PyTorch Kubeflow Pipeline Components
PyTorch Kubeflow Pipeline Components provides an SDK and a set of components that lets you build kubeflow pipelines using PyTorch. You can use the predefined components in this repository to build your pipeline using the Kubeflow Pipelines SDK.
Installation
Requirements
Python >= 3.6 Kubeflow cluster setuo (on-prem or in any of the Clouds)
Install latest release
Use the following command to install PyTorch Pipeline Components from PyPI.
pip install -U pytorch-kfp-components
Install from source
Use the following commands to install PyTorch Kubeflow Pipeline Components from GitHub.
git clone https://github.com/kubeflow/pipelines.git
pip install pipelines/components/PyTorch/pytorch_kfp_components/.
Running the tests
Run the following command
pip install tox
cd ./components/PyTorch/pytorch-kfp-components/
tox -rvve py38
Samples
For running the samples follow the instruction mentioned as below
Metadata
Release files for pytorch-kfp-components 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pytorch-kfp-components-0.1.0.tar.gz | 18.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pytorch_kfp_components-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 48.6 kB
Release files / pytorch-kfp-components-0.1.0.tar.gz
| Download URL | pytorch-kfp-components-0.1.0.tar.gz |
|---|---|
| Size | 18.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
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Release files / pytorch_kfp_components-0.1.0-py3-none-any.whl
| Download URL | pytorch_kfp_components-0.1.0-py3-none-any.whl |
|---|---|
| Size | 30.0 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.8.10
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