[PATCH] D140833: [MLIR][Tosa] Make Tosa_IntArrayAttr5, Tosa_IntArrayAttr6 use DenseI64ArrayAttr
Alexander Shaposhnikov via Phabricator via llvm-commits
llvm-commits at lists.llvm.org
Sun Jan 1 17:49:57 PST 2023
alexander-shaposhnikov created this revision.
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Switch Tosa_IntArrayAttr5, Tosa_IntArrayAttr6 to DenseI64ArrayAttr.
This diff is a continuation of D140832 <https://reviews.llvm.org/D140832>.
Repository:
rG LLVM Github Monorepo
https://reviews.llvm.org/D140833
Files:
mlir/include/mlir/Dialect/Tosa/IR/TosaTypesBase.td
mlir/lib/Dialect/Tosa/IR/TosaOps.cpp
mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir
Index: mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir
===================================================================
--- mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir
+++ mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir
@@ -780,7 +780,7 @@
// CHECK-LABEL: @conv3d_static
func.func @conv3d_static(%input: tensor<2x8x9x10x3xf32>, %weights: tensor<5x3x6x4x3xf32>, %bias: tensor<5xf32>) -> () {
// CHECK: -> tensor<2x6x4x7x5xf32>
- %0 = "tosa.conv3d"(%input, %weights, %bias) {dilation = array<i64: 1, 1, 1>, pad = [0, 0, 0, 0, 0, 0], stride = array<i64: 1, 1, 1>} : (tensor<2x8x9x10x3xf32>, tensor<5x3x6x4x3xf32>, tensor<5xf32>) -> (tensor<?x?x?x?x?xf32>)
+ %0 = "tosa.conv3d"(%input, %weights, %bias) {dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<2x8x9x10x3xf32>, tensor<5x3x6x4x3xf32>, tensor<5xf32>) -> (tensor<?x?x?x?x?xf32>)
return
}
@@ -789,7 +789,7 @@
// CHECK-LABEL: @conv3d_dynamic_input
func.func @conv3d_dynamic_input(%arg0: tensor<?x?x?x?x?xf32>, %arg1: tensor<5x3x6x4x3xf32>, %arg2: tensor<5xf32>) {
// CHECK: -> tensor<?x?x?x?x5xf32>
- %0 = "tosa.conv3d"(%arg0, %arg1, %arg2) {dilation = array<i64: 1, 1, 1>, pad = [0, 0, 0, 0, 0, 0], stride = array<i64: 1, 1, 1>} : (tensor<?x?x?x?x?xf32>, tensor<5x3x6x4x3xf32>, tensor<5xf32>) -> tensor<?x?x?x?x?xf32>
+ %0 = "tosa.conv3d"(%arg0, %arg1, %arg2) {dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<?x?x?x?x?xf32>, tensor<5x3x6x4x3xf32>, tensor<5xf32>) -> tensor<?x?x?x?x?xf32>
return
}
@@ -798,7 +798,7 @@
// CHECK-LABEL: @conv3d_dynamic_weight
func.func @conv3d_dynamic_weight(%arg0: tensor<2x8x9x10x3xf32>, %arg1: tensor<?x?x?x?x?xf32>, %arg2: tensor<5xf32>) {
// CHECK: -> tensor<2x?x?x?x5xf32>
- %0 = "tosa.conv3d"(%arg0, %arg1, %arg2) {dilation = array<i64: 1, 1, 1>, pad = [0, 0, 0, 0, 0, 0], stride = array<i64: 1, 1, 1>} : (tensor<2x8x9x10x3xf32>, tensor<?x?x?x?x?xf32>, tensor<5xf32>) -> tensor<?x?x?x?x?xf32>
+ %0 = "tosa.conv3d"(%arg0, %arg1, %arg2) {dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<2x8x9x10x3xf32>, tensor<?x?x?x?x?xf32>, tensor<5xf32>) -> tensor<?x?x?x?x?xf32>
return
}
@@ -807,7 +807,7 @@
// CHECK-LABEL: @conv3d_dynamic_bias
func.func @conv3d_dynamic_bias(%arg0: tensor<2x8x9x10x3xf32>, %arg1: tensor<5x3x6x4x3xf32>, %arg2: tensor<?xf32>) {
// CHECK: -> tensor<2x6x4x7x5xf32>
- %0 = "tosa.conv3d"(%arg0, %arg1, %arg2) {dilation = array<i64: 1, 1, 1>, pad = [0, 0, 0, 0, 0, 0], stride = array<i64: 1, 1, 1>} : (tensor<2x8x9x10x3xf32>, tensor<5x3x6x4x3xf32>, tensor<?xf32>) -> tensor<?x?x?x?x?xf32>
+ %0 = "tosa.conv3d"(%arg0, %arg1, %arg2) {dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<2x8x9x10x3xf32>, tensor<5x3x6x4x3xf32>, tensor<?xf32>) -> tensor<?x?x?x?x?xf32>
return
}
@@ -816,7 +816,7 @@
