[MLIR][KernelGen] Add asin kernels and tests
PiperOrigin-RevId: 351381423 Change-Id: Idb6bb42a153c472da2b495bc66fd0b0202531e29
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parent
0423a4a075
commit
b8ac43493a
tensorflow
compiler/mlir
hlo
include/mlir-hlo/Dialect/mhlo/IR
lib/Dialect/mhlo/transforms
xla/transforms
core/kernels
@ -359,6 +359,19 @@ def HLOClient_AcosOp : HLOClient_UnaryElementwiseOp<"acos", [],
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}];
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}
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def HLOClient_AsinOp : HLOClient_UnaryElementwiseOp<"asin", [],
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HLO_FpOrComplexTensor> {
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let summary = "Asin operator";
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let description = [{
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Returns `Asin(operand)` element-wise.
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$$
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\asin(x) = 2 * atan(x / (1 + sqrt(1 - x^2)))
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$$
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}];
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}
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def HLOClient_AtanOp : HLOClient_UnaryElementwiseOp<"atan", [],
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HLO_FpOrComplexTensor> {
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let summary = "Atan operator";
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@ -60,6 +60,25 @@ def : Pat<(HLOClient_AcosOp NonComplexElementType:$input),
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(HLO_ConstantLike<"M_PI"> $input)
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)>;
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// Expand asin to MHLO dialect as follows:
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// asin(x) = 2 * atan(x / (1 + sqrt(1 - x^2)))
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def : Pat<(HLOClient_AsinOp $input),
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(HLO_MulOp
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(HLO_ConstantLike<"2"> $input),
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(HLO_Atan2Op
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$input,
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(HLO_AddOp
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(HLO_ConstantLike<"1"> $input),
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(HLO_SqrtOp
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(HLO_SubOp
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(HLO_ConstantLike<"1"> $input),
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(HLO_MulOp $input, $input)
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)
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)
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)
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)
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)>;
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// Express `atan` as
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// atan(x) = atan2(x, 1)
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def : Pat<(HLOClient_AtanOp $input),
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@ -51,8 +51,8 @@ namespace {
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// TODO(herhut): Generate these out of op definitions.
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#define MAP_CHLO_OPERATION_CWISE_UNARY(fn, sep) \
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fn(AcosOp) sep fn(AtanOp) sep fn(ConjOp) sep fn(ErfOp) sep fn(ErfcOp) \
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sep fn(SinhOp) sep fn(TanOp)
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fn(AcosOp) sep fn(AsinOp) sep fn(AtanOp) sep fn(ConjOp) sep fn(ErfOp) \
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sep fn(ErfcOp) sep fn(SinhOp) sep fn(TanOp)
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template <typename OpTy>
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inline void AddLegalOpOnRankedTensor(ConversionTarget *target) {
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@ -586,6 +586,7 @@ def : Pat<(TF_ReverseV2Op AnyRankedTensor:$values, (ConstantLikeMatcher Elements
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foreach Mapping = [
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[TF_AbsOp, HLO_AbsOp],
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[TF_AcosOp, HLOClient_AcosOp],
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[TF_AsinOp, HLOClient_AsinOp],
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[TF_AtanOp, HLOClient_AtanOp],
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[TF_CeilOp, HLO_CeilOp],
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[TF_ComplexAbsOp, HLO_AbsOp],
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@ -19,7 +19,10 @@ namespace tensorflow {
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REGISTER2(UnaryOp, CPU, "Asin", functor::asin, float, double);
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#if GOOGLE_CUDA || TENSORFLOW_USE_ROCM
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#if !defined(MLIR_GENERATED_GPU_KERNELS_ENABLED) || \
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!defined(MLIR_GENERATED_EXPERIMENTAL_GPU_KERNELS_ENABLED)
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REGISTER2(UnaryOp, GPU, "Asin", functor::asin, float, double);
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#endif
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#endif
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} // namespace tensorflow
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@ -47,6 +47,7 @@ filegroup(
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filegroup(
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name = "experimental_unary_kernel_srcs",
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srcs = [
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"gpu_op_asin.cc",
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"gpu_op_atan.cc",
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"gpu_op_ceil.cc",
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"gpu_op_conj.cc",
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@ -107,6 +108,7 @@ tf_kernel_library(
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# sure that those targets can be built, so it should not hurt to
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# link them in even if they are currently not needed yet.
