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[Encoding] Retire original_type field. (iree-org#18586)
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It is no longer needed because the encoding op has the padding semantics
now. We don't need the attribute for the original type.

Signed-off-by: hanhanW <hanhan0912@gmail.com>
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@hanhanW
hanhanW authored Sep 24, 2024
1 parent 863ca01 commit b2dd6db
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Showing 14 changed files with 183 additions and 196 deletions.
108 changes: 54 additions & 54 deletions compiler/src/iree/compiler/Codegen/Common/CPU/test/llvmcpu_materialize_encoding.mlir
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6 changes: 3 additions & 3 deletions compiler/src/iree/compiler/Codegen/Common/CPU/test/vmvx_materialize_encoding.mlir
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Original file line number Diff line number Diff line change
Expand Up @@ -89,9 +89,9 @@ func.func @matmul_lowering_i8i8i32_vmvx_ukernel() attributes {
#map2 = affine_map<(d0, d1, d2) -> (d0, d2)>
#map3 = affine_map<(d0, d1, d2) -> (d2, d1)>
#map4 = affine_map<(d0, d1, d2) -> (d0, d1)>
#encoding_lhs = #iree_encoding.encoding<operand_index = 0, op_type = matmul, element_types = [f32, f32, f32], original_type = tensor<1x2xf32>, user_indexing_maps = [#map2, #map3, #map4], round_dims_to = array<i64: 16, 16, 16>>
#encoding_rhs = #iree_encoding.encoding<operand_index = 1, op_type = matmul, element_types = [f32, f32, f32], original_type = tensor<2x3xf32>, user_indexing_maps = [#map2, #map3, #map4], round_dims_to = array<i64: 16, 16, 16>>
#encoding_result = #iree_encoding.encoding<operand_index = 2, op_type = matmul, element_types = [f32, f32, f32], original_type = tensor<1x3xf32>, user_indexing_maps = [#map2, #map3, #map4], round_dims_to = array<i64: 16, 16, 16>>
#encoding_lhs = #iree_encoding.encoding<operand_index = 0, op_type = matmul, element_types = [f32, f32, f32], user_indexing_maps = [#map2, #map3, #map4], round_dims_to = array<i64: 16, 16, 16>>
#encoding_rhs = #iree_encoding.encoding<operand_index = 1, op_type = matmul, element_types = [f32, f32, f32], user_indexing_maps = [#map2, #map3, #map4], round_dims_to = array<i64: 16, 16, 16>>
#encoding_result = #iree_encoding.encoding<operand_index = 2, op_type = matmul, element_types = [f32, f32, f32], user_indexing_maps = [#map2, #map3, #map4], round_dims_to = array<i64: 16, 16, 16>>
func.func @fill_matmul(%arg0: index, %arg1: index, %arg2: index, %arg3: index, %arg4: index, %arg5: index, %arg6: index, %arg7: index) attributes {
hal.executable.target = #hal.executable.target<"vmvx", "vmvx-bytecode-fb">
} {
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9 changes: 1 addition & 8 deletions compiler/src/iree/compiler/Codegen/Common/EncodingUtils.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -30,13 +30,7 @@ static RankedTensorType transposeIfNarrowNResult(RankedTensorType tensorType) {
return tensorType;
}
auto newIndex = encoding.getOperandIndex();
TypeAttr originalTypeAttr = encoding.getOriginalType();
RankedTensorType originalType = tensorType;
if (originalTypeAttr) {
originalType =
llvm::dyn_cast<RankedTensorType>(originalTypeAttr.getValue());
}
SmallVector<int64_t> newOriginalShape(originalType.getShape());
SmallVector<int64_t> newOriginalShape(tensorType.getShape());
auto userIndexingMaps = encoding.getUserIndexingMaps();
SmallVector<AffineMap> maps;
for (auto a : userIndexingMaps) {
Expand Down Expand Up @@ -92,7 +86,6 @@ static RankedTensorType transposeIfNarrowNResult(RankedTensorType tensorType) {
// just use the original map for the new encoding.
auto newEncoding = IREE::Encoding::EncodingAttr::get(
context, newIndex, opTypeAttr, encoding.getElementTypes(),
TypeAttr::get(RankedTensorType::get(newOriginalShape, elemType)),
encoding.getMatmulNarrow_N(), encoding.getMatmulNarrow_M(),
newIndexingMaps, encoding.getBcastMap(),
DenseI64ArrayAttr::get(context, newRoundDimsTo));
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22 changes: 11 additions & 11 deletions compiler/src/iree/compiler/Codegen/Common/GPU/test/gpu_materialize_encoding.mlir
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Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,7 @@
// 1. MFMA_F32_16x16x4_F32
//-----------------------------------------------------------------------------

