Summary:
Currently there is a mismatch in naming between Python BatchNorm `running_var` and C++ BatchNorm `running_variance`, which causes JIT model parameters loading to fail (pytorch/vision#728 (comment)):
```
terminate called after throwing an instance of 'c10::Error'
  what():  No such serialized tensor 'running_variance' (read at /home/shahriar/Build/pytorch/torch/csrc/api/src/serialize/input-archive.cpp:27)
frame #0: c10::Error::Error(c10::SourceLocation, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) + 0x85 (0x7f2d92d32f95 in /usr/local/lib/libc10.so)
frame #1: torch::serialize::InputArchive::read(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, at::Tensor&, bool) + 0xdeb (0x7f2d938551ab in /usr/local/lib/libtorch.so.1)
frame #2: torch::nn::Module::load(torch::serialize::InputArchive&) + 0x98 (0x7f2d9381cd08 in /usr/local/lib/libtorch.so.1)
frame #3: torch::nn::Module::load(torch::serialize::InputArchive&) + 0xf9 (0x7f2d9381cd69 in /usr/local/lib/libtorch.so.1)
frame #4: torch::nn::Module::load(torch::serialize::InputArchive&) + 0xf9 (0x7f2d9381cd69 in /usr/local/lib/libtorch.so.1)
frame #5: torch::nn::operator>>(torch::serialize::InputArchive&, std::shared_ptr<torch::nn::Module> const&) + 0x32 (0x7f2d9381c7b2 in /usr/local/lib/libtorch.so.1)
frame #6: <unknown function> + 0x2b16c (0x5645f4d1916c in /home/shahriar/Projects/CXX/build-TorchVisionTest-Desktop_Qt_5_12_1_GCC_64bit-Debug/TorchVisionTest)
frame #7: <unknown function> + 0x27a3c (0x5645f4d15a3c in /home/shahriar/Projects/CXX/build-TorchVisionTest-Desktop_Qt_5_12_1_GCC_64bit-Debug/TorchVisionTest)
frame #8: <unknown function> + 0x2165c (0x5645f4d0f65c in /home/shahriar/Projects/CXX/build-TorchVisionTest-Desktop_Qt_5_12_1_GCC_64bit-Debug/TorchVisionTest)
frame #9: <unknown function> + 0x1540b (0x5645f4d0340b in /home/shahriar/Projects/CXX/build-TorchVisionTest-Desktop_Qt_5_12_1_GCC_64bit-Debug/TorchVisionTest)
frame #10: __libc_start_main + 0xf3 (0x7f2d051dd223 in /usr/lib/libc.so.6)
frame #11: <unknown function> + 0x1381e (0x5645f4d0181e in /home/shahriar/Projects/CXX/build-TorchVisionTest-Desktop_Qt_5_12_1_GCC_64bit-Debug/TorchVisionTest)
```
Renaming C++ BatchNorm `running_variance` to `running_var` should fix this problem.

This is a BC-breaking change, but it should be easy for end user to rename `running_variance` to `running_var` in their call sites.
Pull Request resolved: pytorch#17371

Reviewed By: goldsborough

Differential Revision: D14172775

Pulled By: yf225

fbshipit-source-id: b9d3729ec79272a8084269756f28a8f7c4dd16b6

Summary:
Tracing models which attempts to return this in-place value doesn't turn out well.

I haven't run any tests to confirm the results to be honest, but regardless of the outcome, the operation happens in-place, so it should work as before.