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":abs_kernels",
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":asin_kernels",
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":atan_kernels",
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":ceil_kernels",
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":conj_kernels",
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@ -303,6 +305,16 @@ gen_kernel_library(
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unroll_factors = "4",
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)
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gen_kernel_library(
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name = "asin",
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tile_size = "256",
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types = [
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"f32",
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"f64",
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],
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unroll_factors = "4",
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)
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gen_kernel_library(
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name = "atan",
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tile_size = "256",
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24
tensorflow/core/kernels/mlir_generated/gpu_op_asin.cc
Normal file
24
tensorflow/core/kernels/mlir_generated/gpu_op_asin.cc
Normal file
@ -0,0 +1,24 @@
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/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
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#include "tensorflow/core/kernels/mlir_generated/gpu_ops_base.h"
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namespace tensorflow {
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GENERATE_AND_REGISTER_UNARY_KERNEL(Asin, f32, DT_FLOAT, float);
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GENERATE_AND_REGISTER_UNARY_KERNEL(Asin, f64, DT_DOUBLE, double);
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} // namespace tensorflow
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@ -134,7 +134,14 @@ absl::InlinedVector<T, 10> DefaultInputNonZero() {
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{-18, -9, -1, 1, 3, 4, 5, 7, 9, 10, 18});
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}
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/// Helper functions to get default input data.
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template <typename T, std::enable_if_t<
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llvm::is_one_of<T, Eigen::half, float, double>::value,
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bool> = true>
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absl::InlinedVector<T, 10> DefaultInputBetweenZeroAndOne() {
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return test::InputAsVector<T, double>({-0.999, -0.9, -0.8, -0.5, -0.1, -0.001,
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-0, 0, 0.001, 0.1, 0.5, 0.8, 0.9,
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0.999});
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}
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template <typename T,
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std::enable_if_t<llvm::is_one_of<T, int8, int16, int32, int64>::value,
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@ -146,6 +153,8 @@ absl::InlinedVector<T, 10> DefaultInputLessThanBitwidth() {
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return v;
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}
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/// Helper functions to get default input data.
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template <typename T,
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std::enable_if_t<llvm::is_one_of<T, int8, int16, int32, int64>::value,
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bool> = true>
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@ -175,6 +175,17 @@ GENERATE_DEFAULT_TEST_WITH_SPECIFIC_INPUT_VALUES(
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Abs, DT_INT64, DT_INT64, test::NearZeroAndExtremeInput<int64>(), std::abs,
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test::GpuOpsTestConfig().ExpectStrictlyEqual())
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/// Test `tf.Asin`.
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// Test only values in the function domain. The othweise returned nan value
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// fails comparison for equality.
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GENERATE_DEFAULT_TEST_WITH_SPECIFIC_INPUT_VALUES(
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Asin, DT_FLOAT, DT_FLOAT, test::DefaultInputBetweenZeroAndOne<float>(),
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std::asin, test::GpuOpsTestConfig().ExpectStrictlyEqual())
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GENERATE_DEFAULT_TEST_WITH_SPECIFIC_INPUT_VALUES(
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Asin, DT_DOUBLE, DT_DOUBLE, test::DefaultInputBetweenZeroAndOne<double>(),
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std::asin, test::GpuOpsTestConfig().ExpectStrictlyEqual())
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/// Test `tf.Atan`.
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GENERATE_DEFAULT_TEST(Atan, DT_FLOAT, DT_FLOAT, std::atan,
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