[Mlir-commits] [mlir] f426be1 - Revert "[mlir][linalg] Add runtime verification for linalg ops" (#89780)
llvmlistbot at llvm.org
llvmlistbot at llvm.org
Tue Apr 23 08:56:03 PDT 2024
Author: Ryan Holt
Date: 2024-04-23T11:55:59-04:00
New Revision: f426be195a08874686d01783bbc490295bf4afb2
URL: https://github.com/llvm/llvm-project/commit/f426be195a08874686d01783bbc490295bf4afb2
DIFF: https://github.com/llvm/llvm-project/commit/f426be195a08874686d01783bbc490295bf4afb2.diff
LOG: Revert "[mlir][linalg] Add runtime verification for linalg ops" (#89780)
Reverts llvm/llvm-project#89342 due to build failure
Added:
Modified:
mlir/include/mlir/InitAllDialects.h
mlir/include/mlir/Interfaces/RuntimeVerifiableOpInterface.td
mlir/lib/Dialect/Linalg/Transforms/CMakeLists.txt
mlir/lib/Dialect/MemRef/Transforms/RuntimeOpVerification.cpp
mlir/lib/Interfaces/RuntimeVerifiableOpInterface.cpp
Removed:
mlir/include/mlir/Dialect/Linalg/Transforms/RuntimeOpVerification.h
mlir/lib/Dialect/Linalg/Transforms/RuntimeOpVerification.cpp
mlir/test/Dialect/Linalg/runtime-verification.mlir
mlir/test/Integration/Dialect/Linalg/CPU/runtime-verification.mlir
################################################################################
diff --git a/mlir/include/mlir/Dialect/Linalg/Transforms/RuntimeOpVerification.h b/mlir/include/mlir/Dialect/Linalg/Transforms/RuntimeOpVerification.h
deleted file mode 100644
index 6c3643f7835cbe8..000000000000000
--- a/mlir/include/mlir/Dialect/Linalg/Transforms/RuntimeOpVerification.h
+++ /dev/null
@@ -1,21 +0,0 @@
-//===- RuntimeOpVerification.h - Op Verification ----------------*- C++ -*-===//
-//
-// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
-// See https://llvm.org/LICENSE.txt for license information.
-// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
-//
-//===----------------------------------------------------------------------===//
-
-#ifndef MLIR_DIALECT_LINALG_RUNTIMEOPVERIFICATION_H
-#define MLIR_DIALECT_LINALG_RUNTIMEOPVERIFICATION_H
-
-namespace mlir {
-class DialectRegistry;
-
-namespace linalg {
-void registerRuntimeVerifiableOpInterfaceExternalModels(
- DialectRegistry ®istry);
-} // namespace linalg
-} // namespace mlir
-
-#endif // MLIR_DIALECT_LINALG_RUNTIMEOPVERIFICATION_H
diff --git a/mlir/include/mlir/InitAllDialects.h b/mlir/include/mlir/InitAllDialects.h
index d9db21073e15c7a..c4d788cf8ed3166 100644
--- a/mlir/include/mlir/InitAllDialects.h
+++ b/mlir/include/mlir/InitAllDialects.h
@@ -45,7 +45,6 @@
#include "mlir/Dialect/LLVMIR/ROCDLDialect.h"
#include "mlir/Dialect/Linalg/IR/Linalg.h"
#include "mlir/Dialect/Linalg/Transforms/AllInterfaces.h"
-#include "mlir/Dialect/Linalg/Transforms/RuntimeOpVerification.h"
#include "mlir/Dialect/MLProgram/IR/MLProgram.h"
#include "mlir/Dialect/MLProgram/Transforms/BufferizableOpInterfaceImpl.h"
#include "mlir/Dialect/MPI/IR/MPI.h"
@@ -162,7 +161,6 @@ inline void registerAllDialects(DialectRegistry ®istry) {
cf::registerBufferDeallocationOpInterfaceExternalModels(registry);
gpu::registerBufferDeallocationOpInterfaceExternalModels(registry);
linalg::registerAllDialectInterfaceImplementations(registry);
- linalg::registerRuntimeVerifiableOpInterfaceExternalModels(registry);
memref::registerAllocationOpInterfaceExternalModels(registry);
memref::registerBufferViewFlowOpInterfaceExternalModels(registry);
memref::registerRuntimeVerifiableOpInterfaceExternalModels(registry);
diff --git a/mlir/include/mlir/Interfaces/RuntimeVerifiableOpInterface.td b/mlir/include/mlir/Interfaces/RuntimeVerifiableOpInterface.td
index 6fd0df59d9d2e08..d5f11d00cc3d2ab 100644
--- a/mlir/include/mlir/Interfaces/RuntimeVerifiableOpInterface.td
+++ b/mlir/include/mlir/Interfaces/RuntimeVerifiableOpInterface.td
@@ -35,12 +35,6 @@ def RuntimeVerifiableOpInterface : OpInterface<"RuntimeVerifiableOpInterface"> {
"::mlir::Location":$loc)
>,
];
-
- let extraClassDeclaration = [{
- /// Generate the error message that will be printed to the user when
- /// verification fails.
