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[mlir][print]Add functions for printing memref f16/bf16/i16 (#75094)
1. Added functions for printMemrefI16/f16/bf16. 2. Added a new integration test for all the printMemref functions.
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‎mlir/include/mlir/ExecutionEngine/RunnerUtils.h

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@@ -38,6 +38,7 @@
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#include <iostream>
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#include "mlir/ExecutionEngine/CRunnerUtils.h"
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#include "mlir/ExecutionEngine/Float16bits.h"
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template <typename T, typename StreamType>
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void printMemRefMetaData(StreamType &os, const DynamicMemRefType<T> &v) {
@@ -369,10 +370,16 @@ _mlir_ciface_printMemrefShapeC64(UnrankedMemRefType<impl::complex64> *m);
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extern "C" MLIR_RUNNERUTILS_EXPORT void
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_mlir_ciface_printMemrefI8(UnrankedMemRefType<int8_t> *m);
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extern "C" MLIR_RUNNERUTILS_EXPORT void
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_mlir_ciface_printMemrefI16(UnrankedMemRefType<int16_t> *m);
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extern "C" MLIR_RUNNERUTILS_EXPORT void
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_mlir_ciface_printMemrefI32(UnrankedMemRefType<int32_t> *m);
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extern "C" MLIR_RUNNERUTILS_EXPORT void
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_mlir_ciface_printMemrefI64(UnrankedMemRefType<int64_t> *m);
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extern "C" MLIR_RUNNERUTILS_EXPORT void
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_mlir_ciface_printMemrefF16(UnrankedMemRefType<f16> *m);
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extern "C" MLIR_RUNNERUTILS_EXPORT void
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_mlir_ciface_printMemrefBF16(UnrankedMemRefType<bf16> *m);
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extern "C" MLIR_RUNNERUTILS_EXPORT void
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_mlir_ciface_printMemrefF32(UnrankedMemRefType<float> *m);
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extern "C" MLIR_RUNNERUTILS_EXPORT void
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_mlir_ciface_printMemrefF64(UnrankedMemRefType<double> *m);

‎mlir/lib/ExecutionEngine/CMakeLists.txt

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@@ -157,6 +157,9 @@ if(LLVM_ENABLE_PIC)
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RunnerUtils.cpp
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EXCLUDE_FROM_LIBMLIR
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LINK_LIBS PUBLIC
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mlir_float16_utils
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)
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target_compile_definitions(mlir_runner_utils PRIVATE mlir_runner_utils_EXPORTS)
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‎mlir/lib/ExecutionEngine/RunnerUtils.cpp

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@@ -81,6 +81,10 @@ extern "C" void _mlir_ciface_printMemrefI8(UnrankedMemRefType<int8_t> *M) {
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impl::printMemRef(*M);
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}
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extern "C" void _mlir_ciface_printMemrefI16(UnrankedMemRefType<int16_t> *M) {
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impl::printMemRef(*M);
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}
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extern "C" void _mlir_ciface_printMemrefI32(UnrankedMemRefType<int32_t> *M) {
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impl::printMemRef(*M);
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}
@@ -89,6 +93,14 @@ extern "C" void _mlir_ciface_printMemrefI64(UnrankedMemRefType<int64_t> *M) {
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impl::printMemRef(*M);
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}
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extern "C" void _mlir_ciface_printMemrefF16(UnrankedMemRefType<f16> *M) {
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impl::printMemRef(*M);
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}
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extern "C" void _mlir_ciface_printMemrefBF16(UnrankedMemRefType<bf16> *M) {
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impl::printMemRef(*M);
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}
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extern "C" void _mlir_ciface_printMemrefF32(UnrankedMemRefType<float> *M) {
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impl::printMemRef(*M);
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}

