Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18131
ghimport-source-id: 473dae70f6c236d317bec77d894310c0aa0376ec

Stack from [ghstack](https://github.com/ezyang/ghstack

):
* **#18131 Copy-edit CONTRIBUTING and update.**

Signed-off-by: Edward Z. Yang <ezyang@fb.com>

Differential Revision: D14505049

fbshipit-source-id: 02aeae33c0049889243c56dd0d761487dac2351e

Summary:
fixes #18057 according to colesbury 's suggestion. Thanks!
cc: ezyang
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18168

Differential Revision: D14520953

Pulled By: ailzhang

fbshipit-source-id: 970e6cfb482d857a81721ec1d0ee4a4df84a0450

Summary:
Further breakup test_misc.h. The remaining tests don't directly map to a jit file so I left them in test_misc.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18191

Differential Revision: D14533442

Pulled By: eellison

fbshipit-source-id: 7f538ce0aea208b6b55a4716dfcf039548305041

Summary:
Documents the serialization format for `torch.jit.save`. Some of the info is copied from houseroad's internal doc.

[Formatted Markdown](https://github.com/driazati/pytorch/blob/serial_docs/torch/csrc/jit/README.md)

Also refactors the readme to have a heading hierarchy + table of contents
Pull Request resolved: https://github.com/pytorch/pytorch/pull/17951

Differential Revision: D14531644

Pulled By: driazati

fbshipit-source-id: cbcd9462054cc9f8a2f8cea2c98d8aba4e7d227c

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18193
ghimport-source-id: 540859cf0b238a9832f45b3f4c2351e3343fc1a2

Stack from [ghstack](https://github.com/ezyang/ghstack

):
* **#18193 Turn on Travis builds for ghstack PRs.**

Signed-off-by: Edward Z. Yang <ezyang@fb.com>

Differential Revision: D14529945

fbshipit-source-id: 4476e996e311a04f2a997ca9b7c4cf2157dd6286

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18195
ghimport-source-id: 05102cb115c6bd6d141f51905e20155bcd79a908

Stack from [ghstack](https://github.com/ezyang/ghstack):
* **#18195 [build] do not throw when unicode is seen in pull request info**

Differential Revision: D14529707

fbshipit-source-id: 2f6a31b01b3a9b044fd24be466cc5325b70929ad

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18192
ghimport-source-id: 9523a09d7ec202ef08cf0ecdf48c42739ea6b0ce

Stack from [ghstack](https://github.com/ezyang/ghstack

):
* **#18192 Delete bugbear from Python 2 lint.**

Signed-off-by: Edward Z. Yang <ezyang@fb.com>

Differential Revision: D14529240

fbshipit-source-id: 1a433b53dd38d1c455e8c0750d97c594ac51ef09

Summary:
The type of each `initial_ivalue` is completely known at some point but that information is discarded by the time a call to it is emitted. This PR is kind of a hack, as a better (longer) solution, the method should know about the type of each initial value.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18156

Differential Revision: D14525768

Pulled By: driazati

fbshipit-source-id: 52d53e9711a07a4551c988bd95fe997e654aa465

Summary:
fixes https://github.com/pytorch/pytorch/issues/18078
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18079

Reviewed By: ezyang

Differential Revision: D14521192

Pulled By: zou3519

fbshipit-source-id: cec773a3a6f2c405a0d9701e213b7caf81649181

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18138
ghimport-source-id: be62a71ef98714e6f168a00f84120f612363528e

Stack from [ghstack](https://github.com/ezyang/ghstack

):
* **#18138 Enable flake8-bugbear line length checking.**

flake8-bugbear's line length checker (B950) which permits violations
of up to 10% but specifies the "true" limit when you go over.

I had to ignore a bunch of flake8-bugbear's other checks when I
turned this on.  They're good checks though (they're turned on
in fbcode) and we should fix them eventually.

Signed-off-by: Edward Z. Yang <ezyang@fb.com>

Reviewed By: salexspb

Differential Revision: D14508678

fbshipit-source-id: 2610ecc0dd43cc0788d77f4d024ebd85b26b8d41

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18146
ghimport-source-id: 4b061c27c5c44ef0d06066490ed16cab3d0c7a64

Stack from [ghstack](https://github.com/ezyang/ghstack):
* **#18146 [jit] fix bug in alias analysis**

We handled hasWriters() incorrectly in the case of wildcards. There's
even a comment describing the correct behavior. Sad!

Much thanks to t-vi for tracking this down and suggesting the fix!

