Merge pull request #3 from sergey-serebryakov/david/cli_mount

Resolving merge conflicts and updating unit tests.

.github/workflows/README.md

@@ -89,6 +89,6 @@ More Information on python-publish action & Repository Dispatch action can be fo
 ### Secrets used
 | Name  |   |
 |---|---|
-|PYPI_USER        |pypi login credentials used in GitHub workflows    |
-|PYPI_PASSWORD    |pypi login credentials used in GitHub workflows    |
+|PYPI_USER (depreciated)        |pypi login credentials used in GitHub workflows    |
+|PYPI_PASSWORD (depreciated)    |pypi login credentials used in GitHub workflows    |
 |MLCOMMONS_REPO_ACCESS   |public_repo ACL for request dispatch in GitHub workflows  |

.github/workflows/docs-site.yml

@@ -6,6 +6,8 @@ on:
     - '.github/workflows/docs-site.yml'
     - 'docs/**'
     - 'mkdocs.yml'
+    - 'mlcube/mlcube/__main__.py'
+    - 'mlcube/mlcube/cli.py'
 
 jobs:
   docs:

.github/workflows/python-publish.yml

@@ -10,10 +10,12 @@ on:
 jobs:
   deploy:
     runs-on: ubuntu-latest
+    permissions:
+      id-token: write
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v3
     - name: Set up Python
-      uses: actions/setup-python@v2
+      uses: actions/setup-python@v3
       with:
         python-version: '3.x'
     - name: Install dependencies
@@ -27,12 +29,10 @@ jobs:
     - name: Publish
       uses: pypa/gh-action-pypi-publish@release/v1
       with:
-        user: ${{ secrets.PYPI_USER }}
-        verify_metadata: true
-        skip_existing: true
-        password: ${{ secrets.PYPI_PASSWORD }}
-        packages_dir: mlcube/dist/
-        repository_url: https://upload.pypi.org/legacy/
+        verify-metadata: true
+        skip-existing: true
+        packages-dir: mlcube/dist/
+        repository-url: https://upload.pypi.org/legacy/
         verbose: true
       env:
         LOGLEVEL: DEBUG
@@ -42,7 +42,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Repository Dispatch
-        uses: peter-evans/repository-dispatch@v1
+        uses: peter-evans/repository-dispatch@v2
         with:
           token: ${{ secrets.MLCOMMONS_REPO_ACCESS }}
           repository: mlcommons/mlcube

.github/workflows/runner-publish.yml

@@ -10,10 +10,12 @@ on:
 jobs:
   ssh_deploy:
     runs-on: ubuntu-latest
+    permissions:
+      id-token: write
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v3
     - name: Set up Python
-      uses: actions/setup-python@v2
+      uses: actions/setup-python@v3
       with:
         python-version: '3.x'
     - name: Install dependencies
@@ -27,21 +29,21 @@ jobs:
     - name: Publish
       uses: pypa/gh-action-pypi-publish@release/v1
       with:
-        user: ${{ secrets.PYPI_USER }}
-        verify_metadata: true
-        skip_existing: true
-        password: ${{ secrets.PYPI_PASSWORD }}
-        packages_dir: runners/mlcube_ssh/dist/
-        repository_url: https://upload.pypi.org/legacy/
+        verify-metadata: true
+        skip-existing: true
+        packages-dir: runners/mlcube_ssh/dist/
+        repository-url: https://upload.pypi.org/legacy/
       env:
         LOGLEVEL: DEBUG
 
   docker_deploy:
     runs-on: ubuntu-latest
+    permissions:
+      id-token: write
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v3
     - name: Set up Python
-      uses: actions/setup-python@v2
+      uses: actions/setup-python@v3
       with:
         python-version: '3.x'
     - name: Install dependencies
@@ -55,22 +57,22 @@ jobs:
     - name: Publish
       uses: pypa/gh-action-pypi-publish@release/v1
       with:
-        user: ${{ secrets.PYPI_USER }}
-        verify_metadata: true
-        skip_existing: true
-        password: ${{ secrets.PYPI_PASSWORD }}
-        packages_dir: runners/mlcube_docker/dist/
-        repository_url: https://upload.pypi.org/legacy/
+        verify-metadata: true
+        skip-existing: true
+        packages-dir: runners/mlcube_docker/dist/
+        repository-url: https://upload.pypi.org/legacy/
         verbose: true
       env:
         LOGLEVEL: DEBUG
 