- static std::string generateErrorMessage(Operation *op, const std::string &msg);
- }];
}
#endif // MLIR_INTERFACES_RUNTIMEVERIFIABLEOPINTERFACE
diff --git a/mlir/lib/Dialect/Linalg/Transforms/CMakeLists.txt b/mlir/lib/Dialect/Linalg/Transforms/CMakeLists.txt
index 44d95bbc02d4ed8..ee6e391d0cc6826 100644
--- a/mlir/lib/Dialect/Linalg/Transforms/CMakeLists.txt
+++ b/mlir/lib/Dialect/Linalg/Transforms/CMakeLists.txt
@@ -27,7 +27,6 @@ add_mlir_dialect_library(MLIRLinalgTransforms
NamedOpConversions.cpp
Padding.cpp
Promotion.cpp
- RuntimeOpVerification.cpp
Specialize.cpp
Split.cpp
SplitReduction.cpp
diff --git a/mlir/lib/Dialect/Linalg/Transforms/RuntimeOpVerification.cpp b/mlir/lib/Dialect/Linalg/Transforms/RuntimeOpVerification.cpp
deleted file mode 100644
index b30182dc84079fe..000000000000000
--- a/mlir/lib/Dialect/Linalg/Transforms/RuntimeOpVerification.cpp
+++ /dev/null
@@ -1,135 +0,0 @@
-//===- RuntimeOpVerification.cpp - Op Verification ------------------------===//
-//
-// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
-// See https://llvm.org/LICENSE.txt for license information.
-// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
-//
-//===----------------------------------------------------------------------===//
-
-#include "mlir/Dialect/Linalg/Transforms/RuntimeOpVerification.h"
-
-#include "mlir/Dialect/Affine/IR/AffineOps.h"
-#include "mlir/Dialect/Arith/IR/Arith.h"
-#include "mlir/Dialect/Arith/Utils/Utils.h"
-#include "mlir/Dialect/ControlFlow/IR/ControlFlowOps.h"
-#include "mlir/Dialect/Index/IR/IndexAttrs.h"
-#include "mlir/Dialect/Index/IR/IndexDialect.h"
-#include "mlir/Dialect/Index/IR/IndexOps.h"
-#include "mlir/Dialect/Linalg/IR/Linalg.h"
-#include "mlir/Dialect/MemRef/IR/MemRef.h"
-#include "mlir/Dialect/Tensor/IR/Tensor.h"
-#include "mlir/Interfaces/RuntimeVerifiableOpInterface.h"
-
-namespace mlir {
-namespace linalg {
-namespace {
-/// Verify that the runtime sizes of the operands to linalg structured ops are
-/// compatible with the runtime sizes inferred by composing the loop ranges with
-/// the linalg op's indexing maps. This is similar to the verifier except that
-/// here we insert IR to perform the verification at runtime.
-template <typename T>
-struct StructuredOpInterface
- : public RuntimeVerifiableOpInterface::ExternalModel<
- StructuredOpInterface<T>, T> {
- void generateRuntimeVerification(Operation *op, OpBuilder &builder,
- Location loc) const {
- auto linalgOp = llvm::cast<LinalgOp>(op);
-
- SmallVector<Range> loopRanges = linalgOp.createLoopRanges(builder, loc);
- auto [starts, ends, _] = getOffsetsSizesAndStrides(loopRanges);
-
- auto zero = builder.create<arith::ConstantIndexOp>(loc, 0);
- auto one = builder.create<arith::ConstantIndexOp>(loc, 1);
-
- // Subtract one from the loop ends before composing with the indexing map
- transform(ends, ends.begin(), [&](OpFoldResult end) {
- auto endValue = getValueOrCreateConstantIndexOp(builder, loc, end);
- return builder.createOrFold<index::SubOp>(loc, endValue, one);
- });
-
- for (OpOperand &opOperand : linalgOp->getOpOperands()) {
- AffineMap indexingMap = linalgOp.getMatchingIndexingMap(&opOperand);
- auto startIndices = affine::makeComposedFoldedMultiResultAffineApply(
- builder, loc, indexingMap, starts);
- auto endIndices = affine::makeComposedFoldedMultiResultAffineApply(
- builder, loc, indexingMap, ends);
-
- for (auto dim : llvm::seq(linalgOp.getRank(&opOperand))) {
- auto startIndex =
- getValueOrCreateConstantIndexOp(builder, loc, startIndices[dim]);
- auto endIndex =
- getValueOrCreateConstantIndexOp(builder, loc, endIndices[dim]);
-
- // Generate:
- // minIndex = min(startIndex, endIndex)
- // assert(minIndex >= 0)
- // To ensure we do not generate a negative index. We take the minimum of
- // the start and end indices in order to handle reverse loops such as
- // `affine_map<(i) -> (3 - i)>`
- auto min =
- builder.createOrFold<index::MinSOp>(loc, startIndex, endIndex);
- auto cmpOp = builder.createOrFold<index::CmpOp>(
- loc, index::IndexCmpPredicate::SGE, min, zero);
- auto msg = RuntimeVerifiableOpInterface::generateErrorMessage(
- linalgOp, "unexpected negative result on dimension #" +
- std::to_string(dim) + " of input/output operand #" +
- std::to_string(opOperand.getOperandNumber()));
- builder.createOrFold<cf::AssertOp>(loc, cmpOp, msg);
-
- // Generate:
- // inferredDimSize = max(startIndex, endIndex) + 1
- // actualDimSize = dim(operand)
- // assert(inferredDimSize <= actualDimSize)
- // To ensure that we do not index past the bounds of the operands.