Sample output from traced model attempting to set `max_norm` on `Embedding`:
```
a leaf Variable that requires grad has been used in an in-place operation. (check_inplace at /pytorch/torch/csrc/autograd/VariableTypeUtils.h:49)
frame #0: std::function<std::string ()>::operator()() const + 0x11 (0x7f0ecc5cc021 in /usr/local/lib/python3.7/site-packages/torch/lib/libc10.so)
frame #1: c10::Error::Error(c10::SourceLocation, std::string const&) + 0x2a (0x7f0ecc5cb8ea in /usr/local/lib/python3.7/site-packages/torch/lib/libc10.so)
frame #2: <unknown function> + 0x38ab2f (0x7f0ecb55ab2f in /usr/local/lib/python3.7/site-packages/torch/lib/libtorch.so.1)
frame #3: torch::autograd::VariableType::embedding_renorm_(at::Tensor&, at::Tensor const&, double, double) const + 0x76 (0x7f0ecb5b5966 in /usr/local/lib/python3.7/site-packages/torch/lib/libtorch.so.1)
frame #4: <unknown function> + 0x56c958 (0x7f0ecb73c958 in /usr/local/lib/python3.7/site-packages/torch/lib/libtorch.so.1)
frame #5: <unknown function> + 0x672286 (0x7f0ecb842286 in /usr/local/lib/python3.7/site-packages/torch/lib/libtorch.so.1)
frame #6: torch::jit::InterpreterState::run(std::vector<c10::IValue, std::allocator<c10::IValue> >&) + 0x22 (0x7f0ecb83d842 in /usr/local/lib/python3.7/site-packages/torch/lib/libtorch.so.1)
frame #7: <unknown function> + 0x65c6ac (0x7f0ecb82c6ac in /usr/local/lib/python3.7/site-packages/torch/lib/libtorch.so.1)
frame #8: <unknown function> + 0x3c8ab4 (0x7f0f06bc0ab4 in /usr/local/lib/python3.7/site-packages/torch/lib/libtorch_python.so)
frame #9: <unknown function> + 0x3ad2c3 (0x7f0f06ba52c3 in /usr/local/lib/python3.7/site-packages/torch/lib/libtorch_python.so)
frame #10: <unknown function> + 0x11663e (0x7f0f0690e63e in /usr/local/lib/python3.7/site-packages/torch/lib/libtorch_python.so)
<omitting python frames>
frame #39: python_call + 0x11 (0x5563c3c521c1 in uwsgi)
frame #40: uwsgi_request_wsgi + 0x100 (0x5563c3c54410 in uwsgi)
frame #41: wsgi_req_recv + 0xac (0x5563c3becabc in uwsgi)
frame #42: simple_loop_run + 0xc4 (0x5563c3c35be4 in uwsgi)
frame #43: simple_loop + 0x10 (0x5563c3c35a00 in uwsgi)
frame #44: uwsgi_ignition + 0x241 (0x5563c3c3a3a1 in uwsgi)
frame #45: uwsgi_worker_run + 0x275 (0x5563c3c3ec35 in uwsgi)
frame #46: <unknown function> + 0x8f22c (0x5563c3c3f22c in uwsgi)
frame #47: <unknown function> + 0x3c13e (0x5563c3bec13e in uwsgi)
frame #48: __libc_start_main + 0xf1 (0x7f0f138922e1 in /lib/x86_64-linux-gnu/libc.so.6)
frame #49: _start + 0x2a (0x5563c3bec16a in uwsgi)
:
operation failed in interpreter:
op_version_set = 0
def forward(self,
    input_1: Tensor) -> Tensor:
  _0 = torch.norm(self.item_embedding.weight, 2, 1, True)
  _1 = torch.div(self.item_embedding.weight, _0)
  m_weight = torch.t(_1)
  input_2 = torch.contiguous(input_1)
  weight_1 = torch.embedding_renorm_(self.item_embedding.weight, input_2, 1., 2.)
             ~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE
  x = torch.embedding(weight_1, input_2, -1, False, False)
  input_3 = torch.div(x, torch.norm(x, 2, 2, True))
  max_batch_size = ops.prim.NumToTensor(torch.size(input_3, 0))
  hx = torch.zeros([2, int(max_batch_size), 70], dtype=6, layout=0, device=torch.device("cpu"))
  _2 = [self.lstm_layer.weight_ih_l0, self.lstm_layer.weight_hh_l0, self.lstm_layer.weight_ih_l1, self.lstm_layer.weight_hh_l1]
  input_4, _3, _4 = torch.lstm(input_3, [hx, hx], _2, False, 2, 0.10000000000000001, False, False, True)
  input = torch.matmul(input_4, torch.t(self.rnn2item.weight))
  tastevec = torch.div(input, torch.norm(input, 2, 2, True))
  outputs = torch.matmul(tastevec, m_weight)
```
Pull Request resolved: pytorch#18684

