& and | short-circuit, && and || don't. When both arguments to those
are boolean, the short-circuiting version is usually the desired one, so
clang warns on this.
Here, it is inconsequential, so switch to && and || to suppress the warning.
(cherry picked from commit b17bcddbca749f621040990a3efb840046315050)
For vectorized 1-dimensional inputs that do not take the special
blocking path (e.g. `std::complex<...>`), there was an
index-out-of-bounds error causing the broadcast size to be
computed incorrectly. Here we fix this, and make other minor
cleanup changes.
Fixes#2351.
(cherry picked from commit a500da1dc089b08e2f2b3b05a2eb23194425460e)
For some reason, having `take<n, numeric_list<T>>` for `n > 0` causes
g++-11 to ICE with
```
sorry, unimplemented: unexpected AST of kind nontype_argument_pack
```
It does work with other versions of gcc, and with clang.
I filed a GCC bug
[here](https://gcc.gnu.org/bugzilla/show_bug.cgi?id=102999).
Technically we should never actually run into this case, since you
can't take n > 0 elements from an empty list. Commenting it out
allows our Eigen tests to pass.
(cherry picked from commit 8f8c2ba2fe19c6c2e47bbe2fbaf87594642e523d)
All cuda `__half` functions are device-only in CUDA 9, including
conversions. Host-side conversions were added in CUDA 10.
The existing code doesn't build prior to 10.0.
All arithmetic functions are always device-only, so there's
therefore no reason to use vectorization on the host at all.
Modified the code to disable vectorization for `__half` on host,
which required also updating the `TensorReductionGpu` implementation
which previously made assumptions about available packets.
(cherry picked from commit cc3573ab4451853774cd5c3497373d5fe8914774)
The latest version of `mpreal` has a bug that breaks `min`/`max`.
It also breaks with the latest dev version of `mpfr`. Here we
add `FindMPREAL.cmake` which searches for the library and tests if
compilation works.
Removed our internal copy of `mpreal.h` under `unsupported/test`, as
it is out-of-sync with the latest, and similarly breaks with
the latest `mpfr`. It would be best to use the installed version
of `mpreal` anyways, since that's what we actually want to test.
Fixes#2282.
(cherry picked from commit 31f796ebef35eeadd0e26878aab3fe99ca412a45)
This is to enable compiling with the latest trisycl. `FindTriSYCL.cmake` was
broken by commit 00f32752, which modified `add_sycl_to_target` for ComputeCPP.
This makes the corresponding modifications for trisycl to make them consistent.
Also, trisycl now requires c++17.
(cherry picked from commit 8cf6cb27baa9607cc00e5dbb42a1c31efda41b74)
The extra [TOC] tag is generating a huge floating duplicated
table-of-contents, which obscures the majority of the page
(see bottom of https://eigen.tuxfamily.org/dox/unsupported/eigen_tensors.html).
Remove it.
Also, headers do not support markup (see
[doxygen bug](https://github.com/doxygen/doxygen/issues/7467)), so
backticks like
```
```
end up generating titles that looks like
```
Constructor <tt>Tensor<double,2></tt>
```
Removing backticks for now. To generate proper formatted headers, we
must directly use html instead of markdown, i.e.
```
<h2>Constructor <code>Tensor<double,2></code></h2>
```
which is ugly.
Fixes#2254.
(cherry picked from commit f5a9873bbb5488bcba3e37f92b4ec09a8db76081)
- Move constructors can only be defaulted as NOEXCEPT if all members
have NOEXCEPT move constructors.
- gcc 4.8 has some funny parsing bug in `a < b->c`, thinking `b-` is a template parameter.
(cherry picked from commit 6035da5283f12f7e6a49cda0c21696c8e5a115b7)
As written, depending on multithreading/gpu, the returned index from
`argmin`/`argmax` is not currently stable. Here we modify the functors
to always keep the first occurence (i.e. if the value is equal to the
current min/max, then keep the one with the smallest index).
This is otherwise causing unpredictable results in some TF tests.
(cherry picked from commit 3a087ccb99b454dc34484333e608e836e7032213)
The previous balancer overflowed for large row/column norms.
Modified to prevent that.
Fixes#2273.
(cherry picked from commit e9ab4278b7aba6f279c964d99ae5a312d12ab04b)
When using Eigen for gpu, these simplify portability. If
`EIGEN_PERMANENTLY_ENABLE_GPU_HIP_CUDA_DEFINES` is set, then
we do not undefine them.
(cherry picked from commit 514977f31b1c00b233969f12321a25d859dd1efa)
Currently TF lite needs to hack around with the Tensor headers in order
to customize the contraction dispatch method. Here we add simple `#ifndef`
guards to allow them to provide their own dispatch prior to inclusion.
(cherry picked from commit 6aec83263d32c29f6c5623b9716ec7e367693078)
Made a class and singleton to encapsulate initialization and retrieval of
device properties.
Related to !481, which already changed the API to address a static
linkage issue.
(cherry picked from commit 0eba8a1fe3e0fa78f0e6760c0e1265817491845d)
Time-dependence prevents tests from being repeatable. This has long
been an issue with debugging the tensor tests. Removing this will allow
future tests to be repeatable in the usual way.