‎mlir/test/Integration/Dialect/Memref/print-memref.mlir

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// RUN: mlir-opt %s \
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// RUN: -func-bufferize -arith-bufferize --canonicalize \
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// RUN: -finalize-memref-to-llvm\
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// RUN: -convert-func-to-llvm -reconcile-unrealized-casts |\
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// RUN: mlir-cpu-runner \
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// RUN: -e entry -entry-point-result=void \
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// RUN: -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils |\
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// RUN: FileCheck %s
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module {
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func.func private @printMemrefI8(%ptr : tensor<*xi8>) attributes { llvm.emit_c_interface }
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func.func private @printMemrefI16(%ptr : tensor<*xi16>) attributes { llvm.emit_c_interface }
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func.func private @printMemrefI32(%ptr : tensor<*xi32>) attributes { llvm.emit_c_interface }
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func.func private @printMemrefI64(%ptr : tensor<*xi64>) attributes { llvm.emit_c_interface }
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func.func private @printMemrefBF16(%ptr : tensor<*xbf16>) attributes { llvm.emit_c_interface }
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func.func private @printMemrefF16(%ptr : tensor<*xf16>) attributes { llvm.emit_c_interface }
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func.func private @printMemrefF32(%ptr : tensor<*xf32>) attributes { llvm.emit_c_interface }
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func.func private @printMemrefF64(%ptr : tensor<*xf64>) attributes { llvm.emit_c_interface }
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func.func private @printMemrefC32(%ptr : tensor<*xcomplex<f32>>) attributes { llvm.emit_c_interface }
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func.func private @printMemrefC64(%ptr : tensor<*xcomplex<f64>>) attributes { llvm.emit_c_interface }
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func.func private @printMemrefInd(%ptr : tensor<*xindex>) attributes { llvm.emit_c_interface }
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func.func @entry() {
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%i8 = arith.constant dense<90> : tensor<3x3xi8>
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%i16 = arith.constant dense<1> : tensor<3x3xi16>
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%i32 = arith.constant dense<2> : tensor<3x3xi32>
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%i64 = arith.constant dense<3> : tensor<3x3xi64>
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%f16 = arith.constant dense<1.5> : tensor<3x3xf16>
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%bf16 = arith.constant dense<2.5> : tensor<3x3xbf16>
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%f32 = arith.constant dense<3.5> : tensor<3x3xf32>
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%f64 = arith.constant dense<4.5> : tensor<3x3xf64>
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%c32 = arith.constant dense<(1.000000e+01,5.000000e+00)> : tensor<3x3xcomplex<f32>>
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%c64 = arith.constant dense<(2.000000e+01,5.000000e+00)> : tensor<3x3xcomplex<f64>>
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%ind = arith.constant dense<4> : tensor<3x3xindex>
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%1 = tensor.cast %i8 : tensor<3x3xi8> to tensor<*xi8>
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%2 = tensor.cast %i16 : tensor<3x3xi16> to tensor<*xi16>
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%3 = tensor.cast %i32 : tensor<3x3xi32> to tensor<*xi32>
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%4 = tensor.cast %i64 : tensor<3x3xi64> to tensor<*xi64>
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%5 = tensor.cast %f16 : tensor<3x3xf16> to tensor<*xf16>
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%6 = tensor.cast %bf16 : tensor<3x3xbf16> to tensor<*xbf16>
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%7 = tensor.cast %f32 : tensor<3x3xf32> to tensor<*xf32>
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%8 = tensor.cast %f64 : tensor<3x3xf64> to tensor<*xf64>
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%9 = tensor.cast %c32 : tensor<3x3xcomplex<f32>> to tensor<*xcomplex<f32>>
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%10 = tensor.cast %c64 : tensor<3x3xcomplex<f64>> to tensor<*xcomplex<f64>>
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%11 = tensor.cast %ind : tensor<3x3xindex> to tensor<*xindex>
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// CHECK: data =
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// CHECK-NEXT: {{\[}}[Z, Z, Z],
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// CHECK-NEXT: [Z, Z, Z],
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// CHECK-NEXT: [Z, Z, Z]]
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//
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call @printMemrefI8(%1) : (tensor<*xi8>) -> ()
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// CHECK-NEXT: data =
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// CHECK-NEXT: {{\[}}[1, 1, 1],
