Summary:
local build is slow... test in CI...
Pull Request resolved: https://github.com/pytorch/pytorch/pull/26083
Differential Revision: D17346949
Pulled By: ailzhang
fbshipit-source-id: f552d1a4be55ad4e2bd915af7c5a2c1b6667c446
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/25596
Giving up on trying to limit this to just a py2 dependency
Test Plan: Imported from OSS
Differential Revision: D17171063
Pulled By: jamesr66a
fbshipit-source-id: 5df35fd128f3051dd9c6709f7d45323fedc12e65
Summary:
Currently specifying different build options in respect to the "USE_"
series is in quite a disarray. There are a lot of build options that
accept three variants: USE_OPTION, WITH_OPTION, and NO_OPTION. Some
build options only accept USE_ and NO_ variant. Some accept only USE_.
This inconsistency is quite confusing and hard to maintain.
To resolve this inconsistency, we can either let all these build options
support all three variants, or we only support the USE_ variant.
This commit makes a step to the latter choice, i.e., deprecates and sets
a date for removing the NO_ and WITH_ variants and keeps only the
USE_ variant. This is likely better than the former solution because:
- NO_ and WITH_ variants are not documented.
- CMakeLists.txt only has the USE_ variants for relevant build options
defined. It would be a surprise that when user pass these variables to
CMake during rebuild and find them ineffective.
- Multiple variants are difficult to maintain.
- The behavior is confusing if more than one variant is passed. For
example, what to be expected if one sets "NO_CUDA=1 USE_CUDA=1"?
The downside is that this will break backward compatibility for existing
build scripts in the future (if they used the undocumented build
options).
Pull Request resolved: https://github.com/pytorch/pytorch/pull/22474
Differential Revision: D16149396
Pulled By: ezyang
fbshipit-source-id: 7145b88ad195db2051772b9665dd708dfcf50b7d
Summary:
Fixes#21026.
1. Improve build docs for Windows
2. Change `BUILD_SHARED_LIBS=ON` for Caffe2 local builds
3. Change to out-source builds for LibTorch and Caffe2 (transferred to #21452)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/21190
Differential Revision: D15695223
Pulled By: ezyang
fbshipit-source-id: 0ad69d7553a40fe627582c8e0dcf655f6f63bfdf
Summary:
Add an option to setup.py to stop the build process once cmake terminates. This leaves users a chance to fine adjust build options. Also update README accordingly.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/21034
Differential Revision: D15530096
Pulled By: soumith
fbshipit-source-id: 71ac6ff8483c3ee77c38d88f0d059db53a7d3901
Summary:
I didn't update the Windows references because I wasn't sure if they apply to CUDA 9. peterjc123 what should the Windows section say?
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20718
Differential Revision: D15459276
Pulled By: colesbury
fbshipit-source-id: 917e22f8ac75378d88c962c226b5a42b6799c79a
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20726
Edward says it doesn't actually provide compilers,
but it does provide dependencies, so let's mention that instead.
Reviewed By: ezyang
Differential Revision: D15423316
fbshipit-source-id: 9b384f88e5bf7a3d2c132508620c276b49e1569f
Summary:
Sometimes people need to checkout an older version and build PyTorch. In that case, they need to do `git submodule sync` and maybe `git submodule update --init` as mentioned [here](https://github.com/pytorch/pytorch/issues/20074).
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20088
Differential Revision: D15195729
Pulled By: soumith
fbshipit-source-id: 73232b801e5524cdba462dd504fb973d95d0498c
Summary:
Thanks to dusty-nv , we now have Stable and Weekly wheels provided for the NVIDIA Jetson Platform. They require JetPack 4.2.
He's also maintaining source build instructions.
This PR adds links to the binaries and source build instructions to the README.
The links are dynamic, so when new stable / weekly wheels are available, Dustin will update the same URL to point to the new files
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18990
Differential Revision: D14820158
Pulled By: soumith
fbshipit-source-id: 761a56557decb72ad9c1b9f8a2745667f558eec3
Summary:
Trainer has been removed long time ago
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18980
Differential Revision: D14819855
Pulled By: ezyang
fbshipit-source-id: f62020e688ebf6663416aec7435bf1f531607941
Summary:
It will be better to split the CPU job on CI. But unluckily, we are out of Windows machines.
