Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/17764
Original commit changeset: f1923fdca4a1
reverted int8 ops fixes the original runtime regression.
We'll ignore the memory regression since it is flaky, see D14228484
Reviewed By: dzhulgakov
Differential Revision: D13885233
fbshipit-source-id: ccbe4b94acb44b7b4cb3ae4d73e3f6091e1e1195
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/16273
Previously we have SetOutputSize which accept a partially initialized Output Tensor and set it to the correct size,
the diff change this to GetOutputSize that returns the correct size instead.
e.g.
```
auto* Y = Output(0);
ConvPoolOp<Context>::SetOutputSize(X, Y, channels);
...
Y->mutable_data<T>...
```
-->
```
auto sizes = ConvPoolOp<Context>::GetOutputSize(X, channels);
auto* Y = Output(0, sizes, at::dtype<T>());
```
Reviewed By: dzhulgakov
Differential Revision: D13736281
fbshipit-source-id: 64abce3dbaed0b375098463333dfd0ea5a3b1945
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/12180
I had to fix a lot of call sites, because a lot of places assume that
you can actually get a const vector&, and if the internal representation
of sizes in a tensor is NOT a vector, it's not possible to fulfill
this API contract.
Framework changes:
- I deleted TensorImpl::dims(); caffe2::Tensor::dims() just forwards to
sizes() now.
- De-templatized SetDims; now it is an explicit list of ArrayRef and
variadic overloads. This makes implicit conversions work again,
so I don't need to explicitly list the std::vector cases too.
- As a knock-on effect, this causes Reset() to accept at::IntList as well as
const std::vector<int64_t>&
- Edited variadic overloads of SetDims to all forward to the underlying
arbitrary-dim implementation, reducing code duplication. (It's probably
marginally less efficient in the new world.)
- Replace Tensor constructor accepting const std::vector<int64_t>& with at::IntList
- Make MKLTensor accept ArrayRef along with vector in constructor and
Reset (unfortunately, no implicit conversions here, since it's templated on
index type.)
- There are a few other places, like cudnn, where I changed functions
that previously took const std::vector<int64_t>& to take at::IntList
instead.
Classification of call site changes:
- 'const std::vector<int64_t>& x_dims = x.dims()' ==>
'at::IntList x_dims = x.dims()'
- 'std::vector<int64_t> x_dims = x.dims()' ==>
'std::vector<int64_t> x_dims = x.dims().vec()' (we need a copy!)
Usually this is because we're about to mutably modify the vector
to compute some new dimension. However, it also very commonly occurs in the
form: 'x_dims_ = x.dims()' because we frequently cache sizes in operators.
- Instead of constructing std::vector<int64_t>{blah, blah}, construct an
at::IntList directly
ArrayRef changes:
- cbegin()/cend() iterators, they operate the same aas begin()/end() because
everything on ArrayRef is const.
- Moved operator<< into ArrayRef.h, so that it's always available when
working with ArrayRef. I also templated it, so it now works on an
ArrayRef of any type.
- Add operator== overload for ArrayRef, and also add variants to permit
comparison of ArrayRef with std::vector, a very common operation.
(The non-templated version of operator== can get these automatically
via implicit conversion, but with templates C++ refuses to do
any explicit conversions.)
I'm planning to audit all dims() call sites to make sure they don't
expect 'auto x = t.dims()' to give you an x whose lifetime can validly
outlive the tensor.
I opted not to do a dims() to sizes() rename, because dims() also matches
the protobufs accessor. Bad news!
Reviewed By: jerryzh168
Differential Revision: D10111759
fbshipit-source-id: a2a81dc4b92c22ad4b3b8ef4077a7e97b6479452
Summary: This uses `clang-tidy` to comment out unused parameters (in functions, methods and lambdas) in fbcode. Cases that the tool failed to handle are fixed manually.
Reviewed By: igorsugak
Differential Revision: D5454343
fbshipit-source-id: 5dee339b4334e25e963891b519a5aa81fbf627b2
Summary:
In its current form, common_rtc.h can only be included in a file where
```
using namespace std;
```
comes before the include
Closes https://github.com/caffe2/caffe2/pull/398
Differential Revision: D4943125
Pulled By: Yangqing
fbshipit-source-id: 3ef15c9353e6dd7326fc5f60322049c9f594ee6c
Summary:
(Note: previous revert was due to a race condition between D4657831 and
D4659953 that I failed to catch.)
After this, we should have contbuild guarding the Windows build both with
and without CUDA.
This includes a series of changes that are needed to make Windows build,
specifically:
(1) Various flags that are needed in the cmake system, specially dealing
with /MD, /MT, cuda, cudnn, whole static linking, etc.
(2) Contbuild scripts based on appveyo.
