Lu Fang [Fri, 29 Mar 2019 06:44:20 +0000 (23:44 -0700)]
update of fbcode/onnx to
fb1a80692c1ab0bd27b1072f2e7bffacba336777 (#18585)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18585
Previous import was
b29e78a4efb8e5d8995f576bbf19a846807829b6
Included changes:
- **[
fb1a8069](https://github.com/onnx/onnx/commit/
fb1a8069)**: Fix wrongly handled attribute in MVN and test generating scripts (#1877) <Raymond Yang>
- **[
b22041c3](https://github.com/onnx/onnx/commit/
b22041c3)**: Add dilation attribute to MaxPool (#1864) <karljang>
Reviewed By: zrphercule, benoitsteiner
Differential Revision:
D14668623
fbshipit-source-id:
fa7f44b1ecc949d8dd654939d20b1e93db98b1d2
Lu Fang [Fri, 29 Mar 2019 06:17:18 +0000 (23:17 -0700)]
update of fbcode/foxi to
81e1683d6348eee4b5ed1145222dc2c41be4269c (#18596)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18596
Previous import was
2bcc4064c90e87b9638615c733485f07c47b7558
Included changes:
- **[81e1683](https://github.com/houseroad/foxi/commit/81e1683)**: Merge pull request #9 from zrphercule/add_foxi_quantization <Rui Zhu>
- **[580559c](https://github.com/houseroad/foxi/commit/580559c)**: char=>uint8 <zrphercule>
- **[1a572f7](https://github.com/houseroad/foxi/commit/1a572f7)**: add quantization <zrphercule>
Reviewed By: zrphercule
Differential Revision:
D14677404
fbshipit-source-id:
09429b3bf0e7783a25b8145020e505761bad887d
Elias Ellison [Fri, 29 Mar 2019 06:07:45 +0000 (23:07 -0700)]
Delete batch tensor (#18575)
Summary:
Deleting batch tensor since we are no longer maintaining the project and keeping it functional is blocking other improvements.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18575
Differential Revision:
D14671126
Pulled By: eellison
fbshipit-source-id:
b42d5b699c4d12171ed95e6d3a977532167f0d2c
Thomas Viehmann [Fri, 29 Mar 2019 05:20:08 +0000 (22:20 -0700)]
Update NNPACK to current master (#18580)
Summary:
This fixes builds on x86 (32 bits).
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18580
Differential Revision:
D14672462
Pulled By: soumith
fbshipit-source-id:
7629b001c2bfa3e5b6ade7f1b03a8280232a4c16
Gemfield [Fri, 29 Mar 2019 04:35:17 +0000 (21:35 -0700)]
Enhance build_ios.sh to be consistent with build_android.sh (#18564)
Summary:
1, Enhance build_ios.sh to be consistent with build_android.sh;
2, Add docs for build_ios.sh.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18564
Differential Revision:
D14680752
Pulled By: soumith
fbshipit-source-id:
6d2667ed8a3c85a057a522838f5d0461dd4788cf
Hyungjoo Andrew Cho [Fri, 29 Mar 2019 03:49:43 +0000 (20:49 -0700)]
Serialization supports pathlib.Path object for the input argument (#18562)
Summary:
This will allow pathlib.Path object to the torch.load as an input argument.
Fixes #16607
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18562
Differential Revision:
D14668255
Pulled By: soumith
fbshipit-source-id:
0ae4f7c210918582912f2d1ef2a98f1ab288c540
Aurélien Roy [Fri, 29 Mar 2019 03:46:03 +0000 (20:46 -0700)]
Target and input sizes mismatch warning in L1 Loss / L1 Smooth Loss (#18565)
Summary:
Addind the same warning message already present in the mse_loss function to the L1 losses when input and target sizes are different.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18565
Differential Revision:
D14671415
Pulled By: soumith
fbshipit-source-id:
01f5e1fb1ea119dbb2aecf1d94d0cb462f284982
bddppq [Fri, 29 Mar 2019 01:07:10 +0000 (18:07 -0700)]
Resubmit PR-18512: Improved onnx export for 3 onnx ops (#18571)
Summary:
Fix ROCm CI failure
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18571
Differential Revision:
D14669323
Pulled By: bddppq
fbshipit-source-id:
022afe5c20e680295c9cfdfe1ec14650305955a8
Jeff Daily [Fri, 29 Mar 2019 00:43:22 +0000 (17:43 -0700)]
in caching allocator, ignore and clear the error if not ready
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/18584
Differential Revision:
D14675041
Pulled By: bddppq
fbshipit-source-id:
c1fab797e0d224e0a481a0395a3f9975c4265ff6
Ilia Cherniavskii [Fri, 29 Mar 2019 00:42:47 +0000 (17:42 -0700)]
Add external callbacks into RecordFunction (#17844)
Summary:
Add a way to insert external callbacks into PT's RecordFunction
Pull Request resolved: https://github.com/pytorch/pytorch/pull/17844
Differential Revision:
D14399664
Pulled By: ilia-cher
fbshipit-source-id:
76654799811fefd3ffed4abfb46ed95b492cebab
Jing Huang [Thu, 28 Mar 2019 23:58:54 +0000 (16:58 -0700)]
Implement rotated generate_proposals_op without opencv dependency (CPU version)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/18533
Reviewed By: ezyang
Differential Revision:
D14648083
fbshipit-source-id:
e53e8f537100862f8015c4efa4efe4d387cef551
Ahmed Aly [Thu, 28 Mar 2019 22:58:24 +0000 (15:58 -0700)]
Use SetOutputTensor instead of copying outputs manually (#17770)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/17770
As title
Reviewed By: dzhulgakov
Differential Revision:
D14370937
fbshipit-source-id:
f415490c38556cf03bb13dce3643775331483448
Shen Li [Thu, 28 Mar 2019 22:05:53 +0000 (15:05 -0700)]
Fix NCCL/Gloo process groups and DDP stream sync bug (#18465)
Summary:
DDP with NCCL backend uses a [worker stream](https://github.com/pytorch/pytorch/blob/
d3eb941ed96774efb8d89a0b20c9e49807ea85a7/torch/csrc/distributed/c10d/ddp.cpp#L142) to flatten grand batch
tensors, and passes the flattened tensor to [another stream](https://github.com/pytorch/pytorch/blob/
d3eb941ed96774efb8d89a0b20c9e49807ea85a7/torch/lib/c10d/ProcessGroupNCCL.cpp#L379) to
conduct ncclAllReduce. The flattened tensor has to record the
ncclAllReduce stream, otherwise multiple streams might access the
same memory space.
cc ppwwyyxx
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18465
Differential Revision:
D14613449
Pulled By: mrshenli
fbshipit-source-id:
b62773732552d12cc87b7adeb6897e9e11753ea9
Ahmed Aly [Thu, 28 Mar 2019 18:23:22 +0000 (11:23 -0700)]
Inference LSTM integration test (#18559)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18559
Adding integration test for inference LSTM
Reviewed By: houseroad
Differential Revision:
D14656698
fbshipit-source-id:
80fb2a72be30fcb695f4471b72bf9d6e3965bf81
Zachary DeVito [Thu, 28 Mar 2019 17:31:45 +0000 (10:31 -0700)]
Add Slot type to abstract the raw pointers being used for slots. (#18226)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18226
ghimport-source-id:
b9ec8651212875b30971cc6859d2ddec6559ae3a
If modules become first-class IValues, then the slots will no longer be raw pointers but (IValue, index) pairs. This commit inserts the Slot abstraction so that this change can be made in later patches.
