configure.sh

#!/bin/bash
# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
#
# Licensed 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.
# ==============================================================================

set -uo pipefail

PLATFORM="$(uname -s | tr 'A-Z' 'a-z')"
ARCH=$(uname -m)

# --- helpers ---------------------------------------------------------------
function write_bazelrc() {
  echo "${1}" >> .bazelrc
}

function write_tf_rc() {
  echo "${1}" >> .tf_configure.bazelrc
}

function die() {
  echo "ERROR: $*" >&2
  exit 1
}

function is_macos() {
  [[ "${PLATFORM}" == "darwin" ]]
}

function is_windows() {
  [[ "${PLATFORM}" =~ msys_nt*|mingw*|cygwin*|uwin* ]]
}

function inside_docker() {
  if [[ -f /.dockerenv ]]; then
    return 1
  elif [[ "${PLATFORM}" = "linux" ]] && grep -q docker /proc/1/cgroup; then
    return 1
  else
    return 0
  fi
}

function write_legacy_python_repo() {
  mkdir -p third_party/python_legacy

  # empty WORKSPACE
  cat > third_party/python_legacy/WORKSPACE <<'EOF'
# AUTOGENERATED by configure.sh.
# This file is intentionally empty.
EOF

  # simple BUILD that exports defs.bzl
  cat > third_party/python_legacy/BUILD <<'EOF'
# AUTOGENERATED by configure.sh.

package(default_visibility = ["//visibility:public"])
exports_files(["defs.bzl"])
EOF

  # defs.bzl MUST define 'interpreter' as a string, not a function.
  # We also export py_runtime to satisfy older loads.
  cat > third_party/python_legacy/defs.bzl <<EOF
# AUTOGENERATED by configure.sh.
load("@bazel_tools//tools/python:toolchain.bzl", "py_runtime_pair")
# Absolute path to the python interpreter Bazel/TF should use:
interpreter = "${PYTHON_BIN_PATH}"
py_runtime = native.py_runtime
EOF

  echo
  echo "Created third_party/python_legacy."
  echo "Python interpreter = ${PYTHON_BIN_PATH}"
}

# --- parse args ------------------------------------------------------------
USER_PY=""
for arg in "$@"; do
  case "$arg" in
    --python=*) USER_PY="${arg#--python=}" ;;
    *) echo "Unknown arg: $arg" ;;
  esac
done

# --- choose interpreter (venv/conda/system) --------------------------------
if [[ -n "${USER_PY}" ]]; then
  # 1) Explicit --python=... flag
  PY="${USER_PY}"
elif [[ -n "${PYTHON_BIN_PATH:-}" ]]; then
  # 2) Explicit environment override
  PY="${PYTHON_BIN_PATH}"
elif [[ -n "${CONDA_PREFIX:-}" && -x "${CONDA_PREFIX}/bin/python" ]]; then
  # 3) Conda environment python, if available
  PY="${CONDA_PREFIX}/bin/python"
else
  # 4) Fallback: system python3, but require >= 3.10
  if ! command -v python3 >/dev/null 2>&1; then
    die "python3 not found. Pass --python=/path/to/python3.10+ or set PYTHON_BIN_PATH."
  fi

  if ! python3 - <<'PY'
import sys
raise SystemExit(0 if sys.version_info[:2] >= (3, 10) else 1)
PY
  then
    die "Python 3.10+ required for TensorFlow Quantum, but found " \
      "$(python3 -V 2>&1). Pass --python=/path/to/python3.10+ or set PYTHON_BIN_PATH."
  fi

  PY="$(command -v python3)"
fi

# Normalize to an absolute path. Use Python to print sys.executable because
# tools like pyenv use shim scripts that readlink would resolve to the script
# itself, not the actual interpreter binary.
PY_ABS="$("${PY}" -c 'import os,sys; print(os.path.abspath(sys.executable))')"
PYTHON_BIN_PATH="${PY_ABS}"

