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Overview 

TensorFlow is an open source library to help you develop and train machine learning models. 

 RocketCE includes several packages from the TensorFlow ecosystem and these packages are available in channel rocketce of anaconda.org.  

First release of RocketCE is based on OpenCE Release v1.3.1. In this version of RocketCE, there is TensorFlow 2.5.1. 

These packages are supported for both Power 9 and Power 10 Systems of IBM with linux-ppc64le. 


CPU Support
 

RocketCE includes a version of TensorFlow built without GPU support. This inclusion allows for training and inferencing to be done on Power 9 and Power 10 systems that do not have GPUs, or on systems where you want to train and inference without using the GPUs. 

 

GPU Support 

This version of Tensorflow will not support GPU variant. Support of GPU variant will be provided in coming releases. For more information, refer main page of RocketCE.

 

Installation instructions 

CPU Only Variant 

To install Tensorflow built for CPU support run the following command:
  • conda install -c rocketce tensorflow-cpu
 

 Once the installation is success, validate the installation by running the following command which lists the package tensorflow which is pulled from channel rocketce 

  • Conda list tensorflow-cpu 

 

TensorFlow conda packages 

Following packages are available in rocketce channel and gets installed with tensorflow-cpu package 

  1. tensorflow-base 
  2. _tensorflow_select 
  3. tensorboard 
  4. tensorboard-plugin-wit 
  5. tensorflow-estimator 

 

More information 

The Tensorflow has various information, including tutorials, how to documents, and a getting started guide. 

Additional tutorials and examples are available from the community, for example: 



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Rajesh Nukala
Rocket Internal - All Brands
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Overview 

TensorFlow is an open source library to help you develop and train machine learning models. 

 RocketCE includes several packages from the TensorFlow ecosystem and these packages are available in channel rocketce of anaconda.org.  

First release of RocketCE is based on OpenCE Release v1.3.1. In this version of RocketCE, there is TensorFlow 2.5.1. 

These packages are supported for both Power 9 and Power 10 Systems of IBM with linux-ppc64le. 


CPU Support
 

RocketCE includes a version of TensorFlow built without GPU support. This inclusion allows for training and inferencing to be done on Power 9 and Power 10 systems that do not have GPUs, or on systems where you want to train and inference without using the GPUs. 

 

GPU Support 

This version of Tensorflow will not support GPU variant. Support of GPU variant will be provided in coming releases. For more information, refer main page of RocketCE.

 

Installation instructions 

CPU Only Variant 

To install Tensorflow built for CPU support run the following command:
  • conda install -c rocketce tensorflow-cpu
 

 Once the installation is success, validate the installation by running the following command which lists the package tensorflow which is pulled from channel rocketce 

  • Conda list tensorflow-cpu 

 

TensorFlow conda packages 

Following packages are available in rocketce channel and gets installed with tensorflow-cpu package 

  1. tensorflow-base 
  2. _tensorflow_select 
  3. tensorboard 
  4. tensorboard-plugin-wit 
  5. tensorflow-estimator 

 

More information 

The Tensorflow has various information, including tutorials, how to documents, and a getting started guide. 

Additional tutorials and examples are available from the community, for example: 



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Rajesh Nukala
Rocket Internal - All Brands
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  Is there any performance difference / improvement in this tensorflow package when compared to the tensorflow installed from default channel?

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Yeshwanth Kumar
Software Engineer
Rocket Forum Shared Account
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  Is there any performance difference / improvement in this tensorflow package when compared to the tensorflow installed from default channel?

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Yeshwanth Kumar
Software Engineer
Rocket Forum Shared Account
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This version of tensorflow package will support specially for ppc64le architecture in Power 9 and 10 machines. This will make use of the Power architecture with which it will have the performance improvement.

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Rajesh Nukala
Rocket Internal - All Brands
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