From 5fc28ebbaf11808f0a010239f46875458589ce0d Mon Sep 17 00:00:00 2001 From: Nicolas Vasilache Date: Tue, 4 Oct 2022 05:14:30 -0700 Subject: [PATCH] [mlir][Linalg] NFC - Add bbarg pretty printing to linalg::generic Differential Revision: https://reviews.llvm.org/D135151 --- .../mlir/Dialect/Linalg/IR/LinalgStructuredOps.td | 4 +- mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp | 11 +- mlir/test/Analysis/test-match-reduction.mlir | 10 +- .../TosaToLinalg/tosa-to-linalg-named.mlir | 39 +- .../Conversion/TosaToLinalg/tosa-to-linalg.mlir | 396 ++++++++++++--------- .../Linalg/canonicalize-duplicate-inputs.mlir | 18 +- mlir/test/Dialect/Linalg/decompose-ops.mlir | 166 ++++----- .../Dialect/Linalg/fusion-elementwise-ops.mlir | 10 +- mlir/test/Dialect/Linalg/lower-pad-tensor.mlir | 4 +- mlir/test/Dialect/Linalg/reshape_fusion.mlir | 12 +- 10 files changed, 377 insertions(+), 293 deletions(-) diff --git a/mlir/include/mlir/Dialect/Linalg/IR/LinalgStructuredOps.td b/mlir/include/mlir/Dialect/Linalg/IR/LinalgStructuredOps.td index 3d1ee2f..1691291 100644 --- a/mlir/include/mlir/Dialect/Linalg/IR/LinalgStructuredOps.td +++ b/mlir/include/mlir/Dialect/Linalg/IR/LinalgStructuredOps.td @@ -58,7 +58,9 @@ class LinalgStructuredBase_Op props> // Generic Linalg ops. //===----------------------------------------------------------------------===// -def GenericOp : LinalgStructuredBase_Op<"generic", [AttrSizedOperandSegments]> { +def GenericOp : LinalgStructuredBase_Op<"generic", [ + DeclareOpInterfaceMethods, + AttrSizedOperandSegments]> { let description = [{ Generic Linalg op form where the key properties of the computation are specified as attributes. In pretty form, a `linalg.generic` op is written diff --git a/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp b/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp index 3741e7d..ba60572 100644 --- a/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp +++ b/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp @@ -663,8 +663,17 @@ void FillOp::getCanonicalizationPatterns(RewritePatternSet &results, } //===----------------------------------------------------------------------===// -// GenericOps +// GenericOp //===----------------------------------------------------------------------===// + +void GenericOp::getAsmBlockArgumentNames(Region ®ion, + OpAsmSetValueNameFn setNameFn) { + for (Value v : getRegionInputArgs()) + setNameFn(v, "in"); + for (Value v : getRegionOutputArgs()) + setNameFn(v, "out"); +} + void GenericOp::build( OpBuilder &builder, OperationState &result, TypeRange resultTensorTypes, ValueRange inputs, ValueRange outputs, ArrayAttr indexingMaps, diff --git a/mlir/test/Analysis/test-match-reduction.mlir b/mlir/test/Analysis/test-match-reduction.mlir index ef99e76..ecc74c6 100644 --- a/mlir/test/Analysis/test-match-reduction.mlir +++ b/mlir/test/Analysis/test-match-reduction.mlir @@ -7,7 +7,7 @@ func.func @linalg_red_add(%in0t : tensor, %out0t : tensor<1xf32>) { // expected-remark@below {{Reduction found in output #0!}} // expected-remark@below {{Reduced Value: of type 'f32' at index: 0}} - // expected-remark@below {{Combiner Op: %1 = arith.addf %arg2, %arg3 : f32}} + // expected-remark@below {{Combiner Op: %1 = arith.addf }} %red = linalg.generic {indexing_maps = [affine_map<(d0) -> (d0)>, affine_map<(d0) -> (0)>], iterator_types = ["reduction"]} @@ -27,8 +27,8 @@ func.func @affine_red_add(%in: memref<256x512xf32>, %out: memref<256xf32>) { %cst = arith.constant 0.000000e+00 : f32 affine.for %i = 0 to 256 { // expected-remark@below {{Reduction found in output #0!}} - // expected-remark@below {{Reduced Value: %1 = affine.load %arg0[%arg2, %arg3] : memref<256x512xf32>}} - // expected-remark@below {{Combiner Op: %2 = arith.addf %arg4, %1 : f32}} + // expected-remark@below {{Reduced Value: %1 = affine.load }} + // expected-remark@below {{Combiner Op: %2 = arith.addf }} %final_red = affine.for %j = 0 to 512 iter_args(%red_iter = %cst) -> (f32) { %ld = affine.load %in[%i, %j] : memref<256x512xf32> %add = arith.addf %red_iter, %ld : f32 @@ -63,8 +63,8 @@ func.func @linalg_red_max(%in0t: tensor<4x4xf32>, %out0t: tensor<4xf32>) { // expected-remark@below {{Testing function}} func.func @linalg_fused_red_add(%in0t: tensor<4x4xf32>, %out0t: tensor<4xf32>) { // expected-remark@below {{Reduction found in output #0!}} - // expected-remark@below {{Reduced Value: %2 = arith.subf %1, %arg2 : f32}} - // expected-remark@below {{Combiner Op: %3 = arith.addf %2, %arg3 : f32}} + // expected-remark@below {{Reduced Value: %2 = arith.subf}} + // expected-remark@below {{Combiner Op: %3 = arith.addf}} %red = linalg.generic {indexing_maps = [affine_map<(d0, d1) -> (d0, d1)>, affine_map<(d0, d1) -> (d0)>], iterator_types = ["parallel", "reduction"]} diff --git a/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg-named.mlir b/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg-named.mlir index 9bc5db3..811bf28 100644 --- a/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg-named.mlir +++ b/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg-named.mlir @@ -80,8 +80,8 @@ func.func @fully_connected(%arg0: tensor<5x3xf32>, %arg1: tensor<6x3xf32>, %arg2 // CHECK: [[INITB:%.+]] = tensor.empty() // CHECK: [[MATMUL:%.+]] = linalg.matmul ins(%arg0, [[TRANSPOSE]] : tensor<5x3xf32>, tensor<3x6xf32>) outs([[FILL]] : tensor<5x6xf32>) -> tensor<5x6xf32> // CHECK: [[ADDED:%.+]] = linalg.generic {indexing_maps = [#[[$MAP1]], #[[$MAP2]], #[[$MAP2]]], iterator_types = ["parallel", "parallel"]} ins(%arg2, [[MATMUL]] : tensor<6xf32>, tensor<5x6xf32>) outs([[INITB]] : tensor<5x6xf32>) { - // CHECK: ^bb0(%arg3: f32, %arg4: f32, %arg5: f32): - // CHECK: [[ADD:%.+]] = arith.addf %arg3, %arg4 : f32 + // CHECK: ^bb0(%[[ARG3:[0-9a-zA-Z_]+]]: f32, %[[ARG4:[0-9a-zA-Z_]+]]: f32, %[[ARG5:[0-9a-zA-Z_]+]]: f32): + // CHECK: [[ADD:%.+]] = arith.addf %[[ARG3]], %[[ARG4]] : f32 // CHECK: linalg.yield [[ADD]] : f32 %0 = "tosa.fully_connected"(%arg0, %arg1, %arg2) : (tensor<5x3xf32>, tensor<6x3xf32>, tensor<6xf32>) -> (tensor<5x6xf32>) @@ -129,8 +129,8 @@ func.func @fully_connected_dyn(%arg0: tensor, %arg1: tensor<6x3xf32>, % // CHECK: %[[INITB:.+]] = tensor.empty(%[[DIM]]) // CHECK: %[[MATMUL:.+]] = linalg.matmul ins(%arg0, %[[TRANSPOSE]] : tensor, tensor<3x6xf32>) outs(%[[FILL]] : tensor) -> tensor // CHECK: %[[ADDED:.+]] = linalg.generic {indexing_maps = [#[[$MAP1]], #[[$MAP2]], #[[$MAP2]]], iterator_types = ["parallel", "parallel"]} ins(%arg2, %[[MATMUL]] : tensor<6xf32>, tensor) outs(%[[INITB]] : tensor) { - // CHECK: ^bb0(%arg3: f32, %arg4: f32, %arg5: f32): - // CHECK: %[[ADD:.+]] = arith.addf %arg3, %arg4 : f32 + // CHECK: ^bb0(%[[ARG3:[0-9a-zA-Z_]+]]: f32, %[[ARG4:[0-9a-zA-Z_]+]]: f32, %[[ARG5:[0-9a-zA-Z_]+]]: f32): + // CHECK: %[[ADD:.+]] = arith.addf %[[ARG3]], %[[ARG4]] : f32 // CHECK: linalg.yield %[[ADD]] : f32 %0 = "tosa.fully_connected"(%arg0, %arg1, %arg2) : (tensor, tensor<6x3xf32>, tensor<6xf32>) -> (tensor) @@ -214,6 +214,7 @@ func.func @avg_pool(%arg0: tensor<1x6x34x62xf32>) -> (tensor<1x5x33x62xf32>) { // CHECK: [[POOL:%.+]] = linalg.pooling_nhwc_sum {dilations = dense<1> : vector<2xi64>, strides = dense<1> : vector<2xi64>} ins([[PAD]], [[KERNEL]] : tensor<1x8x36x62xf32>, tensor<4x4xf32>) outs([[FILL]] : tensor<1x5x33x62xf32>) // CHECK: [[INIT:%.+]] = tensor.empty() // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#map, #map], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} ins([[POOL]] : tensor<1x5x33x62xf32>) outs([[INIT]] : tensor<1x5x33x62xf32>) + // CHECK: ^bb0(%[[BBARG1:[a-zA-Z0-9_]+]]: f32, // CHECK: [[ZERO:%.0]] = arith.constant 0 // CHECK: [[ONE:%.+]] = arith.constant 1 // CHECK: [[HEIGHT:%.+]] = arith.constant 4 @@ -255,7 +256,7 @@ func.func @avg_pool(%arg0: tensor<1x6x34x62xf32>) -> (tensor<1x5x33x62xf32>) { // CHECK: [[C:%.+]] = arith.muli [[YSEL]], [[XSEL]] // CHECK: [[CI:%.+]] = arith.index_cast [[C]] // CHECK: [[CF:%.+]] = arith.sitofp [[CI]] - // CHECK: [[RESULT:%.+]] = arith.divf %arg1, [[CF]] + // CHECK: [[RESULT:%.+]] = arith.divf %[[BBARG1]], [[CF]] // CHECK: linalg.yield [[RESULT]] %0 = "tosa.avg_pool2d"(%arg0) {pad = [1, 1, 1, 1], kernel = [4, 4], stride = [1, 1]} : (tensor<1x6x34x62xf32>) -> (tensor<1x5x33x62xf32>) return %0 : tensor<1x5x33x62xf32> @@ -286,10 +287,11 @@ func.func @avg_pool_i8(%arg0 : tensor<1x128x128x2xi8>) -> () { // CHECK: linalg.pooling_nhwc_sum // CHECK: linalg.generic + // CHECK: ^bb0(%[[BBARG1:[a-zA-Z0-9_]+]]: i32, // CHECK: %[[INZP:.+]] = arith.constant -128 // CHECK: %[[INZP_OFF:.+]] = arith.muli %{{.+}}, %[[INZP]] - // CHECK: %[[OFFSETED:.+]] = arith.subi %arg1, %[[INZP_OFF]] + // CHECK: %[[OFFSETED:.+]] = arith.subi %[[BBARG1]], %[[INZP_OFF]] // CHECK: %[[NUMERATOR:.+]] = arith.constant 1073741825 // CHECK: %[[MULTIPLIER:.+]] = arith.divui %[[NUMERATOR]], %{{.+}} // CHECK: %[[SHIFT:.+]] = arith.constant 30 @@ -315,10 +317,11 @@ func.func @avg_pool_i16(%arg0 : tensor<1x128x128x2xi16>) -> () { // CHECK: linalg.pooling_nhwc_sum // CHECK: linalg.generic + // CHECK: ^bb0(%[[BBARG1:[a-zA-Z0-9_]+]]: i32, // CHECK: %[[INZP:.+]] = arith.constant -128 // CHECK: %[[INZP_OFF:.+]] = arith.muli %{{.+}}, %[[INZP]] - // CHECK: %[[OFFSETED:.+]] = arith.subi %arg1, %[[INZP_OFF]] + // CHECK: %[[OFFSETED:.+]] = arith.subi %[[BBARG1]], %[[INZP_OFF]] // CHECK: %[[NUMERATOR:.+]] = arith.constant 1073741825 // CHECK: %[[MULTIPLIER:.+]] = arith.divui %[[NUMERATOR]], %{{.+}} // CHECK: %[[SHIFT:.+]] = arith.constant 30 @@ -479,8 +482,8 @@ func.func @depthwise_conv(%arg0 : tensor<1x7x5x3xf32>, %arg1 : tensor<3x1x3x11xf // CHECK: [[DEPTH:%.+]] = linalg.depthwise_conv_2d_nhwc_hwcm {dilations = dense<1> : tensor<2xi64>, strides = dense<1> : tensor<2xi64>} ins(%arg0, %arg1 : tensor<1x7x5x3xf32>, tensor<3x1x3x11xf32>) outs([[FILL]] : tensor<1x5x5x3x11xf32>) // CHECK: [[COLLAPSED:%.+]] = tensor.collapse_shape [[DEPTH]] {{\[}}[0], [1], [2], [3, 4]] // CHECK: [[BIAS:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]], #[[$MAP1]]], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} ins(%arg2, [[COLLAPSED]] : tensor<33xf32>, tensor<1x5x5x33xf32>) outs([[OUT]] : tensor<1x5x5x33xf32>) { - // CHECK: ^bb0(%arg3: f32, %arg4: f32, %arg5: f32): - // CHECK: [[ADD:%.+]] = arith.addf %arg3, %arg4 : f32 + // CHECK: ^bb0(%[[ARG3:[0-9a-zA-Z_]+]]: f32, %[[ARG4:[0-9a-zA-Z_]+]]: f32, %[[ARG5:[0-9a-zA-Z_]+]]: f32): + // CHECK: [[ADD:%.+]] = arith.addf %[[ARG3]], %[[ARG4]] : f32 // CHECK: linalg.yield [[ADD]] : f32 // CHECK: } -> tensor<1x5x5x33xf32> %2 = "tosa.depthwise_conv2d"(%arg0, %arg1, %arg2) { pad = [0, 0, 0, 0], stride = [1, 1], dilation = [1, 1] } : (tensor<1x7x5x3xf32>, tensor<3x1x3x11xf32>, tensor<33xf32>) -> (tensor<1x5x5x33xf32>) @@ -503,8 +506,8 @@ func.func @depthwise_conv_dyn(%arg0 : tensor, %arg1 : tensor<3x1x3x // CHECK: %[[DEPTH:.+]] = linalg.depthwise_conv_2d_nhwc_hwcm {dilations = dense<1> : tensor<2xi64>, strides = dense<1> : tensor<2xi64>} ins(%arg0, %arg1 : tensor, tensor<3x1x3x11xf32>) outs(%[[FILL]] : tensor) // CHECK: %[[COLLAPSED:.+]] = tensor.collapse_shape %[[DEPTH]] {{\[}}[0], [1], [2], [3, 4]] // CHECK: %[[BIAS:.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]], #[[$MAP1]]], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} ins(%arg2, %[[COLLAPSED]] : tensor<33xf32>, tensor) outs(%[[OUT]] : tensor) { - // CHECK: ^bb0(%arg3: f32, %arg4: f32, %arg5: f32): - // CHECK: %[[ADD:.+]] = arith.addf %arg3, %arg4 : f32 + // CHECK: ^bb0(%[[ARG3:[0-9a-zA-Z_]+]]: f32, %[[ARG4:[0-9a-zA-Z_]+]]: f32, %[[ARG5:[0-9a-zA-Z_]+]]: f32): + // CHECK: %[[ADD:.+]] = arith.addf %[[ARG3]], %[[ARG4]] : f32 // CHECK: linalg.yield %[[ADD]] : f32 // CHECK: } -> tensor %2 = "tosa.depthwise_conv2d"(%arg0, %arg1, %arg2) { pad = [0, 0, 0, 0], stride = [1, 1], dilation = [1, 1] } : (tensor, tensor<3x1x3x11xf32>, tensor<33xf32>) -> (tensor) @@ -525,8 +528,8 @@ func.func @depthwise_conv_strides(%arg0 : tensor<1x11x9x3xf32>, %arg1 : tensor<3 // CHECK: [[DEPTH:%.+]] = linalg.depthwise_conv_2d_nhwc_hwcm {dilations = dense<1> : tensor<2xi64>, strides = dense<2> : tensor<2xi64>} ins(%arg0, %arg1 : tensor<1x11x9x3xf32>, tensor<3x1x3x11xf32>) outs([[FILL]] : tensor<1x5x5x3x11xf32>) // CHECK: [[COLLAPSED:%.+]] = tensor.collapse_shape [[DEPTH]] {{\[}}[0], [1], [2], [3, 4]] // CHECK: [[BIAS:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]], #[[$MAP1]]], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} ins(%arg2, [[COLLAPSED]] : tensor<33xf32>, tensor<1x5x5x33xf32>) outs([[OUT]] : tensor<1x5x5x33xf32>) { - // CHECK: ^bb0(%arg3: f32, %arg4: f32, %arg5: f32): - // CHECK: [[ADD:%.+]] = arith.addf %arg3, %arg4 : f32 + // CHECK: ^bb0(%[[ARG3:[0-9a-zA-Z_]+]]: f32, %[[ARG4:[0-9a-zA-Z_]+]]: f32, %[[ARG5:[0-9a-zA-Z_]+]]: f32): + // CHECK: [[ADD:%.