JenkinsfileForBinaries

// -*- mode: groovy -*-
// Licensed to the Apache Software Foundation (ASF) under one
// or more contributor license agreements.  See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership.  The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use this file except in compliance
// with the License.  You may obtain a copy of the License at
//
//   http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing,
// software distributed under the License is distributed on an
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, either express or implied.  See the License for the
// specific language governing permissions and limitations
// under the License.
//
//This is a Jenkinsfile for nightly tests. The format and some functions have been picked up from the top-level Jenkinsfile

mx_lib = 'build/libmxnet.so, build/3rdparty/tvm/libtvm_runtime.so, build/libtvmop.so, build/tvmop.conf, build/libcustomop_lib.so, build/libcustomop_gpu_lib.so, build/libsubgraph_lib.so'

node('utility') {
  // Loading the utilities requires a node context unfortunately
  checkout scm
  utils = load('ci/Jenkinsfile_utils.groovy')
}
utils.assign_node_labels(utility: 'utility', linux_cpu: 'mxnetlinux-cpu', linux_gpu: 'mxnetlinux-gpu', linux_gpu_p3: 'mxnetlinux-gpu-p3', windows_cpu: 'mxnetwindows-cpu', windows_gpu: 'mxnetwindows-gpu')

utils.main_wrapper(
core_logic: {
  stage('Build') {
    parallel 'GPU: CUDA10.1+cuDNN7': {
      node(NODE_LINUX_CPU) {
        ws('workspace/build-onednn-gpu') {
          utils.init_git()
          utils.docker_run('ubuntu_gpu_cu111', 'build_ubuntu_gpu_onednn', false)
          utils.pack_lib('gpu', mx_lib)
        }
      }
    },
    'CPU: USE_INT64_TENSOR_SIZE': {
      node(NODE_LINUX_GPU) {
        ws('workspace/build-cpu-int64') {
          utils.init_git()
          utils.docker_run('ubuntu_cpu', 'build_ubuntu_cpu_large_tensor', false)
          utils.pack_lib('cpu_int64', mx_lib)
        }
      }
    }
  }

  stage('NightlyTests'){
    parallel 'KVStore_SingleNode: GPU': {
      node('mxnetlinux-gpu-p3-8xlarge') {
        ws('workspace/nt-KVStoreTest') {
          utils.unpack_and_init('gpu', mx_lib)
          utils.docker_run('ubuntu_gpu_cu111', 'nightly_test_KVStore_singleNode', true)
        }
      }
    },
    'Test Large Tensor Size: CPU': {
      node(NODE_LINUX_GPU) {
        ws('workspace/large_tensor-cpu') {
            utils.unpack_and_init('cpu_int64', mx_lib)
            utils.docker_run('ubuntu_cpu', 'nightly_test_large_tensor', false)
        }
      }
    },
    'Gluon estimator: GPU': {
      node(NODE_LINUX_GPU) {
        ws('workspace/estimator-test-gpu') {
          utils.unpack_and_init('gpu', mx_lib)
          utils.docker_run('ubuntu_gpu_cu111', 'nightly_estimator', true)
        }
      }
    }
  }
}
,
failure_handler: {
  if (currentBuild.result == "FAILURE") {
    emailext body: 'Nightly tests for MXNet branch ${BRANCH_NAME} failed. Please view the build at ${BUILD_URL}', replyTo: '${EMAIL}', subject: '[NIGHTLY TEST FAILED] build ${BUILD_NUMBER}', to: '${EMAIL}'
  }
}
)