The ultimate launch of TensorFlow v1.3 is now accessible. 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 gives a excessive stage 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 may replace your R set up of TensorFlow utilizing the install_tensorflow perform:
library(tensorflow)
install_tensorflow()Observe that you simply must also present any choices utilized in your unique set up (e.g. methodology = "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. Earlier variations have been constructed in opposition to cuDNN v5.1, so for installations working 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.
Up to date set up directions can be found right here: https://tensorflow.rstudio.com/tensorflow/installation_gpu.html.
Model 1.4 of TensorFlow is predicted emigrate once more to model 7.0 of cuDNN.
Reuse
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Quotation
For attribution, please cite 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 quotation
@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/},
yr = {2017}
}