+]] = arith.addf %[[ARG3]], %[[ARG4]] : f32 // CHECK: linalg.yield [[ADD]] : f32 // CHECK: } -> tensor<1x5x5x33xf32> %2 = "tosa.depthwise_conv2d"(%arg0, %arg1, %arg2) { pad = [0, 0, 0, 0], stride = [2, 2], dilation = [1, 1] } : (tensor<1x11x9x3xf32>, tensor<3x1x3x11xf32>, tensor<33xf32>) -> (tensor<1x5x5x33xf32>) @@ -553,8 +556,8 @@ func.func @depthwise_conv_quant(%arg0 : tensor<1x12x12x4xi8>, %arg1 : tensor<3x3 // CHECK: [[DEPTH:%.+]] = linalg.depthwise_conv_2d_nhwc_hwcm_q {dilations = dense<1> : tensor<2xi64>, strides = dense<1> : tensor<2xi64>} ins([[PAD]], %arg1, [[C128]], [[C42]] : tensor<1x14x14x4xi8>, tensor<3x3x4x128xi8>, i32, i32) outs([[FILL]] : tensor<1x12x12x4x128xi32>) // CHECK: [[COLLAPSED:%.+]] = tensor.collapse_shape [[DEPTH]] {{\[}}[0], [1], [2], [3, 4]] // CHECK: [[BIAS:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]], #[[$MAP1]]], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} ins(%arg2, [[COLLAPSED]] : tensor<512xi32>, tensor<1x12x12x512xi32>) outs([[OUT]] : tensor<1x12x12x512xi32>) { - // CHECK: ^bb0(%arg3: i32, %arg4: i32, %arg5: i32): - // CHECK: [[ADD:%.+]] = arith.addi %arg3, %arg4 : i32 + // CHECK: ^bb0(%[[ARG3:[0-9a-zA-Z_]+]]: i32, %[[ARG4:[0-9a-zA-Z_]+]]: i32, %[[ARG5:[0-9a-zA-Z_]+]]: i32): + // CHECK: [[ADD:%.+]] = arith.addi %[[ARG3]], %[[ARG4]] : i32 // CHECK: linalg.yield [[ADD]] : i32 // CHECK: } -> tensor<1x12x12x512xi32> %0 = "tosa.depthwise_conv2d"(%arg0, %arg1, %arg2) {pad = [1, 1, 1, 1], quantization_info = #tosa.conv_quant, stride = [1, 1], dilation = [1, 1] } : (tensor<1x12x12x4xi8>, tensor<3x3x4x128xi8>, tensor<512xi32>) -> tensor<1x12x12x512xi32> @@ -577,8 +580,8 @@ func.func @depthwise_conv_quant_dilations(%arg0 : tensor<1x14x14x4xi8>, %arg1 : // CHECK: [[DEPTH:%.+]] = linalg.depthwise_conv_2d_nhwc_hwcm_q {dilations = dense<2> : tensor<2xi64>, strides = dense<1> : tensor<2xi64>} ins(%arg0, %arg1, [[C128]], [[C42]] : tensor<1x14x14x4xi8>, tensor<3x3x4x128xi8>, i32, i32) outs([[FILL]] : tensor<1x10x10x4x128xi32>) // CHECK: [[COLLAPSED:%.+]] = tensor.collapse_shape [[DEPTH]] {{\[}}[0], [1], [2], [3, 4]] // CHECK: [[BIAS:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]], #[[$MAP1]]], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} ins(%arg2, [[COLLAPSED]] : tensor<512xi32>, tensor<1x10x10x512xi32>) outs([[OUT]] : tensor<1x10x10x512xi32>) { - // CHECK: ^bb0(%arg3: i32, %arg4: i32, %arg5: i32): - // CHECK: [[ADD:%.+]] = arith.addi %arg3, %arg4 : i32 + // CHECK: ^bb0(%[[ARG3:[0-9a-zA-Z_]+]]: i32, %[[ARG4:[0-9a-zA-Z_]+]]: i32, %[[ARG5:[0-9a-zA-Z_]+]]: i32): + // CHECK: [[ADD:%.+]] = arith.addi %[[ARG3]], %[[ARG4]] : i32 // CHECK: linalg.yield [[ADD]] : i32 // CHECK: } -> tensor<1x10x10x512xi32> %0 = "tosa.depthwise_conv2d"(%arg0, %arg1, %arg2) {pad = [0, 0, 0, 0], quantization_info = #tosa.conv_quant, stride = [1, 1], dilation = [2, 2] } : (tensor<1x14x14x4xi8>, tensor<3x3x4x128xi8>, tensor<512xi32>) -> tensor<1x10x10x512xi32> @@ -592,7 +595,7 @@ func.func @depthwise_conv2d_dyn_w_h(%arg0: tensor<2x?x?x3xf32>, %arg1: tensor<3x // CHECK: arith.muli // CHECK: arith.divui // CHECK: %[[PADDED:.+]] = tensor.pad %arg0 low[0, 1, 3, 0] high[0, 2, 4, 0] { - // CHECK: ^bb0(%arg3: index, %arg4: index, %arg5: index, %arg6: index): + // CHECK: ^bb0(%[[ARG3:[0-9a-zA-Z_]+]]: index, %[[ARG4:[0-9a-zA-Z_]+]]: index, %[[ARG5:[0-9a-zA-Z_]+]]: index, %[[ARG6:[0-9a-zA-Z_]+]]: index): // CHECK: tensor.yield %cst : f32 // CHECK: } : tensor<2x?x?x3xf32> to tensor<2x?x?x3xf32> // CHECK: %[[CONV:.+]] = linalg.depthwise_conv_2d_nhwc_hwcm {dilations = dense<[2, 1]> : tensor<2xi64>, strides = dense<[1, 2]> : tensor<2xi64>} ins(%[[PADDED]], %arg1 : tensor<2x?x?x3xf32>, tensor<3x6x3x5xf32>) outs(%{{.*}} : tensor<2x?x?x3x5xf32>) -> tensor<2x?x?x3x5xf32> diff --git a/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg.mlir b/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg.mlir index 51fb0e6..0c8af01 100644 --- a/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg.mlir +++ b/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg.mlir @@ -3,11 +3,12 @@ // CHECK: #[[$MAP0:.*]] = affine_map<() -> ()> // CHECK-LABEL: @test_abs +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]] func.func @test_abs(%arg0: tensor) -> tensor { // CHECK: [[INIT:%.+]] = tensor.empty() : tensor - // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP0]]], iterator_types = []} ins(%arg0 : tensor) outs([[INIT]] : tensor) { - // CHECK: ^bb0(%arg1: f32, %arg2: f32): - // CHECK: [[ELEMENT:%.+]] = math.absf %arg1 + // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP0]]], iterator_types = []} ins(%[[ARG0]] : tensor) outs([[INIT]] : tensor) { + // CHECK: ^bb0(%[[ARG1:.*]]: f32, %[[ARG2:.*]]: f32): + // CHECK: [[ELEMENT:%.+]] = math.absf %[[ARG1]] // CHECK: linalg.yield [[ELEMENT]] : f32 // CHECK: } -> tensor @@ -22,11 +23,12 @@ func.func @test_abs(%arg0: tensor) -> tensor { // CHECK: #[[$MAP0:.*]] = affine_map<(d0) -> (d0)> // CHECK-LABEL: @test_abs +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]] func.func @test_abs(%arg0: tensor<2xf32>) -> tensor<2xf32> { // CHECK: [[INIT:%.+]] = tensor.empty() : tensor<2xf32> - // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP0]]], iterator_types = ["parallel"]} ins(%arg0 : tensor<2xf32>) outs([[INIT]] : tensor<2xf32>) { - // CHECK: ^bb0(%arg1: f32, %arg2: f32): - // CHECK: [[ELEMENT:%.+]] = math.absf %arg1 + // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP0]]], iterator_types = ["parallel"]} ins(%[[ARG0]] : tensor<2xf32>) outs([[INIT]] : tensor<2xf32>) { + // CHECK: ^bb0(%[[ARG1:.*]]: f32, %[[ARG2:.*]]: f32): + // CHECK: [[ELEMENT:%.+]] = math.absf %[[ARG1]] // CHECK: linalg.yield [[ELEMENT]] : f32 // CHECK: } -> tensor<2xf32> %0 = "tosa.abs"(%arg0) : (tensor<2xf32>) -> tensor<2xf32> @@ -40,11 +42,12 @@ func.func @test_abs(%arg0: tensor<2xf32>) -> tensor<2xf32> { // CHECK: #[[$MAP0:.*]] = affine_map<(d0, d1) -> (d0, d1)> // CHECK-LABEL: @test_abs +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]] func.func @test_abs(%arg0: tensor<2x3xf32>) -> tensor<2x3xf32> { // CHECK: [[INIT:%.+]] = tensor.empty() : tensor<2x3xf32> - // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP0]]], iterator_types = ["parallel", "parallel"]} ins(%arg0 : tensor<2x3xf32>) outs([[INIT]] : tensor<2x3xf32>) { - // CHECK: ^bb0(%arg1: f32, %arg2: f32): - // CHECK: [[ELEMENT:%.+]] = math.absf %arg1 + // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP0]]], iterator_types = ["parallel", "parallel"]} ins(%[[ARG0]] : tensor<2x3xf32>) outs([[INIT]] : tensor<2x3xf32>) { + // CHECK: ^bb0(%[[ARG1:.*]]: f32, %[[ARG2:.*]]: f32): + // CHECK: [[ELEMENT:%.+]] = math.absf %[[ARG1]] // CHECK: linalg.yield [[ELEMENT]] : f32 // CHECK: } -> tensor<2x3xf32> %0 = "tosa.abs"(%arg0) : (tensor<2x3xf32>) -> tensor<2x3xf32> @@ -56,9 +59,10 @@ func.func @test_abs(%arg0: tensor<2x3xf32>) -> tensor<2x3xf32> { // ----- // CHECK-LABEL: @test_abs +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]] func.func @test_abs(%arg0: tensor) -> tensor { // CHECK: %[[C0:.+]] = arith.constant 0 - // CHECK: %[[DIM:.+]] = tensor.dim %arg0, %[[C0]] + // CHECK: %[[DIM:.+]] = tensor.dim %[[ARG0]], %[[C0]] // CHECK: %[[INIT:.+]] = tensor.empty(%[[DIM]]) // CHECK: linalg.generic // CHECK: math.absf @@ -71,9 +75,10 @@ func.func @test_abs(%arg0: tensor) -> tensor { // CHECK: #[[$MAP0:.*]] = affine_map<(d0, d1) -> (d0, d1)> // CHECK-LABEL: @test_abs_dyn +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]] func.func @test_abs_dyn(%arg0: tensor<2x?xf32>) -> tensor<2x?xf32> { // CHECK: %[[C1:.+]] = arith.constant 1 - // CHECK: %[[DIM:.+]] = tensor.dim %arg0, %[[C1]] + // CHECK: %[[DIM:.+]] = tensor.dim %[[ARG0]], %[[C1]] // CHECK: %[[INIT:.+]] = tensor.empty(%[[DIM]]) // CHECK: linalg.generic // CHECK: math.absf @@ -87,12 +92,14 @@ func.func @test_abs_dyn(%arg0: tensor<2x?xf32>) -> tensor<2x?xf32> { // CHECK: #[[$MAP1:.*]] = affine_map<(d0) -> (d0)> // CHECK-LABEL: @test_broadcast +// CHECK-SAME: %[[ARG0:[0-9a-zA-Z_]*]]: tensor<1xf32 +// CHECK-SAME: %[[ARG1:[0-9a-zA-Z_]*]]: tensor<2xf32> func.func @test_broadcast(%arg0: tensor<1xf32>, %arg1: tensor<2xf32>) -> tensor<2xf32> { // CHECK: [[INIT:%.+]] = tensor.empty() : tensor<2xf32> - // CHECK: [[RESHAPE:%.+]] = tensor.collapse_shape %arg0 - // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]], #[[$MAP1]]], iterator_types = ["parallel"]} ins([[RESHAPE]], %arg1 : tensor, tensor<2xf32>) outs([[INIT]] : tensor<2xf32>) { - // CHECK: ^bb0(%arg2: f32, %arg3: f32, %arg4: f32): - // CHECK: [[ELEMENT:%.+]] = arith.addf %arg2, %arg3 : f32 + // CHECK: [[RESHAPE:%.+]] = tensor.collapse_shape %[[ARG0]] + // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]], #[[$MAP1]]], iterator_types = ["parallel"]} ins([[RESHAPE]], %[[ARG1]] : tensor, tensor<2xf32>) outs([[INIT]] : tensor<2xf32>) { + // CHECK: ^bb0(%[[ARG2:.*]]: f32, %[[ARG3:.*]]: f32, %[[ARG4:.*]]: f32): + // CHECK: [[ELEMENT:%.+]] = arith.addf %[[ARG2]], %[[ARG3]] : f32 // CHECK: linalg.yield [[ELEMENT]] : f32 // CHECK: } -> tensor<2xf32> %0 = "tosa.add"(%arg0, %arg1) : (tensor<1xf32>, tensor<2xf32>) -> tensor<2xf32> @@ -105,12 +112,14 @@ func.func @test_broadcast(%arg0: tensor<1xf32>, %arg1: tensor<2xf32>) -> tensor< // CHECK: #[[$MAP1:.*]] = affine_map<(d0) -> ()> // CHECK-LABEL: @test_broadcast_swapped_args +// CHECK-SAME: %[[ARG0:[0-9a-zA-Z_]*]]: tensor<2xf32 +// CHECK-SAME: %[[ARG1:[0-9a-zA-Z_]*]]: tensor<1xf32> func.func @test_broadcast_swapped_args(%arg0: tensor<2xf32>, %arg1: tensor<1xf32>) -> tensor<2xf32> { // CHECK: [[INIT:%.+]] = tensor.empty() : tensor<2xf32> - // CHECK: [[RESHAPE:%.+]] = tensor.collapse_shape %arg1 - // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]], #[[$MAP0]]], iterator_types = ["parallel"]} ins(%arg0, [[RESHAPE]] : tensor<2xf32>, tensor) outs([[INIT]] : tensor<2xf32>) { - // CHECK: ^bb0(%arg2: f32, %arg3: f32, %arg4: f32): - // CHECK: [[ELEMENT:%.+]] = arith.addf %arg2, %arg3 : f32 + // CHECK: [[RESHAPE:%.+]] = tensor.collapse_shape %[[ARG1]] + // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]], #[[$MAP0]]], iterator_types = ["parallel"]} ins(%[[ARG0]], [[RESHAPE]] : tensor<2xf32>, tensor) outs([[INIT]] : tensor<2xf32>) { + // CHECK: ^bb0(%[[ARG2:.*]]: f32, %[[ARG3:.*]]: f32, %[[ARG4:.*]]: f32): + // CHECK: [[ELEMENT:%.+]] = arith.addf %[[ARG2]], %[[ARG3]] : f32 // CHECK: linalg.yield [[ELEMENT]] : f32 // CHECK: } -> tensor<2xf32> %0 = "tosa.add"(%arg0, %arg1) : (tensor<2xf32>, tensor<1xf32>) -> tensor<2xf32> @@ -124,13 +133,15 @@ func.func @test_broadcast_swapped_args(%arg0: tensor<2xf32>, %arg1: tensor<1xf32 // CHECK-DAG: #[[$MAP2:.*]] = affine_map<(d0, d1) -> (d0)> // CHECK-LABEL: @test_multibroadcast +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]] +// CHECK-SAME: %[[ARG1:[0-9a-zA-Z_]*]] func.func @test_multibroadcast(%arg0: tensor<1x3xf32>, %arg1: tensor<2x1xf32>) -> tensor<2x3xf32> { // CHECK: [[INIT:%.+]] = tensor.empty() : tensor<2x3xf32> - // CHECK: [[RESHAPE1:%.+]] = tensor.collapse_shape %arg0 {{\[}}[0, 1]] - // CHECK: [[RESHAPE2:%.+]] = tensor.collapse_shape %arg1 {{\[}}[0, 1]] + // CHECK: [[RESHAPE1:%.+]] = tensor.collapse_shape %[[ARG0]] {{\[}}[0, 1]] + // CHECK: [[RESHAPE2:%.+]] = tensor.collapse_shape %[[ARG1]] {{\[}}[0, 1]] // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP1]], #[[$MAP2]], #[[$MAP0]]], iterator_types = ["parallel", "parallel"]} ins([[RESHAPE1]], [[RESHAPE2]] : tensor<3xf32>, tensor<2xf32>) outs([[INIT]] : tensor<2x3xf32>) { - // CHECK: ^bb0(%arg2: f32, %arg3: f32, %arg4: f32): - // CHECK: [[ELEMENT:%.+]] = arith.addf %arg2, %arg3 : f32 + // CHECK: ^bb0(%[[ARG2:.*]]: f32, %[[ARG3:.*]]: f32, %[[ARG4:.*]]: f32): + // CHECK: [[ELEMENT:%.+]] = arith.addf %[[ARG2]], %[[ARG3]] : f32 // CHECK: linalg.yield [[ELEMENT]] : f32 // CHECK: } -> tensor<2x3xf32> %0 = "tosa.add"(%arg0, %arg1) : (tensor<1x3xf32>, tensor<2x1xf32>) -> tensor<2x3xf32> @@ -315,8 +326,9 @@ func.func @test_simple_i32(%arg0: tensor<1xi32>) -> () { %4 = "tosa.div"(%arg0, %arg0) : (tensor<1xi32>, tensor<1xi32>) -> tensor<1xi32> // CHECK: linalg.generic + // CHECK: ^bb0(%[[ARG1:.*]]: i32, %[[ARG2:.*]]: i32): // CHECK: [[ZERO:%.+]] = arith.constant 0 - // CHECK: arith.subi [[ZERO]], %arg1 + // CHECK: arith.subi [[ZERO]], %[[ARG1]] %5 = "tosa.negate"(%arg0) : (tensor<1xi32>) -> tensor<1xi32> // CHECK: linalg.generic @@ -503,8 +515,9 @@ func.func @test_bool(%arg0: tensor<1xi1>, %arg1: tensor<1xi1>) -> () { // CHECK-LABEL: @test_negate_quantized func.func @test_negate_quantized(%arg0: tensor<1xi8>) -> () { // CHECK: linalg.generic + // CHECK: ^bb0(%[[BBARG0:.+]]: i8, // CHECK: [[ZERO:%.+]] = arith.constant 0 - // CHECK: [[EXT:%.+]] = arith.extsi %arg1 : i8 to i16 + // CHECK: [[EXT:%.+]] = arith.extsi %[[BBARG0]] : i8 to i16 // CHECK: [[SUB:%.+]] = arith.subi [[ZERO]], [[EXT]] // CHECK: [[MIN:%.