#encoding = #iree_encoding.encoding<operand_index = 0, op_type = matmul, element_types = [f32, f32, f32], original_type = tensor<255x513xf32>,
#encoding = #iree_encoding.encoding<operand_index = 0, op_type = matmul, element_types = [f32, f32, f32],
user_indexing_maps = [affine_map<(d0, d1, d2) -> (d0, d2)>, affine_map<(d0, d1, d2) -> (d2, d1)>, affine_map<(d0, d1, d2) -> (d0, d1)>],
round_dims_to = array<i64: 16, 16, 16>>
#pipeline_layout = #hal.pipeline.layout<bindings = [
Expand All @@ -28,7 +28,7 @@ func.func @empty_fill_encoding_unroll8x8x4_MFMA_F32_16x16x4_F32() {

// -----

#encoding = #iree_encoding.encoding<operand_index = 0, op_type = matmul, element_types = [f32, f32, f32], original_type = tensor<255x513xf32>,
#encoding = #iree_encoding.encoding<operand_index = 0, op_type = matmul, element_types = [f32, f32, f32],
user_indexing_maps = [affine_map<(d0, d1, d2) -> (d0, d2)>, affine_map<(d0, d1, d2) -> (d2, d1)>, affine_map<(d0, d1, d2) -> (d0, d1)>],
round_dims_to = array<i64: 16, 16, 16>>
#pipeline_layout = #hal.pipeline.layout<bindings = [
Expand Down Expand Up @@ -61,7 +61,7 @@ func.func @set_encoding_LHS_unroll8x8x4_MFMA_F32_16x16x4_F32() {

// -----

#encoding = #iree_encoding.encoding<operand_index = 0, op_type = matmul, element_types = [f32, f32, f32], original_type = tensor<?x?xf32>,
#encoding = #iree_encoding.encoding<operand_index = 0, op_type = matmul, element_types = [f32, f32, f32],
user_indexing_maps = [affine_map<(d0, d1, d2) -> (d0, d2)>, affine_map<(d0, d1, d2) -> (d2, d1)>, affine_map<(d0, d1, d2) -> (d0, d1)>],
round_dims_to = array<i64: 16, 16, 16>>
#pipeline_layout = #hal.pipeline.layout<constants = 2, bindings = [
Expand Down Expand Up @@ -104,7 +104,7 @@ func.func @set_encoding_LHS_dynamic_unroll8x8x4_MFMA_F32_16x16x4_F32() {

// -----

#encoding = #iree_encoding.encoding<operand_index = 1, op_type = matmul, element_types = [f32, f32, f32], original_type = tensor<255x513xf32>,
#encoding = #iree_encoding.encoding<operand_index = 1, op_type = matmul, element_types = [f32, f32, f32],
user_indexing_maps = [affine_map<(d0, d1, d2) -> (d0, d2)>, affine_map<(d0, d1, d2) -> (d2, d1)>, affine_map<(d0, d1, d2) -> (d0, d1)>],
round_dims_to = array<i64: 16, 16, 16>>
#pipeline_layout = #hal.pipeline.layout<bindings = [
Expand Down Expand Up @@ -137,7 +137,7 @@ func.func @set_encoding_RHS_unroll8x8x4_MFMA_F32_16x16x4_F32() {

