Issue 1:
Currently, we don't allow in-place operations on views if there are any other live Variables sharing the same data. We should allow in-place operations and compute the gradient correctly. There are a few changes necessary to support this.

Viewing operations include view, narrow, select, expand, [un]squeeze, and unfold. By "a view" I mean a Variable that is a view on another Variable.

Add a field "base" to Variable. Every view has a pointer to a single base Variable. (The base is never a view)

In-place operations on views change the grad_fn of the base, not of the view.

The grad_fn on a view may become stale. So views also store an expected_version

In-place operations on views

Every in-place operation on a view inserts three Functions to base.grad_fn. For example:

x = base[2]
x.mul_(y)

becomes:

Stride(MulBackward(Unstride(<old base.grad_fn>), <y.grad_fn>))

Assume, for now, that base is contiguous. The Stride op takes the grad_output, makes it contiguous, and applies the stride, sizes, and storageOffset of the view (x). This performs the identical viewing operation on grad_output that was performed on base to get x. For the above example, this is equivalent to:

grad_input = grad_output[2]

Unstride performs the reverse operation. It creates a grad_input with the same shape as base, applies the striding of the view x to grad_input, and copies grad_output into that view. For the above example, this is equivalent to:

grad_input = zeros_like(base)
grad_input[2] = grad_output

Stride and Unstride are both implemented in terms of a differentiable restride operation that generalizes all of our viewing operations:

Tensor restride(Tensor self, IntList sizes, IntList strides, int offset);

Stale grad_fn on views

An in-place operation on a view makes the grad_fn of all other views stale. The compute_next_functions needs to be updated to handle views: it should re-create the Function for a view if it's stale before returning it.

Non-contiguous base Variables

If base is not contiguous, then we also need the strides/sizes of the base in restride:

Tensor restride(Tensor self, IntList sizes, IntList strides, IntList base_sizes, IntList base_strides, int offset) {
Tensor copy = self.type().tensor(base_sizes, base_strides);
copy.copy_(self);
return restride(copy, sizes, strides, offset);
}

Issue 2:
🐛 Bug

Torch fails to build (even with BUILD_TEST=0) on /opt/pytorch/torch/csrc/Dtype.cpp; looks like another instance of warning converted to errors:

�[0mFirst, rewinding head to replay your work on top of it...
Fast-forwarded HEAD to 733fc908874c71a5285043931a1cf80aa923165c.
Building wheel torch-1.0.0a0+1bafa62
running install
setup.py::run()
running build_deps
�[91m+ SYNC_COMMAND=cp
�[0m�[91m++ command -v rsync
�[0m�[91m+ '[' -x /usr/bin/rsync ']'
�[0m�[91m+ SYNC_COMMAND='rsync -lptgoD'
+ CMAKE_COMMAND=cmake
�[0m�[91m++ command -v cmake3
�[0m�[91m+ [[ -x '' ]]
�[0m�[91m+ USE_CUDA=0
+ USE_FBGEMM=0
�[0m�[91m+ USE_ROCM=0
�[0m�[91m+ USE_NNPACK=0
+ USE_MKLDNN=0
+ USE_QNNPACK=0
�[0m�[91m+ USE_GLOO_IBVERBS=0
+ CAFFE2_STATIC_LINK_CUDA=0
+ RERUN_CMAKE=1
�[0m�[91m+ [[ 4 -gt 0 ]]
+ case "$1" in
+ USE_NNPACK=1
+ shift
+ [[ 3 -gt 0 ]]
+ case "$1" in
�[0m�[91m+ USE_MKLDNN=1
+ shift
+ [[ 2 -gt 0 ]]
+ case "$1" in
�[0m�[91m+ USE_QNNPACK=1
+ shift
+ [[ 1 -gt 0 ]]
+ case "$1" in
�[0m�[91m+ break
�[0m�[91m+ CMAKE_INSTALL='make install'
�[0m�[91m+ BUILD_SHARED_LIBS=ON
�[0m�[91m+ USER_CFLAGS=
+ USER_LDFLAGS=
�[0m�[91m+ [[ -n '' ]]
+ [[ -n '' ]]
�[0m�[91m+ [[ -n '' ]]
�[0m�[91m++ uname
�[0m�[91m+ '[' Linux == Darwin ']'
�[0m�[91m+++ dirname ../tools/build_pytorch_libs.sh
�[0m�[91m++ cd ../tools/..
�[0m�[91m+++ pwd
�[0m�[91m++ printf '%q\n' /opt/pytorch
�[0m�[91m+ BASE_DIR=/opt/pytorch
�[0m�[91m+ TORCH_LIB_DIR=/opt/pytorch/torch/lib
+ INSTALL_DIR=/opt/pytorch/torch/lib/tmp_install
+ THIRD_PARTY_DIR=/opt/pytorch/third_party
+ C_FLAGS=
�[0m�[91m+ C_FLAGS=' -DOMPI_SKIP_MPICXX=1'
+ LDFLAGS=
�[0m�[91m+ LD_POSTFIX=.so
�[0m�[91m++ uname
�[0m�[91m+ [[ Linux == \D\a\r\w\i\n ]]
+ [[ 0 -eq 1 ]]
�[0m�[91m+ LDFLAGS=' -Wl,-rpath,$ORIGIN'
�[0m�[91m+ CPP_FLAGS=' -std=c++11 '
+ THD_FLAGS=
+ [[ 0 -eq 1 ]]
�[0m�[91m+ CUDA_NVCC_FLAGS=' -DOMPI_SKIP_MPICXX=1'
�[0m�[91m+ [[ -z '' ]]
+ CUDA_DEVICE_DEBUG=0
�[0m�[91m+ '[' -z '' ']'
�[0m�[91m++ getconf _NPROCESSORS_ONLN
�[0m�[91m+ MAX_JOBS=8
�[0m�[91m+ BUILD_TYPE=Release
�[0m�[91m+ [[ -n '' ]]
+ [[ -n '' ]]
�[0mBuilding in Release mode
�[91m+ echo 'Building in Release mode'
�[0m�[91m+ mkdir -p /opt/pytorch/torch/lib/tmp_install
�[0m�[91m+ for arg in "$@"
�[0m�[91m+ [[ caffe2 == \c\a\f\f\e\2 ]]
+ build_caffe2
�[0m�[91m+ [[ -z '' ]]
�[0m�[91m+ EXTRA_CAFFE2_CMAKE_FLAGS=()
+ [[ -n '' ]]
+ [[ -n /opt/conda/lib/python3.6/site-packages ]]
�[0m�[91m+ EXTRA_CAFFE2_CMAKE_FLAGS+=("-DCMAKE_PREFIX_PATH=$CMAKE_PREFIX_PATH")
+ [[ 1 -eq 1 ]]
�[0m�[91m+ cmake /opt/pytorch -DPYTHON_EXECUTABLE=/opt/conda/bin/python -DPYTHON_LIBRARY=/opt/conda/lib/libpython3.6m.so.1.0 -DPYTHON_INCLUDE_DIR=/opt/conda/include/python3.6m -DBUILDING_WITH_TORCH_LIBS=ON -DTORCH_BUILD_VERSION=1.0.0a0+1bafa62 -DCMAKE_BUILD_TYPE=Release -DBUILD_TORCH=ON -DBUILD_PYTHON=ON -DBUILD_SHARED_LIBS=ON -DBUILD_BINARY=OFF -DBUILD_TEST=OFF -DINSTALL_TEST=OFF -DBUILD_CAFFE2_OPS=ON -DONNX_NAMESPACE=onnx_torch -DUSE_CUDA=0 -DUSE_DISTRIBUTED=ON -DUSE_FBGEMM=0 -DUSE_NUMPY= -DNUMPY_INCLUDE_DIR=/opt/conda/lib/python3.6/site-packages/numpy-1.16.0.dev0+2668b31-py3.6-linux-x86_64.egg/numpy/core/include -DCAFFE2_STATIC_LINK_CUDA=0 -DUSE_ROCM=0 -DUSE_NNPACK=1 -DUSE_LEVELDB=OFF -DUSE_LMDB=OFF -DUSE_OPENCV=OFF -DUSE_QNNPACK=1 -DUSE_FFMPEG=OFF -DUSE_GLOG=OFF -DUSE_GFLAGS=OFF -DUSE_SYSTEM_EIGEN_INSTALL=OFF -DCUDNN_INCLUDE_DIR= -DCUDNN_LIB_DIR= -DCUDNN_LIBRARY= -DUSE_MKLDNN=1 -DNCCL_EXTERNAL=0 -DCMAKE_INSTALL_PREFIX=/opt/pytorch/torch/lib/tmp_install -DCMAKE_C_FLAGS= -DCMAKE_CXX_FLAGS= '-DCMAKE_EXE_LINKER_FLAGS= -Wl,-rpath,$ORIGIN ' '-DCMAKE_SHARED_LINKER_FLAGS= -Wl,-rpath,$ORIGIN ' -DTHD_SO_VERSION=1 -DCMAKE_PREFIX_PATH=/opt/conda/lib/python3.6/site-packages
�[0m-- The CXX compiler identification is GNU 8.2.0
-- The C compiler identification is GNU 8.2.0
-- Check for working CXX compiler: /usr/local/bin/c++
-- Check for working CXX compiler: /usr/local/bin/c++ -- works
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Detecting CXX compile features
-- Detecting CXX compile features - done
-- Check for working C compiler: /usr/local/bin/gcc
-- Check for working C compiler: /usr/local/bin/gcc -- works
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Detecting C compile features