+]] = arith.constant -128 // CHECK: [[MAX:%.+]] = arith.constant 127 @@ -517,11 +530,13 @@ func.func @test_negate_quantized(%arg0: tensor<1xi8>) -> () { %0 = "tosa.negate"(%arg0) {quantization_info = #tosa.unary_quant} : (tensor<1xi8>) -> tensor<1xi8> // CHECK: linalg.generic - // CHECK: [[EXT:%.+]] = arith.extsi %arg1 : i8 to i16 + // CHECK: ^bb0(%[[BBARG0:.+]]: i8, + // CHECK: [[EXT:%.+]] = arith.extsi %[[BBARG0]] : i8 to i16 %1 = "tosa.negate"(%arg0) {quantization_info = #tosa.unary_quant} : (tensor<1xi8>) -> tensor<1xi8> // CHECK: linalg.generic - // CHECK: [[EXT:%.+]] = arith.extsi %arg1 : i8 to i32 + // CHECK: ^bb0(%[[BBARG0:.+]]: i8, + // CHECK: [[EXT:%.+]] = arith.extsi %[[BBARG0]] : i8 to i32 %2 = "tosa.negate"(%arg0) {quantization_info = #tosa.unary_quant} : (tensor<1xi8>) -> tensor<1xi8> return @@ -530,8 +545,9 @@ func.func @test_negate_quantized(%arg0: tensor<1xi8>) -> () { // ----- // CHECK-LABEL: @test_reshape_downrank +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]] func.func @test_reshape_downrank(%arg0: tensor<2x3xf32>) -> tensor<6xf32> { - // CHECK: [[RESHAPE:%.+]] = tensor.collapse_shape %arg0 {{\[}}[0, 1]] + // CHECK: [[RESHAPE:%.+]] = tensor.collapse_shape %[[ARG0]] {{\[}}[0, 1]] %0 = "tosa.reshape"(%arg0) {new_shape = [6]} : (tensor<2x3xf32>) -> tensor<6xf32> // CHECK: return [[RESHAPE]] return %0 : tensor<6xf32> @@ -540,8 +556,9 @@ func.func @test_reshape_downrank(%arg0: tensor<2x3xf32>) -> tensor<6xf32> { // ----- // CHECK-LABEL: @test_reshape_downrank_dyn +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]] func.func @test_reshape_downrank_dyn(%arg0: tensor<2x?xf32>) -> tensor { - // CHECK: [[RESHAPE:%.+]] = tensor.collapse_shape %arg0 {{\[}}[0, 1]] + // CHECK: [[RESHAPE:%.+]] = tensor.collapse_shape %[[ARG0]] {{\[}}[0, 1]] %0 = "tosa.reshape"(%arg0) {new_shape = [-1]} : (tensor<2x?xf32>) -> tensor // CHECK: return [[RESHAPE]] return %0 : tensor @@ -550,8 +567,9 @@ func.func @test_reshape_downrank_dyn(%arg0: tensor<2x?xf32>) -> tensor { // ----- // CHECK-LABEL: @test_reshape_uprank +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]] func.func @test_reshape_uprank(%arg0: tensor<6xf32>) -> tensor<2x3xf32> { - // CHECK: [[RESHAPE:%.+]] = tensor.expand_shape %arg0 {{\[}}[0, 1]] + // CHECK: [[RESHAPE:%.+]] = tensor.expand_shape %[[ARG0]] {{\[}}[0, 1]] %0 = "tosa.reshape"(%arg0) {new_shape = [2, 3]} : (tensor<6xf32>) -> tensor<2x3xf32> // CHECK: return [[RESHAPE]] return %0 : tensor<2x3xf32> @@ -560,8 +578,9 @@ func.func @test_reshape_uprank(%arg0: tensor<6xf32>) -> tensor<2x3xf32> { // ----- // CHECK-LABEL: @test_reshape_uprank_dyn +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]] func.func @test_reshape_uprank_dyn(%arg0: tensor) -> tensor<2x?xf32> { - // CHECK: [[RESHAPE:%.+]] = tensor.expand_shape %arg0 {{\[}}[0, 1]] + // CHECK: [[RESHAPE:%.+]] = tensor.expand_shape %[[ARG0]] {{\[}}[0, 1]] %0 = "tosa.reshape"(%arg0) {new_shape = [2, -1]} : (tensor) -> tensor<2x?xf32> // CHECK: return [[RESHAPE]] return %0 : tensor<2x?xf32> @@ -570,8 +589,8 @@ func.func @test_reshape_uprank_dyn(%arg0: tensor) -> tensor<2x?xf32> { // ----- // CHECK-LABEL: @test_reshape_samerank +// CHECK-SAME: (%[[ARG0:.*]]: tensor<3x2xf32>) func.func @test_reshape_samerank(%arg0: tensor<3x2xf32>) -> tensor<2x3xf32> { - // CHECK-SAME: (%[[ARG0:.*]]: tensor<3x2xf32>) // CHECK-NEXT: %[[RESHAPE1:.*]] = tensor.collapse_shape %[[ARG0]] {{\[}}[0, 1]] // CHECK-NEXT: %[[RESHAPE2:.*]] = tensor.expand_shape %[[RESHAPE1]] {{\[}}[0, 1]] %0 = "tosa.reshape"(%arg0) {new_shape = [2, 3]} : (tensor<3x2xf32>) -> tensor<2x3xf32> @@ -582,8 +601,8 @@ func.func @test_reshape_samerank(%arg0: tensor<3x2xf32>) -> tensor<2x3xf32> { // ----- // CHECK-LABEL: @test_reshape_samerank_dyn +// CHECK-SAME: (%[[ARG0:.*]]: tensor) func.func @test_reshape_samerank_dyn(%arg0: tensor) -> tensor<2x?xf32> { - // CHECK-SAME: (%[[ARG0:.*]]: tensor) // CHECK-NEXT: %[[RESHAPE1:.*]] = tensor.collapse_shape %[[ARG0]] {{\[}}[0, 1]] // CHECK-NEXT: %[[RESHAPE2:.*]] = tensor.expand_shape %[[RESHAPE1]] {{\[}}[0, 1]] %0 = "tosa.reshape"(%arg0) {new_shape = [2, -1]} : (tensor) -> tensor<2x?xf32> @@ -594,8 +613,9 @@ func.func @test_reshape_samerank_dyn(%arg0: tensor) -> tensor<2x?xf32> // ----- // CHECK-LABEL: @test_reshape_downrank_6D +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]]: func.func @test_reshape_downrank_6D(%arg0: tensor<1x2x3x5x7x11xf32>) -> tensor<6x5x77xf32> { - // CHECK: tensor.collapse_shape %arg0 {{\[}}[0, 1, 2], [3], [4, 5]] + // CHECK: tensor.collapse_shape %[[ARG0]] {{\[}}[0, 1, 2], [3], [4, 5]] %0 = "tosa.reshape"(%arg0) {new_shape = [6, 5, 77]} : (tensor<1x2x3x5x7x11xf32>) -> tensor<6x5x77xf32> return %0 : tensor<6x5x77xf32> } @@ -603,9 +623,10 @@ func.func @test_reshape_downrank_6D(%arg0: tensor<1x2x3x5x7x11xf32>) -> tensor<6 // ----- // CHECK-LABEL: @test_reshape_downrank_6D_dyn +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]]: func.func @test_reshape_downrank_6D_dyn(%arg0: tensor<1x2x?x5x7x11xf32>) -> tensor { - // CHECK: tensor.collapse_shape {{.*}}[0, 1, 2, 3, 4, 5] - // CHECK: tensor.expand_shape {{.*}}[0, 1, 2] + // CHECK: tensor.collapse_shape %[[ARG0]] {{\[}}[0, 1, 2, 3, 4, 5]] + // CHECK: tensor.expand_shape %{{.*}} {{\[}}[0, 1, 2]] %0 = "tosa.reshape"(%arg0) {new_shape = [-1, 5, 77]} : (tensor<1x2x?x5x7x11xf32>) -> tensor return %0 : tensor } @@ -613,11 +634,13 @@ func.func @test_reshape_downrank_6D_dyn(%arg0: tensor<1x2x?x5x7x11xf32>) -> tens // ----- // CHECK-LABEL: @test_identity +// CHECK-SAME: %[[ARG0:[0-9a-zA-Z_]*]]: tensor<1xf32>, +// CHECK-SAME: %[[ARG1:[0-9a-zA-Z_]*]]: tensor<1xi32> func.func @test_identity(%arg0: tensor<1xf32>, %arg1: tensor<1xi32>) -> (tensor<1xf32>, tensor<1xi32>) { %0 = "tosa.identity"(%arg0) : (tensor<1xf32>) -> tensor<1xf32> %1 = "tosa.identity"(%arg1) : (tensor<1xi32>) -> tensor<1xi32> - // CHECK: return %arg0, %arg1 + // CHECK: return %[[ARG0]], %[[ARG1]] return %0, %1 : tensor<1xf32>, tensor<1xi32> } @@ -649,7 +672,7 @@ func.func @test_transpose(%arg0: tensor<1x2x3xi32>) -> () { func.func @test_transpose_dyn(%arg0: tensor<1x?x3x4xi32>) -> () { %0 = arith.constant dense<[1, 3, 0, 2]> : tensor<4xi32> // CHECK: %[[C1:.+]] = arith.constant 1 - // CHECK: %[[DIM:.+]] = tensor.dim %arg0, %[[C1]] + // CHECK: %[[DIM:.+]] = tensor.dim %[[ARG0]], %[[C1]] // CHECK: %[[INIT:.+]] = tensor.empty(%[[DIM]]) : tensor // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]]], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} ins(%[[ARG0]] : tensor<1x?x3x4xi32>) outs([[OUT:%.+]] : tensor) // CHECK: ^bb0([[ARG1:%.+]]: i32, [[ARG2:%.+]]: i32) @@ -669,9 +692,9 @@ func.func @test_transpose_dyn(%arg0: tensor<1x?x3x4xi32>) -> () { func.func @test_transpose_dyn_multiple(%arg0: tensor) -> () { %0 = arith.constant dense<[1, 0]> : tensor<2xi32> // CHECK: %[[C0:.+]] = arith.constant 0 - // CHECK: %[[DIM0:.+]] = tensor.dim %arg0, %[[C0]] + // CHECK: %[[DIM0:.+]] = tensor.dim %[[ARG0]], %[[C0]] // CHECK: %[[C1:.+]] = arith.constant 1 - // CHECK: %[[DIM1:.+]] = tensor.dim %arg0, %[[C1]] + // CHECK: %[[DIM1:.+]] = tensor.dim %[[ARG0]], %[[C1]] // CHECK: %[[INIT:.+]] = tensor.empty(%[[DIM1]], %[[DIM0]]) // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]]], iterator_types = ["parallel", "parallel"]} ins(%[[ARG0]] : tensor) outs([[OUT:%.+]] : tensor) // CHECK: ^bb0([[ARG1:%.+]]: f32, [[ARG2:%.+]]: f32) @@ -694,8 +717,8 @@ func.func @reduce_float(%arg0: tensor<5x4xf32>) -> () { // CHECK: [[CST0:%.+]] = arith.constant 0.0 // CHECK: [[FILL:%.+]] = linalg.fill ins([[CST0]]{{.*}}outs([[INIT]] // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]]], iterator_types = ["reduction", "parallel"]} ins([[ARG0]] : tensor<5x4xf32>) outs([[FILL]] : tensor<4xf32>) - // CHECK: ^bb0(%arg1: f32, %arg2: f32) - // CHECK: [[RES:%.+]] = arith.addf %arg1, %arg2 : f32 + // CHECK: ^bb0(%[[ARG1:.*]]: f32, %[[ARG2:.*]]: f32) + // CHECK: [[RES:%.+]] = arith.addf %[[ARG1]], %[[ARG2]] : f32 // CHECK: linalg.yield [[RES]] : f32 // CHECK: tensor.expand_shape [[GENERIC]] {{\[}}[0, 1]] : tensor<4xf32> into tensor<1x4xf32> %0 = "tosa.reduce_sum"(%arg0) {axis = 0 : i64} : (tensor<5x4xf32>) -> tensor<1x4xf32> @@ -704,8 +727,8 @@ func.func @reduce_float(%arg0: tensor<5x4xf32>) -> () { // CHECK: [[CST0:%.+]] = arith.constant 0.0 // CHECK: [[FILL:%.+]] = linalg.fill ins([[CST0]]{{.*}}outs([[INIT]] // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP2]]], iterator_types = ["parallel", "reduction"]} ins([[ARG0]] : tensor<5x4xf32>) outs([[FILL]] : tensor<5xf32>) - // CHECK: ^bb0(%arg1: f32, %arg2: f32) - // CHECK: [[RES:%.+]] = arith.addf %arg1, %arg2 : f32 + // CHECK: ^bb0(%[[ARG1:.*]]: f32, %[[ARG2:.*]]: f32) + // CHECK: [[RES:%.+]] = arith.addf %[[ARG1]], %[[ARG2]] : f32 // CHECK: linalg.yield [[RES]] : f32 // CHECK: tensor.expand_shape [[GENERIC]] {{\[}}[0, 1]] : tensor<5xf32> into tensor<5x1xf32> %1 = "tosa.reduce_sum"(%arg0) {axis = 1 : i64} : (tensor<5x4xf32>) -> tensor<5x1xf32> @@ -736,15 +759,16 @@ func.func @reduce_float(%arg0: tensor<5x4xf32>) -> () { // CHECK-DAG: #[[$MAP1:.*]] = affine_map<(d0, d1, d2) -> (d0, d2)> // CHECK-LABEL: @reduce_float_dyn +// CHECK-SAME: %[[ARG0:[0-9a-zA-Z_]*]]: tensor func.func @reduce_float_dyn(%arg0: tensor) -> () { // CHECK: %[[C0:.+]] = arith.constant 0 - // CHECK: %[[DYN:.+]] = tensor.dim %arg0, %[[C0]] + // CHECK: %[[DYN:.+]] = tensor.dim %[[ARG0]], %[[C0]] // CHECK: %[[INIT:.+]] = tensor.empty(%[[DYN]]) : tensor // CHECK: %[[CST0:.+]] = arith.constant 0.0 // CHECK: %[[FILL:.+]] = linalg.fill ins(%[[CST0]]{{.*}}outs(%[[INIT]] - // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]]], iterator_types = ["parallel", "reduction", "parallel"]} ins(%arg0 : tensor) outs(%[[FILL]] : tensor) - // CHECK: ^bb0(%arg1: f32, %arg2: f32) - // CHECK: %[[RES:.+]] = arith.addf %arg1, %arg2 : f32 + // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]]], iterator_types = ["parallel", "reduction", "parallel"]} ins(%[[ARG0]] : tensor) outs(%[[FILL]] : tensor) + // CHECK: ^bb0(%[[ARG1:.*]]: f32, %[[ARG2:.*]]: f32) + // CHECK: %[[RES:.+]] = arith.addf %[[ARG1]], %[[ARG2]] : f32 // CHECK: linalg.yield %[[RES]] : f32 // CHECK: tensor.expand_shape %[[GENERIC]] {{\[}}[0], [1, 2]] : tensor into tensor %0 = "tosa.reduce_sum"(%arg0) {axis = 1 : i64} : (tensor) -> tensor @@ -757,15 +781,16 @@ func.func @reduce_float_dyn(%arg0: tensor) -> () { // CHECK-DAG: #[[$MAP1:.*]] = affine_map<(d0, d1, d2) -> (d0, d1)> // CHECK-LABEL: @reduce_float_dyn_nonzero_batch +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]]: func.func @reduce_float_dyn_nonzero_batch(%arg0: tensor<5x?x4xf32>) -> () { // CHECK: %[[C1:.+]] = arith.constant 1 - // CHECK: %[[DYN:.+]] = tensor.dim %arg0, %[[C1]] + // CHECK: %[[DYN:.+]] = tensor.dim %[[ARG0]], %[[C1]] // CHECK: %[[INIT:.+]] = tensor.empty(%[[DYN]]) : tensor<5x?xf32> // CHECK: %[[CST1:.+]] = arith.constant 1.0 // CHECK: %[[FILL:.+]] = linalg.fill ins(%[[CST1]]{{.*}}outs(%[[INIT]] - // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]]], iterator_types = ["parallel", "parallel", "reduction"]} ins(%arg0 : tensor<5x?x4xf32>) outs(%[[FILL]] : tensor<5x?xf32>) - // CHECK: ^bb0(%arg1: f32, %arg2: f32) - // CHECK: %[[RES:.+]] = arith.mulf %arg1, %arg2 : f32 + // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]]], iterator_types = ["parallel", "parallel", "reduction"]} ins(%[[ARG0]] : tensor<5x?x4xf32>) outs(%[[FILL]] : tensor<5x?xf32>) + // CHECK: ^bb0(%[[ARG1:.*]]: f32, %[[ARG2:.*]]: f32) + // CHECK: %[[RES:.+]] = arith.mulf %[[ARG1]], %[[ARG2]] : f32 // CHECK: linalg.yield %[[RES]] : f32 // CHECK: tensor.expand_shape %[[GENERIC]] {{\[}}[0], [1, 2]] : tensor<5x?xf32> into tensor<5x?x1xf32> %0 = "tosa.reduce_prod"(%arg0) {axis = 2 : i64} : (tensor<5x?x4xf32>) -> tensor<5x?x1xf32> @@ -778,15 +803,16 @@ func.func @reduce_float_dyn_nonzero_batch(%arg0: tensor<5x?x4xf32>) -> () { // CHECK-DAG: #[[$MAP1:.*]] = affine_map<(d0, d1) -> (d0)> // CHECK-LABEL: @reduce_float_dyn_multiple +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]]: func.func @reduce_float_dyn_multiple(%arg0: tensor) -> () { // CHECK: %[[C0:.+]] = arith.constant 0 - // CHECK: %[[DYN:.+]] = tensor.dim %arg0, %[[C0]] + // CHECK: %[[DYN:.+]] = tensor.dim %[[ARG0]], %[[C0]] // CHECK: %[[INIT:.+]] = tensor.empty(%[[DYN]]) // CHECK: %[[CMIN:.+]] = arith.constant -3.40282347E+38 // CHECK: %[[FILL:.+]] = linalg.fill ins(%[[CMIN]]{{.*}}outs(%[[INIT]] - // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]]], iterator_types = ["parallel", "reduction"]} ins(%arg0 : tensor) outs(%[[FILL]] : tensor) - // CHECK: ^bb0(%arg1: f32, %arg2: f32) - // CHECK: %[[MAX:.+]] = arith.maxf %arg1, %arg2 : f32 + // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]]], iterator_types = ["parallel", "reduction"]} ins(%[[ARG0]] : tensor) outs(%[[FILL]] : tensor) + // CHECK: ^bb0(%[[ARG1:.