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[dask] dask cudf inplace prediction. (#5512)

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* Add inplace prediction for dask-cudf.

* Remove Dockerfile.release, since it's not used anywhere

* Use Conda exclusively in CUDF and GPU containers

* Improve cupy memory copying.

* Add skip marks to tests.

* Add mgpu-cudf category on the CI to run all distributed tests.

Co-authored-by: Hyunsu Cho <chohyu01@cs.washington.edu>
This commit is contained in:
Jiaming Yuan 2020-04-15 18:15:51 +08:00 committed by GitHub
parent ca4e05660e
commit 8b04736b81
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
15 changed files with 97 additions and 87 deletions
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18
Jenkinsfile vendored
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@ -307,19 +307,25 @@ def TestPythonGPU(args) {
sh """
${dockerRun} ${container_type} ${docker_binary} ${docker_args} tests/ci_build/test_python.sh mgpu
"""
if (args.cuda_version != '9.0') {
echo "Running tests with cuDF..."
sh """
${dockerRun} cudf ${docker_binary} ${docker_args} tests/ci_build/test_python.sh mgpu-cudf
"""
}
} else {
echo "Using a single GPU"
sh """
${dockerRun} ${container_type} ${docker_binary} ${docker_args} tests/ci_build/test_python.sh gpu
"""
if (args.cuda_version != '9.0') {
echo "Running tests with cuDF..."
sh """
${dockerRun} cudf ${docker_binary} ${docker_args} tests/ci_build/test_python.sh cudf
"""
}
}
// For CUDA 10.0 target, run cuDF tests too
if (args.cuda_version == '10.0') {
echo "Running tests with cuDF..."
sh """
${dockerRun} cudf ${docker_binary} ${docker_args} tests/ci_build/test_python.sh cudf
"""
}
deleteDir()
}
}

31
python-package/xgboost/core.py
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@ -209,15 +209,32 @@ def ctypes2numpy(cptr, length, dtype):
def ctypes2cupy(cptr, length, dtype):
"""Convert a ctypes pointer array to a cupy array."""
import cupy # pylint: disable=import-error
mem = cupy.zeros(length.value, dtype=dtype, order='C')
# pylint: disable=import-error
import cupy
from cupy.cuda.memory import MemoryPointer
from cupy.cuda.memory import UnownedMemory
CUPY_TO_CTYPES_MAPPING = {
cupy.float32: ctypes.c_float,
cupy.uint32: ctypes.c_uint
}
if dtype not in CUPY_TO_CTYPES_MAPPING.keys():
raise RuntimeError('Supported types: {}'.format(
CUPY_TO_CTYPES_MAPPING.keys()
))
addr = ctypes.cast(cptr, ctypes.c_void_p).value
# pylint: disable=c-extension-no-member,no-member
cupy.cuda.runtime.memcpy(
mem.__cuda_array_interface__['data'][0], addr,
length.value * ctypes.sizeof(ctypes.c_float),
cupy.cuda.runtime.memcpyDeviceToDevice)
return mem
device = cupy.cuda.runtime.pointerGetAttributes(addr).device
# The owner field is just used to keep the memory alive with ref count. As
# unowned's life time is scoped within this function we don't need that.
unownd = UnownedMemory(
addr, length.value * ctypes.sizeof(CUPY_TO_CTYPES_MAPPING[dtype]),
owner=None)
memptr = MemoryPointer(unownd, 0)
# pylint: disable=unexpected-keyword-arg
mem = cupy.ndarray((length.value, ), dtype=dtype, memptr=memptr)
assert mem.device.id == device
arr = cupy.array(mem, copy=True)
return arr
def ctypes2buffer(cptr, length):

7
python-package/xgboost/dask.py
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@ -101,6 +101,11 @@ def concat(value): # pylint: disable=too-many-return-statements
return CUDF_concat(value, axis=0)
if lazy_isinstance(value[0], 'cupy.core.core', 'ndarray'):
import cupy # pylint: disable=import-error
# pylint: disable=c-extension-no-member,no-member
d = cupy.cuda.runtime.getDevice()
for v in value:
d_v = v.device.id
assert d_v == d, 'Concatenating arrays on different devices.'
return cupy.concatenate(value, axis=0)
return dd.multi.concat(list(value), axis=0)
@ -631,8 +636,6 @@ def inplace_predict(client, model, data,
if is_df:
if lazy_isinstance(data, 'cudf.core.dataframe', 'DataFrame'):
import cudf # pylint: disable=import-error
# There's an error with cudf saying `concat_cudf` got an
# expected argument `ignore_index`. So this is not yet working.
prediction = cudf.DataFrame({'prediction': prediction},
dtype=numpy.float32)
else:

4
tests/ci_build/Dockerfile.cpu
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@ -12,8 +12,8 @@ RUN \
wget -nv -nc https://cmake.org/files/v3.13/cmake-3.13.0-Linux-x86_64.sh --no-check-certificate && \
bash cmake-3.13.0-Linux-x86_64.sh --skip-license --prefix=/usr && \
# Python
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh && \
bash Miniconda3-latest-Linux-x86_64.sh -b -p /opt/python
wget -O Miniconda3.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh && \
bash Miniconda3.sh -b -p /opt/python
ENV PATH=/opt/python/bin:$PATH

16
tests/ci_build/Dockerfile.cudf
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@ -10,20 +10,16 @@ RUN \
apt-get update && \
apt-get install -y wget unzip bzip2 libgomp1 build-essential && \
# Python
wget https://repo.continuum.io/miniconda/Miniconda3-4.5.12-Linux-x86_64.sh && \
bash Miniconda3-4.5.12-Linux-x86_64.sh -b -p /opt/python
wget -O Miniconda3.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh && \
bash Miniconda3.sh -b -p /opt/python
ENV PATH=/opt/python/bin:$PATH
# Create new Conda environment with cuDF and dask
# Create new Conda environment with cuDF, Dask, and cuPy
RUN \
conda create -n cudf_test -c rapidsai -c nvidia -c numba -c conda-forge -c anaconda \
cudf=0.9 python=3.7 anaconda::cudatoolkit=$CUDA_VERSION dask dask-cuda cupy
# Install other Python packages
RUN \
source activate cudf_test && \
pip install numpy pytest scipy scikit-learn pandas matplotlib wheel kubernetes urllib3 graphviz
conda create -n cudf_test -c rapidsai -c nvidia -c conda-forge -c defaults \
python=3.7 cudf cudatoolkit=$CUDA_VERSION dask dask-cuda dask-cudf cupy \
numpy pytest scipy scikit-learn pandas matplotlib wheel python-kubernetes urllib3 graphviz
ENV GOSU_VERSION 1.10

10
tests/ci_build/Dockerfile.gpu
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@ -9,16 +9,16 @@ RUN \
apt-get update && \
apt-get install -y wget unzip bzip2 libgomp1 build-essential && \
# Python
wget https://repo.continuum.io/miniconda/Miniconda3-4.5.12-Linux-x86_64.sh && \
bash Miniconda3-4.5.12-Linux-x86_64.sh -b -p /opt/python
wget -O Miniconda3.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh && \
bash Miniconda3.sh -b -p /opt/python
ENV PATH=/opt/python/bin:$PATH
# Install Python packages
RUN \
pip install numpy pytest scipy scikit-learn pandas matplotlib wheel kubernetes urllib3 graphviz && \
pip install "dask[complete]" && \
conda install -c rapidsai -c nvidia -c numba -c conda-forge -c anaconda dask-cuda
conda create -n gpu_test -c rapidsai -c nvidia -c conda-forge -c defaults \
python=3.7 dask dask-cuda numpy pytest scipy scikit-learn pandas \
matplotlib wheel python-kubernetes urllib3 graphviz
ENV GOSU_VERSION 1.10

4
tests/ci_build/Dockerfile.gpu_build
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@ -17,8 +17,8 @@ RUN \
$DEVTOOLSET_URL_ROOT/devtoolset-4-runtime-4.1-3.sc1.el6.x86_64.rpm \
$DEVTOOLSET_URL_ROOT/devtoolset-4-libstdc++-devel-5.3.1-6.1.el6.x86_64.rpm && \
# Python
wget https://repo.continuum.io/miniconda/Miniconda3-4.5.12-Linux-x86_64.sh && \
bash Miniconda3-4.5.12-Linux-x86_64.sh -b -p /opt/python && \
wget -O Miniconda3.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh && \
bash Miniconda3.sh -b -p /opt/python && \
# CMake
wget -nv -nc https://cmake.org/files/v3.13/cmake-3.13.0-Linux-x86_64.sh --no-check-certificate && \
bash cmake-3.13.0-Linux-x86_64.sh --skip-license --prefix=/usr