Stack from [ghstack](https://github.com/ezyang/ghstack):
* **#18226 Add Slot type to abstract the raw pointers being used for slots.**
Differential Revision:
D14542022
fbshipit-source-id:
b81d7f4334c983d663e7551bda82df43680d7c5f
Junjie Bai [Thu, 28 Mar 2019 17:18:46 +0000 (10:18 -0700)]
Revert
D14635130: Improved onnx export for 3 onnx ops.
Differential Revision:
D14635130
Original commit changeset:
d54a2b6e2950
fbshipit-source-id:
f624e2befdde245cb88435a95508b2a8e6b12e61
Benoit Steiner [Thu, 28 Mar 2019 15:52:01 +0000 (08:52 -0700)]
Improved onnx export for 3 onnx ops. (#18512)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18512
Ceil and Floor have been supported since version 6 of ONNX: export them using the native onnx ops instead of an Aten op.
Similarly, support for the Where op has been added in version 9, so we don't need to wrap these op in an Aten op.
Reviewed By: houseroad
Differential Revision:
D14635130
fbshipit-source-id:
d54a2b6e295074a6214b5939b21051a6735c9958
Elias Ellison [Thu, 28 Mar 2019 07:09:36 +0000 (00:09 -0700)]
Revert
D14652372: [pytorch][PR] Add parsing to file check
Differential Revision:
D14652372
Original commit changeset:
7430b9d1dc2b
fbshipit-source-id:
fa3d0f68515fe53447746469844d2db20c1292e0
Ilia Cherniavskii [Thu, 28 Mar 2019 04:07:36 +0000 (21:07 -0700)]
C++17.h: forward -> c10::guts::forward (#18492)
Summary:
Use c10::guts::forward instead of forward
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18492
Reviewed By: smessmer
Differential Revision:
D14625513
Pulled By: ilia-cher
fbshipit-source-id:
8bc4e20f102fe2a107a22f3e172882d60b95ab0e
Thomas Viehmann [Thu, 28 Mar 2019 03:17:01 +0000 (20:17 -0700)]
Use __ldg for CUDA kernels in fuser (#18540)
Summary:
While benchmarking a kernel with broadcasted inputs, I noticed
that is was much slower than a hand-coded kernel for the smae task.
The kernel in question computed a * b + c for a of shape
32 x 32 x 10240 and b and c of shape 1 x 32 x 1.
This patch accellerates said kernel from 450us to 250us on my GTX1080Ti.
I didn't change half because there doesn't seem to be __ldg for
half.
An alternative could be to sprinkle const and restrict.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18540
Differential Revision:
D14657840
Pulled By: soumith
fbshipit-source-id:
408847346ec12d1d1d9b119ac50bbc70f0d9ed33
Sam Pepose [Thu, 28 Mar 2019 02:47:43 +0000 (19:47 -0700)]
Adds Cyclical Learning Rate and Momentum (#18001)
Summary:
This implements a cyclical learning rate (CLR) schedule with an optional inverse cyclical momentum. More info about CLR: https://github.com/bckenstler/CLR
This is finishing what #2016 started. Resolves #1909.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18001
Differential Revision:
D14451845
Pulled By: sampepose
fbshipit-source-id:
8f682e0c3dee3a73bd2b14cc93fcf5f0e836b8c9
Edward Yang [Thu, 28 Mar 2019 02:46:23 +0000 (19:46 -0700)]
Completely synchronize behavior of Facebook flake8 and public flake8. (#18538)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18538
ghimport-source-id:
665b09f158d1c5dd94686d4212792504b55b7f73
Stack from [ghstack](https://github.com/ezyang/ghstack):
* **#18538 Completely synchronize behavior of Facebook flake8 and public flake8.**
Previously, developers at Facebook had the very funny experience
wherein /usr/local/bin/flake8 behaved differently than a freshly
installed flake8 from pip. In this commit, I add enough ignores to
.flake8 and install enough plugins to make the Facebook flake8
and public flake8 line up exactly. These means you don't have
to care which flake8 you use; they all will report accurate information
on your Python files.
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
Differential Revision:
D14652336
fbshipit-source-id:
ba7776eaa139cf2e3df2e65349da6fd7c99acca4
Elias Ellison [Thu, 28 Mar 2019 02:21:32 +0000 (19:21 -0700)]
add slow tests annotation to some jit tests (#18545)
Summary:
Adds slow test annotation to the following very slow tests -
70.33s test/test_jit.py::TestScript::test_script_module_script_resnet
32.33s test/test_jit.py::TestBatched::test_beam_search
17.70s test/test_jit.py::TestBatched::test_greedy_search
15.58s test/test_jit.py::TestScript::test_script_module_trace_resnet18
The list of remaining slow tests is below. Let me know if you think any of the others should be added to slow tests as well. Slow tests will only run on master.
15.28s call test/test_jit.py::TestJit::test_export_batchnorm
12.96s call test/test_jit.py::TestEndToEndHybridFrontendModels::test_snli
11.65s call test/test_jit.py::TestEndToEndHybridFrontendModels::test_neural_style
6.38s call test/test_jit.py::TestJitGeneratedModule::test_nn_LocalResponseNorm_1d
5.96s call test/test_jit.py::TestJitGeneratedModule::test_nn_LocalResponseNorm_2d_uneven_pad
5.91s call test/test_jit.py::TestJitGeneratedModule::test_nn_LocalResponseNorm_3d_custom_params
4.76s call test/test_jit.py::TestJit::test_alexnet
3.82s call test/test_jit.py::TestScript::test_number_math
3.81s call test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_no_bias
3.76s call test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_groups_thnn
3.65s call test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_stride_pad1circular
3.49s call test/test_jit.py::TestBatched::test_lstm
3.33s call test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_pad2circular
3.19s call test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_stride1_pad2circular
3.11s call test/test_jit.py::TestEndToEndHybridFrontendModels::test_dcgan_models
3.11s call test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_stride_padding
3.11s call test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_stride
3.08s call test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_no_bias
3.08s call test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_stride1_pad1circular
3.07s call test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_groups
3.05s call test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_dilated
3.05s call test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_depthwise_with_multiplier
3.04s call test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_groups
3.03s call test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_dilated
3.02s call test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_depthwise_dilated
3.02s call test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_dilated_strided
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18545
Differential Revision:
D14656064
Pulled By: eellison
fbshipit-source-id:
d17ee23c3b3679276cee983555d43e83ce099356
Elias Ellison [Thu, 28 Mar 2019 01:11:45 +0000 (18:11 -0700)]
Add parsing to file check (#18304)
Summary:
This allows you to embed checks in IR, making the test more readable.