// -----

#encoding = #iree_encoding.encoding<operand_index = 2, op_type = matmul, element_types = [f32, f32, f32], original_type = tensor<255x513xf32>,
#encoding = #iree_encoding.encoding<operand_index = 2, op_type = matmul, element_types = [f32, f32, f32],
user_indexing_maps = [affine_map<(d0, d1, d2) -> (d0, d2)>, affine_map<(d0, d1, d2) -> (d2, d1)>, affine_map<(d0, d1, d2) -> (d0, d1)>],
round_dims_to = array<i64: 16, 16, 16>>
#pipeline_layout = #hal.pipeline.layout<bindings = [
Expand Down Expand Up @@ -170,7 +170,7 @@ func.func @set_encoding_ACC_unroll8x8x4_MFMA_F32_16x16x4_F32() {

// -----

#encoding = #iree_encoding.encoding<operand_index = 2, op_type = matmul, element_types = [f32, f32, f32], original_type = tensor<255x513xf32>,
#encoding = #iree_encoding.encoding<operand_index = 2, op_type = matmul, element_types = [f32, f32, f32],
user_indexing_maps = [affine_map<(d0, d1, d2) -> (d0, d2)>, affine_map<(d0, d1, d2) -> (d2, d1)>, affine_map<(d0, d1, d2) -> (d0, d1)>],
round_dims_to = array<i64: 16, 16, 16>>
#pipeline_layout = #hal.pipeline.layout<bindings = [
Expand Down Expand Up @@ -203,7 +203,7 @@ func.func @unset_encoding_ACC_unroll8x8x4_MFMA_F32_16x16x4_F32() {

// -----

#encoding = #iree_encoding.encoding<operand_index = 2, op_type = matmul, element_types = [f32, f32, f32], original_type = tensor<?x?xf32>,
#encoding = #iree_encoding.encoding<operand_index = 2, op_type = matmul, element_types = [f32, f32, f32],
user_indexing_maps = [affine_map<(d0, d1, d2) -> (d0, d2)>, affine_map<(d0, d1, d2) -> (d2, d1)>, affine_map<(d0, d1, d2) -> (d0, d1)>],
round_dims_to = array<i64: 16, 16, 16>>
#pipeline_layout = #hal.pipeline.layout<constants = 2, bindings = [
Expand Down Expand Up @@ -308,7 +308,7 @@ func.func @matmul_lowering_unroll8x8x4_MFMA_F32_16x16x4_F32() {
// 2. MFMA_I32_16x16x32_I8
//-----------------------------------------------------------------------------

#encoding = #iree_encoding.encoding<operand_index = 0, op_type = matmul, element_types = [i8, i8, i32], original_type = tensor<255x513xi8>,
#encoding = #iree_encoding.encoding<operand_index = 0, op_type = matmul, element_types = [i8, i8, i32],
user_indexing_maps = [affine_map<(d0, d1, d2) -> (d0, d2)>, affine_map<(d0, d1, d2) -> (d2, d1)>, affine_map<(d0, d1, d2) -> (d0, d1)>],
round_dims_to = array<i64: 16, 16, 32>>
#pipeline_layout = #hal.pipeline.layout<bindings = [
Expand Down Expand Up @@ -341,7 +341,7 @@ func.func @set_encoding_LHS_unroll8x8x2_MFMA_I32_16x16x32_I8() {

// -----

#encoding = #iree_encoding.encoding<operand_index = 1, op_type = matmul, element_types = [i8, i8, i32], original_type = tensor<255x513xi8>,
#encoding = #iree_encoding.encoding<operand_index = 1, op_type = matmul, element_types = [i8, i8, i32],
user_indexing_maps = [affine_map<(d0, d1, d2) -> (d0, d2)>, affine_map<(d0, d1, d2) -> (d2, d1)>, affine_map<(d0, d1, d2) -> (d0, d1)>],
round_dims_to = array<i64: 16, 16, 32>>
#pipeline_layout = #hal.pipeline.layout<bindings = [
Expand Down Expand Up @@ -374,7 +374,7 @@ func.func @set_encoding_RHS_unroll8x8x2_MFMA_I32_16x16x32_I8() {