- auto max =
- builder.createOrFold<index::MaxSOp>(loc, startIndex, endIndex);
-
- auto inferredDimSize =
- builder.createOrFold<index::AddOp>(loc, max, one);
-
- auto actualDimSize =
- createOrFoldDimOp(builder, loc, opOperand.get(), dim);
-
- // Similar to the verifier, when the affine expression in the indexing
- // map is complicated, we just check that the inferred dimension sizes
- // are in the boundary of the operands' size. Being more precise than
- // that is
diff icult.
- auto predicate = isa<AffineDimExpr>(indexingMap.getResult(dim))
- ? index::IndexCmpPredicate::EQ
- : index::IndexCmpPredicate::SLE;
-
- cmpOp = builder.createOrFold<index::CmpOp>(
- loc, predicate, inferredDimSize, actualDimSize);
- msg = RuntimeVerifiableOpInterface::generateErrorMessage(
- linalgOp, "dimension #" + std::to_string(dim) +
- " of input/output operand #" +
- std::to_string(opOperand.getOperandNumber()) +
- " is incompatible with inferred dimension size");
- builder.createOrFold<cf::AssertOp>(loc, cmpOp, msg);
- }
- }
- }
-};
-
-template <typename... OpTs>
-void attachInterface(MLIRContext *ctx) {
- (OpTs::template attachInterface<StructuredOpInterface<OpTs>>(*ctx), ...);
-}
-} // namespace
-} // namespace linalg
-} // namespace mlir
-
-void mlir::linalg::registerRuntimeVerifiableOpInterfaceExternalModels(
- DialectRegistry ®istry) {
- registry.addExtension(+[](MLIRContext *ctx, LinalgDialect *) {
- attachInterface<
-#define GET_OP_LIST
-#include "mlir/Dialect/Linalg/IR/LinalgStructuredOps.cpp.inc"
- >(ctx);
-
- // Load additional dialects of which ops may get created.
- ctx->loadDialect<affine::AffineDialect, arith::ArithDialect,
- cf::ControlFlowDialect, index::IndexDialect,
- tensor::TensorDialect>();
- });
-}
diff --git a/mlir/lib/Dialect/MemRef/Transforms/RuntimeOpVerification.cpp b/mlir/lib/Dialect/MemRef/Transforms/RuntimeOpVerification.cpp
index 450bfa0cec0c7ff..05b813a3b1e9084 100644
--- a/mlir/lib/Dialect/MemRef/Transforms/RuntimeOpVerification.cpp
+++ b/mlir/lib/Dialect/MemRef/Transforms/RuntimeOpVerification.cpp
@@ -20,6 +20,25 @@
using namespace mlir;
+/// Generate an error message string for the given op and the specified error.
+static std::string generateErrorMessage(Operation *op, const std::string &msg) {
+ std::string buffer;
+ llvm::raw_string_ostream stream(buffer);
+ OpPrintingFlags flags;
+ // We may generate a lot of error messages and so we need to ensure the
+ // printing is fast.
+ flags.elideLargeElementsAttrs();
+ flags.printGenericOpForm();
+ flags.skipRegions();
+ flags.useLocalScope();
+ stream << "ERROR: Runtime op verification failed\n";
+ op->print(stream, flags);
+ stream << "\n^ " << msg;
+ stream << "\nLocation: ";
+ op->getLoc().print(stream);
+ return stream.str();
+}
+
namespace mlir {
namespace memref {
namespace {
@@ -43,10 +62,8 @@ struct CastOpInterface
builder.create<arith::ConstantIndexOp>(loc, resultType.getRank());
Value isSameRank = builder.create<arith::CmpIOp>(
loc, arith::CmpIPredicate::eq, srcRank, resultRank);
- builder.create<cf::AssertOp>(
- loc, isSameRank,
- RuntimeVerifiableOpInterface::generateErrorMessage(op,
- "rank mismatch"));
+ builder.create<cf::AssertOp>(loc, isSameRank,
+ generateErrorMessage(op, "rank mismatch"));
}
// Get source offset and strides. We do not have an op to get offsets and
@@ -84,8 +101,8 @@ struct CastOpInterface
loc, arith::CmpIPredicate::eq, srcDimSz, resultDimSz);
builder.create<cf::AssertOp>(
loc, isSameSz,
- RuntimeVerifiableOpInterface::generateErrorMessage(
- op, "size mismatch of dim " + std::to_string(it.index())));
+ generateErrorMessage(op, "size mismatch of dim " +
+ std::to_string(it.index())));
}
// Get result offset and strides.