Differential Revision: D14524208

fbshipit-source-id: 8010b54257241bd64013a0d0a8b6e7d22d8c70af

Summary:
Changelog:
- Incorporate a simple backend check in the linearSolveCheckInputs function in LinearAlgebraUtils.h
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18116

Differential Revision: D14504469

Pulled By: soumith

fbshipit-source-id: 7402b6dbaa8d73048946613b806d54f68bcbd8f4

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18123

the motivation of this fix is to resolve things like:
for(auto i = 0; i < N; i++) where N is bigger than int32

These instances of comparison were found by enabling -Wsign-compare

There are way too many things to fix, so issuing this as a series of fixes

The plan is to fix all these issues and then enable this flag into Caffe2 to catch future instances

Reviewed By: ZolotukhinM

Differential Revision: D14497094

fbshipit-source-id: bca3927a2188bd33a508fa503ba221c220cdaefe

Summary:
The momentum buffer is initialized to the value of
d_p, but the current code takes the long way to do this:
1. Create a buffer of zeros
2. Multiply the buffer by the momentum coefficient
3. Add d_p to the buffer

All of these can be collapsed into a single step:
1. Create a clone of d_p
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18114

Differential Revision: D14509122

Pulled By: ezyang

fbshipit-source-id: 4a79b896201d5ff20770b7ae790c244ba744edb8

Summary:
In aten we have a _fused_dropout implementation for CUDA case. As ngimel suggested if we discard it in JIT AD, it hurts performance.

It doesn't seem ideal to include backend specific implementation in AD, but this is helpful to prevent performance regression atm.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/17756

Differential Revision: D14368999

Pulled By: ailzhang

fbshipit-source-id: 9a371c5020f630e8f6e496849ec9772b6f196169

Summary:
Addresses #15738, using fritzo's suggestion. This adds a `torch._sample_dirichlet` method in `Distributions.cpp` and `Distributions.cu`.
 - For CPU, this leads to no perf hit since all we do is to promote the `alpha` to double when getting the gamma samples (the gamma sampler anyways uses `accscalar_t`(double for CPU)) and cast it back to float32 on return.
 - I have added an analogous method for CUDA as well, but the default sampler for CUDA uses scalar_t for efficiency, so I have kept it as that. With this, I do not see the bias towards 1 as reported in #15738 with `float32`, but there is a spurious mode at 0.5, as would be expected. Users would need to explicitly use `float64` for GPU to not see the spurious mode at 0.5. (EDIT: see note below, it appears that the bias issue is still there for certain builds).

Added some tests and checked that there is no perf regression. My experience with C++ is very limited, so apologies in advance if I missed something basic. cc. ailzhang, fritzo, fmassa
Pull Request resolved: https://github.com/pytorch/pytorch/pull/17488

Differential Revision: D14410301

Pulled By: ezyang

fbshipit-source-id: 62b2f694b4642685eab06db96d74ce28e05c3992

Summary:
It's wrong and unused.  Use one of the many other constructors instead :).
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18137

Differential Revision: D14508364

Pulled By: gchanan

fbshipit-source-id: 19c6ff78ad9d9221d0874425edd02b78627c4ca7

Summary:
There are multiple backends for a device type, so we just kill this function.
Also, kill an getNonVariableType instance which was also underspecified.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18135

Differential Revision: D14507474

Pulled By: gchanan

fbshipit-source-id: fc791a76d4b851b23d09a070725f3838621eb13d

Summary:
This gets rid of 'aten_sparse' which was used at one time with legacy THS code, but is now only overloaded in native_parse.py.
The way that 'aten_sparse' worked was wonky -- it extended all backends (default [CPU, CUDA]) to include sparse.
But this is totally unnecessary; we already have the backends we need to generate for from type_method_definition_dispatch.

codegen changes: https://github.com/gchanan/pytorch/blob/fc37c8e171b7ebd1b1755469cf6a146a2abedc13/diff.txt
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18144

Reviewed By: ezyang

Differential Revision: D14511324

Pulled By: gchanan

fbshipit-source-id: 8bb4ac4cf0985f8756790779a22bc229e18e8e7f

Summary:
Fix #16428 by correcting type of 'swap' from `float` to `bool`
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18115

