[arch-commits] Commit in tensorflow/trunk (PKGBUILD)

[Sven-Hendrik Haase]

    Date: Monday, January 29, 2018 @ 23:56:14
  Author: svenstaro
Revision: 287898

Add absl dependency

Modified:
  tensorflow/trunk/PKGBUILD

----------+
 PKGBUILD |   10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

Modified: PKGBUILD
===================================================================
--- PKGBUILD	2018-01-29 22:56:24 UTC (rev 287897)
+++ PKGBUILD	2018-01-29 23:56:14 UTC (rev 287898)
@@ -6,7 +6,7 @@
 pkgname=(tensorflow tensorflow-opt tensorflow-cuda tensorflow-opt-cuda python-tensorflow python-tensorflow-opt python-tensorflow-cuda python-tensorflow-opt-cuda)
 pkgver=1.5.0
 _pkgver=1.5.0
-pkgrel=1
+pkgrel=2
 pkgdesc="Library for computation using data flow graphs for scalable machine learning"
 url="https://www.tensorflow.org/"
 license=('APACHE')
@@ -154,7 +154,7 @@
 }
 
 package_python-tensorflow() {
-  depends=(python python-protobuf)
+  depends=(python python-protobuf absl-py)
 
   cd ${srcdir}/tensorflow-${_pkgver}
 
@@ -170,7 +170,7 @@
 }
 
 package_python-tensorflow-opt() {
-  depends=(python python-protobuf)
+  depends=(python python-protobuf absl-py)
   conflicts=(python-tensorflow)
   provides=(python-tensorflow)
   pkgdesc="Library for computation using data flow graphs for scalable machine learning (with CPU optimizations)"
@@ -189,7 +189,7 @@
 }
 
 package_python-tensorflow-cuda() {
-  depends=(python cuda cudnn python-pycuda python-protobuf)
+  depends=(python cuda cudnn python-pycuda python-protobuf absl-py)
   conflicts=(python-tensorflow)
   provides=(python-tensorflow)
   pkgdesc="Library for computation using data flow graphs for scalable machine learning (with CUDA)"
@@ -208,7 +208,7 @@
 }
 
 package_python-tensorflow-opt-cuda() {
-  depends=(python cuda cudnn python-pycuda python-protobuf)
+  depends=(python cuda cudnn python-pycuda python-protobuf absl-py)
   conflicts=(python-tensorflow)
   provides=(python-tensorflow)
   pkgdesc="Library for computation using data flow graphs for scalable machine learning (with CUDA and CPU optimizations)"