For floating point operations, this uses std.pow.
For integer operations, this lowers to a loop.
This adds a dependency on scf.
PiperOrigin-RevId: 348537232
Shape inference in case of ops with complex element types need to use the element type of complex as the result element type and not the full operand type.
Before:
"mhlo.abs"(%arg0) : (tensor<4xcomplex<f32>>) -> tensor<4xtensor<4xcomplex<f32>>>
After:
"mhlo.abs"(%arg0) : (tensor<4xcomplex<f32>>) -> tensor<4xf32>
PiperOrigin-RevId: 348123967
- MLIR MemRefs do not preserve layout information correctly when unit dimensions
are involved. Operations like convolution that use cuDNN however need the correct
layout to be preserved so that we do not end up creating an incompatible combination
of input/filter/output layout that is not supported by cuDNN.
- Add these layouts to convolution attributes in the form of I32ArrayAttr for representing
the layout in "minor_to_major" form similar to XLA.
PiperOrigin-RevId: 348034757
It didn't return 0 for 0.0 and -0.0.
Currently we emit -0.0 for -0.0 which is correct according to the HLO dialect.
For the TF_SignOp we should emit 0.0 in that case, we will leave that as a TODO.
Enable the tests which work now, and add another one for Int64.
Also improve the registration code, we should not register the Int32 kernel.
PiperOrigin-RevId: 347981124
It didn't return 0 for 0.0 and -0.0.
Currently we emit -0.0 for -0.0 which is correct according to the HLO dialect.
For the TF_SignOp we should emit 0.0 in that case, we will leave that as a TODO.
Enable the tests which work now, and add another one for Int64.
Also improve the registration code, we should not register the Int32 kernel.
PiperOrigin-RevId: 347602378
It didn't return 0 for 0.0 and -0.0.
Currently we emit -0.0 for -0.0 which is correct according to the HLO dialect.
For the TF_SignOp we should emit 0.0 in that case, we will leave that as a TODO.
Enable the tests which work now, and add another one for Int64.
Also improve the registration code, we should not register the Int32 kernel.
PiperOrigin-RevId: 347590340
- Add this attribute to match the corresponding XLA HLO attribute on convolution
operations.
- A true value indicates a reversal of the corresponding kernel spatial dimension.
- Since XLA builder does not support this attribute, use a custom HLO converted to map
from mlir::mhlo::ConvOp to XLA.
PiperOrigin-RevId: 346891737
- Add a variant of the fused convolution that does not need a side input and side input scale.
- Rename the existing one to `ConvForwardFusedSideInputOp`.
- Update tests to exercise all variants of the convolution ops in the GPU dialect.
- Eliminate unused `LHLO_ExtentBuffer` and changed LHLO_Buffer to allow any integer element
type to match what XLA can generate sometimes for scratch buffers.
PiperOrigin-RevId: 345701569
- Split out enum definitions in hlo dialect into a separate .td file (similar to structs)
and generate enum decl/defs for these enums.
- Also split out the LHLO GPU enums into a separate .td file and generate enum
decl/defs for these enums as well.
- Remove unused dialect from ConvolutionAttributes and generate lhlo_gpu enums.
- Add appropriate namespace for all the enums.
PiperOrigin-RevId: 345277240
- Map Custom call for GEMM in XLA HLO to Gemm/Gemm bias operations in LHLO GPU
dialect.
- Make 'algorithm' an optional attribute to better match with XLA HLO backend config.
- Replace 'alpha' with 'alpha_real' and 'alpha_complex' to support complex GEMM correctly.
- Generate GemmThunk off of LHLO GPU Gemm operations.
PiperOrigin-RevId: 345250840
- Restructured LHLO GPU Cholesky to better match XLA HLO by eliminating the
untyped buffer and changing is_upper attribute to is_lower.
- Change LhloDialectEmitter to emit LHLO GPU Cholesky operation.
PiperOrigin-RevId: 343873516
- Extend MHLO CustomCall to have multiple tensors as results.
- Extend LHLO CustomCall to have multiple memrefs for output operands.
- Fix HLO->LHLO and XLA HLO->LHLO mapping for CustomCall to setup the
operand_segment_sizes attribute correctly.
PiperOrigin-RevId: 342067762
This is to match with HLO semantics and general dimension semantics in MLIR.
Also,
* Define minimal verifier for these ops.
* Add folder for SetDimensionSize op on static shaped dimension.
* Fix assumption of ranked shape in GetDimensionSize op.
PiperOrigin-RevId: 341150923
Rahul Joshi
A. Unique TensorFlower
Alexander Belyaev
Tres Popp
Smit Hinsu
Adrian Kuegel
River Riddle
Tim Shen
Benjamin Kramer
Stephan Herhut
Lucy Fox
Sean Silva