[MXNET-703] Fix relative import in TensorRT

.gitmodules

@@ -26,3 +26,6 @@
 [submodule "3rdparty/tvm"]
 	path = 3rdparty/tvm
 	url = https://github.com/dmlc/tvm
+[submodule "3rdparty/onnx-tensorrt"]
+	path = 3rdparty/onnx-tensorrt
+	url = https://github.com/onnx/onnx-tensorrt.git

CMakeLists.txt

@@ -37,6 +37,7 @@ mxnet_option(ENABLE_CUDA_RTC      "Build with CUDA runtime compilation support"
 mxnet_option(BUILD_CPP_EXAMPLES   "Build cpp examples" ON)
 mxnet_option(INSTALL_EXAMPLES     "Install the example source files." OFF)
 mxnet_option(USE_SIGNAL_HANDLER   "Print stack traces on segfaults." OFF)
+mxnet_option(USE_TENSORRT         "Enable infeference optimization with TensorRT." OFF)
 
 message(STATUS "CMAKE_SYSTEM_NAME ${CMAKE_SYSTEM_NAME}")
 if(USE_CUDA AND NOT USE_OLDCMAKECUDA)
@@ -185,6 +186,36 @@ if(USE_VTUNE)
   list(APPEND mxnet_LINKER_LIBS dl)
 endif()
 
+if(USE_TENSORRT)
+  message(STATUS "Using TensorRT")
+  set(ONNX_PATH 3rdparty/onnx-tensorrt/third_party/onnx/build/)
+  set(ONNX_TRT_PATH 3rdparty/onnx-tensorrt/build/)
+
+  include_directories(${ONNX_PATH})
+  include_directories(3rdparty/onnx-tensorrt/)
+  include_directories(3rdparty/)
+  add_definitions(-DMXNET_USE_TENSORRT=1)
+  add_definitions(-DONNX_NAMESPACE=onnx)
+
+  find_package(Protobuf REQUIRED)
+
+  find_library(ONNX_LIBRARY NAMES libonnx.so REQUIRED
+          PATHS ${ONNX_PATH}
+          DOC "Path to onnx library.")
+  find_library(ONNX_PROTO_LIBRARY NAMES libonnx_proto.so REQUIRED
+          PATHS ${ONNX_PATH}
+          DOC "Path to onnx_proto library.")
+  find_library(ONNX_TRT_RUNTIME_LIBRARY NAMES libnvonnxparser_runtime.so REQUIRED
+          PATHS ${ONNX_TRT_PATH}
+          DOC "Path to onnx_proto library.")
+  find_library(ONNX_TRT_PARSER_LIBRARY NAMES libnvonnxparser.so REQUIRED
+          PATHS ${ONNX_TRT_PATH}
+          DOC "Path to onnx_proto library.")
+
+  list(APPEND mxnet_LINKER_LIBS libnvinfer.so ${ONNX_TRT_PARSER_LIBRARY} ${ONNX_TRT_RUNTIME_LIBRARY}
+          ${ONNX_PROTO_LIBRARY} ${ONNX_LIBRARY} ${PROTOBUF_LIBRARY})
+endif()
+
 if(USE_MKLDNN)
   include(cmake/MklDnn.cmake)
   # CPU architecture (e.g., C5) can't run on another architecture (e.g., g3).