@@ -102,10 +119,8 @@ struct CastOpInterface
builder.create<arith::ConstantIndexOp>(loc, resultOffset);
Value isSameOffset = builder.create<arith::CmpIOp>(
loc, arith::CmpIPredicate::eq, srcOffset, resultOffsetVal);
- builder.create<cf::AssertOp>(
- loc, isSameOffset,
- RuntimeVerifiableOpInterface::generateErrorMessage(
- op, "offset mismatch"));
+ builder.create<cf::AssertOp>(loc, isSameOffset,
+ generateErrorMessage(op, "offset mismatch"));
}
// Check strides.
@@ -122,8 +137,8 @@ struct CastOpInterface
loc, arith::CmpIPredicate::eq, srcStride, resultStrideVal);
builder.create<cf::AssertOp>(
loc, isSameStride,
- RuntimeVerifiableOpInterface::generateErrorMessage(
- op, "stride mismatch of dim " + std::to_string(it.index())));
+ generateErrorMessage(op, "stride mismatch of dim " +
+ std::to_string(it.index())));
}
}
};
@@ -163,9 +178,7 @@ struct LoadStoreOpInterface
: andOp;
}
builder.create<cf::AssertOp>(
- loc, assertCond,
- RuntimeVerifiableOpInterface::generateErrorMessage(
- op, "out-of-bounds access"));
+ loc, assertCond, generateErrorMessage(op, "out-of-bounds access"));
}
};
@@ -235,7 +248,7 @@ struct ReinterpretCastOpInterface
builder.create<cf::AssertOp>(
loc, assertCond,
- RuntimeVerifiableOpInterface::generateErrorMessage(
+ generateErrorMessage(
op,
"result of reinterpret_cast is out-of-bounds of the base memref"));
}
@@ -280,8 +293,8 @@ struct SubViewOpInterface
builder.create<cf::AssertOp>(
loc, assertCond,
- RuntimeVerifiableOpInterface::generateErrorMessage(
- op, "subview is out-of-bounds of the base memref"));
+ generateErrorMessage(op,
+ "subview is out-of-bounds of the base memref"));
}
};
@@ -321,9 +334,8 @@ struct ExpandShapeOpInterface
builder.create<arith::ConstantIndexOp>(loc, 0));
builder.create<cf::AssertOp>(
loc, isModZero,
- RuntimeVerifiableOpInterface::generateErrorMessage(
- op, "static result dims in reassoc group do not "
- "divide src dim evenly"));
+ generateErrorMessage(op, "static result dims in reassoc group do not "
+ "divide src dim evenly"));
}
}
};
diff --git a/mlir/lib/Interfaces/RuntimeVerifiableOpInterface.cpp b/mlir/lib/Interfaces/RuntimeVerifiableOpInterface.cpp
index e823b5df179c50d..9205d8d8c34a291 100644
--- a/mlir/lib/Interfaces/RuntimeVerifiableOpInterface.cpp
+++ b/mlir/lib/Interfaces/RuntimeVerifiableOpInterface.cpp
@@ -11,28 +11,6 @@
namespace mlir {
class Location;
class OpBuilder;
-
-/// Generate an error message string for the given op and the specified error.
-std::string
-RuntimeVerifiableOpInterface::generateErrorMessage(Operation *op,
- const std::string &msg) {
- std::string buffer;
- llvm::raw_string_ostream stream(buffer);
- OpPrintingFlags flags;
- // We may generate a lot of error messages and so we need to ensure the
- // printing is fast.
- flags.elideLargeElementsAttrs();
- flags.printGenericOpForm();
- flags.skipRegions();
- flags.useLocalScope();
- stream << "ERROR: Runtime op verification failed\n";
- op->print(stream, flags);
- stream << "\n^ " << msg;
- stream << "\nLocation: ";
- op->getLoc().print(stream);
- return stream.str();
-}
-
} // namespace mlir
/// Include the definitions of the interface.
diff --git a/mlir/test/Dialect/Linalg/runtime-verification.mlir b/mlir/test/Dialect/Linalg/runtime-verification.mlir
deleted file mode 100644
index a4f29d8457e5895..000000000000000
--- a/mlir/test/Dialect/Linalg/runtime-verification.mlir
+++ /dev/null
@@ -1,43 +0,0 @@
-// RUN: mlir-opt %s -generate-runtime-verification | FileCheck %s
-
-// Most of the tests for linalg runtime-verification are implemented as integration tests.