// -----

#encoding = #iree_encoding.encoding<operand_index = 2, op_type = matmul, element_types = [i8, i8, i32], original_type = tensor<255x513xi32>,
#encoding = #iree_encoding.encoding<operand_index = 2, op_type = matmul, element_types = [i8, i8, i32],
user_indexing_maps = [affine_map<(d0, d1, d2) -> (d0, d2)>, affine_map<(d0, d1, d2) -> (d2, d1)>, affine_map<(d0, d1, d2) -> (d0, d1)>],
round_dims_to = array<i64: 16, 16, 32>>
#pipeline_layout = #hal.pipeline.layout<bindings = [
Expand Down Expand Up @@ -407,7 +407,7 @@ func.func @set_encoding_ACC_unroll8x8x2_MFMA_I32_16x16x32_I8() {

// -----

#encoding = #iree_encoding.encoding<operand_index = 2, op_type = matmul, element_types = [i8, i8, i32], original_type = tensor<255x513xi32>,
#encoding = #iree_encoding.encoding<operand_index = 2, op_type = matmul, element_types = [i8, i8, i32],
user_indexing_maps = [affine_map<(d0, d1, d2) -> (d0, d2)>, affine_map<(d0, d1, d2) -> (d2, d1)>, affine_map<(d0, d1, d2) -> (d0, d1)>],
round_dims_to = array<i64: 16, 16, 32>>
#pipeline_layout = #hal.pipeline.layout<bindings = [
Expand Down
4 changes: 2 additions & 2 deletions compiler/src/iree/compiler/Codegen/Common/test/materialize_encoding_into_nop.mlir
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Original file line number Diff line number Diff line change
Expand Up @@ -179,7 +179,7 @@ func.func @batch_matmul_fill_dynamic(%arg0 : tensor<?x?x?xf32>, %arg1 : tensor<?
#hal.pipeline.binding<storage_buffer>,
#hal.pipeline.binding<storage_buffer>
]>
#encoding_lhs = #iree_encoding.encoding<operand_index = 0, op_type = matmul, element_types = [f32, f32, f32], original_type = tensor<1x1xf32>, matmul_narrow_M = 1 : index, matmul_narrow_N = 1 : index, user_indexing_maps = [affine_map<(d0, d1, d2) -> (d0, d2)>, affine_map<(d0, d1, d2) -> (d2, d1)>, affine_map<(d0, d1, d2) -> (d0, d1)>]>
#encoding_lhs = #iree_encoding.encoding<operand_index = 0, op_type = matmul, element_types = [f32, f32, f32], matmul_narrow_M = 1 : index, matmul_narrow_N = 1 : index, user_indexing_maps = [affine_map<(d0, d1, d2) -> (d0, d2)>, affine_map<(d0, d1, d2) -> (d2, d1)>, affine_map<(d0, d1, d2) -> (d0, d1)>]>
func.func @drop_encoding_for_hal_flow_ops_static() {
%c0 = arith.constant 0 : index
%0 = hal.interface.binding.subspan layout(#pipeline_layout) binding(0) alignment(64) offset(%c0) flags(ReadOnly) : !flow.dispatch.tensor<readonly:tensor<1x1xf32>>
Expand All @@ -201,7 +201,7 @@ func.func @drop_encoding_for_hal_flow_ops_static() {
#hal.pipeline.binding<storage_buffer>,
#hal.pipeline.binding<storage_buffer>
]>
#encoding_lhs = #iree_encoding.encoding<operand_index = 0, op_type = matmul, element_types = [bf16, bf16, bf16], original_type = tensor<?x?xbf16>, user_indexing_maps = [affine_map<(d0, d1, d2) -> (d0, d2)>, affine_map<(d0, d1, d2) -> (d2, d1)>, affine_map<(d0, d1, d2) -> (d0, d1)>]>
#encoding_lhs = #iree_encoding.encoding<operand_index = 0, op_type = matmul, element_types = [bf16, bf16, bf16], user_indexing_maps = [affine_map<(d0, d1, d2) -> (d0, d2)>, affine_map<(d0, d1, d2) -> (d2, d1)>, affine_map<(d0, d1, d2) -> (d0, d1)>]>
func.func @drop_encoding_for_hal_flow_ops_dynamic() {
%c0 = arith.constant 0 : index
%c32_i64 = arith.constant 32 : i64
Expand Down
6 changes: 3 additions & 3 deletions compiler/src/iree/compiler/Codegen/VMVX/test/select_lowering_strategy.mlir
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Original file line number Diff line number Diff line change
Expand Up @@ -195,7 +195,7 @@ func.func @elem_pack_ukernels() attributes {hal.executable.target = #executable_
%cst = arith.constant 0.000000e+00 : f32
%c0 = arith.constant 0 : index
%0 = hal.interface.binding.subspan layout(#pipeline_layout) binding(0) alignment(64) offset(%c0) flags(ReadOnly) : !flow.dispatch.tensor<readonly:tensor<1024x2048xf32>>
