Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/13689
Now that typeid.h lives in c10/util, the include paths should reflect that.
Reviewed By: ezyang
Differential Revision: D12912237
fbshipit-source-id: e54225f049f690de77cb6d5f417994b211a6e1fb
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/12180
I had to fix a lot of call sites, because a lot of places assume that
you can actually get a const vector&, and if the internal representation
of sizes in a tensor is NOT a vector, it's not possible to fulfill
this API contract.
Framework changes:
- I deleted TensorImpl::dims(); caffe2::Tensor::dims() just forwards to
sizes() now.
- De-templatized SetDims; now it is an explicit list of ArrayRef and
variadic overloads. This makes implicit conversions work again,
so I don't need to explicitly list the std::vector cases too.
- As a knock-on effect, this causes Reset() to accept at::IntList as well as
const std::vector<int64_t>&
- Edited variadic overloads of SetDims to all forward to the underlying
arbitrary-dim implementation, reducing code duplication. (It's probably
marginally less efficient in the new world.)
- Replace Tensor constructor accepting const std::vector<int64_t>& with at::IntList
- Make MKLTensor accept ArrayRef along with vector in constructor and
Reset (unfortunately, no implicit conversions here, since it's templated on
index type.)
- There are a few other places, like cudnn, where I changed functions
that previously took const std::vector<int64_t>& to take at::IntList
instead.
Classification of call site changes:
- 'const std::vector<int64_t>& x_dims = x.dims()' ==>
'at::IntList x_dims = x.dims()'
- 'std::vector<int64_t> x_dims = x.dims()' ==>
'std::vector<int64_t> x_dims = x.dims().vec()' (we need a copy!)
Usually this is because we're about to mutably modify the vector
to compute some new dimension. However, it also very commonly occurs in the
form: 'x_dims_ = x.dims()' because we frequently cache sizes in operators.
- Instead of constructing std::vector<int64_t>{blah, blah}, construct an
at::IntList directly
ArrayRef changes:
- cbegin()/cend() iterators, they operate the same aas begin()/end() because
everything on ArrayRef is const.
- Moved operator<< into ArrayRef.h, so that it's always available when
working with ArrayRef. I also templated it, so it now works on an
ArrayRef of any type.
- Add operator== overload for ArrayRef, and also add variants to permit
comparison of ArrayRef with std::vector, a very common operation.
(The non-templated version of operator== can get these automatically
via implicit conversion, but with templates C++ refuses to do
any explicit conversions.)
I'm planning to audit all dims() call sites to make sure they don't
expect 'auto x = t.dims()' to give you an x whose lifetime can validly
outlive the tensor.
I opted not to do a dims() to sizes() rename, because dims() also matches
the protobufs accessor. Bad news!
Reviewed By: jerryzh168
Differential Revision: D10111759
fbshipit-source-id: a2a81dc4b92c22ad4b3b8ef4077a7e97b6479452
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/12029
In order to remove New() function in StaticContext(to remove StaticContext) and converge to the Allocator design, we'll first change the return type of New to at::DataPtr.
Reviewed By: ezyang
Differential Revision: D9889990
fbshipit-source-id: 3257c763530b987025f428741bdd2e089d11bad4
Summary:
TSIA. Right now we should basically use C10_EXPORT and C10_IMPORT for explicitly marking dllexport and dllimport, as a continued effort of the C10 unification.
