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ci/official/wheel_test/update_requirements.sh

# script to run pip-compile for keras, tensorboard, estimator deps.
# if there is a change in requirements.in then all lock files will be updated
# accordingly.

# -e: abort script if one command fails
# -u: error if undefined variable used
# -o pipefail: entire command fails if pipe fails. watch out for yes | ...
# -o history: record shell history
set -euo pipefail -o history

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github.com/tensorflow/tensorflow

ci/official/utilities/setup.sh

# exec".
# Important: "tfrun foo | bar" is "( tfrun foo ) | bar", not "tfrun (foo | bar)".
# Therefore, "tfrun" commands cannot include pipes -- which is
# probably for the better. If a pipe is necessary for something, it is probably
# complex. Write a well-documented script under utilities/ to encapsulate the
# functionality instead.
tfrun() { "$@"; }

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github.com/tensorflow/tensorflow

ci/official/utilities/generate_index_html.sh

</head>
<body>
<h1>TensorFlow Job Logs and Links</h1>
<h2>Job Details</h2>
<ul>
<li>Job name: $KOKORO_JOB_NAME</li>
<li>Job pool: $KOKORO_JOB_POOL</li>
<li>Job ID: $KOKORO_BUILD_ID</li>
<li>Current HEAD Piper Changelist, if any: cl/${KOKORO_PIPER_CHANGELIST:-not available}</li>
<li>Pull Request Number, if any: ${KOKORO_GITHUB_PULL_REQUEST_NUMBER_tensorflow:- none}</li>

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github.com/tensorflow/tensorflow

ci/official/containers/linux_arm64/build.sh

  TAG="latest-multi-python"
else
  # If it is a change, grab a good tag for iterative builds
  if [[ -z "${KOKORO_GITHUB_PULL_REQUEST_NUMBER}" ]]; then
    TAG=$(head -n 1 "$KOKORO_PIPER_DIR/presubmit_request.txt" | cut -d" " -f2)
  else
    TAG="pr-${KOKORO_GITHUB_PULL_REQUEST_NUMBER}"
  fi
fi

# Build for both JAX and TF usage.  We do these in one place because they share

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github.com/tensorflow/tensorflow

configure.py

    raise FileNotFoundError(
        "Can't find 'find_cuda_config.py' script inside working directory")
  proc = subprocess.Popen(
      [environ_cp['PYTHON_BIN_PATH'], paths[0]] + cuda_libraries,
      stdout=subprocess.PIPE,
      env=maybe_encode_env(environ_cp))

  if proc.wait():
    # Errors from find_cuda_config.py were sent to stderr.
    print('Asking for detailed CUDA configuration...\n')
    return False

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github.com/tensorflow/tensorflow

ci/official/utilities/code_check_full.bats

//tensorflow/lite/python:interpreter_test.py
EOF

  # Get the full list of files and targets which get included into the pip
  # package
  bazel cquery --keep_going 'deps(//tensorflow/tools/pip_package:wheel)' | sort -u > $BATS_TEST_TMPDIR/pip_deps
  # Find all Python py_test targets not tagged "no_pip" or "manual", excluding
  # any targets in ignored packages. Combine this list of targets into a bazel

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github.com/tensorflow/tensorflow

ci/official/wheel_test/WORKSPACE

python_register_toolchains(
    name = "python",
    ignore_root_user_error = True,
    python_version = TF_PYTHON_VERSION,
)

load("@python//:defs.bzl", "interpreter")
load("@rules_python//python:pip.bzl", "pip_parse")

pip_parse(
    name = "pypi",
    python_interpreter_target = interpreter,
    requirements = "//:requirements_lock_" + TF_PYTHON_VERSION.replace(".", "_") + ".txt",
)

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github.com/tensorflow/tensorflow

ci/official/envs/linux_x86_tpu

TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_tpu
TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow_tpu"
TFCI_LIB_SUFFIX="-tpu-linux-x86_64"
TFCI_WHL_BAZEL_TEST_ENABLE=0
TFCI_WHL_IMPORT_TEST_ENABLE=0
TFCI_WHL_SIZE_LIMIT=580M

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github.com/tensorflow/tensorflow

ci/official/containers/linux_arm64/devel.usertools/wheel_verification.bats

# up in teardown_file() above.
@test "Wheel is installable" {
    python3 -m venv /tf/venv
    source /tf/venv/bin/activate
    python3 -m pip install --upgrade setuptools wheel
    python3 -m pip install "$TF_WHEEL"
}

@test "TensorFlow is importable" {
    source /tf/venv/bin/activate

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github.com/tensorflow/tensorflow

ci/devinfra/docker_windows/Dockerfile

# Installing pip packages
RUN pip install --upgrade setuptools; \
    pip install altgraph appdirs cachetools certifi cffi chardet colorama \
    cryptography cycler Cython decorator google-api-python-client \
    google-auth google-auth-httplib2 grpcio httplib2 idna ipython-genutils \
    kiwisolver macholib matplotlib nose numpy packaging pandas pickleshare pip \

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