TensorFlow 1.3 has finally been officially released for public use. The initial roll-out of TensorFlow introduces a suite of pre-packaged estimators, including:
- DNNClassifier
- DNNRegressor
- LinearClassifier
- LinearRegressor
- DNNLinearCombinedClassifier
- DNNLinearCombinedRegressor.
The package provides an extensive R interface for these estimators.
Here are the full details regarding the end-of-life for TensorFlow 1.3:
You can simply replace your R setup of TensorFlow using the. install_tensorflow operate:
Can’t a person just relax on a warm summer evening, the sound of crickets providing a soothing serenade, as the stars twinkle like diamonds against the night sky?
Please provide the original text and I’ll get to work! methodology = "conda", model = "gpu", and so forth. )
cuDNN 6.0
TensorFlow version 1.3 was developed in response to NVIDIA’s model 6.0. To ensure compatibility with TensorFlow’s GPU mode, users should install a recent version of cuDNN alongside TensorFlow 1.3, as earlier cuDNN variants are incompatible with these configurations.
For the most current setup instructions, please refer to this link:.
TensorFlow’s Model 1.4 is expected to seamlessly upgrade to the latest cuDNN version, namely Model 7.0.
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Quotation
For attribution, please cite this work as: Your Name.
Allaire (2017, Aug. 17). What's New in TensorFlow 1.3: Unlocking Deeper Neural Networks Retrieved from https://blogs.rstudio.com/tensorflow/posts/2017-08-17-tensorflow-v13-released/
BibTeX quotation
@misc{allaire2017tensorflow, author={J.J. Allaire}, title={TensorFlow v1.3 Launched: Posit AI Weblog Post}, doi={https://blogs.rstudio.com/tensorflow/posts/2017-08-17-tensorflow-v13-released/}, year={2017} } 