   singularity_deploy:
     runs-on: ubuntu-latest
+    permissions:
+      id-token: write
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v3
     - name: Set up Python
-      uses: actions/setup-python@v2
+      uses: actions/setup-python@v3
       with:
         python-version: '3.x'
     - name: Install dependencies
@@ -84,22 +86,22 @@ jobs:
     - name: Publish
       uses: pypa/gh-action-pypi-publish@release/v1
       with:
-        user: ${{ secrets.PYPI_USER }}
-        verify_metadata: true
-        skip_existing: true
-        password: ${{ secrets.PYPI_PASSWORD }}
-        packages_dir: runners/mlcube_singularity/dist/
-        repository_url: https://upload.pypi.org/legacy/
+        verify-metadata: true
+        skip-existing: true
+        packages-dir: runners/mlcube_singularity/dist/
+        repository-url: https://upload.pypi.org/legacy/
         verbose: true
       env:
         LOGLEVEL: DEBUG
 
   kubernetes_runner_deploy:
     runs-on: ubuntu-latest
+    permissions:
+      id-token: write
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v3
     - name: Set up Python
-      uses: actions/setup-python@v2
+      uses: actions/setup-python@v3
       with:
         python-version: '3.x'
     - name: Install dependencies
@@ -113,22 +115,22 @@ jobs:
     - name: Publish
       uses: pypa/gh-action-pypi-publish@release/v1
       with:
-        user: ${{ secrets.PYPI_USER }}
-        verify_metadata: true
-        skip_existing: true
-        password: ${{ secrets.PYPI_PASSWORD }}
-        packages_dir: runners/mlcube_k8s/dist/
-        repository_url: https://upload.pypi.org/legacy/
+        verify-metadata: true
+        skip-existing: true
+        packages-dir: runners/mlcube_k8s/dist/
+        repository-url: https://upload.pypi.org/legacy/
         verbose: true
       env:
         LOGLEVEL: DEBUG
 
   gcp_runner_deploy:
     runs-on: ubuntu-latest
+    permissions:
+      id-token: write
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v3
     - name: Set up Python
-      uses: actions/setup-python@v2
+      uses: actions/setup-python@v3
       with:
         python-version: '3.x'
     - name: Install dependencies
@@ -142,22 +144,22 @@ jobs:
     - name: Publish
       uses: pypa/gh-action-pypi-publish@release/v1
       with:
-        user: ${{ secrets.PYPI_USER }}
-        verify_metadata: true
-        skip_existing: true
-        password: ${{ secrets.PYPI_PASSWORD }}
-        packages_dir: runners/mlcube_gcp/dist/
-        repository_url: https://upload.pypi.org/legacy/
+        verify-metadata: true
+        skip-existing: true
+        packages-dir: runners/mlcube_gcp/dist/
+        repository-url: https://upload.pypi.org/legacy/
         verbose: true
       env:
         LOGLEVEL: DEBUG
 
   kubeflow_runner_deploy:
       runs-on: ubuntu-latest
+      permissions:
+        id-token: write
       steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
       - name: Set up Python
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v3
         with:
           python-version: '3.x'
       - name: Install dependencies
@@ -171,12 +173,10 @@ jobs:
       - name: Publish
         uses: pypa/gh-action-pypi-publish@release/v1
         with:
-          user: ${{ secrets.PYPI_USER }}
-          verify_metadata: true
-          skip_existing: true
-          password: ${{ secrets.PYPI_PASSWORD }}
-          packages_dir: runners/mlcube_kubeflow/dist/
-          repository_url: https://upload.pypi.org/legacy/
+          verify-metadata: true
+          skip-existing: true
+          packages-dir: runners/mlcube_kubeflow/dist/
+          repository-url: https://upload.pypi.org/legacy/
           verbose: true
         env:
           LOGLEVEL: DEBUG

README.md

@@ -1,16 +1,16 @@
-# MLCube™
+# MLCube
 
 [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0) 
 
 [![PyPI MLCube](https://img.shields.io/pypi/v/mlcube.svg?label="pypi%20(MLCube)")](https://pypi.org/project/mlcube)
 [![PyPI MLCube Docker Runner](https://img.shields.io/pypi/v/mlcube-docker.svg?label="pypi%20(Docker%20Runner)")](https://pypi.org/project/mlcube-docker)
 [![PyPI MLCube Singularity Runner](https://img.shields.io/pypi/v/mlcube-singularity.svg?label="pypi%20(Singularity%20Runner)")](https://pypi.org/project/mlcube-singularity)
 
-MLCube brings the concept of interchangeable parts to the world of machine learning models.  It is the shipping container that enables researchers and developers to easily share the software that powers machine learning. 
+MLCube® brings the concept of interchangeable parts to the world of machine learning models.  It is the shipping container that enables researchers and developers to easily share the software that powers machine learning. 
 