Also, the recently added macros in !476 are causing headaches across different
platforms. For example, checking `_XOPEN_SOURCE` is leading to multiple
ambiguous macro errors across Google, and `_DEFAULT_SOURCE`/`_SVID_SOURCE`/`_BSD_SOURCE`
are sometimes defined with values, sometimes defined as empty, and sometimes
not defined at all when they probably should be. This is leading to
multiple build breakages.
The simplest approach is to generate a seed via
`Eigen::internal::random<uint64_t>()` if on CPU. For GPU, we use a
hash based on the current thread ID (since `rand()` isn't supported
on GPU).
Fixes#1602.
(cherry picked from commit e3b7f59659689015aa254ed67c48d870831f086f)
m_deviceProperties and m_devicePropInitialized are defined as global
statics which will define multiple copies which can cause issues if
initializeDeviceProp() is called in one translation unit and then
m_deviceProperties is used in a different translation unit. Added
inline functions getDeviceProperties() and getDevicePropInitialized()
which defines those variables as static locals. As per the C++ standard
7.1.2/4, a static local declared in an inline function always refers
to the same object, so this should be safer. Credit to Sun Chenggen
for this fix.
This fixes issue #1475.
(cherry picked from commit 3804ca0d905a0a03357db50abc7468f5f90abc98)
`TensorRandom` currently relies on BSD `random()`, which is not always
available. The [linux manpage](https://man7.org/linux/man-pages/man3/srandom.3.html)
gives the glibc condition:
```
_XOPEN_SOURCE >= 500
|| /* Glibc since 2.19: */ _DEFAULT_SOURCE
|| /* Glibc <= 2.19: */ _SVID_SOURCE || _BSD_SOURCE
```
In particular, this was failing to compile for MinGW via msys2. If not
available, we fall back to using `rand()`.
(cherry picked from commit 045c0609b5c059974104f29dad91bcc3828e91ac)
The namespace declaration for googlehash is a configurable macro that
can be disabled. In particular, it is disabled within google, causing
compile errors since `dense_hash_map`/`sparse_hash_map` are then in
the global namespace instead of in `::google`.
Here we play a bit of gynastics to allow for both `google::*_hash_map`
and `*_hash_map`, while limiting namespace polution. Symbols within
the `::google` namespace are imported into `Eigen::google`.
We also remove checks based on `_SPARSE_HASH_MAP_H_`, as this is
fragile, and instead require `EIGEN_GOOGLEHASH_SUPPORT` to be
defined.
The issue was discovered when the GPU scan unit test was run and resulted in a segmentation fault.
The segmantation fault occurred because the unit test allocated GPU memory and passed a pointer to that memory to the computation that it presumed would execute on the GPU.
But because of the issue, the computation was scheduled to execute on the CPU so a situation was constructed where the CPU attempted to access a GPU memory location.
The fix expands the GPU specific ScanLauncher specialization to handle cases where vectorization is enabled.
Previously, the GPU specialization is chosen only if Vectorization is not used.
The original swap approach leads to potential undefined behavior (reading
uninitialized memory) and results in unnecessary copying of data for static
storage.
Here we pass down the move assignment to the underlying storage. Static
storage does a one-way copy, dynamic storage does a swap.
Modified the tests to no longer read from the moved-from matrix/tensor,
since that can lead to UB. Added a test to ensure we do not access
uninitialized memory in a move.
Fixes: #2119
The macro `__cplusplus` is not defined correctly in MSVC unless building
with the the `/Zc:__cplusplus` flag. Instead, it defines `_MSVC_LANG` to the
specified c++ standard version number.
Here we introduce `EIGEN_CPLUSPLUS` which will contain the c++ version
number both for MSVC and otherwise. This simplifies checks for supported
features.
Also replaced most instances of standard version checking via `__cplusplus`
with the existing `EIGEN_COMP_CXXVER` macro for better clarity.
Fixes: #2170
1.Only computing about half of the factors and use complex conjugate symmetry for the rest instead of all to save time.
2.All twiddles are calculated in double because that gives the maximum achievable precision when doing float transforms.
3.Reducing all angles to the range 0<angle<pi/4 which gives even more precision.
CMake complains that the package name does not match when the case
differs, e.g.:
```
CMake Warning (dev) at /usr/share/cmake-3.18/Modules/FindPackageHandleStandardArgs.cmake:273 (message):
The package name passed to `find_package_handle_standard_args` (UMFPACK)
does not match the name of the calling package (Umfpack). This can lead to
problems in calling code that expects `find_package` result variables
(e.g., `_FOUND`) to follow a certain pattern.
Call Stack (most recent call first):
cmake/FindUmfpack.cmake:50 (find_package_handle_standard_args)
bench/spbench/CMakeLists.txt:24 (find_package)
This warning is for project developers. Use -Wno-dev to suppress it.
```
Here we rename the libraries to match their true cases.
Originating from
[this SO issue](https://stackoverflow.com/questions/65901014/how-to-solve-this-all-error-2-in-this-case),
some win32 compilers define `__int32` as a `long`, but MinGW defines
`std::int32_t` as an `int`, leading to a type conflict.
To avoid this, we remove the custom `typedef` definitions for win32. The
Tensor module requires C++11 anyways, so we are guaranteed to have
included `<cstdint>` already in `Eigen/Core`.
Also re-arranged the headers to only include `<cstdint>` in one place to
avoid this type of error again.
