NFC: Re-organize ATen directory structure and fix warnings.

* Still some more work to do on the Transforms tree to bring it in line with the others (will do that as I add things).
pull/92/head
Stella Laurenzo 2020-10-22 14:13:26 -07:00
parent d09300886a
commit 9618c2dbf7
34 changed files with 166 additions and 2724 deletions

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@ -25,10 +25,10 @@
#include "mlir/Pass/PassManager.h"
#include "mlir/Transforms/Passes.h"
#include "npcomp/Dialect/ATen/ATenDialect.h"
#include "npcomp/Dialect/ATen/ATenOpReport.h"
#include "npcomp/Dialect/ATen/ATenPasses.h"
#include "npcomp/Dialect/ATen/LivenessReport.h"
#include "npcomp/Dialect/ATen/IR/ATenDialect.h"
#include "npcomp/Dialect/ATen/Transforms/ATenOpReport.h"
#include "npcomp/Dialect/ATen/Transforms/ATenPasses.h"
#include "npcomp/Dialect/ATen/Transforms/LivenessReport.h"
#include "init_python_bindings.h"

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@ -1,17 +1,2 @@
include_directories(${PROJECT_SOURCE_DIR}/dialect)
add_mlir_dialect(ATen aten)
set(LLVM_TARGET_DEFINITIONS ATen.td)
mlir_tablegen(ATenEnums.h.inc -gen-enum-decls)
mlir_tablegen(ATenEnums.cpp.inc -gen-enum-defs)
add_public_tablegen_target(MLIRATenEnumsIncGen)
set(LLVM_TARGET_DEFINITIONS ATenOpInterface.td)
mlir_tablegen(ATenOpInterfaces.h.inc -gen-op-interface-decls)
mlir_tablegen(ATenOpInterfaces.cpp.inc -gen-op-interface-defs)
add_public_tablegen_target(MLIRATenOpInterfacesIncGen)
add_dependencies(mlir-generic-headers MLIRATenOpInterfacesIncGen)
set(LLVM_TARGET_DEFINITIONS ATenToStd.td)
mlir_tablegen(ATenToStd.cpp.inc -gen-rewriters)
add_public_tablegen_target(MLIRATenToStdIncGen)
add_subdirectory(IR)
add_subdirectory(Transforms)

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@ -6,8 +6,8 @@
//
//===----------------------------------------------------------------------===//
#ifndef NPCOMP_DIALECT_ATEN_DIALECT_H
#define NPCOMP_DIALECT_ATEN_DIALECT_H
#ifndef NPCOMP_DIALECT_ATEN_IR_DIALECT_H
#define NPCOMP_DIALECT_ATEN_IR_DIALECT_H
#include "mlir/IR/Builders.h"
#include "mlir/IR/Dialect.h"
@ -54,7 +54,7 @@ namespace {
// Return the tensor volume (i.e., the number of elements) of the given shaped
// type. If the type does not have a rank, return 1. If the type doesn't
// have a static shape, return 0.
uint64_t getTensorVolume(const ShapedType ty) {
inline uint64_t getTensorVolume(const ShapedType ty) {
if (!ty.hasRank())
return 1;
@ -71,7 +71,7 @@ uint64_t getTensorVolume(const ShapedType ty) {
// If the type doesn't have a shape, return 1. If the type is shaped, but
// does not have a rank, return 1. If the type is shaped, but doesn't have a
// static shape, return 0.
uint64_t getTensorVolume(const Type ty) {
inline uint64_t getTensorVolume(const Type ty) {
if (auto t = ty.dyn_cast<ShapedType>()) {
return getTensorVolume(t);
} else {
@ -84,12 +84,12 @@ uint64_t getTensorVolume(const Type ty) {
} // namespace NPCOMP
} // namespace mlir
#include "npcomp/Dialect/ATen/ATenOpInterfaces.h"
#include "npcomp/Dialect/ATen/IR/ATenOpInterfaces.h"
// include TableGen generated Op definitions
#define GET_OP_CLASSES
#include "npcomp/Dialect/ATen/ATen.h.inc"
#include "npcomp/Dialect/ATen/IR/ATenOps.h.inc"
#include "npcomp/Dialect/ATen/ATenDialect.h.inc"
#include "npcomp/Dialect/ATen/IR/ATenDialect.h.inc"
#endif
#endif // NPCOMP_DIALECT_ATEN_IR_DIALECT_H

