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
operate:
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 so on. )
cuDNN 6.0
TensorFlow v1.3 is constructed towards model 6.0 of the cuDNN library from NVIDIA. Earlier variations had been constructed towards cuDNN v5.1, so for installations operating the GPU model of TensorFlow this implies that you’ll 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 anticipated emigrate once more to model 7.0 of cuDNN.
Reuse
Textual content and figures are licensed underneath Inventive Commons Attribution CC BY 4.0. The figures which were reused from different sources do not fall underneath this license and will be acknowledged by a be aware of their caption: “Determine from …”.
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, writer = {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} }