-- Detecting C compile features - done
-- Not forcing any particular BLAS to be found
-- Performing Test COMPILER_WORKS
-- Performing Test COMPILER_WORKS - Success
-- Performing Test SUPPORT_GLIBCXX_USE_C99
-- Performing Test SUPPORT_GLIBCXX_USE_C99 - Success
-- Performing Test CAFFE2_EXCEPTION_PTR_SUPPORTED
-- Performing Test CAFFE2_EXCEPTION_PTR_SUPPORTED - Success
-- std::exception_ptr is supported.
-- Performing Test CAFFE2_IS_NUMA_AVAILABLE
-- Performing Test CAFFE2_IS_NUMA_AVAILABLE - Success
-- NUMA is available
-- Performing Test CAFFE2_NEED_TO_TURN_OFF_DEPRECATION_WARNING
-- Performing Test CAFFE2_NEED_TO_TURN_OFF_DEPRECATION_WARNING - Failed
-- Turning off deprecation warning due to glog.
-- Performing Test CAFFE2_COMPILER_SUPPORTS_AVX2_EXTENSIONS
-- Performing Test CAFFE2_COMPILER_SUPPORTS_AVX2_EXTENSIONS - Success
-- Current compiler supports avx2 extension. Will build perfkernels.
-- Performing Test CAFFE2_COMPILER_SUPPORTS_AVX512F_EXTENSIONS
-- Performing Test CAFFE2_COMPILER_SUPPORTS_AVX512F_EXTENSIONS - Success
-- Current compiler supports avx512f extension. Will build fbgemm.
-- Performing Test COMPILER_SUPPORTS_HIDDEN_VISIBILITY
-- Performing Test COMPILER_SUPPORTS_HIDDEN_VISIBILITY - Success
-- Performing Test COMPILER_SUPPORTS_HIDDEN_INLINE_VISIBILITY
-- Performing Test COMPILER_SUPPORTS_HIDDEN_INLINE_VISIBILITY - Success
-- Performing Test COMPILER_SUPPORTS_RDYNAMIC
-- Performing Test COMPILER_SUPPORTS_RDYNAMIC - Success
-- Building using own protobuf under third_party per request.
-- Use custom protobuf build.
-- Looking for pthread.h
-- Looking for pthread.h - found
-- Looking for pthread_create
-- Looking for pthread_create - not found
-- Looking for pthread_create in pthreads
-- Looking for pthread_create in pthreads - not found
-- Looking for pthread_create in pthread
-- Looking for pthread_create in pthread - found
-- Found Threads: TRUE
-- Caffe2 protobuf include directory: $<BUILD_INTERFACE:/opt/pytorch/third_party/protobuf/src>$<INSTALL_INTERFACE:include>
-- The BLAS backend of choice:MKL
-- Looking for sys/types.h
-- Looking for sys/types.h - found
-- Looking for stdint.h
-- Looking for stdint.h - found
-- Looking for stddef.h
-- Looking for stddef.h - found
-- Check size of void*
-- Check size of void* - done
-- Checking for [mkl_intel_lp64 - mkl_gnu_thread - mkl_core - gomp - pthread - m - dl]
-- Library mkl_intel_lp64: /opt/intel/mkl/lib/intel64/libmkl_intel_lp64.so
-- Library mkl_gnu_thread: /opt/intel/mkl/lib/intel64/libmkl_gnu_thread.so
-- Library mkl_core: /opt/intel/mkl/lib/intel64/libmkl_core.so
-- Try OpenMP C flag = [-fopenmp]
-- Performing Test OpenMP_FLAG_DETECTED
-- Performing Test OpenMP_FLAG_DETECTED - Success
-- Try OpenMP CXX flag = [-fopenmp]
-- Performing Test OpenMP_FLAG_DETECTED
-- Performing Test OpenMP_FLAG_DETECTED - Success
-- Found OpenMP: -fopenmp
-- Library gomp: -fopenmp
-- Library pthread: /usr/lib/x86_64-linux-gnu/libpthread.so
-- Library m: /usr/lib/x86_64-linux-gnu/libm.so
-- Library dl: /usr/lib/x86_64-linux-gnu/libdl.so
-- Looking for cblas_sgemm
-- Looking for cblas_sgemm - found
-- The ASM compiler identification is GNU
-- Found assembler: /usr/local/bin/gcc
-- Check if compiler accepts -pthread
-- Check if compiler accepts -pthread - yes
-- Brace yourself, we are building NNPACK
-- Found PythonInterp: /opt/conda/bin/python (found version "3.6.5")
-- Found Numa: /usr/include
-- Found Numa (include: /usr/include, library: /usr/lib/x86_64-linux-gnu/libnuma.so)
-- Using third party subdirectory Eigen.
�[91mPython 3.6.5 :: Anaconda, Inc.
�[0m-- Found PythonInterp: /opt/conda/bin/python (found suitable version "3.6.5", minimum required is "2.7")
-- Found PythonLibs: /opt/conda/lib/libpython3.6m.so.1.0 (found suitable version "3.6.5", minimum required is "2.7")
�[91mCMake Warning at cmake/Dependencies.cmake:583 (find_package):
Could not find a package configuration file provided by "pybind11" with any
of the following names:

pybind11Config.cmake
pybind11-config.cmake

Add the installation prefix of "pybind11" to CMAKE_PREFIX_PATH or set
"pybind11_DIR" to a directory containing one of the above files. If
"pybind11" provides a separate development package or SDK, be sure it has
been installed.
Call Stack (most recent call first):
CMakeLists.txt:201 (include)

�[0m-- Could NOT find pybind11 (missing: pybind11_INCLUDE_DIR)
-- Using third_party/pybind11.
-- Found MPI_C: /usr/lib/x86_64-linux-gnu/openmpi/lib/libmpi.so
-- Found MPI_CXX: /usr/lib/x86_64-linux-gnu/openmpi/lib/libmpi_cxx.so;/usr/lib/x86_64-linux-gnu/openmpi/lib/libmpi.so
-- MPI support found
-- MPI compile flags:
-- MPI include path: /usr/lib/x86_64-linux-gnu/openmpi/include/openmpi/usr/lib/x86_64-linux-gnu/openmpi/include/openmpi/opal/mca/event/libevent2022/libevent/usr/lib/x86_64-linux-gnu/openmpi/include/openmpi/opal/mca/event/libevent2022/libevent/include/usr/lib/x86_64-linux-gnu/openmpi/include
-- MPI LINK flags path:
-- MPI libraries: /usr/lib/x86_64-linux-gnu/openmpi/lib/libmpi_cxx.so/usr/lib/x86_64-linux-gnu/openmpi/lib/libmpi.so
�[91mCMake Warning at cmake/Dependencies.cmake:618 (message):
OpenMPI found, but it is not built with CUDA support.
Call Stack (most recent call first):
CMakeLists.txt:201 (include)