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@ -0,0 +1,40 @@
//===- ATenDialect.td --------------------------------------*- tablegen -*-===//
//
// This file is licensed 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 NPCOMP_DIALECT_ATEN_IR_ATEN_DIALECT
#define NPCOMP_DIALECT_ATEN_IR_ATEN_DIALECT
include "mlir/IR/OpBase.td"
//===----------------------------------------------------------------------===//
// Dialect definition
//===----------------------------------------------------------------------===//
/// The ATenDialect models 'A Tensor library' from Pytorch. The intention
/// is to provide an abstraction which is isomorphic with datastructures
/// returned from the pytorch jit, enabling integration with Pytorch models.
/// Most of the actual operation definitions in tablegen are themselves
/// generated from C APIs exported by Pytorch.
def ATen_Dialect : Dialect {
let name = "aten";
let cppNamespace = "::mlir::NPCOMP::aten";
}
//===----------------------------------------------------------------------===//
// Dialect types
//===----------------------------------------------------------------------===//
def ATen_ListType : DialectType<ATen_Dialect,
CPred<"$_self.isa<::mlir::NPCOMP::aten::ATenListType>()">, "ATen List">,
BuildableType<"$_builder.getType<::mlir::NPCOMP::aten::ATenListType()"> {
let typeDescription = [{
A variadic list of arguments in ATen.
}];
}
#endif // NPCOMP_DIALECT_ATEN_IR_ATEN_DIALECT

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@ -8,8 +8,8 @@
include "mlir/IR/OpBase.td"
#ifndef ATEN_OP_INTERFACES
#define ATEN_OP_INTERFACES
#ifndef NPCOMP_DIALECT_ATEN_IR_ATEN_OP_INTERFACES
#define NPCOMP_DIALECT_ATEN_IR_ATEN_OP_INTERFACES
def StatisticsOpInterface : OpInterface<"StatisticsOpInterface"> {
let description = [{
@ -67,4 +67,4 @@ def AnyScalar : TypeConstraint<Or<[AnySignlessInteger.predicate,
"scalar">;
#endif
#endif // NPCOMP_DIALECT_ATEN_IR_ATEN_OP_INTERFACES

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@ -6,15 +6,15 @@
//
//===----------------------------------------------------------------------===//
#ifndef NPCOMP_DIALECT_ATEN_OPINTERFACES_H
#define NPCOMP_DIALECT_ATEN_OPINTERFACES_H
#ifndef NPCOMP_DIALECT_ATEN_IR_OPINTERFACES_H
#define NPCOMP_DIALECT_ATEN_IR_OPINTERFACES_H
#include "mlir/IR/Types.h"
namespace mlir {
namespace NPCOMP {
#include "npcomp/Dialect/ATen/ATenOpInterfaces.h.inc"
#include "npcomp/Dialect/ATen/IR/ATenOpInterfaces.h.inc"
} // namespace NPCOMP
} // namespace mlir
#endif
#endif // NPCOMP_DIALECT_ATEN_IR_OPINTERFACES_H