Jenkinsfile

@@ -28,6 +28,7 @@ mx_dist_lib = 'lib/libmxnet.so, lib/libmxnet.a, 3rdparty/dmlc-core/libdmlc.a, 3r
 mx_cmake_lib = 'build/libmxnet.so, build/libmxnet.a, build/3rdparty/dmlc-core/libdmlc.a, build/tests/mxnet_unit_tests, build/3rdparty/openmp/runtime/src/libomp.so'
 mx_cmake_mkldnn_lib = 'build/libmxnet.so, build/libmxnet.a, build/3rdparty/dmlc-core/libdmlc.a, build/tests/mxnet_unit_tests, build/3rdparty/openmp/runtime/src/libomp.so, build/3rdparty/mkldnn/src/libmkldnn.so.0'
 mx_mkldnn_lib = 'lib/libmxnet.so, lib/libmxnet.a, lib/libiomp5.so, lib/libmkldnn.so.0, lib/libmklml_intel.so, 3rdparty/dmlc-core/libdmlc.a, 3rdparty/tvm/nnvm/lib/libnnvm.a'
+mx_tensorrt_lib = 'lib/libmxnet.so, lib/libnvonnxparser_runtime.so.0, lib/libnvonnxparser.so.0, lib/libonnx_proto.so, lib/libonnx.so'
 // timeout in minutes
 max_time = 120
 // assign any caught errors here
@@ -372,6 +373,17 @@ try {
         }
       }
     },
+    'TensorRT': {
+      node(NODE_LINUX_CPU) {
+        ws('workspace/build-tensorrt') {
+          timeout(time: max_time, unit: 'MINUTES') {
+            utils.init_git()
+            utils.docker_run('ubuntu_gpu_tensorrt', 'build_ubuntu_gpu_tensorrt', false)
+            utils.pack_lib('tensorrt', mx_tensorrt_lib)
+          }
+        }
+      }
+    },
     'Build CPU windows':{
       node('mxnetwindows-cpu') {
         timeout(time: max_time, unit: 'MINUTES') {
@@ -740,6 +752,22 @@ try {
         }
       }
     },
+    'Python3: TensorRT GPU': {
+      node(NODE_LINUX_GPU_P3) {
+        ws('workspace/build-tensorrt') {
+          timeout(time: max_time, unit: 'MINUTES') {
+            try {
+              utils.init_git()
+              utils.unpack_lib('tensorrt', mx_tensorrt_lib)
+              utils.docker_run('ubuntu_gpu_tensorrt', 'unittest_ubuntu_tensorrt_gpu', true)
+              utils.publish_test_coverage()
+            } finally {
+              utils.collect_test_results_unix('nosetests_tensorrt.xml', 'nosetests_python3_tensorrt_gpu.xml')
+            }
+          }
+        }
+      }
+    },
     'Scala: CPU': {
       node('mxnetlinux-cpu') {
         ws('workspace/ut-scala-cpu') {

Makefile

@@ -91,6 +91,14 @@ else
 endif
 CFLAGS += -I$(TPARTYDIR)/mshadow/ -I$(TPARTYDIR)/dmlc-core/include -fPIC -I$(NNVM_PATH)/include -I$(DLPACK_PATH)/include -I$(TPARTYDIR)/tvm/include -Iinclude $(MSHADOW_CFLAGS)
 LDFLAGS = -pthread $(MSHADOW_LDFLAGS) $(DMLC_LDFLAGS)
+
+
+ifeq ($(USE_TENSORRT), 1)
+	CFLAGS +=  -I$(ROOTDIR) -I$(TPARTYDIR) -DONNX_NAMESPACE=$(ONNX_NAMESPACE) -DMXNET_USE_TENSORRT=1
+	LDFLAGS += -lprotobuf -pthread -lonnx -lonnx_proto -lnvonnxparser -lnvonnxparser_runtime -lnvinfer -lnvinfer_plugin
+endif
+# -L/usr/local/lib
+
 ifeq ($(DEBUG), 1)
 	NVCCFLAGS += -std=c++11 -Xcompiler -D_FORCE_INLINES -g -G -O0 -ccbin $(CXX) $(MSHADOW_NVCCFLAGS)
 else