Differential Revision: D14516615

Pulled By: ezyang

fbshipit-source-id: c61a45d533f3a443edf3c31c1ef3d9742bf46d2b

Summary:
Observed that when there is no GPU support available `workspace `sets `GetGpuPeerAccessPattern `to `[]` in
https://github.com/pytorch/pytorch/blob/master/caffe2/python/workspace.py#L79
and this case is not handled in https://github.com/pytorch/pytorch/blob/master/caffe2/python/data_parallel_model.py#L1065.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/17974

Differential Revision: D14517066

Pulled By: ezyang

fbshipit-source-id: 186911d95c07e9a55ab82a41d0c7c919e4281bb4

Summary:
Maratyszcza harouwu yinghai

This is broken since #13065. `c_str()` returns a pointer that isn't permanent.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18109

Differential Revision: D14516622

Pulled By: ezyang

fbshipit-source-id: 7113d92eac4f61479c4c7b323cf78cc8aa00b17e

Summary:
There are some line breaks in schema_string of Declarations.yaml.
Is this valid yaml? I am reading yaml-spec.
It seems that the “|” indicator or single/double quote is required to insert line-break.
https://yaml.org/spec/1.2/spec.html
![image](https://user-images.githubusercontent.com/2469618/54405834-1e53ac80-471b-11e9-9925-be13a109eb46.png)
Could you increase line-width of yaml to avoid newline?
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18050

Differential Revision: D14516694

Pulled By: ezyang

fbshipit-source-id: 1db9f3bf131b54a783d668de973915892603189e

Reviewed By: yns88

fbshipit-source-id: eeeec4229e05916f2c17e525aee5ac4465ef52db

Summary:
delete unnecessary file .gitkeep in /pytorch/tree/master/torch/csrc/nn
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18136

Differential Revision: D14516584

Pulled By: ezyang

fbshipit-source-id: a7555693cb3df1c5e37fcd3ca9bb379a2258f2d1

Summary:
Allows serialization/loading of attributes (`IValue`s of any type).
* metadata (attribute name, type) is stored in the `model.json`
* The binary format is a subset of the `pickle` module that supports the operations necessary for `IValue`s
    * Attributes are serialized in the order they are defined on a module to a list in a single `attributes` file, with submodule attributes coming first. This order directly matches the order attributes are listed in `model.json`
    * This can be inspected in Python with `pickle.load()` or with `pickletools` (PyTorch need not be installed for this to work)
        * A class is used to store a tensor's index into the tensor table of the model, so to unpickle the file you have to use a custom Unpickler:
        ```python
        class TensorID(object):
            def __setstate__(self, id):
                self.id = id

        class JitUnpickler(pickle.Unpickler):
            def find_class(self, module, name):
                if module == '__main__' and name == 'TensorID':
                    return TensorID

        JitUnpickler(open("my_model/attributes.pkl", "rb")).load()
        ```
    * pickle format: https://svn.python.org/projects/python/trunk/Lib/pickletools.py
* It currently does not support/guarantee that anything saved out with `pickle` (i.e. if you edit `attributes` with `pickle` directly) instead of our tools will be imported correctly

Also will fix #17683 and fix #16367

Followup Work:
* document format / choice of pickle: #17951
* create an example
* list specializations
* int size specializations, large binputs
* do a first pass over attributes to output only necessary `BINPUT` ops
* attribute reassignment (e.g `self.my_attribute = new_value`)
* `tensor.save("some_checkpoint.pkl")` support with tensors embedded in Pickle file
Pull Request resolved: https://github.com/pytorch/pytorch/pull/17423

Differential Revision: D14470965

Pulled By: driazati

fbshipit-source-id: 6a21a9939efdbe59b4bc57fd31d6d630bab5297e

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18141

VLEN should've been 32

Reviewed By: jianyuh

Differential Revision: D14510780

fbshipit-source-id: ddf12746e1c69677a268432432ddb088cc210084

Reviewed By: yns88

fbshipit-source-id: ed297c07c681f5f45d3f99edf48680015ca5b138

Summary:
Changelog:

- Renames `gesv` to `solve` to remain consistent with `cholesky_solve`.
- Rename all tests, fix callsites
- Create a tentative alias for `solve` under the name `gesv`, and add a deprecated warning to not promote usage.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18060

Differential Revision: D14503117

Pulled By: zou3519

fbshipit-source-id: 99c16d94e5970a19d7584b5915f051c030d49ff5

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18107

Pull Request resolved: https://github.com/pytorch/translate/pull/396

also:

1. fix issues with OptionalType not having a createWithContainedType (PyTorch diff)
2. Delete tests for ONNX full beam search export (nobody is using it and it just makes things harder. Currently ONNX doesn't support `_unwrap_optional`)

Reviewed By: jmp84

Differential Revision: D14483771

fbshipit-source-id: 0e37ef1cb5a16d03a535eef808b0488b98802128

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/17240

Added circular padding in addition to zero padding to Conv1D, Conv2D and Conv3D based on the solution suggested in: https://github.com/pytorch/pytorch/issues/3858

Reviewed By: ezyang

Differential Revision: D14126416

fbshipit-source-id: a2f1587503ee0cfff98d5cb0d5b0a600ef8aaeb4

Summary:
...because gcc will have failures with very strange error messages
if you do.