*]]: f32, %[[ARG2:.*]]: f32) + // CHECK: %[[MAX:.+]] = arith.maxf %[[ARG1]], %[[ARG2]] : f32 // CHECK: linalg.yield %[[MAX]] : f32 // CHECK: tensor.expand_shape %[[GENERIC]] {{\[}}[0, 1]] : tensor into tensor %0 = "tosa.reduce_max"(%arg0) {axis = 1 : i64} : (tensor) -> tensor @@ -806,8 +832,8 @@ func.func @reduce_int(%arg0: tensor<5x4xi32>) -> () { // CHECK: [[CST0:%.+]] = arith.constant 0 // CHECK: [[FILL:%.+]] = linalg.fill ins([[CST0]]{{.*}}outs([[INIT]] // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]]], iterator_types = ["reduction", "parallel"]} ins([[ARG0]] : tensor<5x4xi32>) outs([[FILL]] : tensor<4xi32>) - // CHECK: ^bb0(%arg1: i32, %arg2: i32) - // CHECK: [[RES:%.+]] = arith.addi %arg1, %arg2 : i32 + // CHECK: ^bb0(%[[ARG1:.*]]: i32, %[[ARG2:.*]]: i32) + // CHECK: [[RES:%.+]] = arith.addi %[[ARG1]], %[[ARG2]] : i32 // CHECK: linalg.yield [[RES]] : i32 // CHECK: tensor.expand_shape [[GENERIC]] {{\[}}[0, 1]] : tensor<4xi32> into tensor<1x4xi32> %0 = "tosa.reduce_sum"(%arg0) {axis = 0 : i64} : (tensor<5x4xi32>) -> tensor<1x4xi32> @@ -816,8 +842,8 @@ func.func @reduce_int(%arg0: tensor<5x4xi32>) -> () { // CHECK: [[CST0:%.+]] = arith.constant 0 // CHECK: [[FILL:%.+]] = linalg.fill ins([[CST0]]{{.*}}outs([[INIT]] // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP2]]], iterator_types = ["parallel", "reduction"]} ins([[ARG0]] : tensor<5x4xi32>) outs([[FILL]] : tensor<5xi32>) - // CHECK: ^bb0(%arg1: i32, %arg2: i32) - // CHECK: [[RES:%.+]] = arith.addi %arg1, %arg2 : i32 + // CHECK: ^bb0(%[[ARG1:.*]]: i32, %[[ARG2:.*]]: i32) + // CHECK: [[RES:%.+]] = arith.addi %[[ARG1]], %[[ARG2]] : i32 // CHECK: linalg.yield [[RES]] : i32 // CHECK: tensor.expand_shape [[GENERIC]] {{\[}}[0, 1]] : tensor<5xi32> into tensor<5x1xi32> %1 = "tosa.reduce_sum"(%arg0) {axis = 1 : i64} : (tensor<5x4xi32>) -> tensor<5x1xi32> @@ -856,8 +882,8 @@ func.func @reduce_bool(%arg0: tensor<5x4xi1>) -> () { // CHECK: [[CST0:%.+]] = arith.constant true // CHECK: [[FILL:%.+]] = linalg.fill ins([[CST0]]{{.*}}outs([[INIT]] // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]]], iterator_types = ["reduction", "parallel"]} ins([[ARG0]] : tensor<5x4xi1>) outs([[FILL]] : tensor<4xi1>) - // CHECK: ^bb0(%arg1: i1, %arg2: i1) - // CHECK: [[RES:%.+]] = arith.andi %arg1, %arg2 : i1 + // CHECK: ^bb0(%[[ARG1:[0-9a-zA-Z_]+]]: i1, %[[ARG2:[0-9a-zA-Z_]+]]: i1) + // CHECK: [[RES:%.+]] = arith.andi %[[ARG1]], %[[ARG2]] : i1 // CHECK: linalg.yield [[RES]] : i1 // CHECK: tensor.expand_shape [[GENERIC]] {{\[}}[0, 1]] : tensor<4xi1> into tensor<1x4xi1> %0 = "tosa.reduce_all"(%arg0) {axis = 0 : i64} : (tensor<5x4xi1>) -> tensor<1x4xi1> @@ -874,6 +900,8 @@ func.func @reduce_bool(%arg0: tensor<5x4xi1>) -> () { // ----- // CHECK-LABEL: @concat +// CHECK-SAME: %[[ARG0:.+]]: tensor<5x1xf32> +// CHECK-SAME: %[[ARG1:.+]]: tensor<6x1xf32> func.func @concat(%arg0: tensor<5x1xf32>, %arg1: tensor<6x1xf32>) -> () { // CHECK: [[AXIS:%.+]] = arith.constant 0 // CHECK: [[STRIDE:%.+]] = arith.constant 1 @@ -883,8 +911,8 @@ func.func @concat(%arg0: tensor<5x1xf32>, %arg1: tensor<6x1xf32>) -> () { // CHECK: [[INIT:%.+]] = tensor.empty() : tensor<11x1xf32> // CHECK: [[CST:%.+]] = arith.constant 0.0 // CHECK: [[FILL:%.+]] = linalg.fill ins([[CST]]{{.*}}outs([[INIT]] - // CHECK: [[INSERT0:%.+]] = tensor.insert_slice %arg0 into [[FILL]][0, 0] [5, 1] [1, 1] - // CHECK: [[INSERT1:%.+]] = tensor.insert_slice %arg1 into [[INSERT0]][5, 0] [6, 1] [1, 1] + // CHECK: [[INSERT0:%.+]] = tensor.insert_slice %[[ARG0]] into [[FILL]][0, 0] [5, 1] [1, 1] + // CHECK: [[INSERT1:%.+]] = tensor.insert_slice %[[ARG1]] into [[INSERT0]][5, 0] [6, 1] [1, 1] %0 = "tosa.concat"(%arg0, %arg1) { axis = 0 : i64} : (tensor<5x1xf32>, tensor<6x1xf32>) -> (tensor<11x1xf32>) // CHECK: [[AXIS:%.+]] = arith.constant 1 @@ -895,8 +923,8 @@ func.func @concat(%arg0: tensor<5x1xf32>, %arg1: tensor<6x1xf32>) -> () { // CHECK: [[INIT:%.+]] = tensor.empty() : tensor<5x2xf32> // CHECK: [[CST:%.+]] = arith.constant 0.0 // CHECK: [[FILL:%.+]] = linalg.fill ins([[CST]]{{.*}}outs([[INIT]] - // CHECK: [[INSERT0:%.+]] = tensor.insert_slice %arg0 into [[FILL]][0, 0] [5, 1] [1, 1] - // CHECK: [[INSERT1:%.+]] = tensor.insert_slice %arg0 into [[INSERT0]][0, 1] [5, 1] [1, 1] + // CHECK: [[INSERT0:%.+]] = tensor.insert_slice %[[ARG0]] into [[FILL]][0, 0] [5, 1] [1, 1] + // CHECK: [[INSERT1:%.+]] = tensor.insert_slice %[[ARG0]] into [[INSERT0]][0, 1] [5, 1] [1, 1] %1 = "tosa.concat"(%arg0, %arg0) { axis = 1 : i64} : (tensor<5x1xf32>, tensor<5x1xf32>) -> (tensor<5x2xf32>) return } @@ -904,20 +932,22 @@ func.func @concat(%arg0: tensor<5x1xf32>, %arg1: tensor<6x1xf32>) -> () { // ----- // CHECK-LABEL: @concat_non_axis_dyn +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]]: +// CHECK-SAME: %[[ARG1:[0-9a-zA-Z_]*]] func.func @concat_non_axis_dyn(%arg0: tensor<5x?xf32>, %arg1: tensor<6x?xf32>) -> () { // CHECK: %[[AXIS:.+]] = arith.constant 0 // CHECK: %[[STRIDE:.+]] = arith.constant 1 // CHECK: %[[OFFSET:.+]] = arith.constant 0 : index // CHECK: %[[IDX0:.+]] = arith.constant 0 : index // CHECK: %[[IDX1:.+]] = arith.constant 1 : index - // CHECK: %[[SIZE:.+]] = tensor.dim %arg0, %[[IDX1]] + // CHECK: %[[SIZE:.+]] = tensor.dim %[[ARG0]], %[[IDX1]] // CHECK: %[[IDX1_2:.+]] = arith.constant 1 : index - // CHECK: %[[DYN:.+]] = tensor.dim %arg0, %[[IDX1_2]] + // CHECK: %[[DYN:.+]] = tensor.dim %[[ARG0]], %[[IDX1_2]] // CHECK: %[[INIT:.+]] = tensor.empty(%[[DYN]]) : tensor<11x?xf32> // CHECK: %[[CST:.+]] = arith.constant 0.0 // CHECK: %[[FILL:.+]] = linalg.fill ins(%[[CST]]{{.*}}outs(%[[INIT]] - // CHECK: %[[INSERT0:.+]] = tensor.insert_slice %arg0 into %[[FILL]][0, 0] [5, %[[SIZE]]] [1, 1] - // CHECK: %[[INSERT1:.+]] = tensor.insert_slice %arg1 into %[[INSERT0]][5, 0] [6, %[[SIZE]]] [1, 1] + // CHECK: %[[INSERT0:.+]] = tensor.insert_slice %[[ARG0]] into %[[FILL]][0, 0] [5, %[[SIZE]]] [1, 1] + // CHECK: %[[INSERT1:.+]] = tensor.insert_slice %[[ARG1]] into %[[INSERT0]][5, 0] [6, %[[SIZE]]] [1, 1] %0 = "tosa.concat"(%arg0, %arg1) { axis = 0 : i64} : (tensor<5x?xf32>, tensor<6x?xf32>) -> (tensor<11x?xf32>) return } @@ -925,23 +955,25 @@ func.func @concat_non_axis_dyn(%arg0: tensor<5x?xf32>, %arg1: tensor<6x?xf32>) - // ----- // CHECK-LABEL: @concat_axis_dyn +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]]: +// CHECK-SAME: %[[ARG1:[0-9a-zA-Z_]*]]: func.func @concat_axis_dyn(%arg0: tensor, %arg1: tensor) -> () { // CHECK: %[[AXIS:.+]] = arith.constant 0 // CHECK: %[[STRIDE:.+]] = arith.constant 1 // CHECK: %[[OFFSET:.+]] = arith.constant 0 : index // CHECK: %[[IDX0:.+]] = arith.constant 0 : index - // CHECK: %[[SIZE:.+]] = tensor.dim %arg0, %[[IDX0]] + // CHECK: %[[SIZE:.+]] = tensor.dim %[[ARG0]], %[[IDX0]] // CHECK: %[[IDX0_2:.+]] = arith.constant 0 : index - // CHECK: %[[DYN:.+]] = tensor.dim %arg0, %[[IDX0_2]] + // CHECK: %[[DYN:.+]] = tensor.dim %[[ARG0]], %[[IDX0_2]] // CHECK: %[[IDX1:.+]] = arith.constant 1 : index // CHECK: %[[INIT:.+]] = tensor.empty(%[[DYN]]) : tensor // CHECK: %[[CST:.+]] = arith.constant 0.0 // CHECK: %[[FILL:.+]] = linalg.fill ins(%[[CST]]{{.*}}outs(%[[INIT]] - // CHECK: %[[DYN1:.+]] = tensor.dim %arg0, %[[AXIS]] - // CHECK: %[[INSERT0:.+]] = tensor.insert_slice %arg0 into %[[FILL]][0, 0] [%[[DYN1]], 3] [1, 1] + // CHECK: %[[DYN1:.+]] = tensor.dim %[[ARG0]], %[[AXIS]] + // CHECK: %[[INSERT0:.+]] = tensor.insert_slice %[[ARG0]] into %[[FILL]][0, 0] [%[[DYN1]], 3] [1, 1] // CHECK: %[[SUM:.+]] = arith.addi %[[OFFSET]], %[[DYN1]] - // CHECK: %[[DYN2:.+]] = tensor.dim %arg1, %[[AXIS]] - // CHECK: %[[INSERT1:.+]] = tensor.insert_slice %arg1 into %[[INSERT0]][%[[SUM]], 0] [%[[DYN2]], 3] [1, 1] + // CHECK: %[[DYN2:.+]] = tensor.dim %[[ARG1]], %[[AXIS]] + // CHECK: %[[INSERT1:.+]] = tensor.insert_slice %[[ARG1]] into %[[INSERT0]][%[[SUM]], 0] [%[[DYN2]], 3] [1, 1] %0 = "tosa.concat"(%arg0, %arg1) { axis = 0 : i64} : (tensor, tensor) -> (tensor) return } @@ -950,11 +982,12 @@ func.func @concat_axis_dyn(%arg0: tensor, %arg1: tensor) -> () // CHECK: #[[$MAP0:.*]] = affine_map<(d0) -> (d0)> // CHECK-LABEL: @rescale_i8 +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]]: func.func @rescale_i8(%arg0 : tensor<2xi8>) -> () { // CHECK: [[C0:%.+]] = arith.constant 19689 // CHECK: [[C1:%.+]] = arith.constant 15 // CHECK: [[INIT:%.+]] = tensor.empty() - // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP0]]], iterator_types = ["parallel"]} ins(%arg0 : tensor<2xi8>) outs([[INIT]] : tensor<2xi8>) + // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP0]]], iterator_types = ["parallel"]} ins(%[[ARG0]] : tensor<2xi8>) outs([[INIT]] : tensor<2xi8>) // CHECK: ^bb0([[IN:%.+]]: i8, [[UNUSED:%.+]]: i8): // CHECK: [[C17:%.+]] = arith.constant 17 // CHECK: [[C22:%.+]] = arith.constant 22 @@ -975,7 +1008,7 @@ func.func @rescale_i8(%arg0 : tensor<2xi8>) -> () { // CHECK: [[C0:%.+]] = arith.constant 19689 // CHECK: [[C1:%.+]] = arith.constant 15 // CHECK: [[INIT:%.+]] = tensor.empty() - // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP0]]], iterator_types = ["parallel"]} ins(%arg0 : tensor<2xi8>) outs([[INIT]] : tensor<2xui8>) + // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP0]]], iterator_types = ["parallel"]} ins(%[[ARG0]] : tensor<2xi8>) outs([[INIT]] : tensor<2xui8>) // CHECK: ^bb0([[IN:%.+]]: i8, [[UNUSED:%.+]]: ui8): // CHECK: [[C17:%.+]] = arith.constant 17 // CHECK: [[C22:%.+]] = arith.constant 22 @@ -1003,17 +1036,18 @@ func.func @rescale_i8(%arg0 : tensor<2xi8>) -> () { // CHECK: #[[$MAP0:.*]] = affine_map<(d0, d1) -> (d0, d1)> // CHECK-LABEL: @rescale_i8_dyn_batch +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]]: func.func @rescale_i8_dyn_batch(%arg0 : tensor) -> () { // CHECK: %[[C0:.+]] = arith.constant 0 - // CHECK: %[[BATCH:.+]] = tensor.dim %arg0, %[[C0]] + // CHECK: %[[BATCH:.+]] = tensor.dim %[[ARG0]], %[[C0]] // CHECK: %[[INIT:.+]] = tensor.empty(%[[BATCH]]) : tensor - // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP0]]], iterator_types = ["parallel", "parallel"]} ins(%arg0 : tensor) outs(%[[INIT]] : tensor) + // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP0]]], iterator_types = ["parallel", "parallel"]} ins(%[[ARG0]] : tensor) outs(%[[INIT]] : tensor) %0 = "tosa.rescale"(%arg0) {input_zp = 17 : i32, output_zp = 22 : i32, multiplier = [19689 : i32], shift = [15 : i32], scale32 = false, double_round = false, per_channel = false} : (tensor) -> (tensor) // CHECK: %[[C0:.+]] = arith.constant 0 - // CHECK: %[[BATCH:.+]] = tensor.dim %arg0, %[[C0]] + // CHECK: %[[BATCH:.+]] = tensor.dim %[[ARG0]], %[[C0]] // CHECK: %[[INIT:.+]] = tensor.empty(%[[BATCH]]) : tensor - // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP0]]], iterator_types = ["parallel", "parallel"]} ins(%arg0 : tensor) outs(%[[INIT]] : tensor) + // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP0]]], iterator_types = ["parallel", "parallel"]} ins(%[[ARG0]] : tensor) outs(%[[INIT]] : tensor) %1 = "tosa.rescale"(%arg0) {input_zp = 17 : i32, output_zp = 22 : i32, multiplier = [19689 : i32], shift = [15 : i32], scale32 = false, double_round = false, per_channel = false} : (tensor) -> (tensor) return @@ -1024,13 +1058,14 @@ func.func @rescale_i8_dyn_batch(%arg0 : tensor) -> () { // CHECK: #[[$MAP1:.*]] = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)> // CHECK-LABEL: @rescale_dyn +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]]: func.func @rescale_dyn(%arg0 : tensor<1x?x?x32xi32>) -> () { // CHECK: %[[C1:.+]] = arith.constant 1 - // CHECK: %[[DIM1:.+]] = tensor.dim %arg0, %[[C1]] + // CHECK: %[[DIM1:.+]] = tensor.dim %[[ARG0]], %[[C1]] // CHECK: %[[C2:.+]] = arith.constant 2 - // CHECK: %[[DIM2:.+]] = tensor.dim %arg0, %[[C2]] + // CHECK: %[[DIM2:.+]] = tensor.dim %[[ARG0]], %[[C2]] // CHECK: %[[INIT:.+]] = tensor.empty(%[[DIM1]], %[[DIM2]]) - // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP1]], #[[$MAP1]]], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} ins(%arg0 : tensor<1x?x?x32xi32>) outs(%[[INIT]] : tensor<1x?x?x32xi8>) + // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP1]], #[[$MAP1]]], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} ins(%[[ARG0]] : tensor<1x?x?x32xi32>) outs(%[[INIT]] : tensor<1x?x?x32xi8>) %0 = "tosa.rescale"(%arg0) {double_round = true, input_zp = 0 : i32, multiplier = [1376784203 : i32], output_zp = 0 : i32, per_channel = false, scale32 = true, shift = [38 : i32]} : (tensor<1x?x?x32xi32>) -> tensor<1x?x?x32xi8> return } @@ -1040,11 +1075,12 @@ func.func @rescale_dyn(%arg0 : tensor<1x?x?x32xi32>) -> () { // CHECK: #[[$MAP0:.*]] = affine_map<(d0) -> (d0)> // CHECK-LABEL: @rescale_ui8 +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]]: func.func @rescale_ui8(%arg0 : tensor<2xui8>) -> () { // CHECK: [[C0:%.