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@ -6,10 +6,10 @@
//
//===----------------------------------------------------------------------===//
#ifndef NPCOMP_DIALECT_ATEN_OPSTATISTICSUTILS_H
#define NPCOMP_DIALECT_ATEN_OPSTATISTICSUTILS_H
#ifndef NPCOMP_DIALECT_ATEN_IR_OPSTATISTICSUTILS_H
#define NPCOMP_DIALECT_ATEN_IR_OPSTATISTICSUTILS_H
#include "npcomp/Dialect/ATen/ATenDialect.h"
#include "npcomp/Dialect/ATen/IR/ATenDialect.h"
#include "mlir/IR/StandardTypes.h"
#include "mlir/IR/Types.h"
@ -36,7 +36,6 @@ std::map<std::string, uint64_t> getConv2dStatistics(T *o, uint64_t groups) {
TensorType biasTy = o->bias().getType().template cast<TensorType>();
uint64_t ofm_volume = getTensorVolume(resultTy);
uint64_t ofm_depth = resultTy.getShape()[1];
uint64_t ifm_depth = inputTy.getShape()[1];
uint64_t kernel_height = weightTy.getShape()[2];
@ -142,27 +141,20 @@ uint64_t getConv2dOperandTransferVolume(T *o, unsigned int idx, bool read) {
float filter_height = weightTy.getShape()[3];
float batch_sw = inputTy.getShape()[0];
float ifm_depth_sw = inputTy.getShape()[1];
float ih = inputTy.getShape()[2];
float iw = inputTy.getShape()[3];
float ofm_depth_sw = resultTy.getShape()[1];
const float batch_hw = 4;
const float ifm_depth_hw = 32;
const float ofm_depth_hw = 32;
const float ifm_tile_height = 4;
const float ifm_tile_width = 4;
const float ofm_tile_height = 4;
const float ofm_tile_width = 4;
float ifm_aperture = ifm_tile_height - ceilf(filter_height / 2.0f);
float ifm_overlap = ceilf(filter_height / 2.0f);
float bl = ceilf(batch_sw / batch_hw);
float ol = ceilf(ofm_depth_sw / ofm_depth_hw);
float il = ceilf(ifm_depth_sw / ifm_depth_hw);
float ifm_overhead = 1.0f;
float weight_overhead = 1.0f;
@ -274,4 +266,4 @@ std::map<std::string, uint64_t> getReLUOpStatistics(T op) {
} // namespace NPCOMP
} // namespace mlir
#endif
#endif // NPCOMP_DIALECT_ATEN_IR_OPSTATISTICSUTILS_H

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@ -6,39 +6,13 @@
//
//===----------------------------------------------------------------------===//
include "mlir/IR/OpBase.td"
#ifndef NPCOMP_DIALECT_ATEN_IR_ATEN_OPS
#define NPCOMP_DIALECT_ATEN_IR_ATEN_OPS
#ifndef ATEN_OPS
#define ATEN_OPS
include "npcomp/Dialect/ATen/IR/ATenDialect.td"
include "npcomp/Dialect/ATen/IR/ATenOpInterface.td"
include "mlir/Interfaces/SideEffectInterfaces.td"
include "npcomp/Dialect/ATen/ATenOpInterface.td"
//===----------------------------------------------------------------------===//
// Dialect definition
//===----------------------------------------------------------------------===//
/// The ATenDialect models 'A Tensor library' from Pytorch. The intention
/// is to provide an abstraction which is isomorphic with datastructures
/// returned from the pytorch jit, enabling integration with Pytorch models.
/// Most of the actual operation definitions in tablegen are themselves
/// generated from C APIs exported by Pytorch.
def ATen_Dialect : Dialect {
let name = "aten";
let cppNamespace = "::mlir::NPCOMP::aten";
}
//===----------------------------------------------------------------------===//
// Dialect types
//===----------------------------------------------------------------------===//
def ATen_ListType : DialectType<ATen_Dialect,
CPred<"$_self.isa<::mlir::NPCOMP::aten::ATenListType>()">, "ATen List">,
BuildableType<"$_builder.getType<::mlir::NPCOMP::aten::ATenListType()"> {
let typeDescription = [{
A variadic list of arguments in ATen.
}];
}
// TODO: convert to "let results =" style
// TODO: Rename prefix from "aten" to "ATen" for consistency.
@ -48,7 +22,7 @@ class aten_Op<string mnemonic, list<OpTrait> traits = [StatisticsOpInterface]> :
// Most ops are automatically generated from pytorch specs.
include "npcomp/Dialect/ATen/ATenOps.td"
include "npcomp/Dialect/ATen/IR/GeneratedATenOps.td"
def aten_BatchNormOp: aten_Op<"batch_norm", [NoSideEffect, StatisticsOpInterface]>,
@ -179,4 +153,4 @@ def aten_TypeCastOp : aten_Op<"type_cast", [NoSideEffect]>,
);
}
#endif
#endif // NPCOMP_DIALECT_ATEN_IR_ATEN_OPS