�[0m-- Adding -fopenmp
�[91mCMake Warning at cmake/Dependencies.cmake:769 (message):
Not using CUDA, so disabling NCCL. Suppress this warning with
-DUSE_NCCL=OFF.
Call Stack (most recent call first):
CMakeLists.txt:201 (include)

�[0m-- MPI include path: /usr/lib/x86_64-linux-gnu/openmpi/include/openmpi/usr/lib/x86_64-linux-gnu/openmpi/include/openmpi/opal/mca/event/libevent2022/libevent/usr/lib/x86_64-linux-gnu/openmpi/include/openmpi/opal/mca/event/libevent2022/libevent/include/usr/lib/x86_64-linux-gnu/openmpi/include
-- MPI libraries: /usr/lib/x86_64-linux-gnu/openmpi/lib/libmpi_cxx.so/usr/lib/x86_64-linux-gnu/openmpi/lib/libmpi.so
�[91mCMake Warning at cmake/Dependencies.cmake:847 (message):
mobile opengl is only used in android or ios builds.
Call Stack (most recent call first):
CMakeLists.txt:201 (include)

CMake Warning at cmake/Dependencies.cmake:923 (message):
Metal is only used in ios builds.
Call Stack (most recent call first):
CMakeLists.txt:201 (include)

�[0m--
-- ******** Summary ********
-- CMake version : 3.7.2
-- CMake command : /usr/bin/cmake
-- System : Linux
-- C++ compiler : /usr/local/bin/c++
-- C++ compiler version : 8.2.0
-- CXX flags : -Wno-deprecated -fvisibility-inlines-hidden -fopenmp
-- Build type : Release
-- Compile definitions : TH_BLAS_MKL
-- CMAKE_PREFIX_PATH : /opt/conda/lib/python3.6/site-packages
-- CMAKE_INSTALL_PREFIX : /opt/pytorch/torch/lib/tmp_install
-- CMAKE_MODULE_PATH : /opt/pytorch/cmake/Modules
--
-- ONNX version : 1.3.0
-- ONNX NAMESPACE : onnx_torch
-- ONNX_BUILD_TESTS : OFF
-- ONNX_BUILD_BENCHMARKS : OFF
-- ONNX_USE_LITE_PROTO : OFF
-- ONNXIFI_DUMMY_BACKEND : OFF
--
-- Protobuf compiler :
-- Protobuf includes :
-- Protobuf libraries :
-- BUILD_ONNX_PYTHON : OFF
-- Found gcc >=5 and CUDA <= 7.5, adding workaround C++ flags
-- Could not find CUDA with FP16 support, compiling without torch.CudaHalfTensor
-- Removing -DNDEBUG from compile flags
-- Compiling with OpenMP support
-- MAGMA not found. Compiling without MAGMA support
-- Could not find hardware support for NEON on this machine.
-- No OMAP3 processor on this machine.
-- No OMAP4 processor on this machine.
-- Looking for cpuid.h
-- Looking for cpuid.h - found
-- Performing Test HAVE_GCC_GET_CPUID
-- Performing Test HAVE_GCC_GET_CPUID - Success
-- Performing Test NO_GCC_EBX_FPIC_BUG
-- Performing Test NO_GCC_EBX_FPIC_BUG - Success
-- Performing Test C_HAS_AVX_1
-- Performing Test C_HAS_AVX_1 - Failed
-- Performing Test C_HAS_AVX_2
-- Performing Test C_HAS_AVX_2 - Success
-- Performing Test C_HAS_AVX2_1
-- Performing Test C_HAS_AVX2_1 - Failed
-- Performing Test C_HAS_AVX2_2
-- Performing Test C_HAS_AVX2_2 - Success
-- Performing Test CXX_HAS_AVX_1
-- Performing Test CXX_HAS_AVX_1 - Failed
-- Performing Test CXX_HAS_AVX_2
-- Performing Test CXX_HAS_AVX_2 - Success
-- Performing Test CXX_HAS_AVX2_1
-- Performing Test CXX_HAS_AVX2_1 - Failed
-- Performing Test CXX_HAS_AVX2_2
-- Performing Test CXX_HAS_AVX2_2 - Success
-- AVX compiler support found
-- AVX2 compiler support found
-- Performing Test HAS_C11_ATOMICS
-- Performing Test HAS_C11_ATOMICS - Success
-- Atomics: using C11 intrinsics
-- Performing Test BLAS_F2C_DOUBLE_WORKS
-- Performing Test BLAS_F2C_DOUBLE_WORKS - Failed
-- Performing Test BLAS_F2C_FLOAT_WORKS
-- Performing Test BLAS_F2C_FLOAT_WORKS - Success
-- Performing Test BLAS_USE_CBLAS_DOT
-- Performing Test BLAS_USE_CBLAS_DOT - Success
-- Found a library with BLAS API (mkl).
-- Found a library with LAPACK API. (mkl)
�[91mdisabling CUDA because NOT USE_CUDA is set
�[0m�[91mdisabling ROCM because NOT USE_ROCM is set
�[0m-- CuDNN not found. Compiling without CuDNN support
-- MIOpen not found. Compiling without MIOpen support
-- Found MKLDNN: /opt/intel/mkl/lib/intel64/libmkl_intel_lp64.so;/opt/intel/mkl/lib/intel64/libmkl_gnu_thread.so;/opt/intel/mkl/lib/intel64/libmkl_core.so;-fopenmp;/usr/lib/x86_64-linux-gnu/libpthread.so;/usr/lib/x86_64-linux-gnu/libm.so;/usr/lib/x86_64-linux-gnu/libdl.so
-- Detecting Intel(R) MKL: trying mklml_intel
-- Detecting Intel(R) MKL: trying mklml_gnu
-- Detecting Intel(R) MKL: trying mklml
-- Detecting Intel(R) MKL: trying mkl_rt
-- Intel(R) MKL: include /opt/intel/compilers_and_libraries/linux/mkl/include
-- Intel(R) MKL: lib /usr/local/lib64/libmkl_rt.so
-- OpenMP lib: -fopenmp
-- Found Doxygen: /usr/bin/doxygen (found version "1.8.13")
-- VTune profiling environment is unset
-- Looking for clock_gettime in rt
-- Looking for clock_gettime in rt - found
-- Looking for mmap
-- Looking for mmap - found
-- Looking for shm_open
-- Looking for shm_open - found
-- Looking for shm_unlink
-- Looking for shm_unlink - found
-- Looking for malloc_usable_size
-- Looking for malloc_usable_size - found
-- Performing Test C_HAS_THREAD
-- Performing Test C_HAS_THREAD - Success
-- GCC 8.2.0: Adding gcc and gcc_s libs to link line
-- Using python found in /opt/conda/bin/python
�[91mdisabling CUDA because USE_CUDA is set false
�[0m-- Check size of long double
-- Check size of long double - done
-- Performing Test COMPILER_SUPPORTS_LONG_DOUBLE
-- Performing Test COMPILER_SUPPORTS_LONG_DOUBLE - Success
-- Performing Test COMPILER_SUPPORTS_FLOAT128
-- Performing Test COMPILER_SUPPORTS_FLOAT128 - Success
-- Performing Test COMPILER_SUPPORTS_SSE2
-- Performing Test COMPILER_SUPPORTS_SSE2 - Success
-- Performing Test COMPILER_SUPPORTS_SSE4
-- Performing Test COMPILER_SUPPORTS_SSE4 - Success
-- Performing Test COMPILER_SUPPORTS_AVX
-- Performing Test COMPILER_SUPPORTS_AVX - Success
-- Performing Test COMPILER_SUPPORTS_FMA4
-- Performing Test COMPILER_SUPPORTS_FMA4 - Success
-- Performing Test COMPILER_SUPPORTS_AVX2
-- Performing Test COMPILER_SUPPORTS_AVX2 - Success
-- Performing Test COMPILER_SUPPORTS_SVE
-- Performing Test COMPILER_SUPPORTS_SVE - Failed
-- Performing Test COMPILER_SUPPORTS_AVX512F
-- Performing Test COMPILER_SUPPORTS_AVX512F - Success
-- Performing Test COMPILER_SUPPORTS_OPENMP
-- Performing Test COMPILER_SUPPORTS_OPENMP - Success
-- Performing Test COMPILER_SUPPORTS_WEAK_ALIASES
-- Performing Test COMPILER_SUPPORTS_WEAK_ALIASES - Success
-- Performing Test COMPILER_SUPPORTS_BUILTIN_MATH
-- Performing Test COMPILER_SUPPORTS_BUILTIN_MATH - Success
-- Configuring build for SLEEF-v3.2
�[91m Target system: Linux-4.4.0-116-generic
�[0m�[91m Target processor: x86_64
Host system: Linux-4.4.0-116-generic
Host processor: x86_64
Detected C compiler: GNU @ /usr/local/bin/gcc�[0m�[91m
�[0m-- Using option `-Wall -Wno-unused -Wno-attributes -Wno-unused-result -Wno-psabi -ffp-contract=off -fno-math-errno -fno-trapping-math` to compile libsleef
-- Building shared libs : OFF
-- MPFR : /usr/lib/x86_64-linux-gnu/libmpfr.so
-- MPFR header file in /usr/include
-- GMP : /usr/lib/x86_64-linux-gnu/libgmp.so
-- RUNNING_ON_TRAVIS : 0
-- COMPILER_SUPPORTS_OPENMP : 1
-- Using python found in /opt/conda/bin/python
-- /usr/local/bin/c++ /opt/pytorch/torch/abi-check.cpp -o /opt/pytorch/build/abi-check
-- Determined _GLIBCXX_USE_CXX11_ABI=1
-- Performing Test HAS_THREAD_LOCAL
-- Performing Test HAS_THREAD_LOCAL - Success
-- ignoring CUDA
-- MPI_LIBRARIES: /usr/lib/x86_64-linux-gnu/openmpi/lib/libmpi_cxx.so;/usr/lib/x86_64-linux-gnu/openmpi/lib/libmpi.so
-- Building C10D without CUDA support
-- MPI_INCLUDE_PATH: /usr/lib/x86_64-linux-gnu/openmpi/include/openmpi;/usr/lib/x86_64-linux-gnu/openmpi/include/openmpi/opal/mca/event/libevent2022/libevent;/usr/lib/x86_64-linux-gnu/openmpi/include/openmpi/opal/mca/event/libevent2022/libevent/include;/usr/lib/x86_64-linux-gnu/openmpi/include
-- MPI_LIBRARIES: /usr/lib/x86_64-linux-gnu/openmpi/lib/libmpi_cxx.so;/usr/lib/x86_64-linux-gnu/openmpi/lib/libmpi.so
-- MPIEXEC: /usr/bin/mpiexec
-- NCCL operators skipped due to no CUDA support
-- Including IDEEP operators
-- Excluding image processing operators due to no opencv
-- Excluding video processing operators due to no opencv
-- Include Observer library
-- Using lib/python3.6/site-packages as python relative installation path
-- Automatically generating missing __init__.py files.
�[91mCMake Warning at CMakeLists.txt:389 (message):
Generated cmake files are only fully tested if one builds with system glog,
gflags, and protobuf. Other settings may generate files that are not well
tested.