E.g.
```
graph_str = 'graph(%0 : Double(5, 5)):
# CHECK: aten::relu
%1 : Double(5, 5) = aten::relu(%0)
return (%1)'
FileCheck().run(graph_str, parseIR(graph_str))
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18304
Differential Revision:
D14652372
Pulled By: eellison
fbshipit-source-id:
7430b9d1dc2b7584704375aac02d7392ecec76a0
Elias Ellison [Wed, 27 Mar 2019 23:02:10 +0000 (16:02 -0700)]
bug fix for node with writers in create autodiff subgraph (#18491)
Summary:
Previously we were moving nodes with writers into differentiable subgraphs, without necessarily preserving whether or not they were written to. This can lead to bugs with CSE, which needs that context.
I'm not completely sure if there's anything else we can do to be more aggresive here - inline these nodes and not run CSE and just run constant pooling, or possibly something else, but I think we should land this correctness condition first and then possibly think further.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18491
Differential Revision:
D14648562
Pulled By: eellison
fbshipit-source-id:
bc1e444774ccdb708e22f0e06a477a221a231f9e
Xianjie Chen [Wed, 27 Mar 2019 21:52:13 +0000 (14:52 -0700)]
add extra info for the auto gen sum ops
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/17934
Reviewed By: iroot900
Differential Revision:
D14418689
fbshipit-source-id:
9e11e461001467f0000ea7c355d5b0f0d738fa85
Vitaly Fedyunin [Wed, 27 Mar 2019 21:44:00 +0000 (14:44 -0700)]
Clarify error text of the pin_memory function
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/18530
Reviewed By: ezyang
Differential Revision:
D14647578
Pulled By: VitalyFedyunin
fbshipit-source-id:
ddd70240d52d2e9a96e26f5a0dfea8d76fe25078
Wanchao Liang [Wed, 27 Mar 2019 21:39:33 +0000 (14:39 -0700)]
Move fast rnn benchmark to pytorch/pytorch
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/18369
Differential Revision:
D14652039
Pulled By: wanchaol
fbshipit-source-id:
1177b1f60d96672c3e2c9d527b56ee06ca7c0af1
eellison [Wed, 27 Mar 2019 21:29:45 +0000 (14:29 -0700)]
Rename isTensor api -> isCompleteTensor (#18437)
Summary:
Is Tensor has been brought up as misleading a couple times, rename it isCompleteTensor for clarity.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18437
Differential Revision:
D14605223
Pulled By: eellison
fbshipit-source-id:
189f67f12cbecd76516a04e67d8145c260c79036
Elias Ellison [Wed, 27 Mar 2019 21:28:11 +0000 (14:28 -0700)]
Const trace error v2 (#18535)
Summary:
Trying to reland https://github.com/pytorch/pytorch/pull/18298
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18535
Differential Revision:
D14652391
Pulled By: eellison
fbshipit-source-id:
699e30045dd5f14f0a2b98378272045a292e1e2a
jithunnair-amd [Wed, 27 Mar 2019 21:16:01 +0000 (14:16 -0700)]
enable more unit tests (#18537)
Summary:
Enable unit tests working with ROCm 2.3. In particular, these are unit tests where we skipped for double data types previously and some tests for multi-GPU setups.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18537
Differential Revision:
D14651822
Pulled By: ezyang
fbshipit-source-id:
7dd575504ebe235a91489866c91000e9754b1235
Min Ni [Wed, 27 Mar 2019 18:14:32 +0000 (11:14 -0700)]
Skip tests if C2/ONNX models cannot be read (#18494)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18494
Today we have some C2 end2end test run requiring reading model data from external filesystem (for example, Gluster and AWS). This could be a source for flaky test when the external filesystems are not reachable during the tests.
In this diff, we add try/catch logic around where we download models and open model files from external system. In case such attempts fails, we will catch the excption and let the unittest skip the current test instead of failure.
I also refactor the code a little bit by removing some duplicated logic on downloading and build the c2 model data. It has been duplicated in two classes and a few functions...
Reviewed By: yinghai
Differential Revision:
D14442241
fbshipit-source-id:
da8bf56c8d096efa34ca2070de5cd10a18aad70c
zrphercule [Wed, 27 Mar 2019 18:11:01 +0000 (11:11 -0700)]
Add qtensors in caffe2 protobuf argument (#18486)
Summary:
We are about to merge onnxifi quantization support soon. Before that, I would like to merge this diff seperately to make sure it doesnt break anything.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18486
Reviewed By: bddppq, houseroad
Differential Revision:
D14626419
Pulled By: yinghai
fbshipit-source-id:
504c1eae60be1e629203267b59defb8b69d82c0a
Paul O’Shannessy [Wed, 27 Mar 2019 17:55:12 +0000 (10:55 -0700)]
Generate sphinx docs with secure content. (#18508)
Summary:
There are a number of pages in the docs that serve insecure content. AFAICT this is the sole source of that.
I wasn't sure if docs get regenerated for old versions as part of the automation, or if those would need to be manually done.
cf. https://github.com/pytorch/pytorch.github.io/pull/177
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18508
Differential Revision:
D14645665
Pulled By: zpao
fbshipit-source-id:
003563b06048485d4f539feb1675fc80bab47c1b
ZhuBaohe [Wed, 27 Mar 2019 17:15:20 +0000 (10:15 -0700)]
Fix loss functions doc (#18420)
Summary:
Correct docstring display error on web page caused by my previous PR
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18420
Differential Revision:
D14642467
Pulled By: soumith
fbshipit-source-id:
16fdd3301a4c5bad27fbcd8686f7fbfcc1e908ee
Edward Yang [Wed, 27 Mar 2019 15:01:15 +0000 (08:01 -0700)]
Upgrade flake8-bugbear to master, fix the new lints. (#18507)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18507
ghimport-source-id:
1c3642befad2da78a7e5f39d6d58732b85c76267
Stack from [ghstack](https://github.com/ezyang/ghstack):
* **#18507 Upgrade flake8-bugbear to master, fix the new lints.**
It turns out Facebobok is internally using the unreleased master
flake8-bugbear, so upgrading it grabs a few more lints that Phabricator
was complaining about but we didn't get in open source.
A few of the getattr sites that I fixed look very suspicious (they're
written as if Python were a lazy language), but I didn't look more
closely into the matter.
