File size: 2,799 Bytes
7b2177e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 | #!/usr/bin/env bash
# Install IndicDocParser's dependencies into the active Python environment.
#
# ./install.sh # pick the CUDA wheels from your driver
# IDP_CUDA=cu121 ./install.sh # force a CUDA line
# IDP_CUDA=cpu ./install.sh # CPU only -- fine for layout, slow for the recognizer
#
# The one thing pip cannot work out for itself is which CUDA build you need. `pip install torch`
# takes the newest wheel, which on an older driver initialises to CPU with nothing but a warning --
# you get a working install that silently never touches the GPU. And torchvision pins an exact
# torch, so resolving the two separately is how you end up with a mismatched pair and a run of
# import errors. This installs both together, from one index.
set -euo pipefail
cd "$(dirname "$0")"
PY=${PYTHON:-python3}
# `uv venv` creates environments without pip, so `$PY -m pip` is not a safe assumption. Prefer
# whatever the environment actually has; uv is also just faster.
if command -v uv >/dev/null 2>&1; then
pip_install() { uv pip install --python "$PY" "$@"; }
elif "$PY" -m pip --version >/dev/null 2>&1; then
pip_install() { "$PY" -m pip install "$@"; }
elif "$PY" -m ensurepip --upgrade >/dev/null 2>&1; then
pip_install() { "$PY" -m pip install "$@"; }
else
echo "no installer found for $PY -- install pip (python -m ensurepip) or uv, then re-run" >&2
exit 1
fi
detect_cuda() {
command -v nvidia-smi >/dev/null 2>&1 || { echo cpu; return; }
local v
v=$(nvidia-smi 2>/dev/null | sed -n 's/.*CUDA Version: \([0-9]*\)\.\([0-9]*\).*/\1/p' | head -1)
case "$v" in
# CUDA 12.x drivers run any cu12x wheel (minor version compatibility), so one build covers
# the whole line. A 13.x wheel on a 12.x driver does NOT work -- that is the trap.
12) echo cu124 ;;
13|1[4-9]) echo cu130 ;;
"") echo cpu ;;
*) echo cu124 ;;
esac
}
CUDA=${IDP_CUDA:-$(detect_cuda)}
INDEX=https://download.pytorch.org/whl/$CUDA
echo "==> target: $CUDA"
[ "$CUDA" = cpu ] && echo " (no GPU detected -- layout runs fine on CPU, the recognizer is slow)"
echo "==> torch + torchvision, together, from $INDEX"
pip_install torch torchvision --index-url "$INDEX"
echo "==> everything else"
pip_install -r requirements.txt
echo "==> checking"
$PY - <<'PY'
import torch, torchvision, transformers
print(f" torch {torch.__version__}")
print(f" torchvision {torchvision.__version__}")
print(f" transformers {transformers.__version__}")
print(f" cuda {'yes, ' + torch.cuda.get_device_name(0) if torch.cuda.is_available() else 'NO -- running on CPU'}")
import sys; sys.path.insert(0, ".")
from indic_doc_parser import IndicDocParser # noqa: F401
print(" import ok")
PY
echo "==> done"
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