[mlir][tosa] Align check variables naming to use capitals #127830
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Signed-off-by: Georgios Pinitas <[email protected]>
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@llvm/pr-subscribers-mlir @llvm/pr-subscribers-mlir-tosa Author: Georgios Pinitas (GeorgeARM) ChangesMove in using capital letters for variable capture in LIT Full diff: https://github.com/llvm/llvm-project/pull/127830.diff 3 Files Affected:
diff --git a/mlir/test/Dialect/Tosa/tosa-decompose-depthwise.mlir b/mlir/test/Dialect/Tosa/tosa-decompose-depthwise.mlir
index 6562a7c2ab55c..d0c0c8456d1ca 100644
--- a/mlir/test/Dialect/Tosa/tosa-decompose-depthwise.mlir
+++ b/mlir/test/Dialect/Tosa/tosa-decompose-depthwise.mlir
@@ -31,22 +31,22 @@ func.func @depthwise_conv2d_as_mul(%arg0: tensor<4x10x10x2xf32>, %arg1: tensor<1
// CHECK-LABEL: @depthwise_conv2d_as_mul_q
func.func @depthwise_conv2d_as_mul_q(%arg0: tensor<4x10x10x2xi8>, %arg1: tensor<1x1x2x3xi8>, %arg2: tensor<6xi32>) -> tensor<4x10x10x6xi32> {
// CHECK-DAG: %[[CONST0:.+]] = tosa.const_shape {value = dense<[4, 10, 10, 2, 1]> : tensor<5xindex>
- // CHECK-DAG: %[[iZp:.+]] = "tosa.const"() <{value = dense<7> : tensor<1x1x1x1x1xi32>}
- // CHECK-DAG: %[[wZp:.+]] = "tosa.const"() <{value = dense<11> : tensor<1x1x1x1xi32>}
+ // CHECK-DAG: %[[INPUT_ZP:.+]] = "tosa.const"() <{value = dense<7> : tensor<1x1x1x1x1xi32>}
+ // CHECK-DAG: %[[WEIGHT_ZP:.+]] = "tosa.const"() <{value = dense<11> : tensor<1x1x1x1xi32>}
// CHECK-DAG: %[[CONST3:.+]] = tosa.const_shape {value = dense<[1, 1, 1, 2, 3]> : tensor<5xindex>
// CHECK-DAG: %[[CONST4:.+]] = tosa.const_shape {value = dense<[4, 10, 10, 6]> : tensor<4xindex>
// CHECK-DAG: %[[CONST5:.+]] = tosa.const_shape {value = dense<[1, 1, 1, 6]> : tensor<4xindex>
// CHECK-DAG: %[[SHIFT:.*]] = "tosa.const"() <{value = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
- // CHECK: %[[rIn:.+]] = tosa.reshape %arg0, %[[CONST0]]
- // CHECK: %[[cIn:.+]] = tosa.cast %[[rIn]] : (tensor<4x10x10x2x1xi8>) -> tensor<4x10x10x2x1xi32>
- // CHECK: %[[cWe:.+]] = tosa.cast %arg1 : (tensor<1x1x2x3xi8>) -> tensor<1x1x2x3xi32>
- // CHECK: %[[sIn:.+]] = tosa.sub %[[cIn]], %[[iZp]]
- // CHECK: %[[sWe:.+]] = tosa.sub %[[cWe]], %[[wZp]]
- // CHECK: %[[resWe:.+]] = tosa.reshape %[[sWe]], %[[CONST3]]
- // CHECK: %[[mul:.+]] = tosa.mul %[[sIn]], %[[resWe]], %[[SHIFT]]
- // CHECK: %[[reO:.+]] = tosa.reshape %[[mul]], %[[CONST4]]
- // CHECK: %[[reArg2:.+]] = tosa.reshape %arg2, %[[CONST5]]
- // CHECK: %[[add:.+]] = tosa.add %[[reO]], %[[reArg2]]
+ // CHECK: %[[RESHAPE_I:.+]] = tosa.reshape %arg0, %[[CONST0]]
+ // CHECK: %[[CAST_I:.+]] = tosa.cast %[[RESHAPE_I]] : (tensor<4x10x10x2x1xi8>) -> tensor<4x10x10x2x1xi32>
+ // CHECK: %[[CAST_W:.+]] = tosa.cast %arg1 : (tensor<1x1x2x3xi8>) -> tensor<1x1x2x3xi32>
+ // CHECK: %[[SUB_I:.+]] = tosa.sub %[[CAST_I]], %[[INPUT_ZP]]
+ // CHECK: %[[SUB_W:.+]] = tosa.sub %[[CAST_W]], %[[WEIGHT_ZP]]
+ // CHECK: %[[RESHAPE_W:.+]] = tosa.reshape %[[SUB_W]], %[[CONST3]]
+ // CHECK: %[[MUL:.+]] = tosa.mul %[[SUB_I]], %[[RESHAPE_W]], %[[SHIFT]]