amalgamation/amalgamation.py

@@ -23,13 +23,12 @@
 import platform
 
 blacklist = [
-    'Windows.h', 'cublas_v2.h', 'cuda/tensor_gpu-inl.cuh',
-    'cuda_runtime.h', 'cudnn.h', 'cudnn_lrn-inl.h', 'curand.h', 'curand_kernel.h',
-    'glog/logging.h', 'io/azure_filesys.h', 'io/hdfs_filesys.h', 'io/s3_filesys.h',
-    'kvstore_dist.h', 'mach/clock.h', 'mach/mach.h',
-    'malloc.h', 'mkl.h', 'mkl_cblas.h', 'mkl_vsl.h', 'mkl_vsl_functions.h',
-    'nvml.h', 'opencv2/opencv.hpp', 'sys/stat.h', 'sys/types.h', 'cuda.h', 'cuda_fp16.h',
-    'omp.h', 'execinfo.h', 'packet/sse-inl.h', 'emmintrin.h', 'thrust/device_vector.h',
+    'Windows.h', 'cublas_v2.h', 'cuda/tensor_gpu-inl.cuh', 'cuda_runtime.h', 'cudnn.h',
+    'cudnn_lrn-inl.h', 'curand.h', 'curand_kernel.h', 'glog/logging.h', 'io/azure_filesys.h',
+    'io/hdfs_filesys.h', 'io/s3_filesys.h', 'kvstore_dist.h', 'mach/clock.h', 'mach/mach.h',
+    'malloc.h', 'mkl.h', 'mkl_cblas.h', 'mkl_vsl.h', 'mkl_vsl_functions.h', 'NvInfer.h', 'nvml.h',
+    'opencv2/opencv.hpp', 'sys/stat.h', 'sys/types.h', 'cuda.h', 'cuda_fp16.h', 'omp.h',
+    'onnx/onnx.pb.h', 'execinfo.h', 'packet/sse-inl.h', 'emmintrin.h', 'thrust/device_vector.h',
     'cusolverDn.h', 'internal/concurrentqueue_internal_debug.h', 'relacy/relacy_std.hpp',
     'relacy_shims.h', 'ittnotify.h', 'shared_mutex'
     ]
@@ -150,6 +149,7 @@ def expand(x, pending, stage):
                     h not in sysheaders and
                     'mkl' not in h and
                     'nnpack' not in h and
+                    'tensorrt' not in h and
                     not h.endswith('.cuh')): sysheaders.append(h)
             else:
                 expand.treeDepth += 1

ci/docker/Dockerfile.build.ubuntu_gpu_tensorrt

@@ -0,0 +1,41 @@
+# -*- mode: dockerfile -*-
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+#
+# Dockerfile to run MXNet on Ubuntu 16.04 for CPU
+
+FROM nvidia/cuda:9.0-cudnn7-devel
+
+WORKDIR /work/deps
+
+COPY install/ubuntu_core.sh /work/
+RUN /work/ubuntu_core.sh
+COPY install/deb_ubuntu_ccache.sh /work/
+RUN /work/deb_ubuntu_ccache.sh
+COPY install/ubuntu_python.sh /work/
+RUN /work/ubuntu_python.sh
+COPY install/tensorrt.sh /work
+RUN /work/tensorrt.sh
+
+ARG USER_ID=0
+COPY install/ubuntu_adduser.sh /work/
+RUN /work/ubuntu_adduser.sh
+
+COPY runtime_functions.sh /work/
+
+WORKDIR /work/mxnet
+ENV LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:/usr/local/lib

ci/docker/install/tensorrt.sh

@@ -0,0 +1,45 @@
+#!/bin/bash
+
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+# Install gluoncv since we're testing Gluon models as well
+pip2 install gluoncv==0.2.0
+pip3 install gluoncv==0.2.0
+
+# Install Protobuf
+# Install protoc 3.5 and build protobuf here (for onnx and onnx-tensorrt)
+pushd .
+cd ..
+apt-get update
+apt-get install -y automake libtool
+git clone --recursive -b 3.5.1.1 https://github.com/google/protobuf.git
+cd protobuf
+./autogen.sh
+./configure
+make -j$(nproc)
+make install
+ldconfig
+popd
+
+# Install TensorRT
+echo "TensorRT build enabled. Installing TensorRT."
+wget -qO tensorrt.deb https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64/nvinfer-runtime-trt-repo-ubuntu1604-4.0.1-ga-cuda9.0_1-1_amd64.deb
+dpkg -i tensorrt.deb
+apt-get update
+apt-get install -y --allow-downgrades libnvinfer-dev
+rm tensorrt.deb