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// CHECK-NEXT: [1, 1, 1],
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// CHECK-NEXT: [1, 1, 1]]
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//
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call @printMemrefI16(%2) : (tensor<*xi16>) -> ()
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// CHECK-NEXT: data =
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// CHECK-NEXT: {{\[}}[2, 2, 2],
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// CHECK-NEXT: [2, 2, 2],
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// CHECK-NEXT: [2, 2, 2]]
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//
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call @printMemrefI32(%3) : (tensor<*xi32>) -> ()
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// CHECK-NEXT: data =
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// CHECK-NEXT: {{\[}}[3, 3, 3],
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// CHECK-NEXT: [3, 3, 3],
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// CHECK-NEXT: [3, 3, 3]]
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//
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call @printMemrefI64(%4) : (tensor<*xi64>) -> ()
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// CHECK-NEXT: data =
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// CHECK-NEXT: {{\[}}[1.5, 1.5, 1.5],
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// CHECK-NEXT: [1.5, 1.5, 1.5],
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// CHECK-NEXT: [1.5, 1.5, 1.5]]
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//
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call @printMemrefF16(%5) : (tensor<*xf16>) -> ()
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// CHECK-NEXT: data =
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// CHECK-NEXT: {{\[}}[2.5, 2.5, 2.5],
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// CHECK-NEXT: [2.5, 2.5, 2.5],
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// CHECK-NEXT: [2.5, 2.5, 2.5]]
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//
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call @printMemrefBF16(%6) : (tensor<*xbf16>) -> ()
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// CHECK-NEXT: data =
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// CHECK-NEXT: {{\[}}[3.5, 3.5, 3.5],
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// CHECK-NEXT: [3.5, 3.5, 3.5],
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// CHECK-NEXT: [3.5, 3.5, 3.5]]
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//
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call @printMemrefF32(%7) : (tensor<*xf32>) -> ()
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// CHECK-NEXT: data =
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// CHECK-NEXT: {{\[}}[4.5, 4.5, 4.5],
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// CHECK-NEXT: [4.5, 4.5, 4.5],
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// CHECK-NEXT: [4.5, 4.5, 4.5]]
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//
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call @printMemrefF64(%8) : (tensor<*xf64>) -> ()
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// CHECK-NEXT: data =
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// CHECK-NEXT: {{\[}}[(10,5), (10,5), (10,5)],
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// CHECK-NEXT: [(10,5), (10,5), (10,5)],
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// CHECK-NEXT: [(10,5), (10,5), (10,5)]]
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//
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call @printMemrefC32(%9) : (tensor<*xcomplex<f32>>) -> ()
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// CHECK-NEXT: data =
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// CHECK-NEXT: {{\[}}[(20,5), (20,5), (20,5)],
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// CHECK-NEXT: [(20,5), (20,5), (20,5)],
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// CHECK-NEXT: [(20,5), (20,5), (20,5)]]
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//
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call @printMemrefC64(%10) : (tensor<*xcomplex<f64>>) -> ()
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// CHECK-NEXT: data =
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// CHECK-NEXT: {{\[}}[4, 4, 4],
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// CHECK-NEXT: [4, 4, 4],
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// CHECK-NEXT: [4, 4, 4]]
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//
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call @printMemrefInd(%11) : (tensor<*xindex>) -> ()
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return
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}
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}

‎utils/bazel/llvm-project-overlay/mlir/BUILD.bazel

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@@ -9132,6 +9132,7 @@ cc_library(
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includes = ["include"],
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deps = [
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":mlir_c_runner_utils",
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":mlir_float16_utils",
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"//llvm:Support",
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],
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)

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