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@ -0,0 +1,19 @@
set(dialect_namespace aten)
set(LLVM_TARGET_DEFINITIONS ATenOps.td)
mlir_tablegen(ATenOps.h.inc -gen-op-decls)
mlir_tablegen(ATenOps.cpp.inc -gen-op-defs)
mlir_tablegen(ATenDialect.h.inc -gen-dialect-decls -dialect=${dialect_namespace})
mlir_tablegen(ATenEnums.h.inc -gen-enum-decls)
mlir_tablegen(ATenEnums.cpp.inc -gen-enum-defs)
add_public_tablegen_target(MLIRATenIncGen)
add_dependencies(mlir-headers MLIRATenIncGen)
set(LLVM_TARGET_DEFINITIONS ATenOpInterface.td)
mlir_tablegen(ATenOpInterfaces.h.inc -gen-op-interface-decls)
mlir_tablegen(ATenOpInterfaces.cpp.inc -gen-op-interface-defs)
add_public_tablegen_target(MLIRATenOpInterfacesIncGen)
add_dependencies(mlir-generic-headers MLIRATenOpInterfacesIncGen)
add_mlir_doc(ATenDialect -gen-dialect-doc ATenDialect ATen/)
add_mlir_doc(ATenOps -gen-op-doc ATenOps ATen/)

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@ -7,8 +7,8 @@
//
//===----------------------------------------------------------------------===//
#ifndef ATEN_OP_DEFS
#define ATEN_OP_DEFS
#ifndef NPCOMP_DIALECT_ATEN_IR_GENERATED_ATEN_OPS
#define NPCOMP_DIALECT_ATEN_IR_GENERATED_ATEN_OPS
def aten_AddOp: aten_Op<"add", [NoSideEffect, StatisticsOpInterface]>,
Results<(outs AnyTensor)> {
@ -730,4 +730,4 @@ def aten_MaxPool2dWithIndicesBackwardOp: aten_Op<"max_pool2d_with_indices_backwa
}];
}
#endif
#endif // NPCOMP_DIALECT_ATEN_IR_GENERATED_ATEN_OPS

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@ -11,6 +11,8 @@
#include <memory>
#include "mlir/Pass/Pass.h"
namespace mlir {
class Pass;
} // namespace mlir

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@ -9,10 +9,10 @@
#ifndef NPCOMP_DIALECT_ATEN_PASSES_H
#define NPCOMP_DIALECT_ATEN_PASSES_H
#include "npcomp/Dialect/ATen/ATenLayerNamePass.h"
#include "npcomp/Dialect/ATen/ATenLoweringPass.h"
#include "npcomp/Dialect/ATen/ATenOpReport.h"
#include "npcomp/Dialect/ATen/ReturnEliminationPass.h"
#include "npcomp/Dialect/ATen/Transforms/ATenLayerNamePass.h"
#include "npcomp/Dialect/ATen/Transforms/ATenLoweringPass.h"
#include "npcomp/Dialect/ATen/Transforms/ATenOpReport.h"
#include "npcomp/Dialect/ATen/Transforms/ReturnEliminationPass.h"
namespace mlir {
namespace NPCOMP {

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@ -6,19 +6,11 @@
//
//===----------------------------------------------------------------------===//
#ifdef MLIR_ATEN_TO_STD_TD
#else
#ifndef MLIR_ATEN_TO_STD_TD
#define MLIR_ATEN_TO_STD_TD
#ifdef STANDARD_OPS
#else
include "mlir/Dialect/StandardOps/IR/Ops.td"
#endif // STANDARD_OPS
#ifdef ATEN_OPS
#else
include "ATen.td"
#endif
include "npcomp/Dialect/ATen/IR/ATenOps.td"
// The pytorch convolution operator has 9 arguments, but we only have a jit
// library that supports the first six at the moment.