-
-#identity = affine_map<(d0) -> (d0)>
-
-// CHECK-LABEL: @static_dims
-func.func @static_dims(%arg0: tensor<5xf32>, %arg1: tensor<5xf32>) -> (tensor<5xf32>) {
- // CHECK: %[[TRUE:.*]] = index.bool.constant true
- // CHECK: cf.assert %[[TRUE]]
- %result = tensor.empty() : tensor<5xf32>
- %0 = linalg.generic {
- indexing_maps = [#identity, #identity, #identity],
- iterator_types = ["parallel"]
- } ins(%arg0, %arg1 : tensor<5xf32>, tensor<5xf32>)
- outs(%result : tensor<5xf32>) {
- ^bb0(%gen_arg1: f32, %gen_arg2: f32, %out: f32) :
- %tmp1 = arith.addf %gen_arg1, %gen_arg2 : f32
- linalg.yield %tmp1 : f32
- } -> tensor<5xf32>
- return %0 : tensor<5xf32>
-}
-
-// -----
-
-#map = affine_map<() -> ()>
-
-// CHECK-LABEL: @scalars
-func.func @scalars(%arg0: tensor<f32>, %arg1: tensor<f32>) -> (tensor<f32>) {
- // No runtime checks are required if the operands are all scalars
- // CHECK-NOT: cf.assert
- %result = tensor.empty() : tensor<f32>
- %0 = linalg.generic {
- indexing_maps = [#map, #map, #map],
- iterator_types = []
- } ins(%arg0, %arg1 : tensor<f32>, tensor<f32>)
- outs(%result : tensor<f32>) {
- ^bb0(%gen_arg1: f32, %gen_arg2: f32, %out: f32) :
- %tmp1 = arith.addf %gen_arg1, %gen_arg2 : f32
- linalg.yield %tmp1 : f32
- } -> tensor<f32>
- return %0 : tensor<f32>
-}
diff --git a/mlir/test/Integration/Dialect/Linalg/CPU/runtime-verification.mlir b/mlir/test/Integration/Dialect/Linalg/CPU/runtime-verification.mlir
deleted file mode 100644
index b05ef9422e59674..000000000000000
--- a/mlir/test/Integration/Dialect/Linalg/CPU/runtime-verification.mlir
+++ /dev/null
@@ -1,298 +0,0 @@
-// RUN: mlir-opt %s -generate-runtime-verification \
-// RUN: -one-shot-bufferize="bufferize-function-boundaries" \
-// RUN: -convert-linalg-to-loops \
-// RUN: -expand-strided-metadata \
-// RUN: -lower-affine \
-// RUN: -convert-scf-to-cf \
-// RUN: -test-cf-assert \
-// RUN: -convert-index-to-llvm \
-// RUN: -finalize-memref-to-llvm \
-// RUN: -convert-func-to-llvm \
-// RUN: -reconcile-unrealized-casts | \
-// RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN: -shared-libs=%mlir_runner_utils \
-// RUN: -shared-libs=%mlir_c_runner_utils 2>&1 | \
-// RUN: FileCheck %s
-
-func.func @main() {
- %c5x = arith.constant dense<0.0> : tensor<5xf32>
- %c4x = arith.constant dense<0.0> : tensor<4xf32>
- %d5x = tensor.cast %c5x : tensor<5xf32> to tensor<?xf32>
- %d4x = tensor.cast %c4x : tensor<4xf32> to tensor<?xf32>
-
- // CHECK-NOT: ERROR: Runtime op verification failed
- func.call @simple_add(%d5x, %d5x) : (tensor<?xf32>, tensor<?xf32>) -> (tensor<?xf32>)
-
- // CHECK: ERROR: Runtime op verification failed
- // CHECK: linalg.generic
- // CHECK: ^ dimension #0 of input/output operand #1 is incompatible with inferred dimension size
- func.call @simple_add(%d5x, %d4x) : (tensor<?xf32>, tensor<?xf32>) -> (tensor<?xf32>)
-
- // CHECK: ERROR: Runtime op verification failed
- // CHECK: linalg.generic
- // CHECK: ^ dimension #0 of input/output operand #1 is incompatible with inferred dimension size
- func.call @simple_add(%d4x, %d5x) : (tensor<?xf32>, tensor<?xf32>) -> (tensor<?xf32>)
-
- %c1x1 = arith.constant dense<0.0> : tensor<1x1xf32>
- %c1x4 = arith.constant dense<0.0> : tensor<1x4xf32>
- %c4x4 = arith.constant dense<0.0> : tensor<4x4xf32>
- %c4x5 = arith.constant dense<0.0> : tensor<4x5xf32>
- %c5x4 = arith.constant dense<0.0> : tensor<5x4xf32>