(3) For Windows build, note that one will need to use "cmake --build" to
build stuff so that the build type is consistent between configuration and
actual build. see scripts\build_windows.bat for details.
(4) In logging.h, ERROR is already defined by Windows. I don't have a good
solution now, and as a result, LOG(ERROR) on windows is going to be
LOG(INFO).
(5) variable length array is not supported by MSVC (and it is not part of
C++ standard). As a result I replaced them with vectors.
(6) sched.h is not available on Windows, so akyrola 's awesome simple
async net might encounter some slowdown due to no affinity setting on
Windows.
(7) MSVC has a bug that does not work very well with template calls inide
a templated function call, which is a known issue that should be fixed in
MSVC 2017. However for now this means changes to conv_op_impl.h and
recurrent_net_op.h. No actual functionalities are changed.
(8) std host function calls are not supported in CUDA8+MSVC, so I changed
lp_pool (and maybe a few others) to use cuda device functions.
(9) The current Scale and Axpy has heavy templating that does not work
well with MSVC. As a result I reverted azzolini 's changes to the Scale
and Axpy interface, moved the fixed-length version to ScaleFixedSize and
AxpyFixedSize.
(10) CUDA + MSVC does not deal with Eigen well, so I guarded all Eigen
parts to only the non-CUDA part.
(11) In conclusion, it is fun but painful to deal with visual c++.
Differential Revision: D4666745
fbshipit-source-id: 3c9035083067bdb19a16d9c345c1ce66b6a86600
Summary:
After this, we should have contbuild guarding the Windows build both with
and without CUDA.
This includes a series of changes that are needed to make Windows build,
specifically:
(1) Various flags that are needed in the cmake system, specially dealing
with /MD, /MT, cuda, cudnn, whole static linking, etc.
(2) Contbuild scripts based on appveyo.
(3) For Windows build, note that one will need to use "cmake --build" to
build stuff so that the build type is consistent between configuration and
actual build. see scripts\build_windows.bat for details.
(4) In logging.h, ERROR is already defined by Windows. I don't have a good
solution now, and as a result, LOG(ERROR) on windows is going to be
LOG(INFO).
(5) variable length array is not supported by MSVC (and it is not part of
C++ standard). As a result I replaced them with vectors.
(6) sched.h is not available on Windows, so akyrola 's awesome simple
async net might encounter some slowdown due to no affinity setting on
Windows.
(7) MSVC has a
Closes https://github.com/caffe2/caffe2/pull/183
Reviewed By: ajtulloch
Differential Revision: D4657831
Pulled By: Yangqing
fbshipit-source-id: 070ded372ed78a7e3e3919fdffa1d337640f146e
Summary:
In the past we have moved most of the CHECKs to CAFFE_ENFORCE (exceptions).
However, we kept the name "*_CHECK" for cuda calls, and that caused some
confusion especially in the destructor calls: while our destructors are not
written to handle exceptions, these CUDA_CHECKs could actually throw some
exceptions.
As a result, this diff
(1) Renames all cuda related "*_CHECK" to "*_ENFORCE"
(2) Explicitly marked the destructor of core Caffe2 classes as noexcept
(3) Added proper, really-CHECK cuda check macros, and used those in the
corresponding destructors.
This should not change any of existing functionality.
Reviewed By: dzhulgakov
Differential Revision: D4656368
fbshipit-source-id: 32e3056e66c0400156c5ca0187b6151cf3d52404
Summary:
This is a first diff to remove the "easiest" unused includes in fbcode.
* For safety, we only touch .cpp files without #if and #define,
* We do not try to remove redundant systems headers (aka. "packing").
The diff was generated as follows:
```
foundation/scripts/ls-cpp-dirs | grep -v '^\(\.\.\|external/\|.*/external\)' | xargs ffmr -o /tmp/ffmr-diff-1 codegraph/scripts/ffmr/analyze_includes_no_headers_no_packing_skipping_ifdefs.sh
cat /tmp/ffmr-diff-1/*.diff | patch -p2
hg commit -m something
arc diff --prepare --nolint --nounit --less-context --excuse refactoring
```
Note: `grep -v` is just an optimization. The actual configuration is in these two files:
diffusion/FBS/browse/master/fbcode/codegraph/analysis/config.py
diffusion/FBS/browse/master/fbcode/codegraph/scripts/ffmr/analyze_includes_no_headers_no_packing_skipping_ifdefs.sh
See the task for more context, and the recent "safety" improvements on the tool.
depends on D4317825 for very few cases where `nolint` had to be manually added.
Reviewed By: igorsugak
Differential Revision: D4312617
fbshipit-source-id: ecc1f0addfd0651fa4770fcc43cd1314661a311a