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@ -0,0 +1,3 @@
set(LLVM_TARGET_DEFINITIONS ATenToStd.td)
mlir_tablegen(ATenToStd.cpp.inc -gen-rewriters)
add_public_tablegen_target(MLIRATenToStdIncGen)

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@ -11,6 +11,9 @@
#include <string>
#include "mlir/IR/Module.h"
#include "llvm/ADT/DenseMap.h"
namespace mlir {
namespace NPCOMP {
namespace aten {

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@ -1,25 +1,2 @@
add_npcomp_dialect_library(NPCOMPATenDialect
ATenDialect.cpp
ATenDialectOpStats.cpp
ATenPasses.cpp
ATenLayerNamePass.cpp
ATenLoweringPass.cpp
ATenOpReport.cpp
ATenToStd.cpp
LivenessReport.cpp
ReturnEliminationPass.cpp
ADDITIONAL_HEADER_DIRS
${PROJECT_SOURCE_DIR}/dialect/include
${PROJECT_BINARY_DIR}/dialect/include
DEPENDS
MLIRATenIncGen
MLIRATenEnumsIncGen
MLIRATenOpInterfacesIncGen
MLIRATenToStdIncGen
LINK_LIBS PUBLIC
MLIRPass
MLIRTransformUtils
)
add_subdirectory(IR)
add_subdirectory(Transforms)

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@ -6,7 +6,7 @@
//
//===----------------------------------------------------------------------===//
#include "npcomp/Dialect/ATen/ATenDialect.h"
#include "npcomp/Dialect/ATen/IR/ATenDialect.h"
#include "mlir/IR/DialectImplementation.h"
using namespace mlir;
@ -56,8 +56,6 @@ mlir::Type ATenListType::getElementType() {
}
mlir::Type ATenDialect::parseType(DialectAsmParser &parser) const {
Location loc = parser.getEncodedSourceLoc(parser.getNameLoc());
// All types start with an identifier that we switch on.
StringRef typeNameSpelling;
if (failed(parser.parseKeyword(&typeNameSpelling)))
@ -99,11 +97,11 @@ void ATenDialect::initialize() {
addTypes<ATenListType>();
addOperations<
#define GET_OP_LIST
#include "npcomp/Dialect/ATen/ATen.cpp.inc"
#include "npcomp/Dialect/ATen/IR/ATenOps.cpp.inc"
>();
}
#define GET_OP_CLASSES
#include "npcomp/Dialect/ATen/ATen.cpp.inc"
#include "npcomp/Dialect/ATen/IR/ATenOps.cpp.inc"
#include "npcomp/Dialect/ATen/ATenOpInterfaces.cpp.inc"
#include "npcomp/Dialect/ATen/IR/ATenOpInterfaces.cpp.inc"

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@ -6,8 +6,8 @@
//
//===----------------------------------------------------------------------===//
#include "npcomp/Dialect/ATen/ATenDialect.h"
#include "npcomp/Dialect/ATen/ATenOpStatisticsUtils.h"
#include "npcomp/Dialect/ATen/IR/ATenDialect.h"
#include "npcomp/Dialect/ATen/IR/ATenOpStatisticsUtils.h"
#include "llvm/Support/Debug.h"

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@ -0,0 +1,17 @@
add_npcomp_dialect_library(NPCOMPATenDialect
ATenDialect.cpp
ATenDialectOpStats.cpp
ADDITIONAL_HEADER_DIRS
${PROJECT_SOURCE_DIR}/include/npcomp/Dialect/ATen
DEPENDS
MLIRATenIncGen
#MLIRATenEnumsIncGen
MLIRATenOpInterfacesIncGen
#MLIRATenToStdIncGen
LINK_LIBS PUBLIC
MLIRPass
MLIRTransformUtils
)