4
tests/ci_build/Dockerfile.jvm
View File

@ -8,8 +8,8 @@ RUN \
yum -y update && \
yum install -y devtoolset-6-gcc devtoolset-6-binutils devtoolset-6-gcc-c++ && \
# Python
wget https://repo.continuum.io/miniconda/Miniconda3-4.5.12-Linux-x86_64.sh && \
bash Miniconda3-4.5.12-Linux-x86_64.sh -b -p /opt/python && \
wget -O Miniconda3.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh && \
bash Miniconda3.sh -b -p /opt/python && \
# CMake
wget -nv -nc https://cmake.org/files/v3.13/cmake-3.13.0-Linux-x86_64.sh --no-check-certificate && \
bash cmake-3.13.0-Linux-x86_64.sh --skip-license --prefix=/usr && \

4
tests/ci_build/Dockerfile.jvm_cross
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@ -13,8 +13,8 @@ RUN \
apt-get update && \
apt-get install -y tar unzip wget openjdk-$JDK_VERSION-jdk libgomp1 && \
# Python
wget https://repo.continuum.io/miniconda/Miniconda3-4.5.12-Linux-x86_64.sh && \
bash Miniconda3-4.5.12-Linux-x86_64.sh -b -p /opt/python && \
wget -O Miniconda3.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh && \
bash Miniconda3.sh -b -p /opt/python && \
/opt/python/bin/pip install awscli && \
# Maven
wget https://archive.apache.org/dist/maven/maven-3/3.6.1/binaries/apache-maven-3.6.1-bin.tar.gz && \

31
tests/ci_build/Dockerfile.release
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@ -1,31 +0,0 @@
FROM centos:6
# Install all basic requirements
RUN \
yum -y update && \
yum install -y graphviz tar unzip wget xz git && \
# Python
wget https://repo.continuum.io/miniconda/Miniconda2-4.3.27-Linux-x86_64.sh && \
bash Miniconda2-4.3.27-Linux-x86_64.sh -b -p /opt/python
ENV PATH=/opt/python/bin:$PATH
# Install Python packages
RUN \
conda install numpy scipy pandas matplotlib pytest scikit-learn && \
pip install pytest wheel auditwheel graphviz
ENV GOSU_VERSION 1.10
# Install lightweight sudo (not bound to TTY)
RUN set -ex; \
wget -O /usr/local/bin/gosu "https://github.com/tianon/gosu/releases/download/$GOSU_VERSION/gosu-amd64" && \
chmod +x /usr/local/bin/gosu && \
gosu nobody true
# Default entry-point to use if running locally
# It will preserve attributes of created files
COPY entrypoint.sh /scripts/
WORKDIR /workspace
ENTRYPOINT ["/scripts/entrypoint.sh"]

18
tests/ci_build/test_python.sh
View File

@ -28,23 +28,33 @@ function install_xgboost {
# Run specified test suite
case "$suite" in
gpu)
source activate gpu_test
install_xgboost
pytest -v -s --fulltrace -m "not mgpu" tests/python-gpu
pytest -v -s -rxXs --fulltrace -m "not mgpu" tests/python-gpu
;;
mgpu)
source activate gpu_test
install_xgboost
pytest -v -s --fulltrace -m "mgpu" tests/python-gpu
pytest -v -s -rxXs --fulltrace -m "mgpu" tests/python-gpu
cd tests/distributed
./runtests-gpu.sh
cd -
pytest -v -s --fulltrace -m "mgpu" tests/python-gpu/test_gpu_with_dask.py
;;
cudf)
source activate cudf_test
install_xgboost
pytest -v -s --fulltrace -m "not mgpu" tests/python-gpu/test_from_cudf.py tests/python-gpu/test_from_cupy.py
pytest -v -s -rxXs --fulltrace -m "not mgpu" \
tests/python-gpu/test_from_cudf.py tests/python-gpu/test_from_cupy.py \
tests/python-gpu/test_gpu_prediction.py
;;
mgpu-cudf)
source activate cudf_test
install_xgboost
pytest -v -s -rxXs --fulltrace -m "mgpu" tests/python-gpu/test_gpu_with_dask.py
;;
cpu)