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
Differential Revision:
D14633682
fbshipit-source-id:
fc3f97c87dca40bbda943a1d1061953490dbacf8
peter [Wed, 27 Mar 2019 14:55:48 +0000 (07:55 -0700)]
Add export annotations for functions in c10 (#18464)
Summary:
Fixes #18461.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18464
Differential Revision:
D14620963
Pulled By: ezyang
fbshipit-source-id:
c11f3967de2ac69c7140767c8fe73a85555e9f40
Li Yu [Wed, 27 Mar 2019 06:41:35 +0000 (23:41 -0700)]
Back out "Revert
D14613517: [pytorch][PR] Updating onnxtrt submodule to master branch" (#18514)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18514
Original commit changeset:
d6267ddfc339
Reviewed By: bddppq
Differential Revision:
D14634476
fbshipit-source-id:
2633b0b4c512d71001e5c20cd79c0c0d7856f942
Lu Fang [Wed, 27 Mar 2019 04:51:10 +0000 (21:51 -0700)]
update of fbcode/onnx to
b29e78a4efb8e5d8995f576bbf19a846807829b6 (#18503)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18503
Previous import was
c05f2ae412daf8fd64136ca354b97ccf73e0ea6c
Included changes:
- **[
b29e78a4](https://github.com/onnx/onnx/commit/
b29e78a4)**: update copyright for open governance (#1885) <Prasanth Pulavarthi>
- **[
3b0ecd55](https://github.com/onnx/onnx/commit/
3b0ecd55)**: open governance (#1881) <Prasanth Pulavarthi>
- **[
bbe28349](https://github.com/onnx/onnx/commit/
bbe28349)**: Revert "Adding Reverse op (#1804)" (#1882) <Lu Fang>
- **[
5be3e223](https://github.com/onnx/onnx/commit/
5be3e223)**: Adding Reverse op (#1804) <Peyman Manikashani>
Reviewed By: zrphercule
Differential Revision:
D14632717
fbshipit-source-id:
2637a4090e7071a59caff3a910fa4f077906bf3c
Yinghai Lu [Wed, 27 Mar 2019 03:57:18 +0000 (20:57 -0700)]
Move weight offload inside backend construction functor (#18385)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18385
By moving the weight offload into the backend initialization function, we can instantiate the backend once by creating the OnnxifiOp once and then clean up the parameter workspace. And we need to keep hold of that instantiated net (OnnxifiOp) without cleaning it. Subsequent ctor of OnnxifiOp of the same model will hit the cached backend and they will not look into weight offloading, which is safe as the weight is already gone.
Reviewed By: ipiszy
Differential Revision:
D14590379
fbshipit-source-id:
f7f34016e09777ad3df0af487885cd14658e1044
Tongzhou Wang [Wed, 27 Mar 2019 03:55:25 +0000 (20:55 -0700)]
fix #16448 (#18479)
Summary:
Fixes #16448
bddppq
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18479
Differential Revision:
D14635360
Pulled By: ezyang
fbshipit-source-id:
4010319fbce050dd0bdf4da3cd1171b9737f3c4c
James Reed [Wed, 27 Mar 2019 03:47:23 +0000 (20:47 -0700)]
Add section about .code to docs
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/18493
Differential Revision:
D14634677
Pulled By: jamesr66a
fbshipit-source-id:
9ee065f6ce4218f725b93deb4c64b4ef55926145
Stas Bekman [Wed, 27 Mar 2019 02:56:39 +0000 (19:56 -0700)]
how to use the `ccache` package on Ubuntu (#18495)
Summary:
Added full instructions for how to use the `ccache` package. Thanks.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18495
Differential Revision:
D14635351
Pulled By: ezyang
fbshipit-source-id:
158e1052bae580e95f73644252fdbddcc0213128
peterjc123 [Wed, 27 Mar 2019 02:47:37 +0000 (19:47 -0700)]
Append c10 libs to TorchConfig.cmake (#18418)
Summary:
Fixes #18416.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18418
Differential Revision:
D14635322
Pulled By: ezyang
fbshipit-source-id:
81cb658f73583e4cd0358173617f747ebf4f7f8a
Xiang Gao [Wed, 27 Mar 2019 01:00:15 +0000 (18:00 -0700)]
Add some missing docs for tensor methods and attributes, new unittest to enforce tensors.rst no longer miss anything (#16057)
Summary:
This depend on https://github.com/pytorch/pytorch/pull/16039
This prevent people (reviewer, PR author) from forgetting adding things to `tensors.rst`.
When something new is added to `_tensor_doc.py` or `tensor.py` but intentionally not in `tensors.rst`, people should manually whitelist it in `test_docs_coverage.py`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/16057
Differential Revision:
D14619550
Pulled By: ezyang
fbshipit-source-id:
e1c6dd6761142e2e48ec499e118df399e3949fcc
Li Yu [Wed, 27 Mar 2019 00:30:17 +0000 (17:30 -0700)]
Revert
D14613517: [pytorch][PR] Updating onnxtrt submodule to master branch
Differential Revision:
D14613517
Original commit changeset:
dd20d718db55
fbshipit-source-id:
d6267ddfc339d04f182e2de1750a601c8d6bf8c6
Junjie Bai [Wed, 27 Mar 2019 00:16:23 +0000 (17:16 -0700)]
Fix direct comparison of OperatorDef proto structs (#18466)
Summary:
arguments order is okay to be different
ajyu
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18466
Differential Revision:
D14627258
Pulled By: bddppq
fbshipit-source-id:
430e1fb1bea2c5639a547ae7c1652368788c86b9
Soumith Chintala [Wed, 27 Mar 2019 00:14:26 +0000 (17:14 -0700)]
Revert
D14605905: [pytorch][PR] Add return_counts to torch.unique
Differential Revision:
D14605905
Original commit changeset:
555f5a12a8e2
fbshipit-source-id:
c7874f5987893e956c022180a37763d88bba38db
Sameer Indarapu [Tue, 26 Mar 2019 22:29:55 +0000 (15:29 -0700)]
Fix typo in Github links in elementwise_ops_schema.cc (#18018)
Summary:
s/elementwise_op_schema.cc/elementwise_ops_schema.cc
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18018
Differential Revision:
D14612291
Pulled By: soumith
fbshipit-source-id:
09276283b9ff92c039ce530165c62cc8421fb443
Tongzhou Wang [Tue, 26 Mar 2019 22:25:26 +0000 (15:25 -0700)]
Improve numerical precision of (s)logdet (#18449)
Summary:
Fixes https://github.com/pytorch/pytorch/issues/18448 and https://github.com/pytorch/pytorch/issues/18450
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18449
Differential Revision:
D14611638
Pulled By: soumith
fbshipit-source-id:
4f1f27ab5316a92d2783e734169f599afed743cf
Soumith Chintala [Tue, 26 Mar 2019 22:23:43 +0000 (15:23 -0700)]
fix arange shape issue inconsistency across cpu and cuda (#18462)
Summary:
Fixes https://github.com/pytorch/pytorch/issues/18363
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18462
Differential Revision:
D14620263
Pulled By: soumith
fbshipit-source-id:
223524cdda2f5d55c2ca8d4cdcf6f7a05a6c15eb
Kevin Chen [Tue, 26 Mar 2019 21:15:39 +0000 (14:15 -0700)]
Updating onnxtrt submodule to master branch
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/18441
Differential Revision:
D14613517
Pulled By: bddppq
fbshipit-source-id:
dd20d718db55942df9cce7acd1151d6902bc57ff
BowenBao [Tue, 26 Mar 2019 20:00:29 +0000 (13:00 -0700)]
Minor fix for onnx ConstantOfShape export (#18199)
Summary:
Set value as tensor of 1 element instead of scalar, according to ONNX spec.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18199
Reviewed By: dzhulgakov
Differential Revision:
D14542588
Pulled By: houseroad
fbshipit-source-id:
70dc978d870ebe6ef37c519ba4a20061c3f07372
Xiang Gao [Tue, 26 Mar 2019 19:33:09 +0000 (12:33 -0700)]
Namedtuple return for solve, slogdet, sort, topk (#17093)
Summary:
More ops for https://github.com/pytorch/pytorch/issues/394. ~~Also need to rebase after landing #16186, because we need to update the whitelist of the new unit test added in #16186.~~
cc: ezyang
Pull Request resolved: https://github.com/pytorch/pytorch/pull/17093
Differential Revision:
D14620068
Pulled By: ezyang
fbshipit-source-id:
deec5ffc9bf7624e0350c85392ee59789bad4237
Sebastian Messmer [Tue, 26 Mar 2019 19:29:02 +0000 (12:29 -0700)]
Expose c10 operators to caffe2 by operator name (#18160)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18160
When exposing a c10 operator to the caffe2 frontend, don't use the operator schema but use the operator name instead.
This allows us to get rid of the existing mechanism for operator schema registration in a diff stacked on top.
Reviewed By: dzhulgakov
Differential Revision:
D14513420
fbshipit-source-id:
6b08a9c6d9497eaf18b62361dd44bc07c7b4b76b
Edward Yang [Tue, 26 Mar 2019 19:19:14 +0000 (12:19 -0700)]
Test running a CUDA build on CPU machine. (#18242)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18242
ghimport-source-id:
b949d312a48226a34f90304162e910acee7c95cd
Stack from [ghstack](https://github.com/ezyang/ghstack):
* **#18242 Test running a CUDA build on CPU machine.**
* #18362 Add ability to query if built with CUDA and MKL-DNN.
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
Differential Revision:
D14584429
fbshipit-source-id:
b54de5b33f0c795a7d9605d30576cdf9b74050fd
Edward Yang [Tue, 26 Mar 2019 19:17:31 +0000 (12:17 -0700)]
Properly use cudaGetLastError return code. (#18485)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18485
I don't know how (1) we landed the wrong version of the patch and (2) how
this passed the push blocking test
Reviewed By: pjh5
Differential Revision:
D14621961
fbshipit-source-id:
0a3953d7adcdc79727a61c2acff65f436dcafe55
Xiaomeng Yang [Tue, 26 Mar 2019 19:13:51 +0000 (12:13 -0700)]
Move math::Axpy function to elementwise lib (#18316)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18316
Move math::Axpy function to elementwise lib
i-am-not-moving-c2-to-c10
Reviewed By: houseroad
Differential Revision:
D14574697
fbshipit-source-id:
7cfbb2da295c8966c5328bd6b577cce2638eea62
Gu, Jinghui [Tue, 26 Mar 2019 17:52:52 +0000 (10:52 -0700)]
Upgrade mkldnn to version 0.18.1 (#18463)
Summary:
Upgrade mkldnn to version 0.18.1
Fix the MKLDNN build issue if linking with MKL 2019.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18463
Differential Revision:
D14620228
Pulled By: ezyang
fbshipit-source-id:
136074ad0e4631e1dde4ca1b0af4ee6a41e50913
Pat Mellon [Tue, 26 Mar 2019 17:25:01 +0000 (10:25 -0700)]
Add Google tag (#17690)
Summary:
This PR adds a Global Site Tag to the site.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/17690
Differential Revision:
D14620816
Pulled By: zou3519
fbshipit-source-id:
c02407881ce08340289123f5508f92381744e8e3
Gemfield [Tue, 26 Mar 2019 17:14:11 +0000 (10:14 -0700)]
remove redundant --install_dir parameter in GEN_COMMAND (#18473)
Summary:
remove redundant --install_dir parameter in GEN_COMMAND, since "--install_dir parameter " already contained in ${GEN_COMMAND}.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18473
Differential Revision:
D14620193
Pulled By: ezyang
fbshipit-source-id:
ee9953b5d055f4b8beb3557f95f6539051b0028a
Iurii Zdebskyi [Tue, 26 Mar 2019 16:55:50 +0000 (09:55 -0700)]
Resolving comments from Bool Tensor for CPU PR (#18165)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18165
ghimport-source-id:
55cb3fb63a25c2faab1725b4ec14c688bf45bd38
Stack from [ghstack](https://github.com/ezyang/ghstack):
* #18166 Bool Tensor for CUDA
* **#18165 Resolved comments from Bool Tensor for CPU PR**
-------
------------
This is a follow up PR that resolves some additional feedback on one the of previous Bool Tensor PRs.
gchanan, here is a list of almost all the comments from the original PR with respective fixes and replies:
**[utils/python_scalars.h]** why is this converting from uint8_t and not bool? (comment?)
When i was adding this, i was testing by creating a tensor and then calling its .tolist(). it worked for bool and uint8_t equally good so i left uint8_t as thought it makes more sense as we are calling PyBool_FromLong. �Changing it to bool.
**[ATen/Dispatch.h]**better name?.
fixed.
**[test/test_torch.py]** what about other factories, such as full? (and more).
There is a test that goes through the factory methods - test_tensor_factories_empty. i added some bool cases above it and added a comment that once CUDA will be done, i will unite them and it will iterate not just between CUDA and CPU but also all types. ��Adding all bool cases now. Will unite in CUDA PR.
**[generic/THTensorMath.h]** any changes in this file actually needed?
Bad merge. Fixed.
**[TH/THTensor.h]** this generates code for random, clampedRandom, and cappedRandom -- do we have tests for all of these with bool?
Added
**[c10/core/ScalarType.h]** I'm not very confident about the lack of Bool here -- can you look at the call sites and see what makes sense to do here?