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@ -6,8 +6,8 @@
//
//===----------------------------------------------------------------------===//
#include "npcomp/Dialect/ATen/ATenLayerNamePass.h"
#include "npcomp/Dialect/ATen/ATenDialect.h"
#include "npcomp/Dialect/ATen/Transforms/ATenLayerNamePass.h"
#include "npcomp/Dialect/ATen/IR/ATenDialect.h"
#include "llvm/Support/Debug.h"
#include "llvm/Support/ErrorHandling.h"

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@ -6,9 +6,9 @@
//
//===----------------------------------------------------------------------===//
#include "npcomp/Dialect/ATen/ATenLoweringPass.h"
#include "npcomp/Dialect/ATen/ATenDialect.h"
#include "npcomp/Dialect/ATen/ATenToStd.h"
#include "npcomp/Dialect/ATen/Transforms/ATenLoweringPass.h"
#include "npcomp/Dialect/ATen/IR/ATenDialect.h"
#include "npcomp/Dialect/ATen/Transforms/ATenToStd.h"
#include "mlir/Dialect/Affine/EDSC/Builders.h"
#include "mlir/Dialect/Affine/IR/AffineOps.h"
@ -70,7 +70,7 @@ static Value typeCast(PatternRewriter &builder, Value val, Type destTy) {
/// unknown shape.
static MemRefType getShapeErasedMemRefType(MemRefType type) {
std::vector<int64_t> shape = type.getShape();
for (int i = 0; i < shape.size(); i++) {
for (size_t i = 0, e = shape.size(); i < e; i++) {
shape[i] = -1;
}
return MemRefType::get(shape, type.getElementType(), type.getAffineMaps(),
@ -120,27 +120,6 @@ static std::string getFullyMangledType(const Type ty) {
return ret.str();
}
// Mangle the argument shapes into the function name. This is impractical for
// a library-based implementation, since each different shape has to be
// implemented by a different function. The function name is constructed
// from the prefix, the mangled result types, the mangled operand types.
// Types are mangled in a way that encodes the full shape information.
static std::string getFullyMangledFuncName(std::string prefix,
FunctionType fnTy) {
std::string sep = "_";
ArrayRef<Type> resultTy = fnTy.getResults();
ArrayRef<Type> operTy = fnTy.getInputs();
std::string ret = prefix + "_AtenAcapOp_";
for (const Type t : resultTy)
ret = ret + sep + getFullyMangledType(t);
for (const Type t : operTy)
ret = ret + sep + getFullyMangledType(t);
return ret;
}
// Mangle the argument ranks into the function name.
// TODO: Currently only supports MemRef, Float, Integer, and AtenList (poorly)
static std::string getSimplyMangledType(const Type ty) {
@ -192,15 +171,6 @@ static std::string getSimplyMangledFuncName(std::string prefix,
return ret;
}
static std::string getSimplyMangledFuncName(std::string prefix,
FunctionType fnTy) {
return getSimplyMangledFuncName(prefix, fnTy.getInputs(), fnTy.getResults());
}
std::string getMangledFuncName(std::string prefix, FunctionType fnTy) {
return getSimplyMangledFuncName(prefix, fnTy);
}
std::string getMangledFuncName(std::string prefix, ArrayRef<Type> opTys,
ArrayRef<Type> retTys) {
@ -254,13 +224,10 @@ public:
Value result = rewriter.create<AllocOp>(loc, memRefResultTy);
Value lhs = memRefTypeCast(rewriter, operands[0]);
Value rhs = memRefTypeCast(rewriter, operands[1]);
auto indexType = IndexType::get(op->getContext());
using namespace edsc;
ScopedContext scope(rewriter, loc);
Value zero = intrinsics::std_constant_index(0);
Value one = intrinsics::std_constant_index(1);
MemRefBoundsCapture vRes(result), vLHS(lhs), vRHS(rhs);
StdIndexedValue iRes(result), iLHS(lhs), iRHS(rhs);
Value M(vRes.ub(0));
@ -345,8 +312,6 @@ LogicalResult rewriteWithVoidFunctionCallExplicit(
TensorType tensorResultTy = t.cast<TensorType>();
MemRefType memRefResultTy = mlir::MemRefType::get(
tensorResultTy.getShape(), tensorResultTy.getElementType(), {}, 0);
MemRefType erasedMemRefResultTy =
getShapeErasedMemRefType(memRefResultTy);
retTys.push_back(memRefResultTy);
// assume memRefResultTy has known shape, so we don't need any
@ -367,8 +332,7 @@ LogicalResult rewriteWithVoidFunctionCallExplicit(
FuncOp funcOp = getATenFn(op->getParentOfType<ModuleOp>(),
mangledFunctionName, newOps, empty);
auto new_call =
callOperation(empty, rewriter.getSymbolRefAttr(funcOp), newOps);
callOperation(empty, rewriter.getSymbolRefAttr(funcOp), newOps);
rewriter.replaceOp(op, newResults);
return success();
@ -442,8 +406,6 @@ public:
auto loc = op->getLoc();
edsc::ScopedContext scope(rewriter, loc);
auto constOp = cast<mlir::NPCOMP::aten::ConstantOp>(op);
Value result = op->getResult(0);
Type t = result.getType();
if (t.isa<IntegerType>()) {