2
tests/python-gpu/test_gpu_prediction.py
View File

@ -62,6 +62,7 @@ class TestGPUPredict(unittest.TestCase):
# Test case for a bug where multiple batch predictions made on a
# test set produce incorrect results
@pytest.mark.skipif(**tm.no_sklearn())
def test_multi_predict(self):
from sklearn.datasets import make_regression
from sklearn.model_selection import train_test_split
@ -89,6 +90,7 @@ class TestGPUPredict(unittest.TestCase):
assert np.allclose(predict0, predict1)
assert np.allclose(predict0, cpu_predict)
@pytest.mark.skipif(**tm.no_sklearn())
def test_sklearn(self):
m, n = 15000, 14
tr_size = 2500

19
tests/python-gpu/test_gpu_with_dask.py
View File

@ -27,6 +27,7 @@ class TestDistributedGPU(unittest.TestCase):
@pytest.mark.skipif(**tm.no_cudf())
@pytest.mark.skipif(**tm.no_dask_cudf())
@pytest.mark.skipif(**tm.no_dask_cuda())
@pytest.mark.mgpu
def test_dask_dataframe(self):
with LocalCUDACluster() as cluster:
with Client(cluster) as client:
@ -51,18 +52,18 @@ class TestDistributedGPU(unittest.TestCase):
predictions = dxgb.predict(client, out, dtrain).compute()
assert isinstance(predictions, np.ndarray)
# There's an error with cudf saying `concat_cudf` got an
# expected argument `ignore_index`. So the test here is just
# place holder.
# series_predictions = dxgb.inplace_predict(client, out, X)
# assert isinstance(series_predictions, dd.Series)
series_predictions = dxgb.inplace_predict(client, out, X)
assert isinstance(series_predictions, dd.Series)
series_predictions = series_predictions.compute()
single_node = out['booster'].predict(
xgboost.DMatrix(X.compute()))
cupy.testing.assert_allclose(single_node, predictions)
cupy.testing.assert_allclose(single_node, series_predictions)
@pytest.mark.skipif(**tm.no_cupy())
@pytest.mark.mgpu
def test_dask_array(self):
with LocalCUDACluster() as cluster:
with Client(cluster) as client:
@ -82,8 +83,12 @@ class TestDistributedGPU(unittest.TestCase):
single_node = out['booster'].predict(
xgboost.DMatrix(X.compute()))
np.testing.assert_allclose(single_node, from_dmatrix)
device = cupy.cuda.runtime.getDevice()
assert device == inplace_predictions.device.id
single_node = cupy.array(single_node)
assert device == single_node.device.id
cupy.testing.assert_allclose(
cupy.array(single_node),
single_node,
inplace_predictions)

10
tests/python-gpu/test_monotonic_constraints.py
View File

@ -1,12 +1,12 @@
from __future__ import print_function
import sys
import numpy as np
from sklearn.datasets import make_regression
import unittest
import pytest
import xgboost as xgb
sys.path.append("tests/python")
import testing as tm
rng = np.random.RandomState(1994)
@ -20,6 +20,7 @@ def non_increasing(L):
def assert_constraint(constraint, tree_method):
from sklearn.datasets import make_regression
n = 1000
X, y = make_regression(n, random_state=rng, n_features=1, n_informative=1)
dtrain = xgb.DMatrix(X, y)
@ -35,12 +36,13 @@ def assert_constraint(constraint, tree_method):
assert non_increasing(pred)
@pytest.mark.gpu
class TestMonotonicConstraints(unittest.TestCase):
@pytest.mark.skipif(**tm.no_sklearn())
def test_exact(self):
assert_constraint(1, 'exact')
assert_constraint(-1, 'exact')
@pytest.mark.skipif(**tm.no_sklearn())
def test_gpu_hist(self):
assert_constraint(1, 'gpu_hist')
assert_constraint(-1, 'gpu_hist')

6
tests/python/test_predict.py
View File

@ -12,10 +12,10 @@ def run_threaded_predict(X, rows, predict_func):
per_thread = 20
with ThreadPoolExecutor(max_workers=10) as e:
for i in range(0, rows, int(rows / per_thread)):
try:
if hasattr(X, 'iloc'):
predictor = X.iloc[i:i+per_thread, :]
else:
predictor = X[i:i+per_thread, ...]
except TypeError:
predictor = X.iloc[i:i+per_thread, ...]
f = e.submit(predict_func, predictor)
results.append(f)