# --- identify ourselves (useful mainly when redirecting output) ------------
echo "Configuring TensorFlow Quantum build."
info_string="Running on a ${ARCH} $(uname -s) system"
inside_docker && echo "${info_string}." || echo "${info_string} inside Docker."
echo

# --- choose CPU/GPU like upstream script (default CPU) ---------------------
TF_NEED_CUDA=""
y_for_cpu='Build against TensorFlow CPU backend? (Type n to use GPU) [Y/n] '
while [[ -z "${TF_NEED_CUDA}" ]]; do
  read -p "${y_for_cpu}" INPUT || true
  case "${INPUT:-Y}" in
    [Yy]* ) echo "CPU build selected."; TF_NEED_CUDA=0;;
    [Nn]* ) echo "GPU build selected."; TF_NEED_CUDA=1;;
    * ) echo "Please answer y or n.";;
  esac
done

# For TF >= 2.1 this value isn’t actually consulted by TFQ,
# but we keep a compatible prompt/flag.
TF_CUDA_VERSION="12"

# --- sanity: python is importable and has TF -------------------------------
if [[ ! -x "${PYTHON_BIN_PATH}" ]]; then
  die "${PYTHON_BIN_PATH} not found/executable."
fi

# Ensure TF is importable from system python (user should have installed it).
echo "Next, you may see warnings printed by loading TensorFlow packages."
echo "Do not be alarmed unless there are errors."
tf_output=$("${PYTHON_BIN_PATH}" - <<'PY'
import sys
import os
import glob

try:
    import tensorflow as tf
    import tensorflow.sysconfig as sc
except ImportError:
    sys.exit(1)

print(sc.get_include())

lib_path = sc.get_lib()
lib_dir = lib_path if os.path.isdir(lib_path) else os.path.dirname(lib_path)
print(lib_dir)

cands = (glob.glob(os.path.join(lib_dir, 'libtensorflow_framework.so*')) or
         glob.glob(os.path.join(lib_dir, 'libtensorflow.so*')) or
         glob.glob(os.path.join(lib_dir, '_pywrap_tensorflow_internal.*')))
print(os.path.basename(cands[0]) if cands else 'libtensorflow_framework.so.2')
PY
)

if [[ $? -ne 0 ]]; then
  echo "ERROR: tensorflow not importable by Python (${PYTHON_BIN_PATH})" >&2
  exit 1
fi

{
  read -r HDR
  read -r LIBDIR
  read -r LIBNAME
} <<< "${tf_output}"

echo
echo "Configuration values detected:"
echo "  PYTHON_BIN_PATH=${PYTHON_BIN_PATH}"
echo "  TF_HEADER_DIR=${HDR}"
echo "  TF_SHARED_LIBRARY_DIR=${LIBDIR}"
echo "  TF_SHARED_LIBRARY_NAME=${LIBNAME}"

# --- start fresh -----------------------------------------------------------
rm -f .bazelrc .tf_configure.bazelrc

# --- write .tf_configure.bazelrc (repo_env for repository rules) -----------
write_tf_rc "build --repo_env=PYTHON_BIN_PATH=${PYTHON_BIN_PATH}"
write_tf_rc "build --repo_env=TF_HEADER_DIR=${HDR}"
write_tf_rc "build --repo_env=TF_SHARED_LIBRARY_DIR=${LIBDIR}"
write_tf_rc "build --repo_env=TF_SHARED_LIBRARY_NAME=${LIBNAME}"
write_tf_rc "build --repo_env=TF_NEED_CUDA=${TF_NEED_CUDA}"

# Make sure repo rules and sub-config see legacy Keras (keras 2 instead of Keras 3)
write_tf_rc "build --repo_env=TF_USE_LEGACY_KERAS=1"