�[0m--
-- ******** Summary ********
-- General:
-- CMake version : 3.7.2
-- CMake command : /usr/bin/cmake
-- System : Linux
-- C++ compiler : /usr/local/bin/c++
-- C++ compiler version : 8.2.0
-- BLAS : MKL
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for (int i = 0; i < (const int)(ctx.getNumInputs()); ++i) {
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�[91m/opt/pytorch/aten/src/TH/THRandom.cpp: In function ‘THGenerator* THGenerator_newUnseeded()’:
/opt/pytorch/aten/src/TH/THRandom.cpp:18:38: warning: ‘void* memset(void*, int, size_t)’ clearing an object of type ‘THGenerator’ {aka ‘struct THGenerator’} with no trivial copy-assignment; use value-initialization instead [-Wclass-memaccess]
memset(self, 0, sizeof(THGenerator));
^
In file included from /opt/pytorch/aten/src/TH/THRandom.cpp:3:
/opt/pytorch/aten/src/TH/THGenerator.hpp:26:8: note: ‘THGenerator’ {aka ‘struct THGenerator’} declared here
struct THGenerator {
^~~~~~~~~~~
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return torch::getVariableType(at::Backend::CPU, type);
^~~~~~~~~~~~~~~
/opt/pytorch/torch/csrc/torch.cpp:6:28: note: declared here
at::TypeExtendedInterface& getVariableType(at::Backend backend, at::ScalarType type) {
^~~~~~~~~~~~~~~
/opt/pytorch/torch/csrc/torch.cpp:11:55: warning: ‘at::TypeExtendedInterface& torch::getVariableType(at::Backend, at::ScalarType)’ is deprecated [-Wdeprecated-declarations]
return torch::getVariableType(at::Backend::CPU, type);
^
/opt/pytorch/torch/csrc/torch.cpp:6:28: note: declared here
at::TypeExtendedInterface& getVariableType(at::Backend backend, at::ScalarType type) {
^~~~~~~~~~~~~~~
/opt/pytorch/torch/csrc/torch.cpp:11:55: warning: ‘at::TypeExtendedInterface& torch::getVariableType(at::Backend, at::ScalarType)’ is deprecated [-Wdeprecated-declarations]
return torch::getVariableType(at::Backend::CPU, type);
^
/opt/pytorch/torch/csrc/torch.cpp:6:28: note: declared here
at::TypeExtendedInterface& getVariableType(at::Backend backend, at::ScalarType type) {
^~~~~~~~~~~~~~~
�[0m�[91m/opt/pytorch/torch/csrc/torch.cpp: In function ‘at::TypeExtendedInterface& torch::CUDA(at::ScalarType)’:
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return torch::getVariableType(at::Backend::CUDA, type);
^~~~~~~~~~~~~~~
�[0m�[91m/opt/pytorch/torch/csrc/torch.cpp:6:28: note: declared here
at::TypeExtendedInterface& getVariableType(at::Backend backend, at::ScalarType type) {
^~~~~~~~~~~~~~~
�[0m�[91m/opt/pytorch/torch/csrc/torch.cpp:15:56: warning: ‘at::TypeExtendedInterface& torch::getVariableType(at::Backend, at::ScalarType)’ is deprecated [-Wdeprecated-declarations]
return torch::getVariableType(at::Backend::CUDA, type);
^
/opt/pytorch/torch/csrc/torch.cpp:6:28: note: declared here
at::TypeExtendedInterface& getVariableType(at::Backend backend, at::ScalarType type) {
^~~~~~~~~~~~~~~
/opt/pytorch/torch/csrc/torch.cpp:15:56: warning: ‘at::TypeExtendedInterface& torch::getVariableType(at::Backend, at::ScalarType)’ is deprecated [-Wdeprecated-declarations]
return torch::getVariableType(at::Backend::CUDA, type);
^
/opt/pytorch/torch/csrc/torch.cpp:6:28: note: declared here
at::TypeExtendedInterface& getVariableType(at::Backend backend, at::ScalarType type) {
^~~~~~~~~~~~~~~
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[ 96%] Building CXX object caffe2/torch/CMakeFiles/torch_python.dir/csrc/Module.cpp.o
�[91m/opt/pytorch/torch/csrc/Dtype.cpp:44:33: error: cast between incompatible function types from ‘PyObject* (*)(THPDtype*)’ {aka ‘_object* (*)(THPDtype*)’} to ‘getter’ {aka ‘_object* (*)(_object*, void*)’} [-Werror=cast-function-type]
{"is_floating_point", (getter)THPDtype_is_floating_point, nullptr, nullptr, nullptr},
^~~~~~~~~~~~~~~~~~~~~~~~~~
�[0m�[91m/opt/pytorch/torch/csrc/Dtype.cpp:49:31: error: cast between incompatible function types from ‘PyObject* (*)(THPDtype*)’ {aka ‘_object* (*)(THPDtype*)’} to ‘PyCFunction’ {aka ‘_object* (*)(_object*, _object*)’} [-Werror=cast-function-type]
{"__reduce__", (PyCFunction)THPDtype_reduce, METH_NOARGS, nullptr},
^~~~~~~~~~~~~~~
�[0m�[91m/opt/pytorch/torch/csrc/DataLoader.cpp:217:49: error: cast between incompatible function types from ‘PyObject* (*)(PyObject*)’ {aka ‘_object* (*)(_object*)’} to ‘PyCFunction’ {aka ‘_object* (*)(_object*, _object*)’} [-Werror=cast-function-type]
{"_error_if_any_worker_fails", (PyCFunction)THPModule_errorIfAnyWorkerFails, METH_NOARGS, nullptr},
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
�[0m�[91mcc1plus: all warnings being treated as errors
�[0m�[91mmake[2]: *** [caffe2/torch/CMakeFiles/torch_python.dir/csrc/Dtype.cpp.o] Error 1
make[2]: *** Waiting for unfinished jobs....
�[0mcaffe2/torch/CMakeFiles/torch_python.dir/build.make:211: recipe for target 'caffe2/torch/CMakeFiles/torch_python.dir/csrc/Dtype.cpp.o' failed
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�[0mcaffe2/torch/CMakeFiles/torch_python.dir/build.make:163: recipe for target 'caffe2/torch/CMakeFiles/torch_python.dir/csrc/DataLoader.cpp.o' failed
�[91mmake[2]: *** [caffe2/torch/CMakeFiles/torch_python.dir/csrc/DataLoader.cpp.o] Error 1
�[0m�[91m/opt/pytorch/torch/csrc/Generator.cpp:124:36: error: cast between incompatible function types from ‘PyObject* (*)(THPGenerator*)’ {aka ‘_object* (*)(THPGenerator*)’} to ‘PyCFunction’ {aka ‘_object* (*)(_object*, _object*)’} [-Werror=cast-function-type]
