Date: Saturday, April 7, 2018 @ 08:03:42
  Author: svenstaro
Revision: 314766

upgpkg: tensorflow 1.7.0-2

Modified:
  tensorflow/trunk/PKGBUILD

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

Modified: PKGBUILD
===================================================================
--- PKGBUILD    2018-04-07 08:02:30 UTC (rev 314765)
+++ PKGBUILD    2018-04-07 08:03:42 UTC (rev 314766)
@@ -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=1.7.0
 _pkgver=1.7.0
-pkgrel=1
+pkgrel=2
 pkgdesc="Library for computation using data flow graphs for scalable machine 
learning"
 url="https://www.tensorflow.org/";
 license=('APACHE')
@@ -147,7 +147,7 @@
 }
 
 package_python-tensorflow() {
-  depends=(python python-protobuf absl-py)
+  depends=(python-numpy python-protobuf absl-py)
 
   cd ${srcdir}/tensorflow-${_pkgver}
 
@@ -163,7 +163,7 @@
 }
 
 package_python-tensorflow-opt() {
-  depends=(python python-protobuf absl-py)
+  depends=(python-numpy 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)"
@@ -182,7 +182,7 @@
 }
 
 package_python-tensorflow-cuda() {
-  depends=(python cuda cudnn python-pycuda python-protobuf absl-py)
+  depends=(python-numpy 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)"
@@ -201,7 +201,7 @@
 }
 
 package_python-tensorflow-opt-cuda() {
-  depends=(python cuda cudnn python-pycuda python-protobuf absl-py)
+  depends=(python-numpy 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)"

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