%1:2 = iree_codegen.query_tile_sizes tensor<1024x2048xf32, #iree_encoding.encoding<operand_index = 0, op_type = matmul, element_types = [f32, f32, f32], original_type = tensor<1024x2048xf32>>> -> index, index
%1:2 = iree_codegen.query_tile_sizes tensor<1024x2048xf32, #iree_encoding.encoding<operand_index = 0, op_type = matmul, element_types = [f32, f32, f32]>> -> index, index
%2 = affine.apply #map()[%1#0]
%3 = affine.apply #map1()[%1#1]
%4 = hal.interface.binding.subspan layout(#pipeline_layout) binding(1) alignment(64) offset(%c0) : !flow.dispatch.tensor<writeonly:tensor<?x?x?x?xf32>>{%2, %3, %1#0, %1#1}
Expand All @@ -206,12 +206,12 @@ func.func @elem_pack_ukernels() attributes {hal.executable.target = #executable_
%15 = arith.addf %in, %in : f32
linalg.yield %15 : f32
} -> tensor<1024x2048xf32>
%8:2 = iree_codegen.query_tile_sizes tensor<?x?xf32, #iree_encoding.encoding<operand_index = 0, op_type = matmul, element_types = [f32, f32, f32], original_type = tensor<1024x2048xf32>>> -> index, index
%8:2 = iree_codegen.query_tile_sizes tensor<?x?xf32, #iree_encoding.encoding<operand_index = 0, op_type = matmul, element_types = [f32, f32, f32]>> -> index, index
%9 = affine.apply #map()[%8#0]
%10 = affine.apply #map1()[%8#1]
%11 = tensor.empty(%9, %10, %8#0, %8#1) : tensor<?x?x?x?xf32>
%pack = tensor.pack %7 padding_value(%cst : f32) inner_dims_pos = [0, 1] inner_tiles = [%8#0, %8#1] into %11 : tensor<1024x2048xf32> -> tensor<?x?x?x?xf32>
%12:2 = iree_codegen.query_tile_sizes tensor<1024x2048xf32, #iree_encoding.encoding<operand_index = 0, op_type = matmul, element_types = [f32, f32, f32], original_type = tensor<1024x2048xf32>>> -> index, index
%12:2 = iree_codegen.query_tile_sizes tensor<1024x2048xf32, #iree_encoding.encoding<operand_index = 0, op_type = matmul, element_types = [f32, f32, f32]>> -> index, index
%13 = affine.apply #map()[%12#0]
%14 = affine.apply #map1()[%12#1]
flow.dispatch.tensor.store %pack, %4, offsets = [0, 0, 0, 0], sizes = [%13, %14, %12#0, %12#1], strides = [1, 1, 1, 1] : tensor<?x?x?x?xf32> -> !flow.dispatch.tensor<writeonly:tensor<?x?x?x?xf32>>{%13, %14, %12#0, %12#1}
Expand Down
3 changes: 1 addition & 2 deletions compiler/src/iree/compiler/Dialect/Encoding/IR/EncodingBase.td
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Original file line number Diff line number Diff line change
Expand Up @@ -78,7 +78,6 @@ def EncodingAttr :
AttrParameter<"IntegerAttr", "this tensor operand's index in the parameter list">:$operand_index,
AttrParameter<"EncodingOpTypeAttr", "operand type">:$op_type,
AttrParameter<"ArrayAttr", "element types of the user's operands">:$element_types,
OptionalParameter<"TypeAttr", "type of the original tensor type before padding">:$original_type,
// TODO(#15466): generalize matmul_narrow_{M,N} into a list?
OptionalParameter<"IntegerAttr", "optional M narrow dimension size (only for contraction op user_indexing_maps)">:$matmul_narrow_M,
OptionalParameter<"IntegerAttr", "optional N narrow dimension size (only for contraction op user_indexing_maps)">:$matmul_narrow_N,
Expand All @@ -91,7 +90,7 @@ def EncodingAttr :
let builders = [
AttrBuilder<(ins "int64_t":$operandIndex,
"EncodingOpType":$opType,
"ArrayRef<Type>":$elemTypes, "Type":$origType,
"ArrayRef<Type>":$elemTypes,
CArg<"std::optional<int64_t>", "{}">:$matmulNarrowM,
CArg<"std::optional<int64_t>", "{}">:$matmulNarrowN,
CArg<"ArrayRef<AffineMap>", "{}">:$maps,
Expand Down
14 changes: 6 additions & 8 deletions compiler/src/iree/compiler/Dialect/Encoding/IR/EncodingOps.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -98,7 +98,6 @@ LogicalResult UnsetEncodingOp::reifyResultShapes(

