs: List[Any]):
+        print(outputs)
+        pass
+
+    def on_epoch_end(self):
+        # reset metrics at the end of every epoch
+        self.train_mae.reset()
+        self.test_mae.reset()
+        self.val_mae.reset()
+
+    def configure_optimizers(self):
+        """Choose what optimizers and learning-rate schedulers.
+
+        Normally you'd need one. But in the case of GANs or similar you might
+        have multiple.
+
+        See examples here:
+            https://pytorch-lightning.readthedocs.io/en/latest/common/lightning_module.html#configure-optimizers
+        """
+        return torch.optim.Adam(
+            params=self.parameters(),
+            lr=self.hparams.lr,
+            weight_decay=self.hparams.weight_decay,
+        )