- %d1x1 = tensor.cast %c1x1 : tensor<1x1xf32> to tensor<?x?xf32>
- %d1x4 = tensor.cast %c1x4 : tensor<1x4xf32> to tensor<?x?xf32>
- %d4x4 = tensor.cast %c4x4 : tensor<4x4xf32> to tensor<?x?xf32>
- %d4x5 = tensor.cast %c4x5 : tensor<4x5xf32> to tensor<?x?xf32>
- %d5x4 = tensor.cast %c5x4 : tensor<5x4xf32> to tensor<?x?xf32>
-
- // CHECK-NOT: ERROR: Runtime op verification failed
- func.call @broadcast_add(%d1x1, %d1x1) : (tensor<?x?xf32>, tensor<?x?xf32>) -> (tensor<?x?xf32>)
-
- // CHECK-NOT: ERROR: Runtime op verification failed
- func.call @broadcast_add(%d1x1, %d4x5) : (tensor<?x?xf32>, tensor<?x?xf32>) -> (tensor<?x?xf32>)
-
- // CHECK-NOT: ERROR: Runtime op verification failed
- func.call @broadcast_add(%d4x4, %d1x4) : (tensor<?x?xf32>, tensor<?x?xf32>) -> (tensor<?x?xf32>)
-
- // CHECK: ERROR: Runtime op verification failed
- // CHECK: linalg.generic
- // CHECK: ^ dimension #1 of input/output operand #1 is incompatible with inferred dimension size
- func.call @broadcast_add(%d1x4, %d4x5) : (tensor<?x?xf32>, tensor<?x?xf32>) -> (tensor<?x?xf32>)
-
- // CHECK: ERROR: Runtime op verification failed
- // CHECK: linalg.generic
- // CHECK: ^ dimension #0 of input/output operand #1 is incompatible with inferred dimension size
- // CHECK: ERROR: Runtime op verification failed
- // CHECK: linalg.generic
- // CHECK: ^ dimension #1 of input/output operand #1 is incompatible with inferred dimension size
- // CHECK: ERROR: Runtime op verification failed
- // CHECK: linalg.generic
- // CHECK: ^ dimension #1 of input/output operand #2 is incompatible with inferred dimension size
- func.call @broadcast_add(%d5x4, %d4x5) : (tensor<?x?xf32>, tensor<?x?xf32>) -> (tensor<?x?xf32>)
-
- // CHECK-NOT: ERROR: Runtime op verification failed
- func.call @matmul_generic(%d5x4, %d4x5) : (tensor<?x?xf32>, tensor<?x?xf32>) -> (tensor<?x?xf32>)
-
- // CHECK: ERROR: Runtime op verification failed
- // CHECK: linalg.generic
- // CHECK: ^ dimension #0 of input/output operand #1 is incompatible with inferred dimension size
- func.call @matmul_generic(%d4x5, %d4x5) : (tensor<?x?xf32>, tensor<?x?xf32>) -> (tensor<?x?xf32>)
-
- // CHECK-NOT: ERROR: Runtime op verification failed
- func.call @matmul_named(%d5x4, %d4x5) : (tensor<?x?xf32>, tensor<?x?xf32>) -> (tensor<?x?xf32>)
-
- // CHECK: ERROR: Runtime op verification failed
- // CHECK: linalg.matmul
- // CHECK: ^ dimension #0 of input/output operand #1 is incompatible with inferred dimension size
- func.call @matmul_named(%d4x5, %d4x5) : (tensor<?x?xf32>, tensor<?x?xf32>) -> (tensor<?x?xf32>)
-
- %c64x57 = arith.constant dense<0.0> : tensor<16x29xf32>
- %c3x4 = arith.constant dense<0.0> : tensor<3x4xf32>
-
- // CHECK-NOT: ERROR: Runtime op verification failed
- func.call @conv(%c64x57, %c3x4) : (tensor<16x29xf32>, tensor<3x4xf32>) -> (tensor<5x7xf32>)
-
- // CHECK-NOT: ERROR: Runtime op verification failed
- func.call @reverse_from_3(%d4x) : (tensor<?xf32>) -> (tensor<?xf32>)
-
- // CHECK: ERROR: Runtime op verification failed
- // CHECK: linalg.generic
- // CHECK: unexpected negative result on dimension #0 of input/output operand #0
- func.call @reverse_from_3(%d5x) : (tensor<?xf32>) -> (tensor<?xf32>)
-
- return
-}
-
-
-#identity1D = affine_map<(d0) -> (d0)>
-
-func.func @simple_add(%arg0: tensor<?xf32>, %arg1: tensor<?xf32>) -> (tensor<?xf32>) {
- %c0 = arith.constant 0 : index
- %dim = tensor.dim %arg0, %c0 : tensor<?xf32>
