Skip to content

Building TensorFlow

Jump to bottom
aborkar-ibm edited this page Feb 10, 2020 · 44 revisions

Building TensorFlow

The instructions provided below specify the steps to build TensorFlow version 2.0.0 on Linux on IBM Z for the following distributions:

  • Ubuntu (16.04, 18.04)

General Notes:

  • When following the steps below please use a standard permission user unless otherwise specified.
  • A directory /<source_root>/ will be referred to in these instructions, this is a temporary writable directory anywhere you'd like to place it.

Step 1: Building and Installing TensorFlow v2.0.0

1.1) Build using script

If you want to build Tensorflow using manual steps, go to STEP 1.2.

Use the following commands to build Tensorflow using the build script. Please make sure you have wget installed.

wget -q https://raw.githubusercontent.com/linux-on-ibm-z/scripts/master/Tensorflow/2.0.0/build_tensorflow.sh

# Build Tensorflow
bash build_tensorflow.sh    [Provide -t option for executing build with tests]

If the build completes successfully, go to STEP 2. In case of error, check logs for more details or go to STEP 1.2 to follow manual build steps.

1.2) Install the dependencies

export SOURCE_ROOT=/<source_root>/
  • Ubuntu 16.04
 sudo apt-get update  
 sudo apt-get install -y pkg-config zip g++ zlib1g-dev unzip git vim tar wget automake autoconf libtool make curl maven python3-pip python3-virtualenv python3-numpy swig python3-dev libcurl3-dev python3-mock python3-scipy bzip2 python3-sklearn libhdf5-dev patch git patch libssl-dev
 sudo pip3 install numpy==1.16.2 future wheel backports.weakref portpicker futures==2.2.0 enum34 keras_preprocessing keras_applications h5py tensorflow_estimator

  • (For Ubuntu 16.04) Download and install AdoptOpenJDK (OpenJDK 11 with HotSpot) from here

      export JAVA_HOME=/<path to JDK>/
  export PATH=$JAVA_HOME/bin:$PATH

    Note: At the time of creation of these build instructions, TensorFlow was verified with AdoptOpenJDK 11 version (jdk-11.0.5+10).

  • Ubuntu 18.04

 sudo apt-get update  
 sudo apt-get install -y pkg-config zip g++ zlib1g-dev unzip git vim tar wget automake autoconf libtool make curl maven openjdk-11-jdk python3-pip python3-virtualenv python3-numpy swig python3-dev libcurl3-dev python3-mock python3-scipy bzip2 python3-sklearn libhdf5-dev patch git libssl-dev
 sudo pip3 install numpy==1.16.2 future wheel backports.weakref portpicker futures enum34 keras_preprocessing keras_applications h5py tensorflow_estimator
  • Ensure /usr/bin/python points to Python 3 to build TensorFlow in a Python 3 only environment using below command
  sudo ln -s /usr/bin/python3 /usr/bin/python
  • Install grpcio
 export GRPC_PYTHON_BUILD_SYSTEM_OPENSSL=True
 sudo -E pip3 install grpcio  # Ubuntu (16.04, 18.04)
  • Install go
 cd $SOURCE_ROOT   
 wget https://dl.google.com/go/go1.13.3.linux-s390x.tar.gz  
 sudo tar -C /usr/local -xzf go1.13.3.linux-s390x.tar.gz  
 export PATH=/usr/local/go/bin:$PATH  
 go version

1.3) Build Bazel

  • Download Bazel

     cd $SOURCE_ROOT   
 mkdir bazel && cd bazel  
 wget https://github.com/bazelbuild/bazel/releases/download/0.26.1/bazel-0.26.1-dist.zip
 unzip bazel-0.26.1-dist.zip 
 chmod -R +w .

  • Build Bazel

    env EXTRA_BAZEL_ARGS="--host_javabase=@local_jdk//:jdk" bash ./compile.sh
export PATH=$PATH:$SOURCE_ROOT/bazel/output/

    Note: While building Bazel, if build fails with an error java.lang.OutOfMemoryError: Java heap space, apply below patch and rebuild Bazel.