+]] = arith.constant 19689 // CHECK: [[C1:%.+]] = arith.constant 15 // CHECK: [[INIT:%.+]] = tensor.empty() - // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP0]]], iterator_types = ["parallel"]} ins(%arg0 : tensor<2xui8>) outs([[INIT]] : tensor<2xi8>) + // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP0]]], iterator_types = ["parallel"]} ins(%[[ARG0]] : tensor<2xui8>) outs([[INIT]] : tensor<2xi8>) // CHECK: ^bb0([[IN:%.+]]: ui8, [[UNUSED:%.+]]: i8): // CHECK: [[C17:%.+]] = arith.constant 17 // CHECK: [[C22:%.+]] = arith.constant 22 @@ -1071,11 +1107,12 @@ func.func @rescale_ui8(%arg0 : tensor<2xui8>) -> () { // CHECK: #[[$MAP0:.*]] = affine_map<(d0) -> (d0)> // CHECK-LABEL: @rescale_per_channel +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]]: func.func @rescale_per_channel(%arg0 : tensor<3xi8>) -> (tensor<3xi8>) { // CHECK: [[MULTIPLIERS:%.+]] = arith.constant dense<[42, 43, 0]> // CHECK: [[SHIFTS:%.+]] = arith.constant dense<[14, 15, 0]> // CHECK: [[INIT:%.+]] = tensor.empty() - // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP0]], #[[$MAP0]], #[[$MAP0]]], iterator_types = ["parallel"]} ins(%arg0, [[MULTIPLIERS]], [[SHIFTS]] : tensor<3xi8>, tensor<3xi32>, tensor<3xi8>) outs([[INIT]] : tensor<3xi8>) + // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP0]], #[[$MAP0]], #[[$MAP0]]], iterator_types = ["parallel"]} ins(%[[ARG0]], [[MULTIPLIERS]], [[SHIFTS]] : tensor<3xi8>, tensor<3xi32>, tensor<3xi8>) outs([[INIT]] : tensor<3xi8>) // CHECK: ^bb0([[IN:%.+]]: i8, [[MULTIPLIER:%.+]]: i32, [[SHIFT:%.+]]: i8, [[UNUSED:%.+]]: i8): // CHECK: [[C243:%.+]] = arith.constant 243 // CHECK: [[C252:%.+]] = arith.constant 252 @@ -1123,9 +1160,10 @@ func.func @rescaleUnnecessaryDoubleRound(%arg0 : tensor<2xi8>) -> (tensor<2xi8>) // CHECK: #[[$MAP0:.*]] = affine_map<(d0, d1) -> (d0, d1)> // CHECK-LABEL: @reverse +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]]: func.func @reverse(%arg0: tensor<5x4xi32>) -> () { // CHECK: %[[C0:.+]] = arith.constant 0 - // CHECK: %[[RDIM:.+]] = tensor.dim %arg0, %[[C0]] + // CHECK: %[[RDIM:.+]] = tensor.dim %[[ARG0]], %[[C0]] // CHECK: %[[INIT:.+]] = tensor.empty() // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#[[$MAP0]]], iterator_types = ["parallel", "parallel"]} outs(%[[INIT]] : tensor<5x4xi32>) // CHECK-DAG: %[[I0:.+]] = linalg.index 0 @@ -1138,7 +1176,7 @@ func.func @reverse(%arg0: tensor<5x4xi32>) -> () { %0 = "tosa.reverse"(%arg0) {axis = 0 : i64} : (tensor<5x4xi32>) -> tensor<5x4xi32> // CHECK: %[[C1:.+]] = arith.constant 1 - // CHECK: %[[RDIM:.+]] = tensor.dim %arg0, %[[C1]] + // CHECK: %[[RDIM:.+]] = tensor.dim %[[ARG0]], %[[C1]] // CHECK: %[[INIT:.+]] = tensor.empty() // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#[[$MAP0]]], iterator_types = ["parallel", "parallel"]} outs(%[[INIT]] : tensor<5x4xi32>) // CHECK-DAG: %[[I0:.+]] = linalg.index 0 @@ -1157,11 +1195,12 @@ func.func @reverse(%arg0: tensor<5x4xi32>) -> () { // CHECK: #[[$MAP0:.*]] = affine_map<(d0) -> (d0)> // CHECK-LABEL: @reverse_dyn +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]]: func.func @reverse_dyn(%arg0: tensor) -> () { // CHECK: %[[C0_1:.+]] = arith.constant 0 - // CHECK: %[[D0_1:.+]] = tensor.dim %arg0, %[[C0_1]] + // CHECK: %[[D0_1:.+]] = tensor.dim %[[ARG0]], %[[C0_1]] // CHECK: %[[C0_2:.+]] = arith.constant 0 - // CHECK: %[[D0_2:.+]] = tensor.dim %arg0, %[[C0_2]] + // CHECK: %[[D0_2:.+]] = tensor.dim %[[ARG0]], %[[C0_2]] // CHECK: %[[INIT:.+]] = tensor.empty(%[[D0_1]]) // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#[[$MAP0]]], iterator_types = ["parallel"]} outs(%[[INIT]] : tensor) // CHECK-DAG: %[[I0:.+]] = linalg.index 0 @@ -1180,22 +1219,26 @@ func.func @reverse_dyn(%arg0: tensor) -> () { // CHECK-DAG: #[[$MAP1:.*]] = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)> // CHECK-LABEL: @tile +// CHECK-SAME: %[[ARG0:.+]]: tensor<2x3xi8> func.func @tile(%arg0 : tensor<2x3xi8>) -> () { // CHECK: [[INIT:%.+]] = tensor.empty() - // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]]], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} ins(%arg0 : tensor<2x3xi8>) outs([[INIT]] : tensor<2x2x1x3xi8>) - // CHECK: linalg.yield %arg1 : i8 + // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]]], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} ins(%[[ARG0]] : tensor<2x3xi8>) outs([[INIT]] : tensor<2x2x1x3xi8>) + // CHECK: ^bb0(%[[ARG1:[0-9a-zA-Z_]+]]: i8 + // CHECK: linalg.yield %[[ARG1]] : i8 // CHECK: tensor.collapse_shape [[GENERIC]] {{\[}}[0, 1, 2], [3]] %0 = "tosa.tile"(%arg0) {multiples = [2, 1]} : (tensor<2x3xi8>) -> (tensor<4x3xi8>) // CHECK: [[INIT:%.+]] = tensor.empty() - // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]]], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} ins(%arg0 : tensor<2x3xi8>) outs([[INIT]] : tensor<1x2x2x3xi8>) - // CHECK: linalg.yield %arg1 : i8 + // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]]], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} ins(%[[ARG0]] : tensor<2x3xi8>) outs([[INIT]] : tensor<1x2x2x3xi8>) + // CHECK: ^bb0(%[[ARG1:[0-9a-zA-Z_]+]]: i8 + // CHECK: linalg.yield %[[ARG1]] : i8 // CHECK: tensor.collapse_shape [[GENERIC]] {{\[}}[0, 1], [2, 3]] %1 = "tosa.tile"(%arg0) {multiples = [1, 2]} : (tensor<2x3xi8>) -> (tensor<2x6xi8>) // CHECK: [[INIT:%.+]] = tensor.empty() - // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]]], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} ins(%arg0 : tensor<2x3xi8>) outs([[INIT]] : tensor<5x2x7x3xi8>) - // CHECK: linalg.yield %arg1 : i8 + // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]]], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} ins(%[[ARG0]] : tensor<2x3xi8>) outs([[INIT]] : tensor<5x2x7x3xi8>) + // CHECK: ^bb0(%[[ARG1:[0-9a-zA-Z_]+]]: i8 + // CHECK: linalg.yield %[[ARG1]] : i8 // CHECK: tensor.collapse_shape [[GENERIC]] {{\[}}[0, 1], [2, 3]] %2 = "tosa.tile"(%arg0) {multiples = [5, 7]} : (tensor<2x3xi8>) -> (tensor<10x21xi8>) @@ -1208,12 +1251,14 @@ func.func @tile(%arg0 : tensor<2x3xi8>) -> () { // CHECK-DAG: #[[$MAP1:.*]] = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)> // CHECK-LABEL: @tile_dyn_input +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]]: func.func @tile_dyn_input(%arg0 : tensor) -> () { // CHECK: %[[CST0:.+]] = arith.constant 0 - // CHECK: %[[DYN:.+]] = tensor.dim %arg0, %[[CST0]] : tensor + // CHECK: %[[DYN:.+]] = tensor.dim %[[ARG0]], %[[CST0]] : tensor // CHECK: %[[INIT:.+]] = tensor.empty(%[[DYN]]) - // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]]], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} ins(%arg0 : tensor) outs(%[[INIT]] : tensor<2x?x1x3xi8>) - // CHECK: linalg.yield %arg1 : i8 + // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]]], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} ins(%[[ARG0]] : tensor) outs(%[[INIT]] : tensor<2x?x1x3xi8>) + // CHECK: ^bb0(%[[ARG1:.+]]: i8, + // CHECK: linalg.yield %[[ARG1]] : i8 // CHECK: %[[COLLAPSED:.+]] = tensor.collapse_shape %[[GENERIC]] {{\[}}[0, 1, 2, 3]] // CHECK: tensor.expand_shape %[[COLLAPSED]] {{\[}}[0, 1]] %0 = "tosa.tile"(%arg0) {multiples = [2, 1]} : (tensor) -> (tensor) @@ -1227,12 +1272,14 @@ func.func @tile_dyn_input(%arg0 : tensor) -> () { // CHECK-DAG: #[[$MAP1:.*]] = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)> // CHECK-LABEL: @tile_dyn_multiples +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]]: func.func @tile_dyn_multiples(%arg0 : tensor<2x3xi8>) -> () { // CHECK: %[[CST1:.+]] = arith.constant 1 - // CHECK: %[[DYN:.+]] = tensor.dim %arg0, %[[CST1]] : tensor<2x3xi8> + // CHECK: %[[DYN:.+]] = tensor.dim %[[ARG0]], %[[CST1]] : tensor<2x3xi8> // CHECK: %[[INIT:.+]] = tensor.empty(%[[DYN]]) - // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]]], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} ins(%arg0 : tensor<2x3xi8>) outs(%[[INIT]] : tensor<2x2x?x3xi8>) - // CHECK: linalg.yield %arg1 : i8 + // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]]], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} ins(%[[ARG0]] : tensor<2x3xi8>) outs(%[[INIT]] : tensor<2x2x?x3xi8>) + // CHECK: ^bb0(%[[ARG1:.+]]: i8, + // CHECK: linalg.yield %[[ARG1]] : i8 // CHECK: %[[COLLAPSED:.+]] = tensor.collapse_shape %[[GENERIC]] {{\[}}[0, 1, 2, 3]] // CHECK: tensor.expand_shape %[[COLLAPSED]] {{\[}}[0, 1]] %0 = "tosa.tile"(%arg0) {multiples = [2, -1]} : (tensor<2x3xi8>) -> (tensor<2x?xi8>) @@ -1242,6 +1289,8 @@ func.func @tile_dyn_multiples(%arg0 : tensor<2x3xi8>) -> () { // ----- +// CHECK-LABEL: @pad_float +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]]: func.func @pad_float(%arg0 : tensor<1x2xf32>) -> (tensor<4x9xf32>) { %0 = arith.constant dense<[[1, 2], [3, 4]]> : tensor<2x2xi32> // TODO: Output contains multiple "arith.constant 1 : index". @@ -1250,8 +1299,7 @@ func.func @pad_float(%arg0 : tensor<1x2xf32>) -> (tensor<4x9xf32>) { // CHECK-DAG: [[INDEX3:%.+]] = arith.constant 3 : index // CHECK-DAG: [[INDEX4:%.+]] = arith.constant 4 : index // CHECK-DAG: [[CST:%.+]] = arith.constant 0.000000e+00 : f32 - // CHECK: tensor.pad %arg0 low{{\[}}%{{.*}}, [[INDEX3]]] high{{\[}}[[INDEX2]], [[INDEX4]]] { - // CHECK: ^bb0(%arg1: index, %arg2: index): + // CHECK: tensor.pad %[[ARG0]] low{{\[}}%{{.*}}, [[INDEX3]]] high{{\[}}[[INDEX2]], [[INDEX4]]] { // CHECK: tensor.yield [[CST]] // CHECK: } : tensor<1x2xf32> to tensor<4x9xf32> %1 = "tosa.pad"(%arg0, %0) : (tensor<1x2xf32>, tensor<2x2xi32>) -> (tensor<4x9xf32>) @@ -1286,8 +1334,7 @@ func.func @pad_float_explicit(%arg0 : tensor<1x2xf32>) -> (tensor<4x9xf32>) { // CHECK-DAG: [[INDEX3:%.+]] = arith.constant 3 : index // CHECK-DAG: [[INDEX4:%.+]] = arith.constant 4 : index // CHECK-DAG: [[CST:%.+]] = arith.constant 4.200000e+01 : f32 - // CHECK: tensor.pad %arg0 low{{\[}}%{{.*}}, [[INDEX3]]] high{{\[}}[[INDEX2]], [[INDEX4]]] { - // CHECK: ^bb0(%arg1: index, %arg2: index): + // CHECK: tensor.pad %[[ARG0]] low{{\[}}%{{.*}}, [[INDEX3]]] high{{\[}}[[INDEX2]], [[INDEX4]]] { // CHECK: tensor.yield [[CST]] // CHECK: } : tensor<1x2xf32> to tensor<4x9xf32> %1 = arith.constant dense<42.0> : tensor @@ -1305,8 +1352,7 @@ func.func @pad_dyn_input(%arg0 : tensor) -> (tensor) { // CHECK-DAG: [[INDEX3:%.+]] = arith.constant 3 : index // CHECK-DAG: [[INDEX4:%.+]] = arith.constant 4 : index // CHECK-DAG: [[CST:%.+]] = arith.constant 0.000000e+00 : f32 - // CHECK: tensor.pad %arg0 low{{\[}}%{{.*}}, [[INDEX3]]] high{{\[}}[[INDEX2]], [[INDEX4]]] { - // CHECK: ^bb0(%arg1: index, %arg2: index): + // CHECK: tensor.pad %[[ARG0]] low{{\[}}%{{.*}}, [[INDEX3]]] high{{\[}}[[INDEX2]], [[INDEX4]]] { // CHECK: tensor.yield [[CST]] // CHECK: } : tensor to tensor %1 = "tosa.pad"(%arg0, %0) : (tensor, tensor<2x2xi32>) -> (tensor) @@ -1321,8 +1367,7 @@ func.func @pad_dyn_padding(%arg0 : tensor<1x2xf32>) -> (tensor) { // CHECK-DAG: [[INDEX3:%.+]] = arith.constant 3 : index // CHECK-DAG: [[INDEX4:%.+]] = arith.constant 4 : index // CHECK-DAG: [[CST:%.+]] = arith.constant 0.000000e+00 : f32 - // CHECK: tensor.pad %arg0 low{{\[}}%{{.*}}, [[INDEX3]]] high{{\[}}[[INDEX2]], [[INDEX4]]] { - // CHECK: ^bb0(%arg1: index, %arg2: index): + // CHECK: tensor.pad %[[ARG0]] low{{\[}}%{{.*}}, [[INDEX3]]] high{{\[}}[[INDEX2]], [[INDEX4]]] { // CHECK: tensor.yield [[CST]] // CHECK: } : tensor<1x2xf32> to tensor %1 = "tosa.pad"(%arg0, %0) : (tensor<1x2xf32>, tensor<2x2xi32>) -> (tensor) @@ -1344,12 +1389,13 @@ func.func @argmax(%arg0 : tensor<3x2xi32>, %arg1 : tensor<6xf32>) -> () { // CHECK: [[VAL_INIT:%.+]] = tensor.empty() // CHECK: [[VAL_MIN:%.+]] = arith.constant -2147483648 // CHECK: [[VAL_FILL:%.+]] = linalg.fill ins([[VAL_MIN]]{{.*}}outs([[VAL_INIT]] - // CHECK: linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]], #[[$MAP1]]], iterator_types = ["reduction", "parallel"]} ins(%arg0 : tensor<3x2xi32>) outs([[IDX_FILL]], [[VAL_FILL]] : tensor<2xi32>, tensor<2xi32>) + // CHECK: linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]], #[[$MAP1]]], iterator_types = ["reduction", "parallel"]} ins(%[[ARG0]] : tensor<3x2xi32>) outs([[IDX_FILL]], [[VAL_FILL]] : tensor<2xi32>, tensor<2xi32>) + // CHECK: ^bb0(%[[ARG1:[0-9a-zA-Z_]+]]: i32, %[[ARG2:[0-9a-zA-Z_]+]]: i32, %[[ARG3:[0-9a-zA-Z_]+]]: i32 // CHECK: [[IDX:%.+]] = linalg.index 0 // CHECK: [[CAST:%.+]] = arith.index_cast [[IDX]] - // CHECK: [[CMP:%.+]] = arith.cmpi sgt, %arg2, %arg4 - // CHECK: [[SELECT_VAL:%.+]] = arith.select [[CMP]], %arg2, %arg4 - // CHECK: [[SELECT_IDX:%.+]] = arith.select [[CMP]], [[CAST]], %arg3 + // CHECK: [[CMP:%.+]] = arith.cmpi sgt, %[[ARG1]], %[[ARG3]] + // CHECK: [[SELECT_VAL:%.+]] = arith.select [[CMP]], %[[ARG1]], %[[ARG3]] + // CHECK: [[SELECT_IDX:%.