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How to install spark-tensorflow-distributor via python pip




spark-tensorflow-distributor - This package helps users do distributed training with TensorFlow on their Spark clusters., it belongs to Classifiers:

- Development Status :: 1 - Planning
- Intended Audience :: Developers
- Natural Language :: English
- Operating System :: OS Independent
- Programming Language :: Python
- Programming Language :: Python :: 3
- Topic :: Scientific/Engineering
- Topic :: Scientific/Engineering :: Artificial Intelligence
- Topic :: Software Development
- Topic :: Software Development :: Libraries
- Topic :: Software Development :: Libraries :: Python Modules
- Topic :: Software Development :: Version Control
- Topic :: Software Development :: Version Control :: Git

When you know about this project and you want to new install spark-tensorflow-distributor to support your project or you get trouble as ModuleNotFoundError: No module named "spark-tensorflow-distributor" or ImportError: cannot import name "spark-tensorflow-distributor" in your project, let follow this tutorial to install spark-tensorflow-distributor



Installation:

Step 1: First, ensure you installed pip in your os, to check pip has been installed on your computer

In Windows (CMD):

py -m pip --version

In Unix/macOS:

python3 -m pip --version

Ensure pip, setuptools, and wheel are up to date:

In Windows (CMD):

py -m pip install --upgrade pip setuptools wheel

In Unix/macOS:

python3 -m pip install --upgrade pip setuptools wheel


Optional - If you want to install in virtual environment:

In Windows (CMD):

- Install virtualenv - if you installed it, please ignore

py -m pip install --user virtualenv

- Create a virtual environment

py -m venv test_spark-tensorflow-distributor_env

- Active the virtual environment

test_spark-tensorflow-distributor_env\Scripts\active

In Unix/macOS:

- Install virtualenv - if you installed it, please ignore

pip3 install virtualenv

- Create a virtual environment

python3 -m venv test_spark-tensorflow-distributor_env

- Active the virtual environment

source test_spark-tensorflow-distributor_env/bin/active


Step 2: OK, now, let flow below content to start the installation spark-tensorflow-distributor

To install spark-tensorflow-distributor on Windows(CMD):

py -m pip install spark-tensorflow-distributor

To install spark-tensorflow-distributor on Unix/macOs:

pip install spark-tensorflow-distributor


Step 3: If you want to install a specific spark-tensorflow-distributor version, add ==<spark-tensorflow-distributor version> to the end command line

Example:

pip install spark-tensorflow-distributor==0.0.1


Please see the version list below table:

VersionReleased dateCommand
spark-tensorflow-distributor 1.0.02021-08-19T00:32:37Windows:

py -m pip install spark-tensorflow-distributor==1.0.0

Unix/macOs:

pip install spark-tensorflow-distributor==1.0.0

spark-tensorflow-distributor 0.1.02020-06-30T21:26:27Windows:

py -m pip install spark-tensorflow-distributor==0.1.0

Unix/macOs:

pip install spark-tensorflow-distributor==0.1.0

spark-tensorflow-distributor 0.0.32020-04-24T00:27:37Windows:

py -m pip install spark-tensorflow-distributor==0.0.3

Unix/macOs:

pip install spark-tensorflow-distributor==0.0.3

spark-tensorflow-distributor 0.0.22020-04-24T00:16:29Windows:

py -m pip install spark-tensorflow-distributor==0.0.2

Unix/macOs:

pip install spark-tensorflow-distributor==0.0.2

spark-tensorflow-distributor 0.0.12020-04-01T22:05:45Windows:

py -m pip install spark-tensorflow-distributor==0.0.1

Unix/macOs:

pip install spark-tensorflow-distributor==0.0.1


Step 4: Otherwise, you can install spark-tensorflow-distributor from local archives:

Download the distribution file from spark_tensorflow_distributor-1.0.0.tar.gz or the specific spark-tensorflow-distributor version in the below list of distribution

After that, install by command:

On Windows(CMD):

py -m pip install <path_to_spark-tensorflow-distributor_downloaded_file>

On Unix/macOs:

pip install <path_to_spark-tensorflow-distributor_downloaded_file>


List distribution:


Project link:

- Homepage