Differential Revision: D14782041

Pulled By: ezyang

fbshipit-source-id: 7b2fc19b7d5b6600263644498bb728319a19f39d

Summary:
We have encountered `std::bad_cast` error when running PyTorch binary built with cxx11 abi on CentOS7, stack trace:
```
#0  0x00007fec10160207 in raise () from /lib64/libc.so.6
#1  0x00007fec101618f8 in abort () from /lib64/libc.so.6
#2  0x00007fec015767d5 in __gnu_cxx::__verbose_terminate_handler() () from /lib64/libstdc++.so.6
#3  0x00007fec01574746 in ?? () from /lib64/libstdc++.so.6
#4  0x00007fec01574773 in std::terminate() () from /lib64/libstdc++.so.6
#5  0x00007fec01574993 in __cxa_throw () from /lib64/libstdc++.so.6
#6  0x00007fec015c94d2 in std::__throw_bad_cast() () from /lib64/libstdc++.so.6
#7  0x00007feb2ab3c2d7 in std::__cxx11::numpunct<char> const& std::use_facet<std::__cxx11::numpunct<char> >(std::locale const&) ()
   from /root/.local/lib/python2.7/site-packages/torch/lib/libcaffe2.so
#8  0x00007feb28643d62 in torch::jit::script::strtod_c(char const*, char**) () from /root/.local/lib/python2.7/site-packages/torch/lib/libcaffe2.so
```

We are suspecting this line will get compiled to gcc abi dependent symbol:
```
char decimal_point = std::use_facet<std::numpunct<char>>(std::locale()).decimal_point();
```
Pull Request resolved: pytorch#21293

Differential Revision: D15609910

Pulled By: bddppq

fbshipit-source-id: e247059729863868e4b36d6fec4fcbc36fbc4bb1

* checkout correct branch for linting

* try #2

* try #3

* try #4

…_NATIVE_TBB to ATen/Config.h (pytorch#40211)

Summary:
Fixes pytorch#39471

Reland of pytorch#39612 pytorch#39881 pytorch#40045 pytorch#40122

Proof: [green TBB test](https://app.circleci.com/pipelines/github/pytorch/pytorch/182769/workflows/ae9f4f7a-791a-49df-9625-e2f0a51e70e7/jobs/5910591/steps)
Pull Request resolved: pytorch#40211

Reviewed By: malfet

Differential Revision: D22128537

Pulled By: pbelevich

fbshipit-source-id: 98c589405daafc2c81f76e1d5c1aef5e57065351

…ytorch#63339)

Summary:
Pull Request resolved: pytorch#63339

# Context
https://fb.workplace.com/groups/pytorch.dev/permalink/900474523864362/?comment_id=901125403799274&reply_comment_id=905023386742809

##### WHAT IS A STACK TRACE?
A stack trace (also called stack backtrace or stack traceback) is a report of the active stack frames at a certain point in time during the execution of a program.

Typically when an exception is thrown, one would expect to see the code (file:line) that threw the exception, and every intermediate frame up to and including the main function.

We are enabling android stack trace to help debugging on android devices.

