export TFCI_OUTPUT_DIR=$(realpath "$TFCI_OUTPUT_DIR")
mkdir -p "$TFCI_OUTPUT_DIR"

# In addition to dumping all script output to the terminal, place it into
# $TFCI_OUTPUT_DIR/script.log
exec > >(tee "$TFCI_OUTPUT_DIR/script.log") 2>&1

# Setup tfrun, a helper function for executing steps that can either be run
# locally or run under Docker. setup_docker.sh, below, redefines it as "docker
# exec".

warning for "readme.md" because it makes everything lowercase. There are
repeats of these filename(s) with different casing:
EOF
    find . | tr '[A-Z]' '[a-z]' | sort | uniq -d | tee $BATS_FILE_TMPDIR/repeats
    [[ ! -s $BATS_FILE_TMPDIR/repeats ]]
}

# It's unclear why, but running this on //tensorflow/... is faster than running

Chand Shahi, Shubham Goyal, Shashi, Sigrid Keydana, Siju, Siju Samuel,
sleighsoft, smilu97, Snease-Abq, Son Tran, Spencer Schaber, sremedios, Srini511,
srinivasan.narayanamoorthy, Steve Lang, Steve Nesae, Subin, Sumesh Udayakumaran,
Sungmann Cho, sunway513, Supriya Rao, sxwang, Tae-Hwan Jung, Taehoon Lee, Takeo
Sawada, Taylor Jakobson, Taylor Thornton, Ted Chang, TengLu, terryky,

  <mime-type type="application/ssml+xml">
    <glob pattern="*.ssml"/>
  </mime-type>
  <mime-type type="application/timestamp-query"/>
  <mime-type type="application/timestamp-reply"/>
  <mime-type type="application/tve-trigger"/>
  <mime-type type="application/ulpfec"/>
  <mime-type type="application/vemmi"/>
  <mime-type type="application/vividence.scriptfile"/>
  <mime-type type="application/vnd.3gpp.bsf+xml"/>