# Usage: setup_venv_test.sh venv_and_symlink_name "glob pattern for one wheel file"
# Example: setup_venv_test.sh bazel_pip "/tf/pkg/*.whl"
# 
# This will create a venv with that wheel file installed in it, and a symlink
# in ./venv_and_symlink_name/tensorflow to ./tensorflow. We use this for the
# "pip" tests.

python -m venv /$1
mkdir -p $1
rm -f ./$1/tensorflow
ln -s $(ls /$1/lib) /$1/lib/python3

# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================

# script to run pip-compile for each requirement.
# if there is a change in requirements.in then all lock files will be updated
# accordingly

# All commands run relative to this directory
cd "$(dirname "${BASH_SOURCE[0]}")"

# limitations under the License.
# ==============================================================================
# Variables containing version strings extracted from the canonical sources:
# tensorflow/core/public/version.h and tools/pip_package/setup.py.
#
# These variables aren't available by default. Scripts must source this file
# explicitly, *after* checking if update_version.py needs to be run for a

  # replace tensorflow to tf_nightly in the wheel name
  export TFCI_BUILD_PIP_PACKAGE_ARGS="$(echo $TFCI_BUILD_PIP_PACKAGE_ARGS | sed 's/tensorflow/tf_nightly/')"
fi

tfrun bazel build $TFCI_BAZEL_COMMON_ARGS //tensorflow/tools/pip_package:wheel $TFCI_BUILD_PIP_PACKAGE_ARGS
tfrun find ./bazel-bin/tensorflow/tools/pip_package -iname "*.whl" -exec cp {} $TFCI_OUTPUT_DIR \;
tfrun ./ci/official/utilities/rename_and_verify_wheels.sh

  ls -sh *.whl
  exit 2
fi

# Quick install checks
venv=$(mktemp -d)
"python${TFCI_PYTHON_VERSION}" -m venv "$venv"
python="$venv/bin/python3"
"$python" -m pip install *.whl $TFCI_PYTHON_VERIFY_PIP_INSTALL_ARGS
if [[ "$TFCI_WHL_IMPORT_TEST_ENABLE" == "1" ]]; then
  "$python" -c 'import tensorflow as tf; t1=tf.constant([1,2,3,4]); t2=tf.constant([5,6,7,8]); print(tf.add(t1,t2).shape)'

cp CHANGELOG.md docs/changelogs/changelog.md
cp CONTRIBUTING.md docs/contribute/contributing.md

# Build the site and push the new files up to GitHub
python3 -m venv venv
source venv/bin/activate
pip install mkdocs-material mkdocs-redirects
mkdocs gh-deploy

# Restore Javadocs from 1.x, 2.x, and 3.x.
git checkout gh-pages
git cherry-pick bb229b9dcc9a21a73edbf8d936bea88f52e0a3ff

#!/bin/bash

# The website is built using MkDocs with the Material theme.
# https://squidfunk.github.io/mkdocs-material/
# It requires Python to run.
# Install the packages with the following command:
# pip install mkdocs mkdocs-material mkdocs-redirects

set -ex

# Test generating the javadoc jars
./gradlew publishToMavenLocal -DRELEASE_SIGNING_ENABLED=false

# Generate the API docs
./gradlew dokkaHtmlMultiModule

# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================

# 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.

mv BUILD.bazel BUILD

SUPPORTED_VERSIONS=("3_9" "3_10" "3_11" "3_12")

#!/usr/bin/env bash
set -x
set -e
# Install pip
cd /tmp
curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py
python3.6 get-pip.py --user
cd -
# Install Flit to be able to install all
python3.6 -m pip install --user flit
# Install with Flit
python3.6 -m flit install --user --extras doc
# Finally, run mkdocs

# install it manually. We use Twine in nightly builds to upload Python packages
# to PyPI.
if [[ "$TFCI_MACOS_TWINE_INSTALL_ENABLE" == 1 ]]; then
  pip install twine==3.6.0
fi

# Scheduled nightly and release builds upload build artifacts (Pip packages,
# Libtensorflow archives) to GCS buckets. TFCI Mac VMs need to authenticate as
# a service account that has the right permissions to be able to do so.
set +x