    • Create a patch file $SOURCE_ROOT/bazel/scripts/bootstrap/patch_compile.diff with the following contents:

      --- compile.sh.orig     2019-11-01 03:10:36.253437981 -0400
+++ compile.sh  2019-11-01 03:10:59.793427971 -0400
@@ -127,7 +127,7 @@
	# Useful if your system chooses too small of a max heap for javac.
	# We intentionally rely on shell word splitting to allow multiple
	# additional arguments to be passed to javac.
-  run "${JAVAC}" -classpath "${classpath}" -sourcepath "${sourcepath}" \
+  run "${JAVAC}" -J-Xms1g -J-Xmx1g -classpath "${classpath}" -sourcepath "${sourcepath}" \
	 -d "${output}/classes" -source "$JAVA_VERSION" -target "$JAVA_VERSION" \
	 -encoding UTF-8 ${BAZEL_JAVAC_OPTS} "@${paramfile}"

    • Apply the patch file

      cd $SOURCE_ROOT/bazel/scripts/bootstrap/
patch --ignore-whitespace compile.sh < patch_compile.diff

    • Rebuild

      cd $SOURCE_ROOT/bazel/
env EXTRA_BAZEL_ARGS="--host_javabase=@local_jdk//:jdk" bash ./compile.sh
export PATH=$PATH:$SOURCE_ROOT/bazel/output/

1.4) Build TensorFlow

  • Download source code

    cd $SOURCE_ROOT
git clone https://github.com/linux-on-ibm-z/tensorflow.git
cd tensorflow
git checkout v2.0.0-s390x

  • Configure

    ./configure  
Extracting Bazel installation...
You have bazel 0.26.1- (@non-git) installed.
Please specify the location of python. [Default is /usr/bin/python]: /usr/bin/python3

Found possible Python library paths:
  /usr/lib/python3/dist-packages
  /usr/local/lib/python3.7/dist-packages
Please input the desired Python library path to use.  Default is [/usr/lib/python3/dist-packages]

Do you wish to build TensorFlow with XLA JIT support? [Y/n]: N
No XLA JIT support will be enabled for TensorFlow.

Do you wish to build TensorFlow with OpenCL SYCL support? [y/N]: N
No OpenCL SYCL support will be enabled for TensorFlow.

Do you wish to build TensorFlow with ROCm support? [y/N]: N
No ROCm support will be enabled for TensorFlow.

Do you wish to build TensorFlow with CUDA support? [y/N]: N
No CUDA support will be enabled for TensorFlow.

Do you wish to download a fresh release of clang? (Experimental) [y/N]: N
Clang will not be downloaded.

Do you wish to build TensorFlow with MPI support? [y/N]: N
No MPI support will be enabled for TensorFlow.

Please specify optimization flags to use during compilation when bazel option "--config=opt" is specified [Default is -march=native -Wno-sign-compare]:


Would you like to interactively configure ./WORKSPACE for Android builds? [y/N]: N
Not configuring the WORKSPACE for Android builds.

Preconfigured Bazel build configs. You can use any of the below by adding "--config=<>" to your build command. See .bazelrc for more details.
      --config=mkl            # Build with MKL support.
      --config=monolithic     # Config for mostly static monolithic build.
      --config=gdr            # Build with GDR support.
      --config=verbs          # Build with libverbs support.
      --config=ngraph         # Build with Intel nGraph support.
      --config=numa           # Build with NUMA support.
      --config=dynamic_kernels        # (Experimental) Build kernels into separate shared objects.
      --config=v2             # Build TensorFlow 2.x instead of 1.x.
Preconfigured Bazel build configs to DISABLE default on features:
      --config=noaws          # Disable AWS S3 filesystem support.
      --config=nogcp          # Disable GCP support.
      --config=nohdfs         # Disable HDFS support.
      --config=noignite       # Disable Apache Ignite support.
      --config=nokafka        # Disable Apache Kafka support.
      --config=nonccl         # Disable NVIDIA NCCL support.
Configuration finished

  • Build Tensorflow

    bazel --host_jvm_args="-Xms1024m" --host_jvm_args="-Xmx2048m" build  --define=tensorflow_mkldnn_contraction_kernel=0 //tensorflow/tools/pip_package:build_pip_package

