The previous implementation decomposes tanh(x) into
`(exp(2x) - 1)/(exp(2x)+1), x < 0`
`(1 - exp(-2x))/(1 + exp(-2x)), x >= 0`
This is fine as it avoids overflow with the exponential, but the whole
decomposition is computed for both cases unconditionally, then the
result is chosen based off the sign of the input. This results in doing
two expensive exp computations.
The proposed change avoids doing the whole computation twice by
exploiting the reflection symmetry `tanh(-x) = -tanh(x)`. We can
"normalize" the input to be positive by setting `y = sign(x) * x`, where
the sign of `x` is computed as `sign(x) = (float)(x > 0) * (-2) + 1`.
Then compute `z = tanh(y) `with the decomposition above for `x >=0` and
"denormalize" the result `z * sign(x)` to retain the sign. The reason it
is done this way is that it is very amenable to vectorization.
This method trades the duplicate decomposition computations (which takes
5 instructions including an extra expensive exp and div) for 4 cheap
instructions to compute the signs value
`arith.cmpf `(which is a pre-existing instruction in the previous impl)
`arith.sitofp`
`arith.mulf`
`arith.addf`
and 1 more instruction to get the right sign in the result
5. `arith.mulf`.
Moreover, numerically, this implementation will yield the exact same
results as the previous implementation.
As part of the relanding, a casting issue from the original commit has
been fixed, i.e. casting bool to float with `uitofp`. Additionally a
correctness test with `mlir-cpu-runner` has been added.
This simply updates the rewrites to propagate the scalable flags (which
as they do not alter the vector shape, is pretty simple).
The added tests are simply scalable versions of the existing vector
tests.
The previous implementation decomposes `tanh(x)` into
`(exp(2x) - 1)/(exp(2x)+1), x < 0`
`(1 - exp(-2x))/(1 + exp(-2x)), x >= 0`
This is fine as it avoids overflow with the exponential, but the whole
decomposition is computed for both cases unconditionally, then the
result is chosen based off the sign of the input. This results in doing
two expensive `exp` computations.
The proposed change avoids doing the whole computation twice by
exploiting the reflection symmetry `tanh(-x) = -tanh(x)`. We can
"normalize" the input to be positive by setting `y = sign(x) * x`, where
the sign of `x` is computed as `sign(x) = (float)(x > 0) * (-2) + 1`.
Then compute `z = tanh(y)` with the decomposition above for `x >=0` and
"denormalize" the result `z * sign(x)` to retain the sign. The reason it
is done this way is that it is very amenable to vectorization.
This method trades the duplicate decomposition computations (which takes
5 instructions including an extra expensive `exp` and `div`) for 4 cheap
instructions to compute the signs value
1. `arith.cmpf` (which is a pre-existing instruction in the previous
impl)
2. `arith.sitofp`
3. `arith.mulf`
4. `arith.addf`
and 1 more instruction to get the right sign in the result
5. `arith.mulf`. Moreover, numerically, this implementation will yield
the exact same results as the previous implementation.
These patterns can already be used via
populateMathPolynomialApproximationPatterns, but that includes a number
of other patterns that may not be needed.
There are already similar functions for expansion.
For now only adding tanh and erf since I have a concrete use case for
these two.
Common backends (LLVM, SPIR-V) only supports 1D vectors, LLVM conversion
handles ND vectors (N >= 2) as `array<array<... vector>>` and SPIR-V
conversion doesn't handle them at all at the moment. Sometimes it's
preferable to treat multidim vectors as linearized 1D. Add pass to do
this. Only constants and simple elementwise ops are supported for now.
@krzysz00 I've extracted yours result type conversion code from
LegalizeToF32 and moved it to common place.
Also, add ConversionPattern class operating on traits.
Since most of the operations in the `math` dialect don't have
low-precision implementations, add the -math-legalize-to-f32 pass that
goes through and brackets low-precision math funcitons (like `math.sin
%0 : f16`) with `arith.extf` and `arith.truncf`. This preserves the
original semantics of the math operation but allows lowering to proceed.
Versions of this lowering are already implicitly present in some passes,
like ConvertGPUToROCDL. However, because those are implicit rewrites,
they hide the floating-point extension and truncation, preventing anyone
from writing passes that operate on those implitic extf/truncf pairs.