ci/docker/runtime_functions.sh

@@ -436,6 +436,60 @@ build_ubuntu_gpu() {
     build_ubuntu_gpu_cuda91_cudnn7
 }
 
+build_ubuntu_gpu_tensorrt() {
+
+    set -ex
+
+    build_ccache_wrappers
+
+    # Build ONNX
+    pushd .
+    echo "Installing ONNX."
+    cd 3rdparty/onnx-tensorrt/third_party/onnx
+    rm -rf build
+    mkdir -p build
+    cd build
+    cmake \
+        -DCMAKE_CXX_FLAGS=-I/usr/include/python${PYVER}\
+        -DBUILD_SHARED_LIBS=ON ..\
+        -G Ninja
+    ninja -v
+    export LIBRARY_PATH=`pwd`:`pwd`/onnx/:$LIBRARY_PATH
+    export CPLUS_INCLUDE_PATH=`pwd`:$CPLUS_INCLUDE_PATH
+    popd
+
+    # Build ONNX-TensorRT
+    pushd .
+    cd 3rdparty/onnx-tensorrt/
+    mkdir -p build
+    cd build
+    cmake ..
+    make -j$(nproc)
+    export LIBRARY_PATH=`pwd`:$LIBRARY_PATH
+    popd
+
+    mkdir -p /work/mxnet/lib/
+    cp 3rdparty/onnx-tensorrt/third_party/onnx/build/*.so /work/mxnet/lib/
+    cp -L 3rdparty/onnx-tensorrt/build/libnvonnxparser_runtime.so.0 /work/mxnet/lib/
+    cp -L 3rdparty/onnx-tensorrt/build/libnvonnxparser.so.0 /work/mxnet/lib/
+
+    rm -rf build
+    make \
+        DEV=1                                               \
+        USE_BLAS=openblas                                   \
+        USE_CUDA=1                                          \
+        USE_CUDA_PATH=/usr/local/cuda                       \
+        USE_CUDNN=1                                         \
+        USE_OPENCV=0                                        \
+        USE_DIST_KVSTORE=0                                  \
+        USE_TENSORRT=1                                      \
+        USE_JEMALLOC=0                                      \
+        USE_GPERFTOOLS=0                                    \
+        ONNX_NAMESPACE=onnx                                 \
+        CUDA_ARCH="-gencode arch=compute_70,code=compute_70"\
+        -j$(nproc)
+}
+
 build_ubuntu_gpu_mkldnn() {
     set -ex
 
@@ -638,6 +692,15 @@ unittest_ubuntu_python3_gpu_nocudnn() {
     nosetests-3.4 $NOSE_COVERAGE_ARGUMENTS --with-xunit --xunit-file nosetests_gpu.xml --verbose tests/python/gpu
 }
 
+unittest_ubuntu_tensorrt_gpu() {
+    set -ex
+    export PYTHONPATH=./python/
+    export MXNET_STORAGE_FALLBACK_LOG_VERBOSE=0
+    export LD_LIBRARY_PATH=/work/mxnet/lib:$LD_LIBRARY_PATH
+    python tests/python/tensorrt/lenet5_train.py
+    nosetests-3.4 $NOSE_COVERAGE_ARGUMENTS --with-xunit --xunit-file nosetests_trt_gpu.xml --verbose tests/python/tensorrt/
+}
+
 # quantization gpu currently only runs on P3 instances
 # need to separte it from unittest_ubuntu_python2_gpu()
 unittest_ubuntu_python2_quantization_gpu() {
@@ -970,3 +1033,5 @@ EOF
     declare -F | cut -d' ' -f3
     echo
 fi
+
+

include/mxnet/c_api.h

@@ -1714,6 +1714,13 @@ MXNET_DLL int MXExecutorReshape(int partial_shaping,
                                 NDArrayHandle** aux_states,
                                 ExecutorHandle shared_exec,
                                 ExecutorHandle *out);
+
+/*!
+ * \brief get optimized graph from graph executor
+ */
+MXNET_DLL int MXExecutorGetOptimizedSymbol(ExecutorHandle handle,
+                                           SymbolHandle *out);
+
 /*!
  * \brief set a call back to notify the completion of operation
  */

include/mxnet/executor.h

@@ -166,6 +166,7 @@ class Executor {
                               std::unordered_map<std::string, NDArray>*
                                 shared_data_arrays = nullptr,
                               Executor* shared_exec = nullptr);
+
   /*!
    * \brief the prototype of user-defined monitor callback
    */

python/mxnet/base.py

@@ -709,3 +709,19 @@ def write_all_str(module_file, module_all_list):
     module_op_file.close()
     write_all_str(module_internal_file, module_internal_all)
     module_internal_file.close()
+
+def cint(init_val=0):
+    """create a C int with an optional initial value"""
+    return C.c_int(init_val)
+
+def int_addr(x):
+    """given a c_int, return it's address as an int ptr"""
+    x_addr = C.addressof(x)
+    int_p = C.POINTER(C.c_int)
+    x_int_addr = C.cast(x_addr, int_p)
+    return x_int_addr
+
+def checked_call(f, *args):
+    """call a cuda function and check for success"""
+    error_t = f(*args)
+    assert error_t == 0, "Failing cuda call %s returns %s." % (f.__name__, error_t)

python/mxnet/contrib/__init__.py

@@ -32,3 +32,4 @@
 from . import io
 from . import quantization
 from . import quantization as quant
+from . import tensorrt