.circleci/scripts/binary_linux_test.sh

#!/bin/bash

OUTPUT_SCRIPT=${OUTPUT_SCRIPT:-/home/circleci/project/ci_test_script.sh}

# only source if file exists
if [[ -f /home/circleci/project/env ]]; then
  source /home/circleci/project/env
fi
cat >"${OUTPUT_SCRIPT}" <<EOL
# =================== The following code will be executed inside Docker container ===================
set -eux -o pipefail

retry () {
    "\$@"  || (sleep 1 && "\$@") || (sleep 2 && "\$@")
}

# Source binary env file here if exists
if [[ -e "${BINARY_ENV_FILE:-/nofile}" ]]; then
  source "${BINARY_ENV_FILE:-/nofile}"
fi

python_nodot="\$(echo $DESIRED_PYTHON | tr -d m.u)"

# Set up Python
if [[ "$PACKAGE_TYPE" != libtorch ]]; then
  python_path="/opt/python/cp\$python_nodot-cp\${python_nodot}"
  if [[ "\$python_nodot" = *t ]]; then
    python_digits="\$(echo $DESIRED_PYTHON | tr -cd [:digit:])"
    python_path="/opt/python/cp\$python_digits-cp\${python_digits}t"
  fi
  export PATH="\${python_path}/bin:\$PATH"
fi

EXTRA_CONDA_FLAGS=""
NUMPY_PIN=""
PROTOBUF_PACKAGE="defaults::protobuf"

if [[ "\$python_nodot" = *310* ]]; then
  # There's an issue with conda channel priority where it'll randomly pick 1.19 over 1.20
  # we set a lower boundary here just to be safe
  NUMPY_PIN=">=1.21.2"
  PROTOBUF_PACKAGE="protobuf>=3.19.0"
fi

if [[ "\$python_nodot" = *39* ]]; then
  # There's an issue with conda channel priority where it'll randomly pick 1.19 over 1.20
  # we set a lower boundary here just to be safe
  NUMPY_PIN=">=1.20"
fi

# Move debug wheels out of the package dir so they don't get installed
mkdir -p /tmp/debug_final_pkgs
mv /final_pkgs/debug-*.zip /tmp/debug_final_pkgs || echo "no debug packages to move"

# Install the package
# These network calls should not have 'retry's because they are installing
# locally and aren't actually network calls
# Pick only one package of multiple available (which happens as result of workflow re-runs)
pkg="/final_pkgs/\$(ls -1 /final_pkgs|sort|tail -1)"
if [[ "\$PYTORCH_BUILD_VERSION" == *dev* ]]; then
    CHANNEL="nightly"
else
    CHANNEL="test"
fi

if [[ "$PACKAGE_TYPE" != libtorch ]]; then
  if [[ "\$BUILD_ENVIRONMENT" != *s390x* ]]; then
    pip install "\$pkg" --index-url "https://download.pytorch.org/whl/\${CHANNEL}/${DESIRED_CUDA}"
    retry pip install -q numpy protobuf typing-extensions
  else
    pip install "\$pkg"
    retry pip install -q numpy protobuf typing-extensions
  fi
fi
if [[ "$PACKAGE_TYPE" == libtorch ]]; then
  pkg="\$(ls /final_pkgs/*-latest.zip)"
  unzip "\$pkg" -d /tmp
  cd /tmp/libtorch
fi

# Test the package
/pytorch/.ci/pytorch/check_binary.sh

if [[ "\$GPU_ARCH_TYPE" != *s390x* && "\$GPU_ARCH_TYPE" != *xpu* && "\$GPU_ARCH_TYPE" != *rocm*  && "$PACKAGE_TYPE" != libtorch ]]; then

  torch_pkg_size="$(ls -1 /final_pkgs/torch-* | sort |tail -1 |xargs wc -c |cut -d ' ' -f1)"
  # todo: implement check for large binaries
  # if the package is larger than 1.5GB, we disable the pypi check.
  # this package contains all libraries packaged in torch libs folder
  # example of such package is https://download.pytorch.org/whl/cu126_full/torch
  if [[ "\$torch_pkg_size" -gt  1500000000 ]]; then
    python /pytorch/.ci/pytorch/smoke_test/smoke_test.py --package=torchonly --torch-compile-check disabled --pypi-pkg-check disabled
  else
    python /pytorch/.ci/pytorch/smoke_test/smoke_test.py --package=torchonly --torch-compile-check disabled $extra_parameters
  fi

  if [[ "\$GPU_ARCH_TYPE" != *cpu-aarch64* ]]; then
    # https://github.com/pytorch/pytorch/issues/149422
    python /pytorch/.ci/pytorch/smoke_test/check_gomp.py
  fi
fi

# Clean temp files
cd /pytorch/.ci/pytorch/ && git clean -ffdx

# =================== The above code will be executed inside Docker container ===================
EOL
echo
echo
echo "The script that will run in the next step is:"
cat "${OUTPUT_SCRIPT}"