- %result = tensor.empty(%dim) : tensor<?xf32>
- %0 = linalg.generic {
- indexing_maps = [#identity1D, #identity1D, #identity1D],
- iterator_types = ["parallel"]
- } ins(%arg0, %arg1 : tensor<?xf32>, tensor<?xf32>)
- outs(%result : tensor<?xf32>) {
- ^bb0(%gen_arg1: f32, %gen_arg2: f32, %out: f32) :
- %tmp1 = arith.addf %gen_arg1, %gen_arg2 : f32
- linalg.yield %tmp1 : f32
- } -> tensor<?xf32>
- return %0 : tensor<?xf32>
-}
-
-#broadcastD0 = affine_map<(d0, d1) -> (0, d1)>
-#broadcastD1 = affine_map<(d0, d1) -> (d0, 0)>
-#identity2D = affine_map<(d0, d1) -> (d0, d1)>
-
-func.func @broadcast_add(%arg0: tensor<?x?xf32>, %arg1: tensor<?x?xf32>) -> tensor<?x?xf32> {
- // Calculate maximum dimension 0
- %c0 = arith.constant 0 : index
- %dim = tensor.dim %arg0, %c0 : tensor<?x?xf32>
- %dim_0 = tensor.dim %arg1, %c0 : tensor<?x?xf32>
- %0 = arith.maxui %dim, %dim_0 : index
-
- // Calculate maximum dimension 1
- %c1 = arith.constant 1 : index
- %dim_1 = tensor.dim %arg0, %c1 : tensor<?x?xf32>
- %dim_2 = tensor.dim %arg1, %c1 : tensor<?x?xf32>
- %1 = arith.maxui %dim_1, %dim_2 : index
-
- // Broadcast dimension 0 of %arg0
- %dim_3 = tensor.dim %arg0, %c0 : tensor<?x?xf32>
- %2 = arith.cmpi eq, %dim_3, %c1 : index
- %3 = scf.if %2 -> (tensor<?x?xf32>) {
- %dim_7 = tensor.dim %arg0, %c1 : tensor<?x?xf32>
- %12 = tensor.empty(%0, %dim_7) : tensor<?x?xf32>
- %13 = linalg.generic {
- indexing_maps = [#broadcastD0, #identity2D],
- iterator_types = ["parallel", "parallel"]
- } ins(%arg0 : tensor<?x?xf32>) outs(%12 : tensor<?x?xf32>) {
- ^bb0(%in: f32, %out: f32):
- linalg.yield %in : f32
- } -> tensor<?x?xf32>
- scf.yield %13 : tensor<?x?xf32>
- } else {
- scf.yield %arg0 : tensor<?x?xf32>
- }
-
- // Broadcast dimension 1 of %arg0
- %dim_4 = tensor.dim %3, %c1 : tensor<?x?xf32>
- %4 = arith.cmpi eq, %dim_4, %c1 : index
- %5 = scf.if %4 -> (tensor<?x?xf32>) {
- %dim_7 = tensor.dim %3, %c0 : tensor<?x?xf32>
- %12 = tensor.empty(%dim_7, %1) : tensor<?x?xf32>
- %13 = linalg.generic {
- indexing_maps = [#broadcastD1, #identity2D],
- iterator_types = ["parallel", "parallel"]
- } ins(%3 : tensor<?x?xf32>) outs(%12 : tensor<?x?xf32>) {
- ^bb0(%in: f32, %out: f32):
- linalg.yield %in : f32
- } -> tensor<?x?xf32>
- scf.yield %13 : tensor<?x?xf32>
- } else {
- scf.yield %3 : tensor<?x?xf32>
- }
-
- // Broadcast dimension 0 of %arg1
- %dim_5 = tensor.dim %arg1, %c0 : tensor<?x?xf32>
- %6 = arith.cmpi eq, %dim_5, %c1 : index
- %7 = scf.if %6 -> (tensor<?x?xf32>) {
- %dim_7 = tensor.dim %arg1, %c1 : tensor<?x?xf32>
- %12 = tensor.empty(%0, %dim_7) : tensor<?x?xf32>
- %13 = linalg.generic {
- indexing_maps = [#broadcastD0, #identity2D],
- iterator_types = ["parallel", "parallel"]
- } ins(%arg1 : tensor<?x?xf32>) outs(%12 : tensor<?x?xf32>) {
- ^bb0(%in: f32, %out: f32):
- linalg.yield %in : f32
- } -> tensor<?x?xf32>
- scf.yield %13 : tensor<?x?xf32>
- } else {
- scf.yield %arg1 : tensor<?x?xf32>
- }
-
- // Broadcast dimension 1 of %arg1
- %dim_6 = tensor.dim %7, %c1 : tensor<?x?xf32>
- %8 = arith.cmpi eq, %dim_6, %c1 : index
- %9 = scf.if %8 -> (tensor<?x?xf32>) {
- %dim_7 = tensor.dim %7, %c0 : tensor<?x?xf32>
- %12 = tensor.empty(%dim_7, %1) : tensor<?x?xf32>
- %13 = linalg.generic {
- indexing_maps = [#broadcastD1, #identity2D],
- iterator_types = ["parallel", "parallel"]
- } ins(%7 : tensor<?x?xf32>) outs(%12 : tensor<?x?xf32>) {
- ^bb0(%in: f32, %out: f32):