This is a codemod by mechanically doing the following change:
CAFFE2_{EXPORT,IMPORT} -> C10_{EXPORT,IMPORT}
AT_CORE_{EXPORT,IMPORT} -> C10_{EXPORT,IMPORT}
Pull Request resolved: https://github.com/pytorch/pytorch/pull/12019
Reviewed By: ezyang, teng-li
Differential Revision: D10016276
Pulled By: Yangqing
fbshipit-source-id: a420d62c43d1110105fc88f9e9076e28a3203164
Summary:
Let's run CI tests to see what fails given the changes that just landed in https://github.com/pytorch/pytorch/pull/10624
cc mingzhe09088 ezyang Yangqing
Pull Request resolved: https://github.com/pytorch/pytorch/pull/10692
Reviewed By: mingzhe09088
Differential Revision: D9423617
Pulled By: orionr
fbshipit-source-id: 3bda1f118d13f8dd8e823727c93167cae747d8cf
Summary:
Exposed by UBSAN:
```lang=bash
caffe2/caffe2/core/qtensor.h:61:40: runtime error: load of value 190, which is not a valid value for type 'bool'
#0 0x7fb4fc09c289 in caffe2::QTensor<caffe2::CPUContext>::Resize(std::vector<int, std::allocator<int> >) caffe2/caffe2/core/qtensor.h:61
#1 0x7fb4fc090403 in caffe2::QuantizedFullyConnectedOp<float, caffe2::CPUContext, caffe2::DefaultEngine>::RunOnDevice() caffe2/caffe2/fb/operators/quantized_fully_connected_op.h:93
#2 0x7fb4fc08d5ee in caffe2::Operator<caffe2::CPUContext>::Run(int) caffe2/caffe2/core/operator.h:306
#3 0x426d8a in caffe2::QFCTest(float, float, float, int, int, int, int) caffe2/caffe2/fb/operators/quantized_fully_connected_op_test.cc:78
#4 0x4295f6 in caffe2::QuantizedFullyConnectedTest_Test_Test::TestBody() caffe2/caffe2/fb/operators/quantized_fully_connected_op_test.cc:110
#5 0x7fb4eee3b6a1 in void testing::internal::HandleExceptionsInMethodIfSupported<testing::Test, void>(testing::Test*, void (testing::Test::*)(), char const*) /home/engshare/third-party2/googletest/master/src/googletest/googletest/src/gtest.cc:2458
#6 0x7fb4eee2cbe1 in testing::Test::Run() /home/engshare/third-party2/googletest/master/src/googletest/googletest/src/gtest.cc:2475
#7 0x7fb4eee2cd27 in testing::TestInfo::Run() /home/engshare/third-party2/googletest/master/src/googletest/googletest/src/gtest.cc:2656
#8 0x7fb4eee2ce34 in testing::TestCase::Run() /home/engshare/third-party2/googletest/master/src/googletest/googletest/src/gtest.cc:2774
#9 0x7fb4eee2eb8b in testing::internal::UnitTestImpl::RunAllTests() /home/engshare/third-party2/googletest/master/src/googletest/googletest/src/gtest.cc:4649
#10 0x7fb4eee2ef3c in bool testing::internal::HandleExceptionsInMethodIfSupported<testing::internal::UnitTestImpl, bool>(testing::internal::UnitTestImpl*, bool (testing::internal::UnitTestImpl::*)(), char const*) /home/engshare/third-party2/googletest/master/src/googletest/googletest/src/gtest.cc:2458
#11 0x7fb4eee2ef3c in testing::UnitTest::Run() /home/engshare/third-party2/googletest/master/src/googletest/googletest/src/gtest.cc:4257
#12 0x7fb4fbee2ed0 in RUN_ALL_TESTS() third-party-buck/gcc-5-glibc-2.23/build/googletest/include/gtest/gtest.h:2233
#13 0x7fb4fbee2d60 in main common/gtest/LightMain.cpp:12
#14 0x7fb4e0ef7857 in __libc_start_main /home/engshare/third-party2/glibc/2.23/src/glibc-2.23/csu/../csu/libc-start.c:289
#15 0x424e08 in _start /home/engshare/third-party2/glibc/2.23/src/glibc-2.23/csu/../sysdeps/x86_64/start.S:118
UndefinedBehaviorSanitizer: invalid-bool-load caffe2/caffe2/core/qtensor.h:61:40
```
Reviewed By: yfeldblum
Differential Revision: D5898877
fbshipit-source-id: e32b1732a1946fdafaec67b3fbc072dc93bcd917
Summary:
This is in preparation for adding huge pages. There we want to remember for the pointer how we got it - via mmap() or alloc(). One option is to store gigantic map of void* -> destructor, but luckily usages of Context::New are all inside Tensor which already uses shared_ptr with custom deleter.
This diff could have used unique_ptr as the return type but then it's easy to accidentally call release() and loose the deleter. Thus going with std::pair<void*, MemoryDeleter> to be explicit.
Also, now CPUAllocator can be effectively changed to std::function. Haven't done it yet, but can do if necessary.
Let me know whether it's a bad idea to proceed like this.
Reviewed By: Yangqing
Differential Revision: D5429830
fbshipit-source-id: 8382ab7b81592d51272056c05c122894bb203827