Added bool to the macro and created a similar one without for a single case which fails the build with errors:
_./torch/csrc/jit/symbolic_variable.h:79:20: error: ambiguous overload for ‘operator*’ (operand types are ‘const torch::jit::SymbolicVariable’ and ‘torch::jit::Value*’)
return (*this) * insertConstant(rhs);_
Differential Revision:
D14605105
fbshipit-source-id:
abf82d50e8f8c50b386545ac068268651b28496d
Edward Yang [Tue, 26 Mar 2019 16:42:41 +0000 (09:42 -0700)]
Unify cudaGetDeviceCount implementations. (#18445)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18445
ghimport-source-id:
30d018737bf6989bc68b7e3676f44e0ca6141fde
Stack from [ghstack](https://github.com/ezyang/ghstack):
* #18242 Test running a CUDA build on CPU machine.
* **#18445 Unify cudaGetDeviceCount implementations.**
I went about doing this by searching for calls to cudaGetDeviceCount,
and then methodically replacing them with references to c10::cuda::device_count()
or at::cuda::device_count().
There is a point to doing this: the various implementations wildly differed
in their handling of what to do when cudaGetDeviceCount returns an error.
The final standardized behavior is that **all errors are swallowed** and
we return device count of zero. This indirectly fixes running CUDA builds
on CPU, which was broken in #17847.
I added 'noexcept' to the 'deviceCount' virtual method on DeviceGuardImpl.
This is a BC-breaking change for anyone inheriting from DeviceGuardImpl
but all you need to do is put 'noexcept' on your method and it is backwards
compatible with older libtorch.
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
Differential Revision:
D14612189
fbshipit-source-id:
3c8d186e3dd623c0e27625212c7ce30f75d943cb
Christian Puhrsch [Tue, 26 Mar 2019 16:19:51 +0000 (09:19 -0700)]
Use TensorIterator for unary operations
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/18309
Differential Revision:
D14591533
Pulled By: cpuhrsch
fbshipit-source-id:
a3b0788a481bddf1803c9f2d3289263d7364f8d7
vishwakftw [Tue, 26 Mar 2019 14:49:58 +0000 (07:49 -0700)]
Introduce SobolEngine (#10505)
Summary:
`SobolEngine` is a quasi-random sampler used to sample points evenly between [0,1]. Here we use direction numbers to generate these samples. The maximum supported dimension for the sampler is 1111.
Documentation has been added, tests have been added based on Balandat 's references. The implementation is an optimized / tensor-ized implementation of Balandat 's implementation in Cython as provided in #9332.
This closes #9332 .
cc: soumith Balandat
Pull Request resolved: https://github.com/pytorch/pytorch/pull/10505
Reviewed By: zou3519
Differential Revision:
D9330179
Pulled By: ezyang
fbshipit-source-id:
01d5588e765b33b06febe99348f14d1e7fe8e55d
Wanchao Liang [Tue, 26 Mar 2019 06:44:15 +0000 (23:44 -0700)]
fix str of autogradzero
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/18442
Differential Revision:
D14602880
Pulled By: wanchaol
fbshipit-source-id:
ebd00f9bb5f1f7e33964c10d8c9f165b7bb4985f
eellison [Tue, 26 Mar 2019 04:48:11 +0000 (21:48 -0700)]
Optimize boolean expressions & unwraps (#18259)
Summary:
Simplify or eliminate boolean and/or expressions, optimize unwrapping a value that cannot be None, and optimize using `is` with a None and a non-None value
Since peephole optimize is now introducing constants, i added another constant propagation pass after running it.
Previously i had a PR that did this & optimized shape ops - i will add the shape optimizations in a separate PR.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18259
Differential Revision:
D14602749
Pulled By: eellison
fbshipit-source-id:
1c3f5a67067d8dfdf55d7b78dcb616472ea8a267
Junjie Bai [Tue, 26 Mar 2019 03:50:49 +0000 (20:50 -0700)]
Fix python resolution in caffe2 CI scripts
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/18417
Differential Revision:
D14612704
Pulled By: bddppq
fbshipit-source-id:
0942048a9c3990afc50ce73c1fa1005c4d4097aa
Xiang Gao [Tue, 26 Mar 2019 03:36:44 +0000 (20:36 -0700)]
Support dim=None for argmax and argmin (#18264)
Summary:
Fixes: https://github.com/pytorch/pytorch/issues/18263
cc: houseroad
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18264
Reviewed By: ezyang
Differential Revision:
D14559234
Pulled By: houseroad
fbshipit-source-id:
c5b8623752d6c6af41c6d715fd9585a65294868d
Xiang Gao [Tue, 26 Mar 2019 03:30:33 +0000 (20:30 -0700)]
Add return_counts to torch.unique (#18391)
Summary:
Fixes: https://github.com/pytorch/pytorch/issues/12598
This PR was originally authorized by ptrblck at https://github.com/pytorch/pytorch/pull/15495, but since there was no update for months after the request change, I clone that branch and resolve the code reviews here. Hope everything is good now. Especially, the implementation of count is changed from ptrblck's original algorithm to the one ngimel suggest, i.e. using `unique_by_key` and `adjacent_difference`.
The currently implementation of `_unique_dim` is VERY slow for computing inverse index and counts, see https://github.com/pytorch/pytorch/issues/18405. I will refactor `_unique_dim` in a later PR. For this PR, please allow me to keep the implementation as is.
cc: ptrblck ezyang ngimel colesbury
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18391
Reviewed By: soumith
Differential Revision:
D14605905
Pulled By: VitalyFedyunin
fbshipit-source-id:
555f5a12a8e28c38b10dfccf1b6bb16c030bfdce
Natalia Gimelshein [Tue, 26 Mar 2019 02:57:06 +0000 (19:57 -0700)]
change dropout lowering in symbolic_script (#18375)
Summary:
Dropout is now eligible for fusion, and generated fused kernels are just as fast as dropout in ATen. Change its lowering in symbolic script so that it can actually be fused. Still special-cased for cuda, because without fusion this lowering is less efficient than current (bernoulli_ * input). Testing is covered by the test case that ailzhang added (test_dropout_cuda).