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@ -6,8 +6,7 @@
//
//===----------------------------------------------------------------------===//
#include "npcomp/Dialect/ATen/ATenOpReport.h"
#include "npcomp/Dialect/ATen/ATenDialect.h"
#include "npcomp/Dialect/ATen/Transforms/ATenOpReport.h"
#include "llvm/Support/Debug.h"
#include "llvm/Support/ErrorHandling.h"
@ -15,6 +14,7 @@
#include "llvm/Support/raw_ostream.h"
#include "mlir/Pass/Pass.h"
#include "npcomp/Dialect/ATen/IR/ATenDialect.h"
#include <iostream>
#include <vector>
@ -25,10 +25,6 @@ using namespace mlir;
namespace {
std::string getAsString(std::map<std::string, uint64_t> &m, std::string &e) {
return m.count(e) ? std::to_string(m[e]) : " ";
}
/// Query operations through the StatisticsOpInterface and print the result
/// in a human-readable way. This replicates the functionality in various
/// network analysis tools and is a stepping stone toward using the information

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@ -6,7 +6,7 @@
//
//===----------------------------------------------------------------------===//
#include "npcomp/Dialect/ATen/ATenPasses.h"
#include "npcomp/Dialect/ATen/Transforms/ATenPasses.h"
using namespace mlir::NPCOMP::aten;

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@ -6,16 +6,17 @@
//
//===----------------------------------------------------------------------===//
#include "npcomp/Dialect/ATen/ATenToStd.h"
#include "npcomp/Dialect/ATen/Transforms/ATenToStd.h"
#include "mlir/Dialect/StandardOps/IR/Ops.h"
#include "npcomp/Dialect/ATen/ATenDialect.h"
#include "npcomp/Dialect/ATen/IR/ATenDialect.h"
using namespace mlir;
using namespace mlir::NPCOMP;
namespace {
// import patterns
#include "npcomp/Dialect/ATen/ATenToStd.cpp.inc"
#include "npcomp/Dialect/ATen/Transforms/ATenToStd.cpp.inc"
} // namespace
namespace mlir {

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@ -0,0 +1,12 @@
add_npcomp_conversion_library(NPCOMPATenPasses
ATenPasses.cpp
ATenLayerNamePass.cpp
ATenLoweringPass.cpp
ATenOpReport.cpp
ATenToStd.cpp
LivenessReport.cpp
ReturnEliminationPass.cpp
DEPENDS
MLIRATenToStdIncGen
)