// CHECK-LABEL: @conv3d_padded
func.func @conv3d_padded(%arg0: tensor<2x8x9x10x3xf32>, %arg1: tensor<5x3x6x4x3xf32>, %arg2: tensor<5xf32>) {
// CHECK: -> tensor<2x9x11x18x5xf32>
- %0 = "tosa.conv3d"(%arg0, %arg1, %arg2) {dilation = array<i64: 1, 1, 1>, pad = [1, 2, 3, 4, 5, 6], stride = array<i64: 1, 1, 1>} : (tensor<2x8x9x10x3xf32>, tensor<5x3x6x4x3xf32>, tensor<5xf32>) -> tensor<?x?x?x?x?xf32>
+ %0 = "tosa.conv3d"(%arg0, %arg1, %arg2) {dilation = array<i64: 1, 1, 1>, pad = array<i64: 1, 2, 3, 4, 5, 6>, stride = array<i64: 1, 1, 1>} : (tensor<2x8x9x10x3xf32>, tensor<5x3x6x4x3xf32>, tensor<5xf32>) -> tensor<?x?x?x?x?xf32>
return
}
@@ -825,7 +825,7 @@
// CHECK-LABEL: @conv3d_dilated
func.func @conv3d_dilated(%arg0: tensor<2x12x14x16x3xf32>, %arg1: tensor<5x3x6x2x3xf32>, %arg2: tensor<5xf32>) {
// CHECK: -> tensor<2x6x4x12x5xf32>
- %0 = "tosa.conv3d"(%arg0, %arg1, %arg2) {dilation = array<i64: 3, 2, 4>, pad = [0, 0, 0, 0, 0, 0], stride = array<i64: 1, 1, 1>} : (tensor<2x12x14x16x3xf32>, tensor<5x3x6x2x3xf32>, tensor<5xf32>) -> tensor<?x?x?x?x?xf32>
+ %0 = "tosa.conv3d"(%arg0, %arg1, %arg2) {dilation = array<i64: 3, 2, 4>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<2x12x14x16x3xf32>, tensor<5x3x6x2x3xf32>, tensor<5xf32>) -> tensor<?x?x?x?x?xf32>
return
}
@@ -834,7 +834,7 @@
// CHECK-LABEL: @conv3d_strided
func.func @conv3d_strided(%arg0: tensor<1x13x14x15x1xf32>, %arg1: tensor<1x1x1x1x1xf32>, %arg2: tensor<1xf32>) {
// CHECK: -> tensor<1x5x7x4x1xf32>
- %0 = "tosa.conv3d"(%arg0, %arg1, %arg2) {dilation = array<i64: 1, 1, 1>, pad = [0, 0, 0, 0, 0, 0], stride = array<i64: 3, 2, 4>} : (tensor<1x13x14x15x1xf32>, tensor<1x1x1x1x1xf32>, tensor<1xf32>) -> tensor<?x?x?x?x?xf32>
+ %0 = "tosa.conv3d"(%arg0, %arg1, %arg2) {dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 3, 2, 4>} : (tensor<1x13x14x15x1xf32>, tensor<1x1x1x1x1xf32>, tensor<1xf32>) -> tensor<?x?x?x?x?xf32>
return
}
Index: mlir/lib/Dialect/Tosa/IR/TosaOps.cpp
===================================================================
--- mlir/lib/Dialect/Tosa/IR/TosaOps.cpp
+++ mlir/lib/Dialect/Tosa/IR/TosaOps.cpp
@@ -1098,8 +1098,7 @@
llvm::ArrayRef<int64_t> dilation = adaptor.getDilation();
llvm::ArrayRef<int64_t> stride = adaptor.getStride();
- llvm::SmallVector<int64_t> pad;
- getI64Values(adaptor.getPad(), pad);
+ llvm::ArrayRef<int64_t> pad = adaptor.getPad();
if (!ShapedType::isDynamic(inputDepth) &&
!ShapedType::isDynamic(weightDepth)) {
Index: mlir/include/mlir/Dialect/Tosa/IR/TosaTypesBase.td
===================================================================
--- mlir/include/mlir/Dialect/Tosa/IR/TosaTypesBase.td
+++ mlir/include/mlir/Dialect/Tosa/IR/TosaTypesBase.td
@@ -176,8 +176,8 @@
def Tosa_IntArrayAttr2 : ConfinedAttr<DenseI64ArrayAttr, [DenseArrayCount<2>]>;
def Tosa_IntArrayAttr3 : ConfinedAttr<DenseI64ArrayAttr, [DenseArrayCount<3>]>;
def Tosa_IntArrayAttr4 : ConfinedAttr<DenseI64ArrayAttr, [DenseArrayCount<4>]>;
-def Tosa_IntArrayAttr5 : ConfinedAttr<I64ArrayAttr, [ArrayCount<5>]>;
-def Tosa_IntArrayAttr6 : ConfinedAttr<I64ArrayAttr, [ArrayCount<6>]>;
+def Tosa_IntArrayAttr5 : ConfinedAttr<DenseI64ArrayAttr, [DenseArrayCount<5>]>;
+def Tosa_IntArrayAttr6 : ConfinedAttr<DenseI64ArrayAttr, [DenseArrayCount<6>]>;
def Tosa_IntArrayAttrUpto2 : ConfinedAttr<I64ArrayAttr, [ArrayMaxCt<2>]>;
def Tosa_IntArrayAttrUpto4 : ConfinedAttr<I64ArrayAttr, [ArrayMaxCt<4>]>;
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