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Merge pull request #10 from mlf-core/development
Updated train/test datasets and runs
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.github/workflows/publish_docker.yml

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username: mlf-core
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password: '${{ secrets.MLF_CORE_SYNC_TOKEN}}'
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registry: ghcr.io
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tags: "latest,1.0.0"
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tags: "latest,1.0.1"
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.github/workflows/train_cpu.yml

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with:
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dockerfile: Dockerfile
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repository: ghcr.io/mlf-core/lcep
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tags: 1.0.0
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tags: 1.0.1
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push: false
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- name: Setup Python
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uses: actions/setup-python@v1
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with:
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python-version: ${{ matrix.python }}
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python-version: ${{ matrix.python }}
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- name: Install mlflow
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run: pip install mlflow

.mlf_core.yml

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project_name: lcep
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project_short_description: Classifying cancerous liver samples from gene expression
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data.
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version: 1.0.0
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version: 1.0.1
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license: MIT

CHANGELOG.rst

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This project adheres to `Semantic Versioning <https://semver.org/>`_.
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1.0.1 (2021-04-08)
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------------------
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**Added**
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**Fixed**
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* Fixed train/test dataset float point variation of some samples. The new dataset was generated by the nextflow-lcep pipeline.
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**Dependencies**
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**Deprecated**
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1.0.0 (2021-03-11)
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------------------
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MLproject

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# Author: Lukas Heumos
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# Version: 1.0.0
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# Version: 1.0.1
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# License: MIT
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name: lcep
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# conda_env: environment.yml
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docker_env:
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image: ghcr.io/mlf-core/lcep:1.0.0
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image: ghcr.io/mlf-core/lcep:1.0.1
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volumes: ["${PWD}/data:/data"]
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entry_points:

data/test.tsv

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data/train.tsv

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docs/conf.py

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# the built documents.
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#
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# The short X.Y version.
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version = '1.0.0'
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version = '1.0.1'
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# The full version, including alpha/beta/rc tags.
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release = '1.0.0'
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release = '1.0.1'
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# The language for content autogenerated by Sphinx. Refer to documentation
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# for a list of supported languages.

docs/usage.rst

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Parameters
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+++++++++++++++
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- training-data Path to the training data csv file ['train.csv': string]
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- test-data Path to the test data csv file ['test.csv': string]
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- cuda: Whether to train with CUDA support (=GPU) ['True': string]
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- max_epochs: Number of epochs to train [1000: int]
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- general-seed: Python, Random, Numpy seed [0: int]
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- xgboost-seed: XGBoost specific seed [0: int]
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- single-precision-histogram Whether to enable `single precision for histogram building <https://xgboost.readthedocs.io/en/latest/parameter.html#additional-parameters-for-hist-and-gpu-hist-tree-method>`_ ['True': string]
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- ``training-data`` Path to the training data csv file ``['train.csv': string]``
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- ``test-data`` Path to the test data csv file ``['test.csv': string]``
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- ``cuda`` Whether to train with CUDA support (=GPU) ``['True': string]``
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- ``max_epochs`` Number of epochs to train ``[1000: int]``
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- ``general-seed`` Python, Random, Numpy seed ``[0: int]``
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- ``xgboost-seed`` XGBoost specific seed ``[0: int]``
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- ``single-precision-histogram`` Whether to enable `single precision for histogram building <https://xgboost.readthedocs.io/en/latest/parameter.html#additional-parameters-for-hist-and-gpu-hist-tree-method>`_ ``['True': string]``

mlf_core.cfg

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[bumpversion]
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current_version = 1.0.0
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current_version = 1.0.1
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[bumpversion_files_whitelisted]
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dot_mlf_core = .mlf_core.yml

mlruns/0/001340615e0748de91c15a9f0afd111f/artifacts/model/MLmodel

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mlruns/0/001340615e0748de91c15a9f0afd111f/artifacts/model/input_example.json

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