Disable pytorch_short_perf_test_gpu CI job (#27797)

Summary:
The `pytorch_short_perf_test_gpu` CI job hasn't been giving useful signal compared to https://apaszke.github.io/pytorch-perf-hud/ or the FAI-PEP effort. This PR disables it to reduce maintenance workload for CI admins.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/27797

Differential Revision: D17897180

Pulled By: yf225

fbshipit-source-id: 91a66ebac3d15a44094a669da38c43e3ea9c20d2

.circleci/cimodel/data/pytorch_build_definitions.py

@@ -160,7 +160,7 @@ def gen_dependent_configs(xenial_parent_config):
 
         configs.append(c)
 
-    for x in ["pytorch_short_perf_test_gpu", "pytorch_python_doc_push", "pytorch_cpp_doc_push"]:
+    for x in ["pytorch_python_doc_push", "pytorch_cpp_doc_push"]:
         configs.append(HiddenConf(x, parent_build=xenial_parent_config))
 
     return configs

.circleci/config.yml

@@ -904,41 +904,6 @@ jobs:
           root: .
           paths: .circleci/scripts
 
-  pytorch_short_perf_test_gpu:
-    environment:
-      BUILD_ENVIRONMENT: pytorch-short-perf-test-gpu
-      DOCKER_IMAGE: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda9-cudnn7-py3:347"
-      PYTHON_VERSION: "3.6"
-      USE_CUDA_DOCKER_RUNTIME: "1"
-    resource_class: gpu.medium
-    machine:
-      image: ubuntu-1604:201903-01
-    steps:
-    # See Note [Workspace for CircleCI scripts] in job-specs-setup.yml
-    - should_run_job
-    - setup_linux_system_environment
-    - setup_ci_environment
-    - run:
-        name: Perf Test
-        no_output_timeout: "1h"
-        command: |
-          set -e
-          export COMMIT_DOCKER_IMAGE=${DOCKER_IMAGE}-${CIRCLE_SHA1}
-          echo "DOCKER_IMAGE: "${COMMIT_DOCKER_IMAGE}
-          time docker pull ${COMMIT_DOCKER_IMAGE} >/dev/null
-          export id=$(docker run --runtime=nvidia -t -d -w /var/lib/jenkins ${COMMIT_DOCKER_IMAGE})
-
-          docker cp $id:/var/lib/jenkins/workspace/env /home/circleci/project/env
-          # This IAM user allows write access to S3 bucket for perf test numbers
-          set +x
-          echo "declare -x AWS_ACCESS_KEY_ID=${CIRCLECI_AWS_ACCESS_KEY_FOR_PERF_TEST_S3_BUCKET_V4}" >> /home/circleci/project/env
-          echo "declare -x AWS_SECRET_ACCESS_KEY=${CIRCLECI_AWS_SECRET_KEY_FOR_PERF_TEST_S3_BUCKET_V4}" >> /home/circleci/project/env
-          set -x
-          docker cp /home/circleci/project/env $id:/var/lib/jenkins/workspace/env
-
-          export COMMAND='((echo "export BUILD_ENVIRONMENT=${BUILD_ENVIRONMENT}" && echo "source ./workspace/env" && echo "sudo chown -R jenkins workspace && cd workspace && .jenkins/pytorch/short-perf-test-gpu.sh") | docker exec -u jenkins -i "$id" bash) 2>&1'
-          echo ${COMMAND} > ./command.sh && unbuffer bash ./command.sh | ts
-
   pytorch_python_doc_push:
     environment:
       BUILD_ENVIRONMENT: pytorch-python-doc-push
@@ -1804,9 +1769,6 @@ workflows:
           build_environment: "pytorch-linux-xenial-cuda9-cudnn7-py3-nogpu-test"
           docker_image: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda9-cudnn7-py3:347"
           resource_class: large
-      - pytorch_short_perf_test_gpu:
-          requires:
-            - pytorch_linux_xenial_cuda9_cudnn7_py3_build
       - pytorch_python_doc_push:
           requires:
             - pytorch_linux_xenial_cuda9_cudnn7_py3_build

.circleci/verbatim-sources/job-specs-custom.yml

@@ -1,38 +1,3 @@
-  pytorch_short_perf_test_gpu:
-    environment:
-      BUILD_ENVIRONMENT: pytorch-short-perf-test-gpu
-      DOCKER_IMAGE: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda9-cudnn7-py3:347"
-      PYTHON_VERSION: "3.6"
-      USE_CUDA_DOCKER_RUNTIME: "1"
-    resource_class: gpu.medium
-    machine:
-      image: ubuntu-1604:201903-01
-    steps:
-    # See Note [Workspace for CircleCI scripts] in job-specs-setup.yml
-    - should_run_job
-    - setup_linux_system_environment
-    - setup_ci_environment
-    - run:
-        name: Perf Test
-        no_output_timeout: "1h"
-        command: |
-          set -e
-          export COMMIT_DOCKER_IMAGE=${DOCKER_IMAGE}-${CIRCLE_SHA1}
-          echo "DOCKER_IMAGE: "${COMMIT_DOCKER_IMAGE}
-          time docker pull ${COMMIT_DOCKER_IMAGE} >/dev/null
-          export id=$(docker run --runtime=nvidia -t -d -w /var/lib/jenkins ${COMMIT_DOCKER_IMAGE})
-
-          docker cp $id:/var/lib/jenkins/workspace/env /home/circleci/project/env
-          # This IAM user allows write access to S3 bucket for perf test numbers
-          set +x
-          echo "declare -x AWS_ACCESS_KEY_ID=${CIRCLECI_AWS_ACCESS_KEY_FOR_PERF_TEST_S3_BUCKET_V4}" >> /home/circleci/project/env
-          echo "declare -x AWS_SECRET_ACCESS_KEY=${CIRCLECI_AWS_SECRET_KEY_FOR_PERF_TEST_S3_BUCKET_V4}" >> /home/circleci/project/env
-          set -x
-          docker cp /home/circleci/project/env $id:/var/lib/jenkins/workspace/env
-
-          export COMMAND='((echo "export BUILD_ENVIRONMENT=${BUILD_ENVIRONMENT}" && echo "source ./workspace/env" && echo "sudo chown -R jenkins workspace && cd workspace && .jenkins/pytorch/short-perf-test-gpu.sh") | docker exec -u jenkins -i "$id" bash) 2>&1'
-          echo ${COMMAND} > ./command.sh && unbuffer bash ./command.sh | ts
-
   pytorch_python_doc_push:
     environment:
       BUILD_ENVIRONMENT: pytorch-python-doc-push