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Merge pull request #312 from dfalbel/tf-1.13
Tf 1.13
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.Rbuildignore

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run_tests.sh
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testenv
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MNIST-data
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^appveyor\.yml$

DESCRIPTION

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Package: tensorflow
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Type: Package
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Title: R Interface to 'TensorFlow'
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Version: 1.10.0.9001
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Version: 1.13.1
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Authors@R: c(
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person("JJ", "Allaire", role = c("aut", "cre"), email = "[email protected]"),
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person(family = "RStudio", role = c("cph", "fnd")),
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rstudioapi (>= 0.7)
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Roxygen: list(markdown = TRUE)
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Suggests: testthat, keras, tfestimators
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RoxygenNote: 6.1.0
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RoxygenNote: 6.1.1

NEWS.md

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## Development version
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## TensorFlow 1.13.1 (CRAN)
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- added option to silence TF CPP info output
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- `tf_gpu_configured` function to check if GPU was correctly
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R/generics.R

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#' @export
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Re.tensorflow.tensor <- function(x) {
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tf$real(x)
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Re.tensorflow.tensor <- function(z) {
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tf$real(z)
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}
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#' @export
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Im.tensorflow.tensor <- function(x) {
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tf$imag(x)
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Im.tensorflow.tensor <- function(z) {
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tf$imag(z)
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}
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#' @export
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Conj.tensorflow.tensor <- function(x) {
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tf$conj(x)
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Conj.tensorflow.tensor <- function(z) {
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tf$conj(z)
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}
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#' @export
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Arg.tensorflow.tensor <- function(x) {
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tf$angle(x)
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Arg.tensorflow.tensor <- function(z) {
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tf$angle(z)
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}
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#' @export
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Mod.tensorflow.tensor <- function(x) {
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tf$abs(x)
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Mod.tensorflow.tensor <- function(z) {
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tf$abs(z)
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}

README.md

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## TensorFlow for R
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[![Travis-CI Build Status](https://travis-ci.org/rstudio/tensorflow.svg?branch=master)](https://travis-ci.org/rstudio/tensorflow) [![CRAN\_Status\_Badge](https://www.r-pkg.org/badges/version/tensorflow)](https://cran.r-project.org/package=tensorflow)
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[![Travis-CI Build Status](https://travis-ci.org/rstudio/tensorflow.svg?branch=master)](https://travis-ci.org/rstudio/tensorflow) [![AppVeyor Build Status](https://ci.appveyor.com/api/projects/status/github/rstudio/tensorflow?branch=master&svg=true)](https://ci.appveyor.com/project/rstudio/tensorflow) [![CRAN\_Status\_Badge](https://www.r-pkg.org/badges/version/tensorflow)](https://cran.r-project.org/package=tensorflow)
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[TensorFlow™](https://www.tensorflow.org) is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
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appveyor.yml

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# DO NOT CHANGE the "init" and "install" sections below
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environment:
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matrix:
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- TF_VERSION: 1.13.1
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- TF_VERSION: 1.12.0
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# Download script file from GitHub
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init:
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ps: |
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$ErrorActionPreference = "Stop"
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Invoke-WebRequest http://raw.github.com/krlmlr/r-appveyor/master/scripts/appveyor-tool.ps1 -OutFile "..\appveyor-tool.ps1"
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Import-Module '..\appveyor-tool.ps1'
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install:
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ps: Bootstrap
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cache:
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- C:\RLibrary
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# Adapt as necessary starting from here
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build_script:
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- C:\Miniconda3-x64\Scripts\conda create -y --name r-tensorflow tensorflow=%TF_VERSION% numpy python=3.6.8
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- travis-tool.sh install_deps
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test_script:
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- travis-tool.sh run_tests
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on_failure:
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- 7z a failure.zip *.Rcheck\*
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- appveyor PushArtifact failure.zip
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artifacts:
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- path: '*.Rcheck\**\*.log'
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name: Logs
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- path: '*.Rcheck\**\*.out'
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name: Logs
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- path: '*.Rcheck\**\*.fail'
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name: Logs
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- path: '*.Rcheck\**\*.Rout'
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name: Logs
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- path: '\*_*.tar.gz'
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name: Bits
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- path: '\*_*.zip'
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name: Bits

man/install_tensorflow.Rd

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man/sub-.tensorflow.tensor.Rd

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