+]] = arith.select [[CMP]], [[CAST]], %[[ARG2]] // CHECK: linalg.yield [[SELECT_IDX]], [[SELECT_VAL]] %0 = "tosa.argmax"(%arg0) { axis = 0 : i64} : (tensor<3x2xi32>) -> (tensor<2xi32>) @@ -1359,12 +1405,13 @@ func.func @argmax(%arg0 : tensor<3x2xi32>, %arg1 : tensor<6xf32>) -> () { // CHECK: [[VAL_INIT:%.+]] = tensor.empty() // CHECK: [[VAL_MIN:%.+]] = arith.constant -2147483648 // CHECK: [[VAL_FILL:%.+]] = linalg.fill ins([[VAL_MIN]]{{.*}}outs([[VAL_INIT]] - // CHECK: linalg.generic {indexing_maps = [#map0, #map2, #map2], iterator_types = ["parallel", "reduction"]} ins(%arg0 : tensor<3x2xi32>) outs([[IDX_FILL]], [[VAL_FILL]] : tensor<3xi32>, tensor<3xi32>) + // CHECK: linalg.generic {indexing_maps = [#map0, #map2, #map2], iterator_types = ["parallel", "reduction"]} ins(%[[ARG0]] : tensor<3x2xi32>) outs([[IDX_FILL]], [[VAL_FILL]] : tensor<3xi32>, tensor<3xi32>) + // CHECK: ^bb0(%[[ARG1:[0-9a-zA-Z_]+]]: i32, %[[ARG2:[0-9a-zA-Z_]+]]: i32, %[[ARG3:[0-9a-zA-Z_]+]]: i32 // CHECK: [[IDX:%.+]] = linalg.index 1 // CHECK: [[CAST:%.+]] = arith.index_cast [[IDX]] - // CHECK: [[CMP:%.+]] = arith.cmpi sgt, %arg2, %arg4 - // CHECK: [[SELECT_VAL:%.+]] = arith.select [[CMP]], %arg2, %arg4 - // CHECK: [[SELECT_IDX:%.+]] = arith.select [[CMP]], [[CAST]], %arg3 + // CHECK: [[CMP:%.+]] = arith.cmpi sgt, %[[ARG1]], %[[ARG3]] + // CHECK: [[SELECT_VAL:%.+]] = arith.select [[CMP]], %[[ARG1]], %[[ARG3]] + // CHECK: [[SELECT_IDX:%.+]] = arith.select [[CMP]], [[CAST]], %[[ARG2]] // CHECK: linalg.yield [[SELECT_IDX]], [[SELECT_VAL]] %1 = "tosa.argmax"(%arg0) { axis = 1 : i64} : (tensor<3x2xi32>) -> (tensor<3xi32>) @@ -1387,19 +1434,20 @@ func.func @argmax(%arg0 : tensor<3x2xi32>, %arg1 : tensor<6xf32>) -> () { func.func @argmax_dyn_non_axis(%arg0 : tensor<3x?xi32>) -> () { // CHECK: %[[CST1:.+]] = arith.constant 1 - // CHECK: %[[DYN:.+]] = tensor.dim %arg0, %[[CST1]] + // CHECK: %[[DYN:.+]] = tensor.dim %[[ARG0]], %[[CST1]] // CHECK: %[[IDX_INIT:.+]] = tensor.empty(%[[DYN]]) // CHECK: %[[IDX_MIN:.+]] = arith.constant 0 : i32 // CHECK: %[[IDX_FILL:.+]] = linalg.fill ins(%[[IDX_MIN]]{{.*}}outs(%[[IDX_INIT]] // CHECK: %[[VAL_INIT:.+]] = tensor.empty(%[[DYN]]) // CHECK: %[[VAL_MIN:.+]] = arith.constant -2147483648 // CHECK: %[[VAL_FILL:.+]] = linalg.fill ins(%[[VAL_MIN]]{{.*}}outs(%[[VAL_INIT]] - // CHECK: linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]], #[[$MAP1]]], iterator_types = ["reduction", "parallel"]} ins(%arg0 : tensor<3x?xi32>) outs(%[[IDX_FILL]], %[[VAL_FILL]] : tensor, tensor) + // CHECK: linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]], #[[$MAP1]]], iterator_types = ["reduction", "parallel"]} ins(%[[ARG0]] : tensor<3x?xi32>) outs(%[[IDX_FILL]], %[[VAL_FILL]] : tensor, tensor) + // CHECK: ^bb0(%[[ARG1:[0-9a-zA-Z_]+]]: i32, %[[ARG2:[0-9a-zA-Z_]+]]: i32, %[[ARG3:[0-9a-zA-Z_]+]]: i32 // CHECK: %[[IDX:.+]] = linalg.index 0 // CHECK: %[[CAST:.+]] = arith.index_cast %[[IDX]] - // CHECK: %[[CMP:.+]] = arith.cmpi sgt, %arg1, %arg3 - // CHECK: %[[SELECT_VAL:.+]] = arith.select %[[CMP]], %arg1, %arg3 - // CHECK: %[[SELECT_IDX:.+]] = arith.select %[[CMP]], %[[CAST]], %arg2 + // CHECK: %[[CMP:.+]] = arith.cmpi sgt, %[[ARG1]], %[[ARG3]] + // CHECK: %[[SELECT_VAL:.+]] = arith.select %[[CMP]], %[[ARG1]], %[[ARG3]] + // CHECK: %[[SELECT_IDX:.+]] = arith.select %[[CMP]], %[[CAST]], %[[ARG2]] // CHECK: linalg.yield %[[SELECT_IDX]], %[[SELECT_VAL]] %0 = "tosa.argmax"(%arg0) { axis = 0 : i64} : (tensor<3x?xi32>) -> (tensor) return @@ -1417,12 +1465,12 @@ func.func @argmax_dyn_axis(%arg0 : tensor<3x?xi32>) -> () { // CHECK: %[[VAL_INIT:.+]] = tensor.empty() // CHECK: %[[VAL_MIN:.+]] = arith.constant -2147483648 // CHECK: %[[VAL_FILL:.+]] = linalg.fill ins(%[[VAL_MIN]]{{.*}}outs(%[[VAL_INIT]] - // CHECK: linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]], #[[$MAP1]]], iterator_types = ["parallel", "reduction"]} ins(%arg0 : tensor<3x?xi32>) outs(%[[IDX_FILL]], %[[VAL_FILL]] : tensor<3xi32>, tensor<3xi32>) + // CHECK: linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]], #[[$MAP1]]], iterator_types = ["parallel", "reduction"]} ins(%[[ARG0]] : tensor<3x?xi32>) outs(%[[IDX_FILL]], %[[VAL_FILL]] : tensor<3xi32>, tensor<3xi32>) // CHECK: %[[IDX:.+]] = linalg.index 1 // CHECK: %[[CAST:.+]] = arith.index_cast %[[IDX]] - // CHECK: %[[CMP:.+]] = arith.cmpi sgt, %arg1, %arg3 - // CHECK: %[[SELECT_VAL:.+]] = arith.select %[[CMP]], %arg1, %arg3 - // CHECK: %[[SELECT_IDX:.+]] = arith.select %[[CMP]], %[[CAST]], %arg2 + // CHECK: %[[CMP:.+]] = arith.cmpi sgt, %[[ARG1]], %[[ARG3]] + // CHECK: %[[SELECT_VAL:.+]] = arith.select %[[CMP]], %[[ARG1]], %[[ARG3]] + // CHECK: %[[SELECT_IDX:.+]] = arith.select %[[CMP]], %[[CAST]], %[[ARG2]] // CHECK: linalg.yield %[[SELECT_IDX]], %[[SELECT_VAL]] %0 = "tosa.argmax"(%arg0) { axis = 1 : i64} : (tensor<3x?xi32>) -> (tensor<3xi32>) return @@ -1431,44 +1479,54 @@ func.func @argmax_dyn_axis(%arg0 : tensor<3x?xi32>) -> () { // ----- // CHECK-LABEL: @gather_float +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]] +// CHECK-SAME: %[[ARG1:[0-9a-zA-Z_]*]] func.func @gather_float(%arg0: tensor<2x3x2xf32>, %arg1: tensor<2x3xi32>) -> () { // CHECK: %[[INIT:.+]] = tensor.empty() - // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#map0, #map1], iterator_types = ["parallel", "parallel", "parallel"]} ins(%arg1 : tensor<2x3xi32>) outs(%[[INIT]] : tensor<2x3x2xf32>) - // CHECK: ^bb0(%[[ARG0:.+]]: i32, %[[ARG1:.+]]: f32) + // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#map0, #map1], iterator_types = ["parallel", "parallel", "parallel"]} ins(%[[ARG1]] : tensor<2x3xi32>) outs(%[[INIT]] : tensor<2x3x2xf32>) + // CHECK: ^bb0(%[[BBARG0:.+]]: i32, %[[BBARG1:.+]]: f32) // CHECK: %[[IDX0:.+]] = linalg.index 0 - // CHECK: %[[CAST:.+]] = arith.index_cast %[[ARG0]] + // CHECK: %[[CAST:.+]] = arith.index_cast %[[BBARG0]] // CHECK: %[[IDX2:.+]] = linalg.index 2 - // CHECK: %[[EXTRACT:.+]] = tensor.extract %arg0[%[[IDX0]], %[[CAST]], %[[IDX2]]] : tensor<2x3x2xf32> + // CHECK: %[[EXTRACT:.+]] = tensor.extract %[[ARG0]][%[[IDX0]], %[[CAST]], %[[IDX2]]] : tensor<2x3x2xf32> // CHECK: linalg.yield %[[EXTRACT]] %0 = "tosa.gather"(%arg0, %arg1) : (tensor<2x3x2xf32>, tensor<2x3xi32>) -> (tensor<2x3x2xf32>) return } +// ----- + // CHECK-LABEL: @gather_float_dyn +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]] +// CHECK-SAME: %[[ARG1:[0-9a-zA-Z_]*]] func.func @gather_float_dyn(%arg0: tensor, %arg1: tensor) -> () { // CHECK: %[[C0:.+]] = arith.constant 0 - // CHECK: %[[BATCH:.+]] = tensor.dim %arg0, %[[C0]] + // CHECK: %[[BATCH:.+]] = tensor.dim %[[ARG0]], %[[C0]] // CHECK: %[[INIT:.+]] = tensor.empty(%[[BATCH]]) - // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#map0, #map1], iterator_types = ["parallel", "parallel", "parallel"]} ins(%arg1 : tensor) outs(%[[INIT]] : tensor) - // CHECK: ^bb0(%[[ARG0:.+]]: i32, %[[ARG1:.+]]: f32) + // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#map0, #map1], iterator_types = ["parallel", "parallel", "parallel"]} ins(%[[ARG1]] : tensor) outs(%[[INIT]] : tensor) + // CHECK: ^bb0(%[[BBARG0:.+]]: i32, %[[BBARG1:.+]]: f32) // CHECK: %[[IDX0:.+]] = linalg.index 0 - // CHECK: %[[CAST:.+]] = arith.index_cast %[[ARG0]] + // CHECK: %[[CAST:.+]] = arith.index_cast %[[BBARG0]] // CHECK: %[[IDX2:.+]] = linalg.index 2 - // CHECK: %[[EXTRACT:.+]] = tensor.extract %arg0[%[[IDX0]], %[[CAST]], %[[IDX2]]] : tensor + // CHECK: %[[EXTRACT:.+]] = tensor.extract %[[ARG0]][%[[IDX0]], %[[CAST]], %[[IDX2]]] : tensor // CHECK: linalg.yield %[[EXTRACT]] %0 = "tosa.gather"(%arg0, %arg1) : (tensor, tensor) -> (tensor) return } +// ----- + // CHECK-LABEL: @gather_int +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]] +// CHECK-SAME: %[[ARG1:[0-9a-zA-Z_]*]] func.func @gather_int(%arg0: tensor<2x3x2xi32>, %arg1: tensor<2x3xi32>) -> () { // CHECK: %[[INIT:.+]] = tensor.empty() - // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#map0, #map1], iterator_types = ["parallel", "parallel", "parallel"]} ins(%arg1 : tensor<2x3xi32>) outs(%[[INIT]] : tensor<2x3x2xi32>) - // CHECK: ^bb0(%[[ARG0:.+]]: i32, %[[ARG1:.+]]: i32) + // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#map0, #map1], iterator_types = ["parallel", "parallel", "parallel"]} ins(%[[ARG1]] : tensor<2x3xi32>) outs(%[[INIT]] : tensor<2x3x2xi32>) + // CHECK: ^bb0(%[[BBARG0:.+]]: i32, %[[BBARG1:.+]]: i32) // CHECK: %[[IDX0:.+]] = linalg.index 0 - // CHECK: %[[CAST:.+]] = arith.index_cast %[[ARG0]] + // CHECK: %[[CAST:.+]] = arith.index_cast %[[BBARG0]] // CHECK: %[[IDX2:.+]] = linalg.index 2 - // CHECK: %[[EXTRACT:.+]] = tensor.extract %arg0[%[[IDX0]], %[[CAST]], %[[IDX2]]] : tensor<2x3x2xi32> + // CHECK: %[[EXTRACT:.+]] = tensor.extract %[[ARG0]][%[[IDX0]], %[[CAST]], %[[IDX2]]] : tensor<2x3x2xi32> // CHECK: linalg.yield %[[EXTRACT]] %0 = "tosa.gather"(%arg0, %arg1) : (tensor<2x3x2xi32>, tensor<2x3xi32>) -> (tensor<2x3x2xi32>) return @@ -1477,14 +1535,16 @@ func.func @gather_int(%arg0: tensor<2x3x2xi32>, %arg1: tensor<2x3xi32>) -> () { // ----- // CHECK-LABEL: @table8 +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]]: +// CHECK-SAME: %[[ARG1:[0-9a-zA-Z_]*]]: func.func @table8(%arg0: tensor<6xi8>, %arg1: tensor<512xi8>) -> () { // CHECK: %[[INIT:.+]] = tensor.empty() - // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#map, #map], iterator_types = ["parallel"]} ins(%arg0 : tensor<6xi8>) outs(%[[INIT]] : tensor<6xi8>) + // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#map, #map], iterator_types = ["parallel"]} ins(%[[ARG0]] : tensor<6xi8>) outs(%[[INIT]] : tensor<6xi8>) // CHECK: ^bb0(%[[ARG_IN:.+]]: i8, %[[ARG_INIT:.+]]: i8) // CHECK: %[[CAST:.+]] = arith.index_cast %[[ARG_IN]] // CHECK: %[[OFFSET:.+]] = arith.constant 128 // CHECK: %[[ADD:.+]] = arith.addi %[[CAST]], %[[OFFSET]] - // CHECK: %[[EXTRACT:.+]] = tensor.extract %arg1[%[[ADD]]] + // CHECK: %[[EXTRACT:.+]] = tensor.extract %[[ARG1]][%[[ADD]]] // CHECK: linalg.yield %[[EXTRACT]] %0 = "tosa.table"(%arg0, %arg1) : (tensor<6xi8>, tensor<512xi8>) -> (tensor<6xi8>) return @@ -1493,11 +1553,13 @@ func.func @table8(%arg0: tensor<6xi8>, %arg1: tensor<512xi8>) -> () { // ----- // CHECK-LABEL: @table16 +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]]: +// CHECK-SAME: %[[ARG1:[0-9a-zA-Z_]*]]: func.func @table16(%arg0: tensor<6xi16>, %arg1: tensor<513xi16>) -> () { // CHECK: %[[INIT:.+]] = tensor.empty() - // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#map, #map], iterator_types = ["parallel"]} ins(%arg0 : tensor<6xi16>) outs(%[[INIT]] : tensor<6xi32>) - // CHECK: ^bb0(%arg2: i16, %arg3: i32) - // CHECK: %[[EXT_IN:.+]] = arith.extsi %arg2 + // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#map, #map], iterator_types = ["parallel"]} ins(%[[ARG0]] : tensor<6xi16>) outs(%[[INIT]] : tensor<6xi32>) + // CHECK: ^bb0(%[[ARG2:.*]]: i16, %[[ARG3:.*]]: i32) + // CHECK: %[[EXT_IN:.+]] = arith.extsi %[[ARG2]] // CHECK: %[[C32768:.+]] = arith.constant 32768 // CHECK: %[[C7:.+]] = arith.constant 7 // CHECK: %[[C1:.+]] = arith.constant 1 @@ -1508,8 +1570,8 @@ func.func @table16(%arg0: tensor<6xi16>, %arg1: tensor<513xi16>) -> () { // CHECK: %[[IDXPLUS1:.+]] = arith.addi %[[IDX]], %[[C1]] // CHECK: %[[IDX_CAST:.+]] = arith.index_cast %[[IDX]] // CHECK: %[[IDXPLUS1_CAST:.+]] = arith.index_cast %[[IDXPLUS1]] - // CHECK: %[[BASE:.+]] = tensor.extract %arg1[%[[IDX_CAST]]] - // CHECK: %[[NEXT:.+]] = tensor.extract %arg1[%[[IDXPLUS1_CAST]]] + // CHECK: %[[BASE:.+]] = tensor.extract %[[ARG1]][%[[IDX_CAST]]] + // CHECK: %[[NEXT:.+]] = tensor.extract %[[ARG1]][%[[IDXPLUS1_CAST]]] // CHECK: %[[BASE_EXT:.+]] = arith.extsi %[[BASE]] // CHECK: %[[NEXT_EXT:.+]] = arith.extsi %[[NEXT]] // CHECK: %[[BASE_MUL:.+]] = arith.shli %[[BASE_EXT]], %[[C7]] @@ -1524,16 +1586,18 @@ func.func @table16(%arg0: tensor<6xi16>, %arg1: tensor<513xi16>) -> () { // ----- // CHECK-LABEL: @table8_dyn +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]]: +// CHECK-SAME: %[[ARG1:[0-9a-zA-Z_]*]]: func.func @table8_dyn(%arg0: tensor, %arg1: tensor<512xi8>) -> () { // CHECK: %[[CST0:.+]] = arith.constant 0 - // CHECK: %[[DYN:.+]] = tensor.dim %arg0, %[[CST0]] + // CHECK: %[[DYN:.+]] = tensor.dim %[[ARG0]], %[[CST0]] // CHECK: %[[INIT:.+]] = tensor.empty(%[[DYN]]) - // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#map, #map], iterator_types = ["parallel"]} ins(%arg0 : tensor) outs(%[[INIT]] : tensor) + // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#map, #map], iterator_types = ["parallel"]} ins(%[[ARG0]] : tensor) outs(%[[INIT]] : tensor) // CHECK: ^bb0(%[[ARG_IN:.+]]: i8, %[[ARG_INIT:.+]]: i8) // CHECK: %[[CAST:.+]] = arith.index_cast %[[ARG_IN]] // CHECK: %[[OFFSET:.+]] = arith.constant 128 // CHECK: %[[ADD:.+]] = arith.addi %[[CAST]], %[[OFFSET]] - // CHECK: %[[EXTRACT:.+]] = tensor.extract %arg1[%[[ADD]]] + // CHECK: %[[EXTRACT:.