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18375
Differential Revision:
D14611938
Pulled By: soumith
fbshipit-source-id:
11b18f4784e6c9265e382a8f8deca7add8df3b37
Gao, Xiang [Tue, 26 Mar 2019 02:54:27 +0000 (19:54 -0700)]
Add torch.version.git_version (#18299)
Summary:
Fixes: https://github.com/pytorch/pytorch/issues/18293
cc: colesbury
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18299
Differential Revision:
D14611972
Pulled By: soumith
fbshipit-source-id:
cdb48ef37c8869713a9a43ea0da08e1bed9279a2
Xiang Gao [Tue, 26 Mar 2019 02:42:01 +0000 (19:42 -0700)]
Change deprecated IntList to IntArrayRef
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/18262
Differential Revision:
D14612244
Pulled By: ezyang
fbshipit-source-id:
5d21c7b94d64104fececcb15c6d38d9bd2a1fc70
Tongzhou Wang [Tue, 26 Mar 2019 02:17:00 +0000 (19:17 -0700)]
Enable printing to stderr for test_proper_exit for better debugging (#18458)
Summary:
related to https://github.com/pytorch/pytorch/issues/16608
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18458
Differential Revision:
D14611718
Pulled By: soumith
fbshipit-source-id:
6dc903ff2d32b9c3b76470869d1f4e9a67f706df
Karl Ostmo [Tue, 26 Mar 2019 01:01:39 +0000 (18:01 -0700)]
Don't require pygraphviz for regenerate.sh (#17485)
Summary:
closes #17336
Do not overwrite config.yml if script throws an error
Pull Request resolved: https://github.com/pytorch/pytorch/pull/17485
Differential Revision:
D14604388
Pulled By: kostmo
fbshipit-source-id:
5024545e3a8711abdbc0800911c766929dbca196
Mikhail Zolotukhin [Tue, 26 Mar 2019 00:39:01 +0000 (17:39 -0700)]
Add quant-passes stubs. (#18151)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18151
ghimport-source-id:
7d12462971bdf3e5e26a3f150f1fcad05bba1a15
Stack from [ghstack](https://github.com/ezyang/ghstack):
* #18152 Initial implementation of InsertObserverNodes pass.
* **#18151 Add quant-passes stubs.**
gh-metadata: pytorch pytorch 18149 gh/zolotukhinm@gmail.com/1/head
Differential Revision:
D14584224
fbshipit-source-id:
b3d0b5ff797160d5ad23f91f732e627b0129086c
Duc Ngo [Mon, 25 Mar 2019 23:55:30 +0000 (16:55 -0700)]
caffe2 - support flaky operator tests for caffe2 build (#18155)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18155
- Make a python decorator caffe2_flaky for caffe2 operator unit tests.
- The environment variable CAFFE2_RUN_FLAKY_TESTS are now used to mark flaky test mode
During test run,
- If flaky tests mode are on, only flaky tests are run
- If flaky tests mode are off, only non-flaky tests are run
Mark ctc_beam_search_decoder_op_test as flaky
Reviewed By: ezyang, salexspb
Differential Revision:
D14468816
fbshipit-source-id:
dceb4a48daeb5437ad9cc714bef3343e9761f3a4
iurii zdebskyi [Mon, 25 Mar 2019 22:48:11 +0000 (15:48 -0700)]
Remove unused th_scalar_type (#18390)
Summary:
th_scalar_type seems to be unused anywhere so can be removed.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18390
Reviewed By: ezyang
Differential Revision:
D14591374
Pulled By: izdeby
fbshipit-source-id:
2113aa81229cdfdfb8dc5c951ea6dea3725b8582
Ivan Ogasawara [Mon, 25 Mar 2019 21:31:43 +0000 (14:31 -0700)]
Porting CPU UpSample functions to ATen (#18020)
Summary:
This PR resolves partially #10482
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18020
Differential Revision:
D14598029
Pulled By: ezyang
fbshipit-source-id:
513e7c6438ab6d5dc3f43241e7cb724744e9a287
nihui [Mon, 25 Mar 2019 18:55:52 +0000 (11:55 -0700)]
Fix caffe2 build with BLAS=OpenBLAS (#18422)
Summary:
g++ complains about failing to find the declaration of cblas_sscal and cblas_dscal BLAS function
let's fix it :)
fedora 29, gcc 8.3.1, openblas 0.3.5
build with cmake -DBLAS=OpenBLAS ..
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18422
Differential Revision:
D14598977
Pulled By: soumith
fbshipit-source-id:
bde77bfb359d2ff38226401caeed78c114ef7468
Wanchao Liang [Mon, 25 Mar 2019 18:02:17 +0000 (11:02 -0700)]
Add addcmul, lerp to fuser, enable scalar->float specialization in symbolic script (#18081)
Summary:
This PR did two things:
1. Enable scalar->float specialization in symbolic script, so AD formula that contains scalar in the schema, should write `float` instead.
2. add addcmul, lerp to AD and fuser.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18081
Differential Revision:
D14490493
Pulled By: wanchaol
fbshipit-source-id:
b3b86d960d5f051b30733bc908b19786111cdaa4
Edward Yang [Mon, 25 Mar 2019 17:22:54 +0000 (10:22 -0700)]
Add ability to query if built with CUDA and MKL-DNN. (#18362)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18362
ghimport-source-id:
374b7ab97e2d6a894368007133201f510539296f
Stack from [ghstack](https://github.com/ezyang/ghstack):
* #18242 Test running a CUDA build on CPU machine.
* **#18362 Add ability to query if built with CUDA and MKL-DNN.**
Fixes #18108.
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
Differential Revision:
D14584430
fbshipit-source-id:
7605a1ac4e8f2a7c70d52e5a43ad7f03f0457473
svcscm [Mon, 25 Mar 2019 17:22:22 +0000 (10:22 -0700)]
Updating submodules
Reviewed By: yns88
fbshipit-source-id:
b2c5eb7dfa9048e399461c00d1103e945a30a5bc
Vitaly Fedyunin [Mon, 25 Mar 2019 17:18:29 +0000 (10:18 -0700)]
Implement reference counting for shared IPC CUDA tensors (#16854)
Summary:
This is to fix #16141 and similar issues.
The idea is to track a reference to every shared CUDA Storage and deallocate memory only after a consumer process deallocates received Storage.
ezyang Done with cleanup. Same (insignificantly better) performance as in file-per-share solution, but handles millions of shared tensors easily. Note [ ] documentation in progress.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/16854
Differential Revision:
D13994490
Pulled By: VitalyFedyunin
fbshipit-source-id:
565148ec3ac4fafb32d37fde0486b325bed6fbd1
Gregory Chanan [Mon, 25 Mar 2019 15:53:42 +0000 (08:53 -0700)]
Don't segfault on trying to get data_ptr of sparse tensor. (#18347)
Summary:
Also asserts in storage_initialized that there is a storage.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18347
Differential Revision:
D14582028
Pulled By: gchanan
fbshipit-source-id:
df3f5d181188f39e361839169fd054539c3b2839
Gregory Chanan [Mon, 25 Mar 2019 15:38:11 +0000 (08:38 -0700)]
Assert tensor isn't sparse in enforce_invariants. (#18338)
Summary:
There's no reason we can't check this, but I'm punting on implementing it for now. But it currently segfaults, so this is an improvements.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18338
Differential Revision:
D14580308
Pulled By: gchanan
fbshipit-source-id:
44d4cafeab12e1beeb3453a2d4068d221c2e9c4f
Sacha [Mon, 25 Mar 2019 14:21:37 +0000 (07:21 -0700)]
Only look for Caffe2 package when shared (#18421)
Summary:
Previously it would look for the Config even if it was not written.