EncodingAttr EncodingAttr::get(MLIRContext *ctx, int64_t operandIndex,
EncodingOpType opType, ArrayRef<Type> elemTypes,
Type origType,
std::optional<int64_t> matmulNarrowM,
std::optional<int64_t> matmulNarrowN,
ArrayRef<AffineMap> maps,
Expand All @@ -109,17 +108,16 @@ EncodingAttr EncodingAttr::get(MLIRContext *ctx, int64_t operandIndex,
return x ? b.getIndexAttr(*x) : IntegerAttr();
};
auto opTypeAttr = EncodingOpTypeAttr::get(ctx, opType);
auto origTypeAttr = origType ? TypeAttr::get(origType) : TypeAttr();
auto roundDimsToAttr = roundDimsTo.empty()
? DenseI64ArrayAttr()
: b.getDenseI64ArrayAttr(roundDimsTo);
auto bcastMapAttr = bcastMap.has_value()
? AffineMapAttr::get(bcastMap.value())
: AffineMapAttr();
return get(ctx, b.getIndexAttr(operandIndex), opTypeAttr,
b.getTypeArrayAttr(elemTypes), origTypeAttr,
optionalToAttr(matmulNarrowM), optionalToAttr(matmulNarrowN),
b.getAffineMapArrayAttr(maps), bcastMapAttr, roundDimsToAttr);
b.getTypeArrayAttr(elemTypes), optionalToAttr(matmulNarrowM),
optionalToAttr(matmulNarrowN), b.getAffineMapArrayAttr(maps),
bcastMapAttr, roundDimsToAttr);
}

AffineMap EncodingAttr::getMapForOperandIndex() {
Expand Down Expand Up @@ -155,9 +153,9 @@ ArrayRef<int64_t> EncodingAttr::getRoundDimsToArray() {

EncodingAttr EncodingAttr::clone(AffineMap bcastMap) {
return get(bcastMap.getContext(), getOperandIndex(), getOpType(),
getElementTypes(), getOriginalType(), getMatmulNarrow_M(),
getMatmulNarrow_N(), getUserIndexingMaps(),
AffineMapAttr::get(bcastMap), getRoundDimsTo());
getElementTypes(), getMatmulNarrow_M(), getMatmulNarrow_N(),
getUserIndexingMaps(), AffineMapAttr::get(bcastMap),
getRoundDimsTo());
}

//===---------------------------------------------------------------------===//
Expand Down
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