{"get_state", (PyCFunction)THPGenerator_getState, METH_NOARGS, nullptr},
^~~~~~~~~~~~~~~~~~~~~
�[0m�[91m/opt/pytorch/torch/csrc/Generator.cpp:127:36: error: cast between incompatible function types from ‘PyObject* (*)(THPGenerator*)’ {aka ‘_object* (*)(THPGenerator*)’} to ‘PyCFunction’ {aka ‘_object* (*)(_object*, _object*)’} [-Werror=cast-function-type]
{"seed", (PyCFunction)THPGenerator_seed, METH_NOARGS, nullptr},
^~~~~~~~~~~~~~~~~
/opt/pytorch/torch/csrc/Generator.cpp:128:36: error: cast between incompatible function types from ‘PyObject* (*)(THPGenerator*)’ {aka ‘_object* (*)(THPGenerator*)’} to ‘PyCFunction’ {aka ‘_object* (*)(_object*, _object*)’} [-Werror=cast-function-type]
{"initial_seed", (PyCFunction)THPGenerator_initialSeed, METH_NOARGS, nullptr},
^~~~~~~~~~~~~~~~~~~~~~~~
�[0m�[91m/opt/pytorch/torch/csrc/Device.cpp:169:26: error: cast between incompatible function types from ‘PyObject* (*)(THPDevice*)’ {aka ‘_object* (*)(THPDevice*)’} to ‘getter’ {aka ‘_object* (*)(_object*, void*)’} [-Werror=cast-function-type]
{"type", (getter)THPDevice_type, nullptr, nullptr, nullptr},
^~~~~~~~~~~~~~
/opt/pytorch/torch/csrc/Device.cpp:170:26: error: cast between incompatible function types from ‘PyObject* (*)(THPDevice*)’ {aka ‘_object* (*)(THPDevice*)’} to ‘getter’ {aka ‘_object* (*)(_object*, void*)’} [-Werror=cast-function-type]
{"index", (getter)THPDevice_index, nullptr, nullptr, nullptr},
^~~~~~~~~~~~~~~
�[0m�[91m/opt/pytorch/torch/csrc/Device.cpp:175:31: error: cast between incompatible function types from ‘PyObject* (*)(THPDevice*)’ {aka ‘_object* (*)(THPDevice*)’} to ‘PyCFunction’ {aka ‘_object* (*)(_object*, _object*)’} [-Werror=cast-function-type]
{"__reduce__", (PyCFunction)THPDevice_reduce, METH_NOARGS, nullptr},
^~~~~~~~~~~~~~~~
�[0m�[91m/opt/pytorch/torch/csrc/Module.cpp:410:36: error: cast between incompatible function types from ‘PyObject* (*)(PyObject*)’ {aka ‘_object* (*)(_object*)’} to ‘PyCFunction’ {aka ‘_object* (*)(_object*, _object*)’} [-Werror=cast-function-type]
{"_autograd_init", (PyCFunction)THPAutograd_initExtension, METH_NOARGS, nullptr},
^~~~~~~~~~~~~~~~~~~~~~~~~
/opt/pytorch/torch/csrc/Module.cpp:413:36: error: cast between incompatible function types from ‘PyObject* (*)(PyObject*)’ {aka ‘_object* (*)(_object*)’} to ‘PyCFunction’ {aka ‘_object* (*)(_object*, _object*)’} [-Werror=cast-function-type]
{"_has_distributed",(PyCFunction)THPModule_hasDistributed, METH_NOARGS, nullptr},
^~~~~~~~~~~~~~~~~~~~~~~~
/opt/pytorch/torch/csrc/Module.cpp:414:36: error: cast between incompatible function types from ‘PyObject* (*)(PyObject*, PyObject*, PyObject*)’ {aka ‘_object* (*)(_object*, _object*, _object*)’} to ‘PyCFunction’ {aka ‘_object* (*)(_object*, _object*)’} [-Werror=cast-function-type]
{"_safe_call", (PyCFunction)THPModule_safeCall, METH_VARARGS | METH_KEYWORDS, nullptr},
^~~~~~~~~~~~~~~~~~
/opt/pytorch/torch/csrc/Module.cpp:422:51: error: cast between incompatible function types from ‘PyObject* (*)(PyObject*)’ {aka ‘_object* (*)(_object*)’} to ‘PyCFunction’ {aka ‘_object* (*)(_object*, _object*)’} [-Werror=cast-function-type]
{"_get_backcompat_broadcast_warn", (PyCFunction)THPModule_getBackcompatBroadcastWarn, METH_NOARGS, nullptr},
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
�[0m�[91m/opt/pytorch/torch/csrc/Module.cpp:424:49: error: cast between incompatible function types from ‘PyObject* (*)(PyObject*)’ {aka ‘_object* (*)(_object*)’} to ‘PyCFunction’ {aka ‘_object* (*)(_object*, _object*)’} [-Werror=cast-function-type]
{"_get_backcompat_keepdim_warn", (PyCFunction)THPModule_getBackcompatKeepdimWarn, METH_NOARGS, nullptr},
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/opt/pytorch/torch/csrc/Module.cpp:425:36: error: cast between incompatible function types from ‘PyObject* (*)(PyObject*)’ {aka ‘_object* (*)(_object*)’} to ‘PyCFunction’ {aka ‘_object* (*)(_object*, _object*)’} [-Werror=cast-function-type]
{"get_num_threads", (PyCFunction)THPModule_getNumThreads, METH_NOARGS, nullptr},
^~~~~~~~~~~~~~~~~~~~~~~
�[0m�[91m/opt/pytorch/torch/csrc/Module.cpp:427:39: error: cast between incompatible function types from ‘PyObject* (*)(PyObject*)’ {aka ‘_object* (*)(_object*)’} to ‘PyCFunction’ {aka ‘_object* (*)(_object*, _object*)’} [-Werror=cast-function-type]
{"_get_cudnn_enabled", (PyCFunction)THPModule_userEnabledCuDNN, METH_NOARGS, nullptr},
^~~~~~~~~~~~~~~~~~~~~~~~~~
/opt/pytorch/torch/csrc/Module.cpp:429:41: error: cast between incompatible function types from ‘PyObject* (*)(PyObject*)’ {aka ‘_object* (*)(_object*)’} to ‘PyCFunction’ {aka ‘_object* (*)(_object*, _object*)’} [-Werror=cast-function-type]
{"_get_cudnn_benchmark", (PyCFunction)THPModule_benchmarkCuDNN, METH_NOARGS, nullptr},
^~~~~~~~~~~~~~~~~~~~~~~~
/opt/pytorch/torch/csrc/Module.cpp:431:45: error: cast between incompatible function types from ‘PyObject* (*)(PyObject*)’ {aka ‘_object* (*)(_object*)’} to ‘PyCFunction’ {aka ‘_object* (*)(_object*, _object*)’} [-Werror=cast-function-type]
{"_get_cudnn_deterministic", (PyCFunction)THPModule_deterministicCuDNN, METH_NOARGS, nullptr},
^~~~~~~~~~~~~~~~~~~~~~~~~~~~
�[0m�[91mcc1plus: all warnings being treated as errors
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Failed to run 'bash ../tools/build_pytorch_libs.sh --use-nnpack --use-mkldnn --use-qnnpack caffe2'