This affects people with Debian/Ubuntu-provided NVCC, the PR should
not change anything for anyone else.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18127

Differential Revision: D14504386

Pulled By: soumith

fbshipit-source-id: 1aea168723cdc71cdcfffb3193ee116108ae755e

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18121
ghimport-source-id: 70c273bfbcb68f7b25cf87f5614c662960864758

Stack from [ghstack](https://github.com/ezyang/ghstack):
* **#18121 [jit] fix double free in test_jit**

These definitions used to be in anonymous namespace so they weren't exported from the translation unit. #18071 put those in a `test` namespace so I guess they were getting their destructors called twice on exit somehow. Making them static again fixes the problem.

Reviewed By: ezyang

Differential Revision: D14498349

fbshipit-source-id: f969781695dcbebdfcfce667fce5b986222a373e

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18059

Replace resize_dim() with set_sizes_and_strides() in `THTensor_(squeeze)` in aten/src/TH/generic/THTensor.cpp and `THCTensor_(squeeze)` in aten/src/THC/generic/THCTensor.cpp

Reviewed By: ezyang

Differential Revision: D14471066

fbshipit-source-id: 1c8c412ff09246c4df6843736e3bf0279bfadea8

Summary:
sphinx doesn't understand hyphen. it does not merge the two halves together in html.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18118

Differential Revision: D14498012

Pulled By: mrshenli

fbshipit-source-id: d6f4cfddc0a8e3a8f91578da43c26ca9c6fff3ce

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18073
ghimport-source-id: f4dadebafa0423c4c5a0e46c15b38129402d830a

Stack:
* #18072 properly device_guard IndexTensor and BoolTensor.
* **#18073 Change one_hot from IndexTensor to Tensor.**

There is no codegen change.

Reviewed By: ezyang

Differential Revision: D14485248

fbshipit-source-id: ee2ba8e5dcbbbaf0214a026c8e7ed4e6712becb0

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18072
ghimport-source-id: 9653731602c72f299e095dd50e3afe6bcc8b01d6

Stack:
* **#18072 properly device_guard IndexTensor and BoolTensor.**
* #18073 Change one_hot from IndexTensor to Tensor.

Currently IndexTensor and BoolTensors do not have device_guards applied to them.
This is bad in the case where the only tensor(s) are IndexTensors or BoolTensors, because no device guard is present.

The only case this currently happens is with one_hot which ends up not mattering because of the way the implementation is written.  But I wanted to make sure we are covered here.

Reviewed By: ezyang

Differential Revision: D14485249

fbshipit-source-id: e57b28086fa1ad2fdd248bb1220e8a2e42da03e1

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18093
ghimport-source-id: 021adc52aa7bfe5fff74531c76a8cd28cab30b2a

Stack:
* **#18093 [jit] fix corner case for optional aliasing**

Occasionally the compiler can insert constant Nones to make types line
up. In that case, don't try to make a pointer from the optional type to
None, since we know statically that None won't be mutated or whatever.

Reviewed By: shannonzhu

Differential Revision: D14493004

fbshipit-source-id: 6564065f39d99ee5af664f3a0fe235892973d9be

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18089

Typo fix for the fully connected layer documentation.

Reviewed By: jspark1105

Differential Revision: D14488632

fbshipit-source-id: ca0271ca0250c1d653ed7f250e8588f7b2ce1056

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18040

Add flag to fails if float point exceptions is detected in operator runs

Sample exception

Exception [enforce fail at operator.h:837] !std::fetestexcept(FE_DIVBYZERO). Division by zero floating point exception (FE_DIVBYZERO) reported.
Error from operator:
input: "1" input: "0" output: "out" name: "" type: "Div"

Reviewed By: jspark1105

Differential Revision: D14467731

fbshipit-source-id: fad030b1d619a5a661ff2114edb947e4562cecdd