Fixed #18419
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18421
Differential Revision:
D14597139
Pulled By: ezyang
fbshipit-source-id:
c212cbf5dc91564c12d9d07e507c8285e11c6bdf
Summer Deng [Mon, 25 Mar 2019 11:18:09 +0000 (04:18 -0700)]
Add more options to the quantization model exporter (#18383)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18383
Add command line options for different quantization schemes.
Reviewed By: amylittleyang
Differential Revision:
D14476862
fbshipit-source-id:
37fbf5b4c1c550121eae313f5a71d703a0a87f0f
Thomas Viehmann [Mon, 25 Mar 2019 04:26:45 +0000 (21:26 -0700)]
Revert "Specialize optional tensor inputs to graphs in the JIT (#18360)" (#18411)
Summary:
This reverts commit
7cc7ed1322405ba3c627b9c5661a330f92c4183d.
I think it's better to sort out the issues raised in #18407 firs. I'm sorry for not stopping it earlier.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18411
Differential Revision:
D14594937
Pulled By: soumith
fbshipit-source-id:
3c90b7fa7694e2f59e55607acecde4a47af801ea
Gao, Xiang [Mon, 25 Mar 2019 02:40:08 +0000 (19:40 -0700)]
Fix deprecated: type() -> scalar_type() (#18406)
Summary:
Sorry for not sending these fixes in a single PR. I found this compiler warning when I was working on something else, and I just go to GitHub and modify the file directly for convenience...
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18406
Differential Revision:
D14594180
Pulled By: soumith
fbshipit-source-id:
92f48513bc62fbe2c67c759d68830a973296e43b
Gao, Xiang [Mon, 25 Mar 2019 02:24:08 +0000 (19:24 -0700)]
Fix deprecated: type() -> scalar_type()
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/18394
Differential Revision:
D14593890
Pulled By: soumith
fbshipit-source-id:
92b9a8c22008341c0cc3b7a721bef1973c528daf
mc-robinson [Mon, 25 Mar 2019 02:17:00 +0000 (19:17 -0700)]
Added tensor size warning to F.mse_loss() (#18349)
Summary:
To address the issue of broadcasting giving the wrong result in `nn.MSELoss()` as mentioned here https://github.com/pytorch/pytorch/issues/16045 . In particular, the issue often arises when computing the loss between tensors with shapes (n, 1) and (n,)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18349
Differential Revision:
D14594176
Pulled By: soumith
fbshipit-source-id:
f23ae68a4bf42f3554ad7678a314ba2c7532a6db
Elias Ellison [Sun, 24 Mar 2019 21:28:22 +0000 (14:28 -0700)]
Fix For Requires Grad Infinite Loop (#18361)
Summary:
Previously, we would continue to run requires grad on a loop body when the outputs and inputs disagreed. This adds a check so that we don't continue running if the results haven't changed since the last run.
Fix for https://github.com/pytorch/pytorch/issues/18320
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18361
Differential Revision:
D14584332
Pulled By: eellison
fbshipit-source-id:
696b225f80a2036318540946428b525985a9e735
Soumith Chintala [Sun, 24 Mar 2019 20:11:20 +0000 (13:11 -0700)]
update magma instructions (#18410)
Summary:
fixes https://github.com/pytorch/pytorch/issues/18389
cc: stas00
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18410
Differential Revision:
D14594198
Pulled By: soumith
fbshipit-source-id:
fb46ef77a36c90ad95e47f7066f5d32aa1f1370f
Iurii Zdebskyi [Sun, 24 Mar 2019 15:17:34 +0000 (08:17 -0700)]
Removed some dead code (#18201)
Summary:
Removed some dead code.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18201
Differential Revision:
D14555251
Pulled By: izdeby
fbshipit-source-id:
f49640133ef4ae1b0306f7cec6655f23869cc6e7
Thomas Viehmann [Sun, 24 Mar 2019 05:54:36 +0000 (22:54 -0700)]
Specialize optional tensor inputs to graphs in the JIT (#18360)
Summary:
This specializes optional tensor inputs to either a DimensionedTensorType or, when None is passed,
UndefinedTensor (aka AutogradZeroTensorType).
This works because we already have different specs and thus separate plans for the two cases.
It enhances the shape analysis - because now unwrapped optional tensors will have DimensionedTensorType with appropriate shape and required grad etc.
Also, when combined with "if-pruning" (which I understand #18259 works towards), we actually get much nicer concrete graphs, too.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18360
Differential Revision:
D14590577
Pulled By: soumith
fbshipit-source-id:
cac204a506d1d38b15703cbcc67a6b75fd4979f4
Will Feng [Sat, 23 Mar 2019 19:47:15 +0000 (12:47 -0700)]
Move pyobj_ to TensorImpl (#18225)
Summary:
Currently, `THPVariable_Wrap(…)` and `THPVariable_NewWithVar(…)` depend on the existence of `pyobj_` in the autograd metadata of a Variable to convert the Variable to a Python tensor. However, after the Variable/Tensor merge, there will be Variables that don't contain autograd metadata, and to allow the conversion from non-autograd-meta Variable to a Python tensor we need to store the `pyobj_` outside of autograd metadata and in a place where it will always be available.
This PR makes it possible by moving `pyobj_` into TensorImpl, so that `THPVariable_Wrap(…)` and `THPVariable_NewWithVar(…)` can always access a Variable's `pyobj_` and convert the Variable to a Python tensor.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18225
Differential Revision:
D14562616
Pulled By: yf225
fbshipit-source-id:
18d4aaace70eee6120abaf9276036d1f8f51b18d
Xiang Gao [Sat, 23 Mar 2019 17:01:28 +0000 (10:01 -0700)]
Fix deprecated scalar type in ATen/native/Distributions.cpp
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/18265
Differential Revision:
D14577543
Pulled By: ezyang
fbshipit-source-id:
36674530b32366c51835e4073d7ba23d455d2fda
Edward Yang [Sat, 23 Mar 2019 16:33:40 +0000 (09:33 -0700)]
Revert
D14446895: [C2] Implement rotated generate_proposals_op without opencv dependency (~2x faster)
Differential Revision:
D14446895
Original commit changeset:
847f2443e645
fbshipit-source-id:
fc6ab5ee59e027f125f5ab0f7ee51ad7db37d4a4
Michael Suo [Sat, 23 Mar 2019 09:47:57 +0000 (02:47 -0700)]
Revert
D14584266: [pytorch][PR] Better error message for tensor with grad as constant in tracing
Differential Revision:
D14584266
Original commit changeset:
4e7850dadc78
fbshipit-source-id:
3bb3b5006e469edff984c16e0ff8d5dac2862d88
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