# --- write third_party/python_legacy/ with interpreter --------------------
write_legacy_python_repo

# --- write .bazelrc (imports TF config  usual flags) -----------------
write_bazelrc "# WARNING: this file (.bazelrc) is AUTOGENERATED and overwritten"
write_bazelrc "# when configure.sh runs. Put customizations in .bazelrc.user."
write_bazelrc ""
write_bazelrc "try-import %workspace%/.tf_configure.bazelrc"
write_bazelrc "common --experimental_repo_remote_exec"
write_bazelrc "build --spawn_strategy=standalone"
write_bazelrc "build --strategy=Genrule=standalone"
write_bazelrc "build -c opt"
write_bazelrc "build --cxxopt=-D_GLIBCXX_USE_CXX11_ABI=1"
write_bazelrc "build --cxxopt=-std=c++17"
write_bazelrc "build --action_env=TF_USE_LEGACY_KERAS=1"
write_bazelrc "build --action_env=PYTHON_BIN_PATH=${PYTHON_BIN_PATH}"

# rpath so the dynamic linker finds TF’s shared lib
if ! is_windows; then
  write_bazelrc "build --linkopt=-Wl,-rpath,${LIBDIR}"
fi

write_bazelrc ""

# The following supressions are for warnings coming from external dependencies.
# They're most likely inconsequential or false positives. Since we can't fix
# them, we suppress the warnings to reduce noise. Note: single quotes are needed
# for the first two so that the $ anchors are preserved in the .bazelrc file.

write_bazelrc 'build --per_file_copt=external/.*[.]c$@-Wno-deprecated-non-prototype'
write_bazelrc 'build --host_per_file_copt=external/.*[.]c$@-Wno-deprecated-non-prototype'
write_bazelrc "build --per_file_copt=external/com_google_protobuf/.*@-Wno-unused-function"
write_bazelrc "build --host_per_file_copt=external/com_google_protobuf/.*@-Wno-unused-function"
write_bazelrc "build --per_file_copt=external/eigen/.*@-Wno-maybe-uninitialized"
write_bazelrc "build --host_per_file_copt=external/eigen/.*@-Wno-maybe-uninitialized"

# The following warnings come from qsim.
# TODO: fix the code in qsim & update TFQ to use the updated version.
write_bazelrc "build --per_file_copt=tensorflow_quantum/core/ops/noise/tfq_.*@-Wno-unused-but-set-variable"
write_bazelrc "build --host_per_file_copt=tensorflow_quantum/core/ops/noise/tfq_.*@-Wno-unused-but-set-variable"
write_bazelrc "build --per_file_copt=tensorflow_quantum/core/ops/math_ops/tfq_.*@-Wno-deprecated-declarations"
write_bazelrc "build --host_per_file_copt=tensorflow_quantum/core/ops/math_ops/tfq_.*@-Wno-deprecated-declarations"

# CUDA toggle
if [[ "${TF_NEED_CUDA}" == "1" ]]; then
  write_tf_rc "build --repo_env=TF_CUDA_VERSION=${TF_CUDA_VERSION}"

  write_bazelrc ""
  write_bazelrc "build:cuda --define=using_cuda=true --define=using_cuda_nvcc=true"
  write_bazelrc "build:cuda --@local_config_cuda//:enable_cuda"
  write_bazelrc "build:cuda --crosstool_top=@local_config_cuda//crosstool:toolchain"
  if is_windows; then
    write_tf_rc "build --repo_env=CUDNN_INSTALL_PATH=C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v${TF_CUDA_VERSION}"
    write_tf_rc "build --repo_env=CUDA_TOOLKIT_PATH=C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v${TF_CUDA_VERSION}"
  else
    write_tf_rc "build --repo_env=CUDNN_INSTALL_PATH=/usr/lib/x86_64-linux-gnu"
    write_tf_rc "build --repo_env=CUDA_TOOLKIT_PATH=/usr/local/cuda"
  fi
  write_bazelrc "build --config=cuda"
  write_bazelrc "test --config=cuda"
else
  write_bazelrc "build --define=using_cuda=false"
fi

# Follow TensorFlow's approach and load an optional user bazelrc file.
write_bazelrc ""
write_bazelrc "try-import %workspace%/.bazelrc.user"

echo "Wrote .tf_configure.bazelrc and .bazelrc successfully."