1.5) Build and install TensorFlow wheel

cd $SOURCE_ROOT/tensorflow
bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_wheel
sudo pip3 install /tmp/tensorflow_wheel/tensorflow-2.0.0-cp*-linux_s390x.whl

Step 2: Verify TensorFlow (Optional)

  • Run TensorFlow from command Line

     $ cd $SOURCE_ROOT
 $ /usr/bin/python3
  >>> import tensorflow as tf
  >>> tf.add(1, 2).numpy()
  3
  >>> hello = tf.constant('Hello, TensorFlow!')
  >>> hello.numpy()
  'Hello, TensorFlow!'
  >>>

Step 3: Execute Test Suite (Optional)

  • Run complete testsuite

    cd $SOURCE_ROOT/tensorflow
bazel --host_jvm_args="-Xms1024m" --host_jvm_args="-Xmx2048m" test --define=tensorflow_mkldnn_contraction_kernel=0 --host_javabase="@local_jdk//:jdk" --test_tag_filters=-gpu,-benchmark-test,-v1only -k   --test_timeout 300,450,1200,3600 --build_tests_only --test_output=errors -- //tensorflow/... -//tensorflow/compiler/... -//tensorflow/lite/... -//tensorflow/core/platform/cloud/... -//tensorflow/java/... -//tensorflow/contrib/...

    Note: If tests fail with '_NamespacePath' object has no attribute 'sort' error, upgrade setuptools dependency with below command and rerun the test:

    sudo pip3 install --upgrade setuptools

    Note: Skipping some test modules due to below issues:

    • //tensorflow/lite and //tensorflow/core/platform/cloud skipped due to BoringSSL, refer #14039 for details
    • //tensorflow/java is under investigation, refer #19770 for details
    • //tensorflow/contrib skipped as tf.contrib has been deprecated from v2.x onwards

  • Run individual test

    bazel --host_jvm_args="-Xms1024m" --host_jvm_args="-Xmx2048m" test --define=tensorflow_mkldnn_contraction_kernel=0 --host_javabase="@local_jdk//:jdk" //tensorflow/<module_name>:<testcase_name>

    For example,

    bazel --host_jvm_args="-Xms1024m" --host_jvm_args="-Xmx2048m" test --define=tensorflow_mkldnn_contraction_kernel=0 --host_javabase="@local_jdk//:jdk" //tensorflow/python/kernel_tests:topk_op_test

    Note:
    1. Below tests are failing on s390x and those are either known or equivalent to Intel:
    //tensorflow/python:session_clusterspec_prop_test
    //tensorflow/python/autograph/pyct:inspect_utils_test_par
    //tensorflow/python/compiler/xla:xla_test
    //tensorflow/python/debug:dist_session_debug_grpc_test
    //tensorflow/python/distribute:values_test
    //tensorflow/python/eager:def_function_xla_test_cpu
    //tensorflow/python/eager:remote_test
    //tensorflow/python/kernel_tests:reader_ops_test
    //tensorflow/python/ops/parallel_for:xla_control_flow_ops_test
    //tensorflow/python/tpu:tpu_test
    //tensorflow/python/training/tracking:util_xla_test_cpu
    //tensorflow/python/tpu:datasets_test
    //tensorflow/python/kernel_tests/random:random_binomial_test
    //tensorflow/python/autograph/pyct/static_analysis:activity_py3_test (For Ubuntu 16.04 only)
    //tensorflow/python/distribute:distribute_lib_test (For Ubuntu 16.04 only)
    //tensorflow/python/keras/optimizer_v2:optimizer_v2_test (For Ubuntu 16.04 only)
    //tensorflow/python/keras:base_layer_test (For Ubuntu 16.04 only)

    2. Below tests are failing on s390x and investigation is in progress:
    //tensorflow/python/kernel_tests:unicode_decode_op_test
    //tensorflow/python/kernel_tests:unicode_transcode_op_test
    //tensorflow/python:cluster_test
    //tensorflow/python:cost_analyzer_test

References:

https://www.tensorflow.org/
https://github.com/tensorflow/tensorflow
http://bazel.io/

The information provided in this article is accurate at the time of writing, but on-going development in the open-source projects involved may make the information incorrect or obsolete. Please open issue or contact us on IBM Z Community if you have any questions or feedback.

Clone this wiki locally