Move ppc64le CI to TF 2.6.0 and PyTorch 1.9.1 (horovod#3208)

Signed-off-by: Nicolas Castet <26874160+nvcastet@users.noreply.github.com>

Jenkinsfile.ppc64le

@@ -6,8 +6,8 @@ pipeline {
     agent {
         docker {
             alwaysPull true
-            // WMLCE 1.7.0 has CUDA 10.2, NCCL 2.5.6, TensorFlow 2.1.0, and PyTorch 1.8.0
-            image 'tensorflowppc64le/tensorflow-ppc64le:osuosl-ubuntu-horovod-wlmce1.7.0-py3.7-ppc64le'
+            // Open-CE 1.4.1 has CUDA 10.2, NCCL 2.8.3, TensorFlow 2.6.0, and PyTorch 1.9.1
+            image 'tensorflowppc64le/tensorflow-ppc64le:osuosl-ubi7-horovod-opence1.4.1-py3.9-ppc64le'
             args '--cap-add=SYS_PTRACE --shm-size=256g'
             label 'power8-gpu'
             registryCredentialsId 'TensorFlow'
@@ -25,10 +25,9 @@ pipeline {
                       git submodule update --init --recursive
                       . ${CONDA_INIT}
                       conda activate ${CONDA_ENV}
-                      conda install -y cmake make
                       set -xe
-                      HOROVOD_WITHOUT_MXNET=1 HOROVOD_WITHOUT_GLOO=1 HOROVOD_WITHOUT_PYTORCH=1 HOROVOD_WITH_TENSORFLOW=1 \
-                          HOROVOD_CUDA_HOME=$CONDA_PREFIX HOROVOD_GPU_OPERATIONS=NCCL MAKEFLAGS="-j1" \
+                      HOROVOD_WITHOUT_MXNET=1 HOROVOD_WITHOUT_GLOO=1 HOROVOD_WITH_PYTORCH=1 HOROVOD_WITH_TENSORFLOW=1 \
+                          HOROVOD_CUDA_HOME="/usr/local/cuda" HOROVOD_GPU_OPERATIONS=NCCL \
                           pip install -v . --no-cache-dir --no-deps
                 '''
             }
@@ -42,12 +41,12 @@ pipeline {
                           set -xe
 
                           # TensorFlow unit tests
-                          horovodrun -n 2 -H localhost:2 --mpi-args="-pami_noib" pytest -k 'not multi_gpu' -v -s test/parallel/test_tensorflow.py
+                          horovodrun -n 2 -H localhost:2 pytest -k 'not multi_gpu' -v -s test/parallel/test_tensorflow.py
                           # Container has only 2 GPUs, so run the 'multi_gpu' test seperatly on one process
-                          horovodrun -n 1 -H localhost:1 --mpi-args="-pami_noib" pytest -k 'multi_gpu' -v -s test/parallel/test_tensorflow.py
+                          horovodrun -n 1 -H localhost:1 pytest -k 'multi_gpu' -v -s test/parallel/test_tensorflow.py
 
                           # PyTorch unit tests
-                          # horovodrun -n 2 -H localhost:2 --mpi-args="-pami_noib" pytest -v -s test/parallel/test_torch.py
+                          horovodrun -n 2 -H localhost:2 pytest -v -s test/parallel/test_torch.py
                     '''
                 }
             }