+ // CHECK: %[[RESHAPE_O:.+]] = tosa.reshape %[[MUL]], %[[CONST4]]
+ // CHECK: %[[RESHAPE_ARG2:.+]] = tosa.reshape %arg2, %[[CONST5]]
+ // CHECK: %[[ADD:.+]] = tosa.add %[[RESHAPE_O]], %[[RESHAPE_ARG2]]
%input_zp = "tosa.const"() {value = dense<7> : tensor<1xi8>} : () -> tensor<1xi8>
%weight_zp = "tosa.const"() {value = dense<11> : tensor<1xi8>} : () -> tensor<1xi8>
%0 = tosa.depthwise_conv2d %arg0, %arg1, %arg2, %input_zp, %weight_zp {acc_type = i32, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>, dilation = array<i64: 1, 1> } : (tensor<4x10x10x2xi8>, tensor<1x1x2x3xi8>, tensor<6xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<4x10x10x6xi32>
@@ -58,19 +58,19 @@ func.func @depthwise_conv2d_as_mul_q(%arg0: tensor<4x10x10x2xi8>, %arg1: tensor<
// CHECK-LABEL: @depthwise_conv2d_as_mul_padded
func.func @depthwise_conv2d_as_mul_padded(%arg0: tensor<4x10x10x2xf32>, %arg1: tensor<1x1x2x3xf32>, %arg2: tensor<6xf32>) -> tensor<4x12x12x6xf32> {
// CHECK-DAG: %[[CONST0:.+]] = tosa.const_shape {value = dense<[4, 10, 10, 2, 1]> : tensor<5xindex>}
- // CHECK-DAG: %[[pad:.+]] = tosa.const_shape {value = dense<[0, 0, 1, 1, 1, 1, 0, 0, 0, 0]> : tensor<10xindex>} : () -> !tosa.shape<10>
- // CHECK-DAG: %[[zero:.+]] = "tosa.const"() <{value = dense<0.000000e+00> : tensor<f32>}
+ // CHECK-DAG: %[[PAD:.+]] = tosa.const_shape {value = dense<[0, 0, 1, 1, 1, 1, 0, 0, 0, 0]> : tensor<10xindex>} : () -> !tosa.shape<10>
+ // CHECK-DAG: %[[ZERO:.+]] = "tosa.const"() <{value = dense<0.000000e+00> : tensor<f32>}
// CHECK-DAG: %[[CONST3:.+]] = tosa.const_shape {value = dense<[1, 1, 1, 2, 3]> : tensor<5xindex>}
// CHECK-DAG: %[[CONST4:.+]] = tosa.const_shape {value = dense<[4, 12, 12, 6]> : tensor<4xindex>}
// CHECK-DAG: %[[CONST5:.+]] = tosa.const_shape {value = dense<[1, 1, 1, 6]> : tensor<4xindex>}
// CHECK-DAG: %[[SHIFT:.*]] = "tosa.const"() <{value = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
- // CHECK: %[[reIn:.+]] = tosa.reshape %arg0, %[[CONST0]]
- // CHECK: %[[padded:.+]] = tosa.pad %[[reIn]], %[[pad]], %[[zero]] : (tensor<4x10x10x2x1xf32>, !tosa.shape<10>, tensor<f32>) -> tensor<4x12x12x2x1xf32>
- // CHECK: %[[reArg1:.+]] = tosa.reshape %arg1, %[[CONST3]]
- // CHECK: %[[mul:.+]] = tosa.mul %[[padded]], %[[reArg1]], %[[SHIFT]]
- // CHECK: %[[reOut:.+]] = tosa.reshape %[[mul]], %[[CONST4]]
- // CHECK: %[[reArg2:.+]] = tosa.reshape %arg2, %[[CONST5]]
- // CHECK: %[[add:.+]] = tosa.add %[[reOut]], %[[reArg2]]
+ // CHECK: %[[RESHAPE_I:.+]] = tosa.reshape %arg0, %[[CONST0]]
+ // CHECK: %[[PAD_I:.+]] = tosa.pad %[[RESHAPE_I]], %[[PAD]], %[[ZERO]] : (tensor<4x10x10x2x1xf32>, !tosa.shape<10>, tensor<f32>) -> tensor<4x12x12x2x1xf32>
+ // CHECK: %[[RESHAPE_ARG1:.+]] = tosa.reshape %arg1, %[[CONST3]]
+ // CHECK: %[[MUL:.+]] = tosa.mul %[[PAD_I]], %[[RESHAPE_ARG1]], %[[SHIFT]]
+ // CHECK: %[[RESHAPE_O:.+]] = tosa.reshape %[[MUL]], %[[CONST4]]
+ // CHECK: %[[RESHAPE_ARG2:.+]] = tosa.reshape %arg2, %[[CONST5]]
+ // CHECK: %[[ADD:.+]] = tosa.add %[[RESHAPE_O]], %[[RESHAPE_ARG2]]