+]] = tensor.extract %[[ARG1]][%[[ADD]]] // CHECK: linalg.yield %[[EXTRACT]] %0 = "tosa.table"(%arg0, %arg1) : (tensor, tensor<512xi8>) -> (tensor) return @@ -1542,14 +1606,16 @@ func.func @table8_dyn(%arg0: tensor, %arg1: tensor<512xi8>) -> () { // ----- // CHECK-LABEL: @table8_dyn_table +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]]: +// CHECK-SAME: %[[ARG1:[0-9a-zA-Z_]*]]: func.func @table8_dyn_table(%arg0: tensor<6xi8>, %arg1: tensor) -> () { // CHECK: %[[INIT:.+]] = tensor.empty() - // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#map, #map], iterator_types = ["parallel"]} ins(%arg0 : tensor<6xi8>) outs(%[[INIT]] : tensor<6xi8>) + // CHECK: %[[GENERIC:.+]] = linalg.generic {indexing_maps = [#map, #map], iterator_types = ["parallel"]} ins(%[[ARG0]] : tensor<6xi8>) outs(%[[INIT]] : tensor<6xi8>) // CHECK: ^bb0(%[[ARG_IN:.+]]: i8, %[[ARG_INIT:.+]]: i8) // CHECK: %[[CAST:.+]] = arith.index_cast %[[ARG_IN]] // CHECK: %[[OFFSET:.+]] = arith.constant 128 // CHECK: %[[ADD:.+]] = arith.addi %[[CAST]], %[[OFFSET]] - // CHECK: %[[EXTRACT:.+]] = tensor.extract %arg1[%[[ADD]]] + // CHECK: %[[EXTRACT:.+]] = tensor.extract %[[ARG1]][%[[ADD]]] // CHECK: linalg.yield %[[EXTRACT]] %0 = "tosa.table"(%arg0, %arg1) : (tensor<6xi8>, tensor) -> (tensor<6xi8>) return @@ -1627,6 +1693,7 @@ func.func @resize_nearest(%input: tensor<1x2x2x1xf32>) -> () { // ----- // CHECK-LABEL: @resize_bilinear +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]]: func.func @resize_bilinear(%input: tensor<1x2x2x1xf32>) -> () { // CHECK: %[[INIT:.+]] = tensor.empty() // CHECK: %[[GENERIC:.+]] = linalg.generic @@ -1682,10 +1749,10 @@ func.func @resize_bilinear(%input: tensor<1x2x2x1xf32>) -> () { // CHECK: %[[XLOI:.+]] = arith.index_cast %[[XLO]] // CHECK: %[[XHII:.+]] = arith.index_cast %[[XHI]] - // CHECK: %[[LOLO:.+]] = tensor.extract %arg0[%[[IDX0]], %[[YLOI]], %[[XLOI]], %[[IDX3]]] - // CHECK: %[[LOHI:.+]] = tensor.extract %arg0[%[[IDX0]], %[[YLOI]], %[[XHII]], %[[IDX3]]] - // CHECK: %[[HILO:.+]] = tensor.extract %arg0[%[[IDX0]], %[[YHII]], %[[XLOI]], %[[IDX3]]] - // CHECK: %[[HIHI:.+]] = tensor.extract %arg0[%[[IDX0]], %[[YHII]], %[[XHII]], %[[IDX3]]] + // CHECK: %[[LOLO:.+]] = tensor.extract %[[ARG0]][%[[IDX0]], %[[YLOI]], %[[XLOI]], %[[IDX3]]] + // CHECK: %[[LOHI:.+]] = tensor.extract %[[ARG0]][%[[IDX0]], %[[YLOI]], %[[XHII]], %[[IDX3]]] + // CHECK: %[[HILO:.+]] = tensor.extract %[[ARG0]][%[[IDX0]], %[[YHII]], %[[XLOI]], %[[IDX3]]] + // CHECK: %[[HIHI:.+]] = tensor.extract %[[ARG0]][%[[IDX0]], %[[YHII]], %[[XHII]], %[[IDX3]]] // Compute the bilinear interpolation. @@ -1709,6 +1776,7 @@ func.func @resize_bilinear(%input: tensor<1x2x2x1xf32>) -> () { // ----- // CHECK-LABEL: @resize_nearest_int +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]]: func.func @resize_nearest_int(%input: tensor<1x2x2x1xi32>) -> () { // CHECK: %[[INIT:.+]] = tensor.empty() // CHECK: %[[GENERIC:.+]] = linalg.generic @@ -1768,7 +1836,7 @@ func.func @resize_nearest_int(%input: tensor<1x2x2x1xi32>) -> () { // CHECK-DAG: %[[IDY:.+]] = arith.index_cast %[[VAL25]] // CHECK-DAG: %[[IDX:.+]] = arith.index_cast %[[VAL29]] - // CHECK: %[[EXTRACT:.+]] = tensor.extract %arg0[%[[IDX0]], %[[IDY]], %[[IDX]], %[[IDX3]]] + // CHECK: %[[EXTRACT:.+]] = tensor.extract %[[ARG0]][%[[IDX0]], %[[IDY]], %[[IDX]], %[[IDX3]]] // CHECK: linalg.yield %[[EXTRACT]] %output = "tosa.resize"(%input) { output_size = [4, 4], stride = [128, 128], offset = [1, 2], stride_fp = [0. : f32, 0. : f32], offset_fp = [0. : f32, 0. : f32], shift = 8 : i32, mode = "NEAREST_NEIGHBOR" } : (tensor<1x2x2x1xi32>) -> (tensor<1x4x4x1xi32>) return @@ -1777,6 +1845,7 @@ func.func @resize_nearest_int(%input: tensor<1x2x2x1xi32>) -> () { // ----- // CHECK-LABEL: @resize_bilinear_int +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]]: func.func @resize_bilinear_int(%input: tensor<1x2x2x1xi8>) -> () { // CHECK: %[[INIT:.+]] = tensor.empty() // CHECK: %[[GENERIC:.+]] = linalg.generic @@ -1830,10 +1899,10 @@ func.func @resize_bilinear_int(%input: tensor<1x2x2x1xi8>) -> () { // CHECK: %[[XLOI:.+]] = arith.index_cast %[[XLO]] // CHECK: %[[XHII:.+]] = arith.index_cast %[[XHI]] - // CHECK: %[[LOLO:.+]] = tensor.extract %arg0[%[[IDX0]], %[[YLOI]], %[[XLOI]], %[[IDX3]]] - // CHECK: %[[LOHI:.+]] = tensor.extract %arg0[%[[IDX0]], %[[YLOI]], %[[XHII]], %[[IDX3]]] - // CHECK: %[[HILO:.+]] = tensor.extract %arg0[%[[IDX0]], %[[YHII]], %[[XLOI]], %[[IDX3]]] - // CHECK: %[[HIHI:.+]] = tensor.extract %arg0[%[[IDX0]], %[[YHII]], %[[XHII]], %[[IDX3]]] + // CHECK: %[[LOLO:.+]] = tensor.extract %[[ARG0]][%[[IDX0]], %[[YLOI]], %[[XLOI]], %[[IDX3]]] + // CHECK: %[[LOHI:.+]] = tensor.extract %[[ARG0]][%[[IDX0]], %[[YLOI]], %[[XHII]], %[[IDX3]]] + // CHECK: %[[HILO:.+]] = tensor.extract %[[ARG0]][%[[IDX0]], %[[YHII]], %[[XLOI]], %[[IDX3]]] + // CHECK: %[[HIHI:.+]] = tensor.extract %[[ARG0]][%[[IDX0]], %[[YHII]], %[[XHII]], %[[IDX3]]] // CHECK: %[[XLOLO:.+]] = arith.extsi %[[LOLO]] // CHECK: %[[XLOHI:.+]] = arith.extsi %[[LOHI]] @@ -1862,9 +1931,10 @@ func.func @resize_bilinear_int(%input: tensor<1x2x2x1xi8>) -> () { // ----- // CHECK-LABEL: @resize_dyn +// CHECK-SAME: (%[[ARG0:[0-9a-zA-Z_]*]]: func.func @resize_dyn(%input: tensor) -> () { // CHECK: %[[C0:.+]] = arith.constant 0 - // CHECK: %[[BATCH:.+]] = tensor.dim %arg0, %[[C0]] + // CHECK: %[[BATCH:.+]] = tensor.dim %[[ARG0]], %[[C0]] // CHECK: %[[INIT:.+]] = tensor.empty(%[[BATCH]]) // CHECK: %[[GENERIC:.+]] = linalg.generic %output = "tosa.resize"(%input) { output_size = [4, 4], stride = [128, 128], offset = [1, 2], stride_fp = [0. : f32, 0. : f32], offset_fp = [0. : f32, 0. : f32], shift = 8 : i32, mode = "BILINEAR" } : (tensor) -> (tensor) diff --git a/mlir/test/Dialect/Linalg/canonicalize-duplicate-inputs.mlir b/mlir/test/Dialect/Linalg/canonicalize-duplicate-inputs.mlir index 5ca63d9..108d870 100644 --- a/mlir/test/Dialect/Linalg/canonicalize-duplicate-inputs.mlir +++ b/mlir/test/Dialect/Linalg/canonicalize-duplicate-inputs.mlir @@ -239,21 +239,21 @@ func.func @multiple_redundant_args(%arg0 : tensor, %arg1 : tensor (d0)> // CHECK-DAG: #[[MAP3:.+]] = affine_map<(d0, d1) -> (d1, d0)> // CHECK: func @multiple_redundant_args( -// CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]]: tensor -// CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]]: tensor -// CHECK-SAME: %[[ARG2:[a-zA-Z0-9]+]]: tensor -// CHECK-SAME: %[[ARG3:[a-zA-Z0-9]+]]: tensor -// CHECK-SAME: %[[ARG4:[a-zA-Z0-9]+]]: tensor) +// CHECK-SAME: %[[ARG0:[a-zA-Z0-9_]+]]: tensor +// CHECK-SAME: %[[ARG1:[a-zA-Z0-9_]+]]: tensor +// CHECK-SAME: %[[ARG2:[a-zA-Z0-9_]+]]: tensor +// CHECK-SAME: %[[ARG3:[a-zA-Z0-9_]+]]: tensor +// CHECK-SAME: %[[ARG4:[a-zA-Z0-9_]+]]: tensor) // CHECK: %[[RETURN:.+]] = linalg.generic // CHECK-SAME: indexing_maps = [#[[MAP0]], #[[MAP1]], #[[MAP2]], #[[MAP3]], #[[MAP2]]] // CHECK-SAME: iterator_types = ["parallel", "reduction"] // CHECK-SAME: ins(%[[ARG4]], %[[ARG0]], %[[ARG1]], %[[ARG3]] : // CHECK-SAME: outs(%[[ARG2]] : // CHECK: ^{{.+}}(%[[B0:[a-zA-Z0-9]+]]: i32 -// CHECK-SAME: %[[B1:[a-zA-Z0-9]+]]: i32 -// CHECK-SAME: %[[B2:[a-zA-Z0-9]+]]: i32 -// CHECK-SAME: %[[B3:[a-zA-Z0-9]+]]: i32 -// CHECK-SAME: %[[B4:[a-zA-Z0-9]+]]: i32) +// CHECK-SAME: %[[B1:[a-zA-Z0-9_]+]]: i32 +// CHECK-SAME: %[[B2:[a-zA-Z0-9_]+]]: i32 +// CHECK-SAME: %[[B3:[a-zA-Z0-9_]+]]: i32 +// CHECK-SAME: %[[B4:[a-zA-Z0-9_]+]]: i32) // CHECK: %[[T0:.+]] = arith.addi %[[B0]], %[[B1]] // CHECK: %[[T1:.+]] = arith.addi %[[T0]], %[[B1]] // CHECK: %[[T2:.+]] = arith.addi %[[T1]], %[[B2]] diff --git a/mlir/test/Dialect/Linalg/decompose-ops.mlir b/mlir/test/Dialect/Linalg/decompose-ops.mlir index 3eed6d2..b562715 100644 --- a/mlir/test/Dialect/Linalg/decompose-ops.mlir +++ b/mlir/test/Dialect/Linalg/decompose-ops.mlir @@ -28,9 +28,9 @@ func.func @simple_op(%arg0 : tensor, %arg1 : tensor, %arg2 : ten // CHECK-DAG: #[[MAP2:.+]] = affine_map<(d0, d1) -> (d1)> // CHECK-DAG: #[[MAP3:.+]] = affine_map<(d0, d1) -> (d1, d0)> // CHECK: func @simple_op( -// CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]]: tensor -// CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]]: tensor -// CHECK-SAME: %[[ARG2:[a-zA-Z0-9]+]]: tensor +// CHECK-SAME: %[[ARG0:[a-zA-Z0-9_]+]]: tensor +// CHECK-SAME: %[[ARG1:[a-zA-Z0-9_]+]]: tensor +// CHECK-SAME: %[[ARG2:[a-zA-Z0-9_]+]]: tensor // CHECK-DAG: %[[C0:.+]] = arith.constant 0 : index // CHECK-DAG: %[[C1:.+]] = arith.constant 1 : index // CHECK-DAG: %[[D0:.+]] = tensor.dim %[[ARG0]], %[[C0]] @@ -43,26 +43,26 @@ func.func @simple_op(%arg0 : tensor, %arg1 : tensor, %arg2 : ten // CHECK-SAME: ins(%[[ARG0]], %[[ARG1]], %[[ARG2]] : // CHECK-SAME: outs(%[[INIT1]], %[[INIT2]], %[[INIT1]] : // CHECK-NEXT: ^bb0( -// CHECK-SAME: %[[B0:[a-zA-Z0-9]+]]: f32 -// CHECK-SAME: %[[B1:[a-zA-Z0-9]+]]: f32 -// CHECK-SAME: %[[B2:[a-zA-Z0-9]+]]: f32 -// CHECK-SAME: %[[B3:[a-zA-Z0-9]+]]: f32 -// CHECK-SAME: %[[B4:[a-zA-Z0-9]+]]: f32 -// CHECK-SAME: %[[B5:[a-zA-Z0-9]+]]: f32): +// CHECK-SAME: %[[B0:[a-zA-Z0-9_]+]]: f32 +// CHECK-SAME: %[[B1:[a-zA-Z0-9_]+]]: f32 +// CHECK-SAME: %[[B2:[a-zA-Z0-9_]+]]: f32 +// CHECK-SAME: %[[B3:[a-zA-Z0-9_]+]]: f32 +// CHECK-SAME: %[[B4:[a-zA-Z0-9_]+]]: f32 +// CHECK-SAME: %[[B5:[a-zA-Z0-9_]+]]: f32): // CHECK-NEXT: %[[S0:.+]] = arith.addf %[[B0]], %[[B1]] -// CHECK-NEXT: linalg.yield %[[S0]], %{{[a-zA-Z0-9]+}}, %[[S0]] +// CHECK-NEXT: linalg.yield %[[S0]], %{{[a-zA-Z0-9_]+}}, %[[S0]] // CHECK: %[[GENERIC2:.+]]:2 = linalg.generic // CHECK-SAME: [#[[MAP0]], #[[MAP1]], #[[MAP2]], #[[MAP3]], #[[MAP3]], #[[MAP0]]] // CHECK-SAME: ["parallel", "parallel"] // CHECK-SAME: ins(%[[ARG0]], %[[ARG1]], %[[ARG2]], %[[GENERIC1]]#2 : // CHECK-SAME: outs(%[[INIT1]], %[[INIT2]] : // CHECK-NEXT: ^bb0( -// CHECK-SAME: %[[B6:[a-zA-Z0-9]+]]: f32 -// CHECK-SAME: %[[B7:[a-zA-Z0-9]+]]: f32 -// CHECK-SAME: %[[B8:[a-zA-Z0-9]+]]: f32 -// CHECK-SAME: %[[B9:[a-zA-Z0-9]+]]: f32 -// CHECK-SAME: %[[B10:[a-zA-Z0-9]+]]: f32 -// CHECK-SAME: %[[B11:[a-zA-Z0-9]+]]: f32): +// CHECK-SAME: %[[B6:[a-zA-Z0-9_]+]]: f32 +// CHECK-SAME: %[[B7:[a-zA-Z0-9_]+]]: f32 +// CHECK-SAME: %[[B8:[a-zA-Z0-9_]+]]: f32 +// CHECK-SAME: %[[B9:[a-zA-Z0-9_]+]]: f32 +// CHECK-SAME: %[[B10:[a-zA-Z0-9_]+]]: f32 +// CHECK-SAME: %[[B11:[a-zA-Z0-9_]+]]: f32): // CHECK-NEXT: %[[S1:.+]] = arith.mulf %[[B9]], %[[B8]] // CHECK-NEXT: linalg.yield %[[B9]], %[[S1]] // CHECK: return %[[GENERIC1]]#0, %[[GENERIC2]]#1 @@ -74,9 +74,9 @@ func.func @simple_op(%arg0 : tensor, %arg1 : tensor, %arg2 : ten // CANONICALIZECHECK-DAG: #[[MAP2:.+]] = affine_map<(d0, d1) -> (d1, d0)> // CANONICALIZECHECK-DAG: #[[MAP3:.+]] = affine_map<(d0, d1) -> (d1)> // CANONICALIZECHECK: func @simple_op( -// CANONICALIZECHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]]: tensor -// CANONICALIZECHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]]: tensor -// CANONICALIZECHECK-SAME: %[[ARG2:[a-zA-Z0-9]+]]: tensor +// CANONICALIZECHECK-SAME: %[[ARG0:[a-zA-Z0-9_]+]]: tensor +// CANONICALIZECHECK-SAME: %[[ARG1:[a-zA-Z0-9_]+]]: tensor +// CANONICALIZECHECK-SAME: %[[ARG2:[a-zA-Z0-9_]+]]: tensor // CANONICALIZECHECK-DAG: %[[C0:.+]] = arith.constant 0 : index // CANONICALIZECHECK-DAG: %[[C1:.+]] = arith.constant 1 : index // CANONICALIZECHECK-DAG: %[[D0:.+]] = tensor.dim %[[ARG0]], %[[C0]] @@ -89,9 +89,9 @@ func.func @simple_op(%arg0 : tensor, %arg1 : tensor, %arg2 : ten // CANONICALIZECHECK-SAME: ins(%[[ARG0]], %[[ARG1]] : // CANONICALIZECHECK-SAME: outs(%[[INIT1]] : // CANONICALIZECHECK-NEXT: ^bb0( -// CANONICALIZECHECK-SAME: %[[B0:[a-zA-Z0-9]+]]: f32 -// CANONICALIZECHECK-SAME: %[[B1:[a-zA-Z0-9]+]]: f32 -// CANONICALIZECHECK-SAME: %[[B2:[a-zA-Z0-9]+]]: f32): +// CANONICALIZECHECK-SAME: %[[B0:[a-zA-Z0-9_]+]]: f32 +// CANONICALIZECHECK-SAME: %[[B1:[a-zA-Z0-9_]+]]: f32 +// CANONICALIZECHECK-SAME: %[[B2:[a-zA-Z0-9_]+]]: f32): // CANONICALIZECHECK-NEXT: %[[S0:.+]] = arith.addf %[[B0]], %[[B1]] // CANONICALIZECHECK-NEXT: linalg.yield %[[S0]] // CANONICALIZECHECK: %[[GENERIC2:.+]] = linalg.generic @@ -100,9 +100,9 @@ func.func @simple_op(%arg0 : tensor, %arg1 : tensor, %arg2 : ten // CANONICALIZECHECK-SAME: ins(%[[ARG2]], %[[GENERIC1]] : // CANONICALIZECHECK-SAME: outs(%[[INIT2]] : // CANONICALIZECHECK-NEXT: ^bb0( -// CANONICALIZECHECK-SAME: %[[B3:[a-zA-Z0-9]+]]: f32 -// CANONICALIZECHECK-SAME: %[[B4:[a-zA-Z0-9]+]]: f32 -// CANONICALIZECHECK-SAME: %[[B5:[a-zA-Z0-9]+]]: f32): +// CANONICALIZECHECK-SAME: %[[B3:[a-zA-Z0-9_]+]]: f32 +// CANONICALIZECHECK-SAME: %[[B4:[a-zA-Z0-9_]+]]: f32 +// CANONICALIZECHECK-SAME: %[[B5:[a-zA-Z0-9_]+]]: f32): // CANONICALIZECHECK-NEXT: %[[S1:.+]] = arith.mulf %[[B4]], %[[B3]] // CANONICALIZECHECK-NEXT: linalg.yield %[[S1]] // CANONICALIZECHECK: return %[[GENERIC1]], %[[GENERIC2]] @@ -137,9 +137,9 @@ func.func @simple_op_permuted_outputs(%arg0 : tensor, %arg1 : tensor (d1)> // CHECK-DAG: #[[MAP3:.