The ultimate launch of Tensorflow V1.3 is now out there. This tensorflow launch marks the preliminary availability of a number of canned estimators, which embody:
- Dnnclassifier
- Dnnregressor
- Linear traditional
- Lineage
- DNNLinearcombineDclassifier
- DNNLinearcombineDregressor.
He TFESTIMATORS PACKAGE It offers a excessive -level R interface for these estimators.
The complete particulars concerning the launch of Tensorflow V1.3 can be found right here: https://github.com/tensorflow/tensorflow/releases/tag/v1.3.0
You’ll be able to replace its set up R tensorflow utilizing the install_tensorflow
operate:
library(tensorflow)
install_tensorflow()
Observe that you should additionally present any possibility utilized in its unique set up (for instance, technique = "conda"
, model = "gpu"
and many others )
CUDNN 6.0
Tensorflow V1.3 is predicated on model 6.0 of the CUDNN LIBRARY of Nvidia. The earlier variations have been constructed towards Cudnn V5.1, so for the services that execute the GPU model of Tensorflow which means that you should set up an up to date model of CUDNN along with Tensorflow V1.3.
Up to date set up directions can be found right here: https://tensorflow.rstudio.com/tensorflow/installation_gpu.html.
Tensorflow model 1.4 is predicted emigrate once more to Cudnn model 7.0.
Re-use
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Quotation
For attribution, he cites this work as
Allaire (2017, Aug. 17). Posit AI Weblog: TensorFlow v1.3 Launched. Retrieved from https://blogs.rstudio.com/tensorflow/posts/2017-08-17-tensorflow-v13-released/
Bibtex appointment
@misc{allaire2017tensorflow, creator = {Allaire, J.J.}, title = {Posit AI Weblog: TensorFlow v1.3 Launched}, url = {https://blogs.rstudio.com/tensorflow/posts/2017-08-17-tensorflow-v13-released/}, 12 months = {2017} }