The remaining launch of TensorFlow v1.3 is now obtainable. This launch of TensorFlow marks the preliminary availability of a number of canned estimators, together with:
- DNNClassifier
- DNNRegressor
- LinearClassifier
- LinearRegressor
- DNNLinearCombinedClassifier
- DNNLinearCombinedRegressor.
The tfestimators bundle offers a excessive degree R interface for these estimators.
Full particulars on the discharge of TensorFlow v1.3 can be found right here: https://github.com/tensorflow/tensorflow/releases/tag/v1.3.0
You can replace your R set up of TensorFlow utilizing the install_tensorflow perform:
library(tensorflow)
install_tensorflow()Note that you just also needs to present any choices utilized in your authentic set up (e.g. technique = "conda", model = "gpu", and many others. )
cuDNN 6.0
TensorFlow v1.3 is constructed in opposition to model 6.0 of the cuDNN library from NVIDIA. Previous variations had been constructed in opposition to cuDNN v5.1, so for installations operating the GPU model of TensorFlow this implies that you will want to put in an up to date model of cuDNN together with TensorFlow v1.3.
Updated set up directions can be found right here: https://tensorflow.rstudio.com/tensorflow/installation_gpu.html.
Version 1.4 of TensorFlow is predicted emigrate once more to model 7.0 of cuDNN.
Reuse
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Citation
For attribution, please cite this work as
Allaire (2017, Aug. 17). Posit AI Blog: TensorFlow v1.3 Released. Retrieved from https://blogs.rstudio.com/tensorflow/posts/2017-08-17-tensorflow-v13-released/
BibTeX quotation
@misc{allaire2017tensorflow,
writer = {Allaire, J.J.},
title = {Posit AI Blog: TensorFlow v1.3 Released},
url = {https://blogs.rstudio.com/tensorflow/posts/2017-08-17-tensorflow-v13-released/},
yr = {2017}
}