 MLCube is a set of common conventions for creating ML software that can just "plug-and-play" on many systems. MLCube makes it easier for researchers to share innovative ML models, for a developer to experiment with many models, and for software companies to create infrastructure for models. It creates opportunities by putting ML in the hands of more people.
 
-MLCube isn’t a new framework or service; MLCube is a consistent interface to machine learning models in containers like Docker.  Models published with the MLCube interface can be run on local machines, on a variety of major clouds, or in Kubernetes clusters - all using the same code. MLCommons provides open source “runners” for each of these environments that make training a model in an MLCube™ a single command. 
+MLCube isn’t a new framework or service; MLCube is a consistent interface to machine learning models in containers like Docker.  Models published with the MLCube interface can be run on local machines, on a variety of major clouds, or in Kubernetes clusters - all using the same code. MLCommons provides open source “runners” for each of these environments that make training a model in an MLCube a single command. 
 
 *Note: This project is still in the very early stages and under active development, some parts may have unexpected/inconsistent behaviours.*
 
@@ -37,7 +37,7 @@ Check out the [examples](https://github.com/mlcommons/mlcube_examples) for detai
 
 See [LICENSE](https://github.com/mlcommons/mlcube/blob/master/LICENSE.md) for more information.
 
-MLCube is a trademark of the MLCommons™ Association.
+MLCube is a trademark of the MLCommons® Association.
 
 ## Support
 

docs/getting-started/concepts.md

@@ -1,7 +1,7 @@
 # MLCube concepts
 
 ### Command Line Arguments
-MLCube runtime and MLCube runners accept multiple command line arguments. They can be classified into two categories:
+MLCube® runtime and MLCube runners accept multiple command line arguments. They can be classified into two categories:
 
 - Fixed command-specific parameters such as `--mlcube`, `--platform` and `--task` for the MLCube's `run` command, or
   `create_platform` and `rename_platform` for the `config` command.

docs/getting-started/hello-world.md

@@ -1,5 +1,5 @@
 # Hello World
-Hello World MLCube is an example of a Docker-based MLCube.  
+Hello World MLCube® is an example of a Docker-based MLCube.  
 
 
 ## QuickStart

docs/getting-started/index.md

@@ -1,6 +1,6 @@
 # Installation
 
-Here is the step-by-step guide to install MLCube library and run simple MLCube cubes.
+Here is the step-by-step guide to install MLCube® library and run simple MLCube cubes.
 
 ## Create a python environment
 

docs/getting-started/mlcube-configuration.md

@@ -1,6 +1,6 @@
 # MLCube Configuration
 
-MLCube configuration provides information about MLCube's authors, requirements and  
+MLCube® configuration provides information about MLCube's authors, requirements and  
 [tasks](https://mlcommons.github.io/mlcube/getting-started/concepts/#task). This is example configuration for
 the [MNIST MLCube](https://github.com/mlcommons/mlcube_examples/tree/master/mnist):
 

docs/getting-started/mnist.md

@@ -1,6 +1,6 @@
 # MNIST
 The [MNIST dataset](http://yann.lecun.com/exdb/mnist/) is a collection of 60,000 handwritten digits widely used for
-training statistical, Machine Learning (ML) and Deep Learning (DL) models. The MNIST MLCube example demonstrates
+training statistical, Machine Learning (ML) and Deep Learning (DL) models. The MNIST MLCube® example demonstrates
 how data scientists, ML and DL researchers and developers can distribute their ML projects (including training,
 validation and inference code) as MLCube cubes. MLCube establishes a standard to package user workloads,
 and provides unified command line interface. In addition, MLCube provides a number of reference 

docs/getting-started/system-settings.md

@@ -1,7 +1,7 @@
 # MLCube System Settings
-MLCube system settings configure MLCube and MLCube runners at a system level. The term `system level` here implies that
-these settings are not tied to particular MLCubes (MLCube compliant ML projects). Instead, these settings are used by
-MLCube runners on every machine where MLCube runtime is configured to use these settings.
+MLCube® system settings configure MLCube and MLCube runners at a system level. The term `system level` here implies 
+that these settings are not tied to particular MLCubes (MLCube compliant ML projects). Instead, these settings are used 
+by MLCube runners on every machine where MLCube runtime is configured to use these settings.
 