Exposing this legalization explicitly is needed to allow lowening 8-bit
floats on AMD GPUs, as the implementation of extf and truncf on that
platform requires the complex logic found in ArithToAMDGPU, which runs
before the GPU to ROCDL lowering.
Powf expansion currently returns NaN when the base is negative.
This is because taking natural log of a negative number gives
NaN. This patch will square the base and half the exponent, thereby
getting around the negative base problem.
Reviewed By: rsuderman
Differential Revision: https://reviews.llvm.org/D158797
Used the cephes numerical approximation for `math.atan`. This is a
significant accuracy improvement over the previous taylor series
approximation.
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D153656
The existing lowering has lower precision for certain use cases, e.g.
tanh. Improved version should demonstrate an overall higher level of precision.
Reviewed By: cota, jpienaar
Differential Revision: https://reviews.llvm.org/D153592
The MLIR classes Type/Attribute/Operation/Op/Value support
cast/dyn_cast/isa/dyn_cast_or_null functionality through llvm's doCast
functionality in addition to defining methods with the same name.
This change begins the migration of uses of the method to the
corresponding function call as has been decided as more consistent.
Note that there still exist classes that only define methods directly,
such as AffineExpr, and this does not include work currently to support
a functional cast/isa call.
Caveats include:
- This clang-tidy script probably has more problems.
- This only touches C++ code, so nothing that is being generated.
Context:
- https://mlir.llvm.org/deprecation/ at "Use the free function variants
for dyn_cast/cast/isa/…"
- Original discussion at https://discourse.llvm.org/t/preferred-casting-style-going-forward/68443
Implementation:
This first patch was created with the following steps. The intention is
to only do automated changes at first, so I waste less time if it's
reverted, and so the first mass change is more clear as an example to
other teams that will need to follow similar steps.
Steps are described per line, as comments are removed by git:
0. Retrieve the change from the following to build clang-tidy with an
additional check:
https://github.com/llvm/llvm-project/compare/main...tpopp:llvm-project:tidy-cast-check
1. Build clang-tidy
2. Run clang-tidy over your entire codebase while disabling all checks
and enabling the one relevant one. Run on all header files also.
3. Delete .inc files that were also modified, so the next build rebuilds
them to a pure state.
4. Some changes have been deleted for the following reasons:
- Some files had a variable also named cast
- Some files had not included a header file that defines the cast
functions
- Some files are definitions of the classes that have the casting
methods, so the code still refers to the method instead of the
function without adding a prefix or removing the method declaration
at the same time.
```
ninja -C $BUILD_DIR clang-tidy
run-clang-tidy -clang-tidy-binary=$BUILD_DIR/bin/clang-tidy -checks='-*,misc-cast-functions'\
-header-filter=mlir/ mlir/* -fix
rm -rf $BUILD_DIR/tools/mlir/**/*.inc
git restore mlir/lib/IR mlir/lib/Dialect/DLTI/DLTI.cpp\
mlir/lib/Dialect/Complex/IR/ComplexDialect.cpp\
mlir/lib/**/IR/\
mlir/lib/Dialect/SparseTensor/Transforms/SparseVectorization.cpp\
mlir/lib/Dialect/Vector/Transforms/LowerVectorMultiReduction.cpp\
mlir/test/lib/Dialect/Test/TestTypes.cpp\
mlir/test/lib/Dialect/Transform/TestTransformDialectExtension.cpp\
mlir/test/lib/Dialect/Test/TestAttributes.cpp\
mlir/unittests/TableGen/EnumsGenTest.cpp\
mlir/test/python/lib/PythonTestCAPI.cpp\
mlir/include/mlir/IR/
```
Differential Revision: https://reviews.llvm.org/D150123
The dependencies were set up improperly likely due to past code
locations. MathTransforms shouldn't depend on VectorUtils which add a
whole bunch of additional dependencies; it instead depends on the SCF
dialect.
Differential Revision: https://reviews.llvm.org/D149797
This reverts commit 87cef78fa1.
The issue in the original revert is that a lit test expecting a `-nan`
as an output was failing on M2. Since the IEEE 754-2008 standard does
not require the sign to be printed when displaying a `nan`, this
commit changes the `CHECK` for `-nan` to one that checks the result
value bitcasted to an `i32` to ensure that input is being left
unchanged. This check should now be independent of platform being used
to run test.