Test Plan:
## Steps to test
```
buck build fbsource//xplat/caffe2/mode/aibench_pytorch_android -c pt.enable_qpl=0 -c pt.has_backtraces=1 fbsource//xplat/caffe2/fb/lite_predictor:lite_predictorAndroid#android-x86_64

one_world android emulator android-28

adb push ~/fbsource/buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictorAndroid#android-x86_64 /data/local/tmp

cd /data/local/tmp
./lite_predictorAndroid#android-x86_64

./lite_predictorAndroid#android-x86_64 --model ./detect.bc --input_dims "1,3,192,192" --input_type float --warmup 20 --iter 5 --report_pep true
```

## See how model file is not found stack traces is:

### before
```
./lite_predictorAndroid#android-x86_64 --model ./detect.bc --input_dims "1,3,192,192" --input_type float --warmup 20 --iter 5 --report_pep true

Run with 2 threads
Run with 2 threads
Loading model...
terminating with uncaught exception of type c10::Error: open file failed, file path: ./detect.bc
Exception raised from RAIIFile at xplat/caffe2/caffe2/serialize/file_adapter.cc:13 (most recent call first):
(no backtrace available)
Aborted
```

### after
```
134|generic_x86_64:/data/local/tmp $ ./lite_predictorAndroid#android-x86_64 --model ./detect.bc --input_dims "1,3,192,192" --input_type float --warmup 20 --iter 5 --report_pep true
Run with 2 threads
Run with 2 threads
Loading model...
terminating with uncaught exception of type c10::Error: open file failed, file path: ./detect.bc
Exception raised from RAIIFile at xplat/caffe2/caffe2/serialize/file_adapter.cc:13 (most recent call first):
 frame #0       c10::get_backtrace(unsigned long, unsigned long, bool)[0x59494274f10e]
 frame #1       [0x5949427b1eee]
 frame #2       [0x5949427b1eb2]
 frame #3       [0x5949427b1cdc]
 frame #4       std::__ndk1::function<std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > ()>::operator()() const[0x5949427afc34]
 frame #5       c10::Error::Error(c10::SourceLocation, std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> >)[0x5949427b05b1]
 frame #6       c10::detail::torchCheckFail(char const*, char const*, unsigned int, std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > const&)[0x5949427aca5f]
 frame #7       caffe2::serialize::FileAdapter::RAIIFile::RAIIFile(std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > const&)[0x5949426b37b2]
 frame #8       caffe2::serialize::FileAdapter::FileAdapter(std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > const&)[0x5949426b3903]
 frame #9       torch::jit::_load_for_mobile(std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > const&, c10::optional<c10::Device>, std::__ndk1::unordered_map<std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> >, std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> >, std::__ndk1::hash<std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > >, std::__ndk1::equal_to<std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > >, std::__ndk1::allocator<std::__ndk1::pair<std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > const, std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > > > >&)[0x5949422737bd]
 frame #10      torch::jit::_load_for_mobile(std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > const&, c10::optional<c10::Device>)[0x594942273769]
 frame #11      benchmark(std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > const&, int, std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > const&, std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > const&, std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > const&, bool, int, int, int, bool, int, bool, int, double, bool, bool, bool, std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > const&)[0x59494189b21d]
 frame #12      main[0x594941882aff]
 frame #13      __libc_init[0x7b699d08578d]
```