 ## Introduction
 When MLCube runners run MLCubes, they need to know not only the content of MLCubes (tasks that MLCubes provide), but 

docs/index.md

@@ -1,6 +1,6 @@
 # MLCube
 
-MLCube is a project that reduces friction for machine learning by ensuring that models are easily portable and 
+MLCube® is a project that reduces friction for machine learning by ensuring that models are easily portable and 
 reproducible, e.g., between different stacks such as different clouds, between cloud and on-prem, etc.
 
 Interested in getting started with MLCube? Follow the 

docs/requirements.txt

@@ -1,5 +1,9 @@
 mkdocs>=1.0.4
+
+# This slightly updated version respects Click's help feature to skip everything that comes after the \f symbol.
+# mkdocs-click
+mkdocs-click @ git+https://github.com/sergey-serebryakov/mkdocs-click@feature/respect-ff-escape-char
+
 mkdocs-material>=4.4.0
-mkdocs-click
 pymdown-extensions>=7.1
 -r ../mlcube/requirements.txt

docs/runners/docker-runner.md

@@ -1,5 +1,5 @@
 # Docker Runner
-Docker runner uses docker/nvidia-docker/podman to run MLCube cubes. It supports two mandatory commands - `configure` and
+Docker runner uses docker/nvidia-docker/podman to run MLCube® cubes. It supports two mandatory commands - `configure` and
 `run` with standard arguments - `mlcube`, `platform` and `task`. Users can configure docker runner in MLCube 
 configuration file, system setting file, and override parameters on a command line.
 

docs/runners/gcp-runner.md

@@ -1,7 +1,7 @@
 # Google Compute Platform (GCP) Runner
 
 !!! attention
-      MLCube is under active development. Allocating and using instances in clouds are associated with costs. Users of 
+      MLCube® is under active development. Allocating and using instances in clouds are associated with costs. Users of 
       GCP runners should be aware about it, especially, taking into account capability of GCP runners to automatically 
       create and start remote instances. GCP RUNNERS in current implementation DO NOT stop/destroy remote instances. 
       Users are encouraged to visit web consoles to identify what virtual instances exist and run.

docs/runners/index.md

@@ -1,5 +1,5 @@
 # Runners
-MLCube runners run MLCube cubes on one or multiple platforms. Examples of platforms are Docker and Singularity 
+MLCube® runners run MLCube cubes on one or multiple platforms. Examples of platforms are Docker and Singularity 
 containers, Kubernetes, remote hosts, virtual machines in the cloud, etc. Every runner has a fixed set of configuration
 parameters that users can change to configure MLCubes and runners for their environments. Concretely, runners can take
 information from three different sources:

docs/runners/kubeflow.md

@@ -1,7 +1,7 @@
 # Kubeflow Runner
 
 !!! warning
-    Work in progress. Some functionality described below may not be available.
+    MLCube® Kubeflow runner is work in progress. Some functionality described below may not be available.
 
 Kubeflow supports two mandatory commands - `configure` and `run` with standard arguments - `mlcube`, `platform` and 
 `task`. Users can configure SSH runner in system setting file, and override parameters on a command line.

docs/runners/kubernetes.md

@@ -3,7 +3,7 @@
 !!! warning
     Work in progress. Some functionality described below may not be available.
 
-The Kubernetes Runner runs a MLCube on a Kubernetes cluster.
+The Kubernetes Runner runs a MLCube® on a Kubernetes cluster.
 
 ## Why Kubernetes?
 

docs/runners/singularity-runner.md

@@ -1,5 +1,5 @@
 # Singularity Runner
-Singularity runner uses singularity to run MLCube cubes. It supports two mandatory commands - `configure` and
+Singularity runner uses singularity to run MLCube® cubes. It supports two mandatory commands - `configure` and
 `run` with standard arguments - `mlcube`, `platform` and `task`. Users can configure Singularity runner in MLCube 
 configuration file, system setting file, and override parameters on a command line.