Reviewed By: jpienaar, mehdi_amini
Differential Revision: https://reviews.llvm.org/D148941
Currently conversions to interfaces may happen implicitly (e.g.
`Attribute -> TypedAttr`), failing a runtime assert if the interface
isn't actually implemented. This change marks the `Interface(ValueT)`
constructor as explicit so that a cast is required.
Where it was straightforward to I adjusted code to not require casts,
otherwise I just made them explicit.
Depends on D148491, D148492
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D148493
This commit adds a pattern that expands `math.roundeven` into
`math.round` + some ops from `arith`. This is needed to be able to run
`math.roundeven` in a vectorized manner.
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D148285
The current expand pattern for `math.round` does not handle the
special values -0.0, +-inf, and +-nan correctly. It also does not
properly handle values with magnitude |x| >= 2^23. Lastly, the pattern
generates invalid IR when the input to `math.round` is a vector. This
patch fixes these issues.
Reviewed By: rsuderman
Differential Revision: https://reviews.llvm.org/D148398
Powf functions are pushed directly to libm. This is problematic for
situations where libm is not available. This patch will decompose the
powf function into log of exponent multiplied by log of base and raise
it to the exp.
Reviewed By: rsuderman
Differential Revision: https://reviews.llvm.org/D148164
Round functions are pushed directly to libm. This is problematic for
situations where libm is not available. This patch will decompose the
roundf function by adding 0.5 to positive number to input
(subtracting for negative) following by a truncate.
Reviewed By: rsuderman
Differential Revision: https://reviews.llvm.org/D148026
Exp2 functions are pushed directly to libm. This is problematic for
situations where libm is not available. This patch will expand the exp2
function to use exp2 with the input multiplied by ln2 (natural log).
Reviewed By: rsuderman
Differential Revision: https://reviews.llvm.org/D148064
Ceilf are pushed directly to libm. This is problematic for
situations where libm is not available. This patch will break down
a ceilf function to truncate followed by an increment if the
truncated value is smaller than the input value.
Reviewed By: rsuderman
Differential Revision: https://reviews.llvm.org/D147974
Floorf are pushed directly to libm. This is problematic for
situations where libm is not available. This patch will break down
a floorf function to truncate followed by an increment for negative
values, if necessary.
Reviewed By: rsuderman
Differential Revision: https://reviews.llvm.org/D147966
Fused multiply and add are being pushed directly to the libm. This is problematic
for situations where libm is not available. This patch will break down a fused multiply and
add into a multiply followed by an add.
Reviewed By: rsuderman
Differential Revision: https://reviews.llvm.org/D147811
The math arithmetic expansions do not support vectorized types.
Updated the lowerings so that they support vectorized types. This
includes a different implementation for `math.ctlz` to be a binary
search and not have variable termination time.
Reviewed By: jpienaar, NatashaKnk
Differential Revision: https://reviews.llvm.org/D147289
Polynomial approximations assume F32 values. We can convert all non-f32
cases to operate on f32s with intermediate casts.
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D146677
Cbrt can be approximated with some relatively simple polynomial
operators. This includes a lit test validating the implementation
and some run tests that validate numerical correct.
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D145019
We can implement a polynomial approximation of math.tan by
decomposing to `math.sin` and `math.cos`. While it is not
technically a polynomial approximation it should be the most
straight forward approximation.
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D144980
This revision refactors and cleans up a bunch of infra related to vector, shapes and indexing into more reusable APIs.
Differential Revision: https://reviews.llvm.org/D138501
This is a similar builder to the one for SCF::IfOp which allows users to pass region builders to it. Refer to the builders for IfOp.
Reviewed By: tpopp
Differential Revision: https://reviews.llvm.org/D137709
This patch fixes:
mlir/lib/Dialect/Math/Transforms/PolynomialApproximation.cpp:171:30:
warning: suggest parentheses around ‘&&’ within ‘||’ [-Wparentheses]
mlir/lib/Dialect/Math/Transforms/PolynomialApproximation.cpp:283:30:
warning: suggest parentheses around ‘&&’ within ‘||’ [-Wparentheses]
The operation computes pow(b, p), where 'b' is floating point
and 'p' is a signed integer. The result's type matches 'b' type.
The operands must have the same shape.
Differential Revision: https://reviews.llvm.org/D129811