cc, davidbrownellWork yf225
Pull Request resolved: https://github.com/pytorch/pytorch/pull/17608
Differential Revision: D14281393
Pulled By: soumith
fbshipit-source-id: ae9a6140b7207ce56cfb2da3d812bc3fe060764a
Summary:
+ All quotes for ENV VARS are erroneous;
+ Toolset hasn't be specified;
+ Provide paths for all 3 Visual Studio 2017 products: Community/Professional/Enterprise.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/17475
Differential Revision: D14262968
Pulled By: soumith
fbshipit-source-id: c0504e0a6be9c697ead83b06b0c5cf569b5c8625
Summary:
Emphasize on the fact that docker build should be triggered from pytorch repo directory.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/16812
Differential Revision: D13985531
Pulled By: soumith
fbshipit-source-id: c6511d1e81476eb795b37fb0ad23e8951dbca617
Summary:
In current README.md, `CMAKE_PREFIX_PATH` is set to conda root even when you have activated an virtual environment. When an conda virtualenv is activated, packages are installed in `CONDA_PREFIX`, not conda root. I think `CMAKE_PREFIX_PATH` should also be set to `CONDA_PREFIX` in this case. I think some build issues can be solved with the new instruction. Maybe something like #14954.
soumith,
When I made PR #15335 I was confused and made a wrong point. I think this PR could be the real solution.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/15548
Differential Revision: D13549681
Pulled By: soumith
fbshipit-source-id: 42d855b6e49ee58d735d2f4715d3e5752a748693
Summary:
This PR makes some small changes for better consistency in our README and
CONTRIBUTING docs
Pull Request resolved: https://github.com/pytorch/pytorch/pull/15373
Differential Revision: D13512753
Pulled By: driazati
fbshipit-source-id: 44398ad1894eef521d5f5acb1d06acaad67728cf
Summary:
Now that PyTorch 1.0 is out, this should be updated :)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/15136
Differential Revision: D13447377
Pulled By: soumith
fbshipit-source-id: bd4e662c53d0699f25d4d90c1b4c1e182b4427c2
Summary: we now get mkldnn automatically from third_party/ideep
Differential Revision: D13396480
Pulled By: soumith
fbshipit-source-id: 20f819ba4b78cbe9c7d0baeab1c575669cbf6c20
Summary:
Hi, I think it might be better to use https instead of http in the README.md.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/12258
Differential Revision: D10162279
Pulled By: soumith
fbshipit-source-id: 4658aa75175909b4fea6972b437765d8b49c749f
Summary:
Source build doc section **LAPACK GPU** only lists magma-cuda80
The magma-cuda version should reflect the installed version of cuda.
- Verified on ubuntu with magma-cuda92 with build and test
- Verified 91 is available
Pull Request resolved: https://github.com/pytorch/pytorch/pull/12000
Differential Revision: D10024158
Pulled By: soumith
fbshipit-source-id: a34c85a5e87b52657f1e6f7b21d235306ab7b2aa
Summary:
This adds a Note on making experiments reproducible.
It also adds Instructions for building the Documentation to `README.md`. Please ping if I missed any requirements.
I'm not sure what to do about the submodule changes. Please advise.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/11329
Differential Revision: D9784939
Pulled By: ezyang
fbshipit-source-id: 5c5acbe343d1fffb15bdcb84c6d8d925c2ffcc5e
Summary:
Current Dockerfile builds pytorch using default python within miniconda, which happens to be Python 3.6
This patch allows users to specify which python should be installed in the default miniconda environment used by the pytorch dockerfile. I have tested the build for python 2.7, 3.5, 3.6 and 3.7. Python 2.7 required typing and cython
Pull Request resolved: https://github.com/pytorch/pytorch/pull/10317
Differential Revision: D9204401
Pulled By: ezyang
fbshipit-source-id: 11355cab3bf448bbe8369a2ed1de0d409c9a2d6e
Summary:
The tutorials url with http is not valid, replacing it with https.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/9812
Differential Revision: D8991344
Pulled By: ezyang
fbshipit-source-id: c12faa57905b50eadc320f9938c39c4139bd093b
Summary:
This change makes README.md compatible with both Github and VSTS markdown engines. Images can be reduced if necessary
Pull Request resolved: https://github.com/pytorch/pytorch/pull/9296
Differential Revision: D8874931
Pulled By: soumith
fbshipit-source-id: 0c530c1e00b06fc891301644c92c33007060bf27
This is the first of three PRs that #5537 will be split into.
This PR adds mkl headers to included files, and provides helper functions for MKL fft and cuFFT.
In particular, on POSIX, headers are using mkl-include from conda, and on Windows, it is from a new file @yf225 and I made and uploaded to s3.
* add mkl-include to required packages
* include MKL headers; add AT_MKL_ENABLED flag; add a method to query MKL availability
* Add MKL and CUFFT helpers
* Add python typing module as build dependency
* Change output_declarations to be a NamedTuple
* Add mypy configuration files
mypy-files.txt includes a list of all files that should be typed checked
with mypy. Run mypy with `mypy @mypyfiles.txt`.
mypy.ini includes mypy options. Unfortunately this can't be merged with
mypy-files.txt.
Update .travis.yml so that one doesn't have to specify what files to
type check inside it.
* Add RuntimeError on missing `typing` module
Alerts users to the new build dependency.