- linalg.yield %in : f32
- } -> tensor<?x?xf32>
- scf.yield %13 : tensor<?x?xf32>
- } else {
- scf.yield %7 : tensor<?x?xf32>
- }
-
- // Perform element-wise computation
- %10 = tensor.empty(%0, %1) : tensor<?x?xf32>
- %11 = linalg.generic {
- indexing_maps = [#identity2D, #identity2D, #identity2D],
- iterator_types = ["parallel", "parallel"]
- } ins(%5, %9 : tensor<?x?xf32>, tensor<?x?xf32>) outs(%10 : tensor<?x?xf32>) {
- ^bb0(%in: f32, %in_7: f32, %out: f32):
- %12 = arith.addf %in, %in_7 : f32
- linalg.yield %12 : f32
- } -> tensor<?x?xf32>
- return %11 : tensor<?x?xf32>
-}
-
-#matmul_accesses = [
- affine_map<(m, n, k) -> (m, k)>,
- affine_map<(m, n, k) -> (k, n)>,
- affine_map<(m, n, k) -> (m, n)>
-]
-#matmul_trait = {
- iterator_types = ["parallel", "parallel", "reduction"],
- indexing_maps = #matmul_accesses
-}
-
-func.func @matmul_generic(%arg0: tensor<?x?xf32>, %arg1: tensor<?x?xf32>) -> tensor<?x?xf32> {
- %cf0 = arith.constant 0.0 : f32
- %ci0 = arith.constant 0 : index
- %ci1 = arith.constant 1 : index
- %d0 = tensor.dim %arg0, %ci0 : tensor<?x?xf32>
- %d1 = tensor.dim %arg1, %ci1 : tensor<?x?xf32>
- %splat = tensor.splat %cf0[%d0, %d1] : tensor<?x?xf32>
- %0 = linalg.generic #matmul_trait ins(%arg0, %arg1 : tensor<?x?xf32>, tensor<?x?xf32>) outs(%splat : tensor<?x?xf32>) {
- ^bb0(%in: f32, %in_0: f32, %out: f32):
- %1 = arith.mulf %in, %in_0 : f32
- %2 = arith.addf %out, %1 : f32
- linalg.yield %2 : f32
- } -> tensor<?x?xf32>
- return %0 : tensor<?x?xf32>
-}
-
-func.func @matmul_named(%arg0: tensor<?x?xf32>, %arg1: tensor<?x?xf32>) -> tensor<?x?xf32> {
- %cf0 = arith.constant 0.0 : f32
- %ci0 = arith.constant 0 : index
- %ci1 = arith.constant 1 : index
- %d0 = tensor.dim %arg0, %ci0 : tensor<?x?xf32>
- %d1 = tensor.dim %arg1, %ci1 : tensor<?x?xf32>
- %splat = tensor.splat %cf0[%d0, %d1] : tensor<?x?xf32>
- %0 = linalg.matmul ins(%arg0, %arg1 : tensor<?x?xf32>, tensor<?x?xf32>) outs(%splat : tensor<?x?xf32>) -> tensor<?x?xf32>
- return %0 : tensor<?x?xf32>
-}
-
-#conv_trait = {
- indexing_maps = [affine_map<(d0, d1, d2, d3) -> (d0 * 3 + d2, d1 * 4 + d3)>, affine_map<(d0, d1, d2, d3) -> (d2, d3)>, affine_map<(d0, d1, d2, d3) -> (d0, d1)>],
- iterator_types = ["parallel", "parallel", "reduction", "reduction"]
-}
-
-func.func @conv(%arg0: tensor<16x29xf32>, %arg1: tensor<3x4xf32>) -> (tensor<5x7xf32>) {
- %c0 = arith.constant 0.0 : f32
- %splat = tensor.splat %c0 : tensor<5x7xf32>
- %result = linalg.generic #conv_trait ins(%arg0, %arg1 : tensor<16x29xf32>, tensor<3x4xf32>) outs(%splat : tensor<5x7xf32>) {
- ^bb0(%in: f32, %in_64: f32, %out: f32):
- %5 = arith.mulf %in, %in_64 : f32
- %6 = arith.addf %out, %5 : f32
- linalg.yield %6 : f32
- } -> tensor<5x7xf32>
- return %result : tensor<5x7xf32>
-}
-
-#reverse_trait = {
- indexing_maps = [
- affine_map<(i) -> (3 - i)>,
- affine_map<(i) -> (i)>
- ],
- iterator_types = ["parallel"]
-}
-
-func.func @reverse_from_3(%arg0: tensor<?xf32>) -> (tensor<?xf32>) {
- %cf0 = arith.constant 0.0 : f32
- %ci0 = arith.constant 0 : index
- %d0 = tensor.dim %arg0, %ci0 : tensor<?xf32>
- %splat = tensor.splat %cf0[%d0] : tensor<?xf32>
- %result = linalg.generic #reverse_trait ins(%arg0: tensor<?xf32>) outs(%splat: tensor<?xf32>) {
- ^bb0(%a: f32, %b: f32):
- linalg.yield %a : f32
- } -> tensor<?xf32>
- return %result : tensor<?xf32>
-}
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