### what we get for os:linux
```
(base) [[email protected] /data/users/pavithran/fbsource] ./buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictor --model ./detect.bc --input_dims "1,3,192,192" --input_type float --warmup 20 --iter 5 --report_pep true
Run with 24 threads
Run with 24 threads
Loading model...
terminate called after throwing an instance of 'c10::Error'
  what():  open file failed, file path: ./detect.bc
Exception raised from RAIIFile at xplat/caffe2/caffe2/serialize/file_adapter.cc:13 (most recent call first):
frame #0: ./buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictor() [0x20cb7fe]
frame #1: ./buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictor() [0x20cb6c6]
frame #2: std::function<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > ()>::operator()() const + 0x54 (0x20ca4e4 in ./buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictor)
frame #3: c10::Error::Error(c10::SourceLocation, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >) + 0x57 (0x20ca9a7 in ./buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictor)
frame #4: c10::detail::torchCheckFail(char const*, char const*, unsigned int, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) + 0x7a (0x20c823a in ./buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictor)
frame #5: caffe2::serialize::FileAdapter::RAIIFile::RAIIFile(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) + 0x96 (0x206f3d6 in ./buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictor)
frame #6: caffe2::serialize::FileAdapter::FileAdapter(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) + 0x42 (0x206f502 in ./buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictor)
frame #7: torch::jit::_load_for_mobile(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, c10::optional<c10::Device>, std::unordered_map<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::hash<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > >, std::equal_to<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > >, std::allocator<std::pair<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > > > >&) + 0x30 (0x1be826c in ./buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictor)
frame #8: torch::jit::_load_for_mobile(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, c10::optional<c10::Device>) + 0x35 (0x1be8214 in ./buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictor)
frame #9: benchmark(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, int, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, bool, int, int, int, bool, int, bool, int, double, bool, bool, bool, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) + 0x16d (0x12093ad in ./buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictor)
frame #10: main + 0x25c (0x11f933c in ./buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictor)
frame #11: __libc_start_main + 0x105 (0x7fc7b9f2ed95 in /usr/local/fbcode/platform009/lib/libc.so.6)
frame #12: _start + 0x2a (0x11f902a in ./buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictor)

Aborted (core dumped)
````

Reviewed By: dhruvbird

Differential Revision: D30135947

fbshipit-source-id: f50c634ef4545843305cad4b4a14a8776b1aec76

Summary:
Pull Request resolved: pytorch#66009

Fixes
```
test_trace_c10_ops (jit.test_tracer.TestTracer) ... third-party-buck/platform009/build/eigen/include/Eigen/src/Core/Block.h:374:24: runtime error: applying non-zero offset 4 to null pointer
    #0 0x7f5228f72227 in Eigen::internal::BlockImpl_dense<Eigen::Map<Eigen::Array<float, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, false, true>::BlockImpl_dense(Eigen::Map<Eigen::Array<float, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> >&, long, long, long, long) third-party-buck/platform009/build/eigen/include/Eigen/src/Core/Block.h:374
    #1 0x7f5228f7212c in Eigen::BlockImpl<Eigen::Map<Eigen::Array<float, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, false, Eigen::Dense>::BlockImpl(Eigen::Map<Eigen::Array<float, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> >&, long, long, long, long) third-party-buck/platform009/build/eigen/include/Eigen/src/Core/Block.h:166
    #2 0x7f5228f720dc in Eigen::Block<Eigen::Map<Eigen::Array<float, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, false>::Block(Eigen::Map<Eigen::Array<float, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> >&, long, long, long, long) third-party-buck/platform009/build/eigen/include/Eigen/src/Core/Block.h:142
    #3 0x7f5229b0e059 in Eigen::DenseBase<Eigen::Map<Eigen::Array<float, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::FixedBlockXpr<internal::get_fixed_value<int>::value, internal::get_fixed_value<long>::value>::Type Eigen::DenseBase<Eigen::Map<Eigen::Array<float, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::block<int, long>(long, long, int, long) third-party-buck/platform009/build/eigen/include/Eigen/src/Core/../plugins/BlockMethods.h:98
    #4 0x7f5229b0c5ca in caffe2::GenerateProposalsOp<caffe2::CPUContext>::RunOnDevice() caffe2/caffe2/operators/generate_proposals_op.cc:348
```
Also cleans up some data type and const issues around the area.

Test Plan: Sandcastle

Reviewed By: xush6528

Differential Revision: D31343046

fbshipit-source-id: fd9096c8e47a0aad529c72fd313f64ca98dcb80b

Summary:
Pull Request resolved: pytorch/pytorch-canary#4

Pull Request resolved: pytorch#67211

Record the algorithm selection, dump it in json format and replay it. This has potential to
1. consistently repro the issue (algo selection could be sensitive to local benchmark timing)
2. manual edit the dumped json file to control algorithm selection.

Reviewed By: wushirong, 842974287

Differential Revision: D31888836

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