To Reproduce

cd /opt && git clone --recursive https://github.com/pytorch/pytorch \
&& cd pytorch && git submodule update --init && \
cd /opt/pytorch/third_party/ideep/mkl-dnn && \
git pull https://github.com/intel/mkl-dnn.git --no-commit --rebase && \
cd /opt/pytorch && \
sed -i 's/"Use MKLDNN" OFF/"Use MKLDNN" ON /g' CMakeLists.txt && \
sed -i 's/"Use DISTRIBUTED" OFF/"Use DISTRIBUTED" ON /g' CMakeLists.txt && \
sed -i 's/for parallel code" OFF/for parallel code" ON /g' CMakeLists.txt && \
PYTHON_EXECUTABLE=/opt/conda/bin/python \
PYTHON_LIBRARY=/opt/conda/lib/libpython3.6m.so \
PYTHON_INCLUDE_DIR=/opt/conda/include/python3.6m \
FULL_CAFFE2=1 \
USE_OPENMP=1 \
USE_MKL=1 \
USE_MKLDNN=1 \
USE_MKLML=1 \
USE_SYSTEM_EIGEN_INSTALL=1 \
USE_ZMQ=1 \
USE_DISTRIBUTED=1 \
BUILD_TEST=0 \
# MKLDNN_LIBRARY="" \
# MKLDNN_INCLUDE_DIR="" \
# MKLDNN_LIB_DIR="" \
MKLDNN_LIBRARY=/usr/local/lib \
MKLDNN_INCLUDE_DIR=/usr/local/include \
MKLDNN_LIB_DIR=/usr/local/lib \
# CFLAGS=" -w -g -O3 -m64 -fno-gnu-unique -I${MKLROOT}/include -I/usr/include -fno-optimize-sibling-calls -mavx -msse3 -msse4.1 -msse4.2 -msse2 -mfpmath=sse " \
python setup.py install && \
cd /opt && rm -rf /opt/pytorch && \
cd /usr/lib && sudo ldconfig

Environment

PyTorch Version (e.g., 1.0): Master branch (1.0)

OS (e.g., Linux): Debian:Stretch

How you installed PyTorch (conda, pip, source): source

Build command you used (if compiling from source): see above

Python version: 3.6

CUDA/cuDNN version: N/A

GPU models and configuration: N/A

Any other relevant information: N/A