MLproject

# Author: Julian Wanner
# Email: jwgithub@mailbox.org
# Version: 1.0.0
# License: MIT


name: root-tissue-segmentation

#conda_env: environment.yml
docker_env:
  image: ghcr.io/qbic-pipelines/root_tissue_segmentation:1.0.0
  volumes: ["${PWD}/data:/data"]
  run_params: [['--gpus', 'all'], ['--ipc','host']]
environment: [["MLF_CORE_DOCKER_RUN", "TRUE"],["CUBLAS_WORKSPACE_CONFIG", ":4096:8"]]

entry_points:
  main:
    parameters:
      max_epochs: {type: int, default: 74}
      gpus: {type: int, default: 2}
      accelerator: {type str, default: "dp"}
      training-batch-size: {type: int, default: 10}
      test-batch-size: {type: int, default: 60}
      lr: {type: float, default: 0.0005739979509018617}
      weight-decay: {type: float, default: 0.08843850663784153}
      gamma-factor: {type: float, default: 2.8074708243593878}
      model: {type: str, default: "u2net"}
      epsilon: {type: float, default: 2.1335101419972938e-14}
      alpha-0: {type: float, default: 0.39228916176765655}
      alpha-1: {type: float, default: 0.4476337434213018}
      alpha-2: {type: float, default: 0.8902483094365905}
      alpha-3: {type: float, default: 0.6695418278351652}
      alpha-4: {type: float, default: 0.9382751049017035}
      general-seed: {type: int, default: 0}
      pytorch-seed: {type: int, default: 0}
      log-interval: {type: int, default: 100}
    command: |
          python root_tissue_segmentation/root_tissue_segmentation.py \
            --max_epochs {max_epochs} \
            --gpus {gpus} \
            --accelerator {accelerator} \
            --training-batch-size {training-batch-size} \
            --test-batch-size {test-batch-size} \
            --lr {lr} \
            --model {model} \
            --weight-decay {weight-decay} \
            --gamma-factor {gamma-factor} \
            --epsilon {epsilon} \
            --alpha-0 {alpha-0} \
            --alpha-1 {alpha-1} \
            --alpha-2 {alpha-2} \
            --alpha-3 {alpha-3} \
            --alpha-4 {alpha-4} \
            --general-seed {general-seed} \
            --pytorch-seed {pytorch-seed} \
            --log-interval {log-interval}