Difference between revisions of "TensorFlow"
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TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) that flow between them. This flexible architecture lets you deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device without rewriting code. TensorFlow also includes TensorBoard, a data visualization toolkit. | TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) that flow between them. This flexible architecture lets you deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device without rewriting code. TensorFlow also includes TensorBoard, a data visualization toolkit. | ||
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$ launch_tensorflow python -c 'import os; import inspect; import tensorflow; print(os.path.dirname(inspect.getfile(tensorflow)))' | $ launch_tensorflow python -c 'import os; import inspect; import tensorflow; print(os.path.dirname(inspect.getfile(tensorflow)))' | ||
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| + | A number of useful python modules have been installed inside the tensorflow container e.g. keras. | ||
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| + | $ launch_tensorflow python -c 'import keras' | ||
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Revision as of 22:24, 17 March 2017
Description
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) that flow between them. This flexible architecture lets you deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device without rewriting code. TensorFlow also includes TensorBoard, a data visualization toolkit.
Required Modules
- tensorflow
Parallel (OpenMP)
System Variables
- HPC_{{#uppercase:tensorflow}}_DIR - installation directory
Additional Information
TensorFlow is installed in a container. Use the 'launch_tensorflow' command to access TensorFlow:
$ launch_tensorflow python >>> import tensorflow
or
$ launch_tensorflow python -c 'import os; import inspect; import tensorflow; print(os.path.dirname(inspect.getfile(tensorflow)))'
A number of useful python modules have been installed inside the tensorflow container e.g. keras.
$ launch_tensorflow python -c 'import keras'
Citation
If you publish research that uses tensorflow you have to cite it as follows:
https://www.tensorflow.org/versions/r0.11/resources/bib.html