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@ -6,7 +6,8 @@
//
//===----------------------------------------------------------------------===//
#include "npcomp/Dialect/ATen/ATenDialect.h"
#include "npcomp/Dialect/ATen/Transforms/LivenessReport.h"
#include "npcomp/Dialect/ATen/IR/ATenDialect.h"
#include "mlir/Analysis/Liveness.h"
#include "mlir/Dialect/StandardOps/IR/Ops.h"
@ -15,8 +16,6 @@
#include "llvm/Support/Debug.h"
#include "llvm/Support/JSON.h"
#include "npcomp/Dialect/ATen/LivenessReport.h"
#include <iostream>
#include <sstream>
#include <vector>
@ -25,28 +24,6 @@
using namespace mlir;
namespace {
uint64_t getTensorVolume(const ShapedType ty) {
if (!ty.hasRank())
return 1;
uint64_t volume = 1;
for (auto &d : ty.getShape())
volume *= d;
return volume;
}
uint64_t getTensorVolume(const Type ty) {
if (auto t = ty.dyn_cast<ShapedType>()) {
return getTensorVolume(t);
} else {
return 1;
}
}
} // namespace
namespace mlir {
namespace NPCOMP {
namespace aten {
@ -72,9 +49,6 @@ std::string LivenessReport::generateTextReport() {
std::string LivenessReport::emitJSONReport() {
resolveLiveness();
llvm::json::Object top;
auto context = module.getContext();
auto loc = mlir::UnknownLoc::get(context);
auto graph = module.lookupSymbol<mlir::FuncOp>("graph");
std::map<Operation *, std::vector<Value>> liveAt;
@ -117,7 +91,6 @@ std::string LivenessReport::emitJSONReport() {
if (v.getDefiningOp()) {
if (auto a =
v.getDefiningOp()->getAttrOfType<StringAttr>("layer_name")) {
auto definingOp = v.getDefiningOp();
auto ld = layerDetail.getInteger(a.getValue().str());
if (ld)
layerDetail[a.getValue().str()] = *ld + vol;

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@ -6,8 +6,8 @@
//
//===----------------------------------------------------------------------===//
#include "npcomp/Dialect/ATen/ReturnEliminationPass.h"
#include "npcomp/Dialect/ATen/ATenDialect.h"
#include "npcomp/Dialect/ATen/Transforms/ReturnEliminationPass.h"
#include "npcomp/Dialect/ATen/IR/ATenDialect.h"
#include "llvm/Support/Debug.h"
#include "llvm/Support/ErrorHandling.h"
@ -78,8 +78,8 @@ public:
newCallArgs.push_back(valueMap[v]);
}
auto newCallOp = builder->create<CallOp>(op->getLoc(), newFnName,
ArrayRef<Type>{}, newCallArgs);
builder->create<CallOp>(op->getLoc(), newFnName, ArrayRef<Type>{},
newCallArgs);
erasedOps.insert(op);
auto fn = module.lookupSymbol<FuncOp>(callOp.callee());
if (fn && fn.use_empty())
@ -105,7 +105,6 @@ public:
void runOnOperation() override {
auto module = getOperation();
auto context = module.getContext();
// check that a function called "graph" exists
auto graph = module.lookupSymbol<mlir::FuncOp>("graph");

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@ -8,8 +8,8 @@
#include "npcomp/InitAll.h"
#include "npcomp/Dialect/ATen/ATenDialect.h"
#include "npcomp/Dialect/ATen/ATenPasses.h"
#include "npcomp/Dialect/ATen/IR/ATenDialect.h"
#include "npcomp/Dialect/ATen/Transforms/ATenPasses.h"
#include "npcomp/Dialect/Basicpy/IR/BasicpyDialect.h"
#include "npcomp/Dialect/Basicpy/Transforms/Passes.h"
#include "npcomp/Dialect/Numpy/IR/NumpyDialect.h"

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@ -28,8 +28,6 @@ using namespace mlir::NPCOMP;
// conversion about them.
//===----------------------------------------------------------------------===//
namespace {
// This is a type conversion similar to CallOpSignatureConversion.
class LowerSelectOpTypes : public OpConversionPattern<SelectOp> {