+]] = affine_map<(d0, d1) -> (d1, d0)> // CHECK: func @simple_op_permuted_outputs( -// CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]]: tensor -// CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]]: tensor -// CHECK-SAME: %[[ARG2:[a-zA-Z0-9]+]]: tensor +// CHECK-SAME: %[[ARG0:[a-zA-Z0-9_]+]]: tensor +// CHECK-SAME: %[[ARG1:[a-zA-Z0-9_]+]]: tensor +// CHECK-SAME: %[[ARG2:[a-zA-Z0-9_]+]]: tensor // CHECK-DAG: %[[C0:.+]] = arith.constant 0 : index // CHECK-DAG: %[[C1:.+]] = arith.constant 1 : index // CHECK-DAG: %[[D0:.+]] = tensor.dim %[[ARG0]], %[[C0]] @@ -152,27 +152,27 @@ func.func @simple_op_permuted_outputs(%arg0 : tensor, %arg1 : tensor, %arg1 : tensor (d1, d0)> // CANONICALIZECHECK-DAG: #[[MAP3:.+]] = affine_map<(d0, d1) -> (d1)> // CANONICALIZECHECK: func @simple_op_permuted_outputs( -// CANONICALIZECHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]]: tensor -// CANONICALIZECHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]]: tensor -// CANONICALIZECHECK-SAME: %[[ARG2:[a-zA-Z0-9]+]]: tensor +// CANONICALIZECHECK-SAME: %[[ARG0:[a-zA-Z0-9_]+]]: tensor +// CANONICALIZECHECK-SAME: %[[ARG1:[a-zA-Z0-9_]+]]: tensor +// CANONICALIZECHECK-SAME: %[[ARG2:[a-zA-Z0-9_]+]]: tensor // CANONICALIZECHECK-DAG: %[[C0:.+]] = arith.constant 0 : index // CANONICALIZECHECK-DAG: %[[C1:.+]] = arith.constant 1 : index // CANONICALIZECHECK-DAG: %[[D0:.+]] = tensor.dim %[[ARG0]], %[[C0]] @@ -197,9 +197,9 @@ func.func @simple_op_permuted_outputs(%arg0 : tensor, %arg1 : tensor, %arg1 : tensor, %arg1 : tensor<10xi32>) -> // CHECK-NEXT: ^bb0( // CHECK-SAME: %[[B0:.+]]: f32 // CHECK-SAME: %[[B1:.+]]: i32 -// CHECK-SAME: %[[B2:[a-zA-Z0-9]+]]: f64 +// CHECK-SAME: %[[B2:[a-zA-Z0-9_]+]]: f64 // CHECK-SAME: %[[B3:.+]]: f64 // CHECK-NEXT: %[[S0:.+]] = arith.sitofp %[[B1]] : i32 to f64 // CHECK-NEXT: linalg.yield %{{.+}}, %[[S0]] @@ -264,8 +264,8 @@ func.func @multi_statement(%arg0 : tensor<10x20xf32>, %arg1 : tensor<10xi32>) -> // CHECK-NEXT: ^bb0( // CHECK-SAME: %[[B4:.+]]: f32 // CHECK-SAME: %[[B5:.+]]: i32 -// CHECK-SAME: %[[B6:[a-zA-Z0-9]+]]: f64 -// CHECK-SAME: %[[B7:[a-zA-Z0-9]+]]: f64 +// CHECK-SAME: %[[B6:[a-zA-Z0-9_]+]]: f64 +// CHECK-SAME: %[[B7:[a-zA-Z0-9_]+]]: f64 // CHECK-SAME: %[[B8:.+]]: f64 // CHECK-NEXT: %[[S1:.+]] = arith.extf %[[B4]] : f32 to f64 // CHECK-NEXT: linalg.yield %{{.+}}, %[[S1]] @@ -277,8 +277,8 @@ func.func @multi_statement(%arg0 : tensor<10x20xf32>, %arg1 : tensor<10xi32>) -> // CHECK-NEXT: ^bb0( // CHECK-SAME: %[[B9:.+]]: f32 // CHECK-SAME: %[[B10:.+]]: i32 -// CHECK-SAME: %[[B11:[a-zA-Z0-9]+]]: f64 -// CHECK-SAME: %[[B12:[a-zA-Z0-9]+]]: f64 +// CHECK-SAME: %[[B11:[a-zA-Z0-9_]+]]: f64 +// CHECK-SAME: %[[B12:[a-zA-Z0-9_]+]]: f64 // CHECK-SAME: %[[B13:.+]]: f64 // CHECK-NEXT: %[[S2:.+]] = arith.addf %[[B11]], %[[B12]] : f64 // CHECK-NEXT: linalg.yield %[[S2]] @@ -318,8 +318,8 @@ func.func @multi_statement(%arg0 : tensor<10x20xf32>, %arg1 : tensor<10xi32>) -> // CANONICALIZECHECK-SAME: ins(%[[GENERIC0]], %[[GENERIC1]] : // CANONICALIZECHECK-SAME: outs(%[[INIT0]] : // CANONICALIZECHECK-NEXT: ^bb0( -// CANONICALIZECHECK-SAME: %[[B4:[a-zA-Z0-9]+]]: f64 -// CANONICALIZECHECK-SAME: %[[B5:[a-zA-Z0-9]+]]: f64 +// CANONICALIZECHECK-SAME: %[[B4:[a-zA-Z0-9_]+]]: f64 +// CANONICALIZECHECK-SAME: %[[B5:[a-zA-Z0-9_]+]]: f64 // CANONICALIZECHECK-SAME: %[[B6:.+]]: f64 // CANONICALIZECHECK-NEXT: %[[S2:.+]] = arith.addf %[[B4]], %[[B5]] : f64 // CANONICALIZECHECK-NEXT: linalg.yield %[[S2]] @@ -352,21 +352,21 @@ func.func @destination_passing_style( // CHECK-DAG: #[[MAP2:.+]] = affine_map<(d0, d1) -> (d0, d1)> // CHECK-DAG: #[[MAP3:.+]] = affine_map<(d0, d1) -> (d1, d0)> // CHECK: func.func @destination_passing_style( -// CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]]: tensor -// CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]]: tensor -// CHECK-SAME: %[[ARG2:[a-zA-Z0-9]+]]: tensor -// CHECK-SAME: %[[ARG3:[a-zA-Z0-9]+]]: tensor) +// CHECK-SAME: %[[ARG0:[a-zA-Z0-9_]+]]: tensor +// CHECK-SAME: %[[ARG1:[a-zA-Z0-9_]+]]: tensor +// CHECK-SAME: %[[ARG2:[a-zA-Z0-9_]+]]: tensor +// CHECK-SAME: %[[ARG3:[a-zA-Z0-9_]+]]: tensor) // CHECK: %[[GENERIC1:.+]]:3 = linalg.generic // CHECK-SAME: indexing_maps = [#[[MAP0]], #[[MAP1]], #[[MAP2]], #[[MAP3]], #[[MAP2]]] // CHECK-SAME: iterator_types = ["parallel", "parallel"] // CHECK-SAME: ins(%[[ARG0]], %[[ARG1]] : // CHECK-SAME: outs(%[[ARG2]], %[[ARG3]], %[[ARG2]] : // CHECK-NEXT: ^bb0( -// CHECK-SAME: %[[ARG4:[a-zA-Z0-9]+]]: f32 -// CHECK-SAME: %[[ARG5:[a-zA-Z0-9]+]]: f32 -// CHECK-SAME: %[[ARG6:[a-zA-Z0-9]+]]: f32 -// CHECK-SAME: %[[ARG7:[a-zA-Z0-9]+]]: f32 -// CHECK-SAME: %[[ARG8:[a-zA-Z0-9]+]]: f32 +// CHECK-SAME: %[[ARG4:[a-zA-Z0-9_]+]]: f32 +// CHECK-SAME: %[[ARG5:[a-zA-Z0-9_]+]]: f32 +// CHECK-SAME: %[[ARG6:[a-zA-Z0-9_]+]]: f32 +// CHECK-SAME: %[[ARG7:[a-zA-Z0-9_]+]]: f32 +// CHECK-SAME: %[[ARG8:[a-zA-Z0-9_]+]]: f32 // CHECK-NEXT: %[[S1:.+]] = arith.addf %[[ARG4]], %[[ARG6]] // CHECK-NEXT: linalg.yield %[[S1]], %{{.+}}, %[[S1]] // CHECK: %[[GENERIC2:.+]]:2 = linalg.generic @@ -375,13 +375,13 @@ func.func @destination_passing_style( // CHECK-SAME: ins(%[[ARG0]], %[[ARG1]], %[[GENERIC1]]#2 : // CHECK-SAME: outs(%[[ARG2]], %[[ARG3]] : // CHECK-NEXT: ^bb0( -// CHECK-SAME: %[[ARG9:[a-zA-Z0-9]+]]: f32 -// CHECK-SAME: %[[ARG10:[a-zA-Z0-9]+]]: f32 -// CHECK-SAME: %[[ARG11:[a-zA-Z0-9]+]]: f32 -// CHECK-SAME: %[[ARG12:[a-zA-Z0-9]+]]: f32 -// CHECK-SAME: %[[ARG13:[a-zA-Z0-9]+]]: f32 +// CHECK-SAME: %[[ARG9:[a-zA-Z0-9_]+]]: f32 +// CHECK-SAME: %[[ARG10:[a-zA-Z0-9_]+]]: f32 +// CHECK-SAME: %[[ARG11:[a-zA-Z0-9_]+]]: f32 +// CHECK-SAME: %[[ARG12:[a-zA-Z0-9_]+]]: f32 +// CHECK-SAME: %[[ARG13:[a-zA-Z0-9_]+]]: f32 // CHECK-NEXT: %[[S2:.+]] = arith.mulf %[[ARG10]], %[[ARG12]] -// CHECK-NEXT: linalg.yield %[[ARG6]], %[[S2]] +// CHECK-NEXT: linalg.yield %[[ARG11]], %[[S2]] // CHECK: return %[[GENERIC1]]#0, %[[GENERIC2]]#1 // CANONICALIZECHECK-DAG: #[[MAP0:.+]] = affine_map<(d0, d1) -> (d0)> @@ -389,18 +389,18 @@ func.func @destination_passing_style( // CANONICALIZECHECK-DAG: #[[MAP2:.+]] = affine_map<(d0, d1) -> (d1)> // CANONICALIZECHECK-DAG: #[[MAP3:.+]] = affine_map<(d0, d1) -> (d1, d0)> // CANONICALIZECHECK: func.func @destination_passing_style( -// CANONICALIZECHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]]: tensor -// CANONICALIZECHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]]: tensor -// CANONICALIZECHECK-SAME: %[[ARG2:[a-zA-Z0-9]+]]: tensor -// CANONICALIZECHECK-SAME: %[[ARG3:[a-zA-Z0-9]+]]: tensor) +// CANONICALIZECHECK-SAME: %[[ARG0:[a-zA-Z0-9_]+]]: tensor +// CANONICALIZECHECK-SAME: %[[ARG1:[a-zA-Z0-9_]+]]: tensor +// CANONICALIZECHECK-SAME: %[[ARG2:[a-zA-Z0-9_]+]]: tensor +// CANONICALIZECHECK-SAME: %[[ARG3:[a-zA-Z0-9_]+]]: tensor) // CANONICALIZECHECK: %[[GENERIC1:.+]] = linalg.generic // CANONICALIZECHECK-SAME: indexing_maps = [#[[MAP0]], #[[MAP1]]] // CANONICALIZECHECK-SAME: iterator_types = ["parallel", "parallel"] // CANONICALIZECHECK-SAME: ins(%[[ARG0]] : // CANONICALIZECHECK-SAME: outs(%[[ARG2]] : // CANONICALIZECHECK-NEXT: ^bb0( -// CANONICALIZECHECK-SAME: %[[ARG4:[a-zA-Z0-9]+]]: f32 -// CANONICALIZECHECK-SAME: %[[ARG5:[a-zA-Z0-9]+]]: f32 +// CANONICALIZECHECK-SAME: %[[ARG4:[a-zA-Z0-9_]+]]: f32 +// CANONICALIZECHECK-SAME: %[[ARG5:[a-zA-Z0-9_]+]]: f32 // CANONICALIZECHECK-NEXT: %[[S1:.+]] = arith.addf %[[ARG4]], %[[ARG5]] // CANONICALIZECHECK-NEXT: linalg.yield %[[S1]] // CANONICALIZECHECK: %[[GENERIC2:.+]]:2 = linalg.generic @@ -409,10 +409,10 @@ func.func @destination_passing_style( // CANONICALIZECHECK-SAME: ins(%[[ARG1]], %[[GENERIC1]] : // CANONICALIZECHECK-SAME: outs(%[[ARG2]], %[[ARG3]] : // CANONICALIZECHECK-NEXT: ^bb0( -// CANONICALIZECHECK-SAME: %[[ARG4:[a-zA-Z0-9]+]]: f32 -// CANONICALIZECHECK-SAME: %[[ARG5:[a-zA-Z0-9]+]]: f32 -// CANONICALIZECHECK-SAME: %[[ARG6:[a-zA-Z0-9]+]]: f32 -// CANONICALIZECHECK-SAME: %[[ARG7:[a-zA-Z0-9]+]]: f32 +// CANONICALIZECHECK-SAME: %[[ARG4:[a-zA-Z0-9_]+]]: f32 +// CANONICALIZECHECK-SAME: %[[ARG5:[a-zA-Z0-9_]+]]: f32 +// CANONICALIZECHECK-SAME: %[[ARG6:[a-zA-Z0-9_]+]]: f32 +// CANONICALIZECHECK-SAME: %[[ARG7:[a-zA-Z0-9_]+]]: f32 // CANONICALIZECHECK-NEXT: %[[S2:.+]] = arith.mulf %[[ARG4]], %[[ARG6]] // CANONICALIZECHECK-NEXT: linalg.yield %[[ARG5]], %[[S2]] // CANONICALIZECHECK: return %[[GENERIC1]], %[[GENERIC2]]#1 diff --git a/mlir/test/Dialect/Linalg/fusion-elementwise-ops.mlir b/mlir/test/Dialect/Linalg/fusion-elementwise-ops.mlir index cf69f04..ca142e3 100644 --- a/mlir/test/Dialect/Linalg/fusion-elementwise-ops.mlir +++ b/mlir/test/Dialect/Linalg/fusion-elementwise-ops.mlir @@ -663,7 +663,7 @@ func.func @generic_index_op2(%arg0: tensor<1x8xf64>, %arg1: tensor<1x8xi32>) -> } -> tensor<1x8xf64> // CHECK-NEXT: %[[R:.*]]:2 = linalg.generic - // CHECK: bb0(%[[BBA:[0-9a-z]*]]: f64, %[[BBB:[0-9a-z]*]]: i32): + // CHECK: bb0(%[[BBA:[0-9a-zA-Z_]*]]: f64, %[[BBB:[0-9a-zA-Z_]*]]: i32): // CHECK-NEXT: %[[A:.*]] = func.call @compute1(%[[BBA]]) : (f64) -> f64 // CHECK-NEXT: %[[B:.*]] = func.call @compute2(%[[A]], %[[BBB]]) : (f64, i32) -> i32 // CHECK-NEXT: linalg.yield %[[A]], %[[B]] : f64, i32 @@ -1071,15 +1071,15 @@ module { } } // CHECK-LABEL: func.func @fuse_multi_result_producer -// CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]]: tensor -// CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]]: tensor +// CHECK-SAME: %[[ARG0:[a-zA-Z0-9_]+]]: tensor +// CHECK-SAME: %[[ARG1:[a-zA-Z0-9_]+]]: tensor // CHECK: %[[INIT:.+]] = tensor.empty // CHECK: %[[GENERIC:.+]] = linalg.generic // CHECK-SAME: ins(%[[ARG0]], %[[ARG1]] : // CHECK-SAME: outs(%[[INIT]] : // CHECK-NEXT: ^bb0 -// CHECK-SAME: %[[B0:[a-zA-Z0-9]+]]: f32 -// CHECK-SAME: %[[B1:[a-zA-Z0-9]+]]: f32 +// CHECK-SAME: %[[B0:[a-zA-Z0-9_]+]]: f32 +// CHECK-SAME: %[[B1:[a-zA-Z0-9_]+]]: f32 // CHECK-DAG: %[[T0:.+]] = arith.addf %[[B0]], %[[B1]] // CHECK-DAG: %[[T1:.+]] = arith.addf %[[T0]], %[[B1]] // CHECK-DAG: %[[T2:.+]] = arith.addf %[[T1]], %[[B1]] diff --git a/mlir/test/Dialect/Linalg/lower-pad-tensor.mlir b/mlir/test/Dialect/Linalg/lower-pad-tensor.mlir index b98086a..3349af6 100644 --- a/mlir/test/Dialect/Linalg/lower-pad-tensor.mlir +++ b/mlir/test/Dialect/Linalg/lower-pad-tensor.mlir @@ -57,7 +57,7 @@ func.func @pad_tensor_detailed(%arg0: tensor<1x28x28x1xf32>) -> tensor<1x32x32x1 // CHECK: %[[R2c:.+]] = linalg.generic // CHECK-SAME: indexing_maps = [#[[$MAP4]], #[[$MAP5]]] // CHECK-SAME: iterator_types = ["parallel", "parallel", "parallel", "parallel"] -// CHECK: ins(%arg0 : tensor<1x28x28x1xf32>) outs(%1 : tensor<1x32x32x1xf32>) -// CHECK: ^bb0(%[[VAL:.+]]: f32, %arg2: f32) +// CHECK: ins(%{{.*}} : tensor<1x28x28x1xf32>) outs(%{{.*}} : tensor<1x32x32x1xf32>) +// CHECK: ^bb0(%[[VAL:.+]]: f32, %{{.*}}: f32) // CHECK: linalg.yield %[[VAL]] : f32 // CHECK: return %[[R2c:.+]] diff --git a/mlir/test/Dialect/Linalg/reshape_fusion.mlir b/mlir/test/Dialect/Linalg/reshape_fusion.mlir index 5c4be8a..2506eee 100644 --- a/mlir/test/Dialect/Linalg/reshape_fusion.mlir +++ b/mlir/test/Dialect/Linalg/reshape_fusion.mlir @@ -212,8 +212,8 @@ func.func @indexed_consumer_reshape_producer_fusion(%arg0 : tensor, // CHECK: func @indexed_consumer_reshape_producer_fusion // CHECK: linalg.generic // CHECK: ^{{.*}}( -// CHECK-SAME: %[[ARG3:[a-zA-Z0-9]+]]: i32, %[[ARG4:[a-zA-Z0-9]+]]: i32, -// CHECK-SAME: %[[ARG8:[a-zA-Z0-9]+]]: i32) +// CHECK-SAME: %[[ARG3:[a-zA-Z0-9_]+]]: i32, %[[ARG4:[a-zA-Z0-9_]+]]: i32, +// CHECK-SAME: %[[ARG8:[a-zA-Z0-9_]+]]: i32) // CHECK-DAG: %[[IDX0:.+]] = linalg.index 0 : index // CHECK-DAG: %[[IDX1:.+]] = linalg.index 1 : index // CHECK-DAG: %[[IDX2:.+]] = linalg.index 2 : index @@ -261,8 +261,8 @@ func.func @indexed_producer_reshape_consumer_fusion(%arg0 : tensor, // CHECK: func @indexed_producer_reshape_consumer_fusion // CHECK: linalg.generic // CHECK: ^{{.*}}( -// CHECK-SAME: %[[ARG3:[a-zA-Z0-9]+]]: i32, %[[ARG4:[a-zA-Z0-9]+]]: i32, -// CHECK-SAME: %[[ARG5:[a-zA-Z0-9]+]]: i32) +// CHECK-SAME: %[[ARG3:[a-zA-Z0-9_]+]]: i32, %[[ARG4:[a-zA-Z0-9_]+]]: i32, +// CHECK-SAME: %[[ARG5:[a-zA-Z0-9_]+]]: i32) // CHECK-DAG: %[[IDX0:.+]] = linalg.index 0 : index // CHECK-DAG: %[[IDX1:.+]] = linalg.index 1 : index // CHECK-DAG: %[[IDX2:.+]] = linalg.index 2 : index @@ -331,8 +331,8 @@ func.func @reshape_as_consumer_permutation // CHECK-SAME: ins(%[[T1]], %[[T2]] : tensor<5x6x7x2x3x4xi32>, tensor<5x6x7x4xi32>) // CHECK-SAME: outs(%[[T3]] : tensor<2x3x4x5x6x7xi32>) // CHECK: ^{{.+}}( -// CHECK-SAME: %[[ARG8:[a-zA-Z0-9]+]]: i32, %[[ARG9:[a-zA-Z0-9]+]]: i32, -// CHECK-SAME: %[[ARG10:[a-zA-Z0-9]+]]: i32) +// CHECK-SAME: %[[ARG8:[a-zA-Z0-9_]+]]: i32, %[[ARG9:[a-zA-Z0-9_]+]]: i32, +// CHECK-SAME: %[[ARG10:[a-zA-Z0-9_]+]]: i32) // CHECK-DAG: %[[IDX0:.+]] = linalg.index 0 : index // CHECK-DAG: %[[IDX1:.+]] = linalg.index 1 : index // CHECK-DAG: %[[IDX2:.+]] = linalg.index 2 : index -- 2.7.4