%0 = tosa.depthwise_conv2d %arg0, %arg1, %arg2 {acc_type = f32, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>, dilation = array<i64: 1, 1>} : (tensor<4x10x10x2xf32>, tensor<1x1x2x3xf32>, tensor<6xf32>) -> tensor<4x12x12x6xf32>
return %0 : tensor<4x12x12x6xf32>
}
diff --git a/mlir/test/Dialect/Tosa/tosa-decompose-transpose-conv.mlir b/mlir/test/Dialect/Tosa/tosa-decompose-transpose-conv.mlir
index bd18b7ea0fdff..ae7a8e90b4281 100644
--- a/mlir/test/Dialect/Tosa/tosa-decompose-transpose-conv.mlir
+++ b/mlir/test/Dialect/Tosa/tosa-decompose-transpose-conv.mlir
@@ -120,8 +120,8 @@ func.func @transpose_conv2d_strided_quantized(%arg0: tensor<2x17x15x3xi8>, %arg1
// CHECK-DAG: %[[CONV_NEW_SHAPE:.*]] = tosa.const_shape {value = dense<[2, 18, 16, 2, 3, 5]> : tensor<6xindex>}
// CHECK-DAG: %[[RESHAPE_OUT_1:.+]] = tosa.reshape %[[CONV]], %[[CONV_NEW_SHAPE]]
// CHECK-DAG: %[[TRANS_OUT:.+]] = tosa.transpose %[[RESHAPE_OUT_1]], %[[TRANS2]]
- // CHECK-DAG: %[[TEANS_NEW_SHAPE:.+]] = tosa.const_shape {value = dense<[2, 36, 48, 5]> : tensor<4xindex>}
- // CHECK-DAG: %[[RESHAPE_OUT_2:.+]] = tosa.reshape %[[TRANS_OUT]], %[[TEANS_NEW_SHAPE]]
+ // CHECK-DAG: %[[TRANS_NEW_SHAPE:.+]] = tosa.const_shape {value = dense<[2, 36, 48, 5]> : tensor<4xindex>}
+ // CHECK-DAG: %[[RESHAPE_OUT_2:.+]] = tosa.reshape %[[TRANS_OUT]], %[[TRANS_NEW_SHAPE]]
// CHECK-DAG: %[[SLICE:.+]] = tosa.slice %[[RESHAPE_OUT_2]], %[[START]], %[[SIZE]]
// CHECK-DAG: %[[ARG2_NEW_SHAPE:.+]] = tosa.const_shape {value = dense<[1, 1, 1, 5]> : tensor<4xindex>}
// CHECK-DAG: %[[RESHAPE_ARG2:.+]] = tosa.reshape %arg2, %[[ARG2_NEW_SHAPE]]
diff --git a/mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir b/mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir
index fa590ab495ada..7e714d0f8547a 100644
--- a/mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir
+++ b/mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir
@@ -501,9 +501,9 @@ func.func @test_slice(%arg0 : tensor<?xi32>) -> () {
// CHECK-LABEL: @test_slice_size_minus_one
func.func @test_slice_size_minus_one(%arg0 : tensor<?x8x8x8xi32>) -> () {
- // CHECK: %[[Start:.+]] = tosa.const_shape
- // CHECK: %[[Size:.+]] = tosa.const_shape
- // CHECK: %[[VAL:.+]] = tosa.slice %arg0, %[[Start]], %[[Size]] : (tensor<?x8x8x8xi32>, !tosa.shape<4>, !tosa.shape<4>) -> tensor<?x7x?x?xi32>
+ // CHECK: %[[START:.+]] = tosa.const_shape
+ // CHECK: %[[SIZE:.+]] = tosa.const_shape
+ // CHECK: %[[VAL:.+]] = tosa.slice %arg0, %[[START]], %[[SIZE]] : (tensor<?x8x8x8xi32>, !tosa.shape<4>, !tosa.shape<4>) -> tensor<?x7x?x?xi32>
// this checks following
// dim 0: size=-1, input dim=? => inferred output dim is ?
// dim 1: size=-1 => inferred output dim is input_dim - start
@@ -519,9 +519,9 @@ func.func @test_slice_size_minus_one(%arg0 : tensor<?x8x8x8xi32>) -> () {
// CHECK-LABEL: @test_slice_size_out_of_bound
func.func @test_slice_size_out_of_bound(%arg0 : tensor<8x8x8x?xi32>) -> () {
- // CHECK: %[[Start:.+]] = tosa.const_shape
- // CHECK: %[[Size:.+]] = tosa.const_shape
- // CHECK: %[[VAL:.+]] = tosa.slice %arg0, %[[Start]], %[[Size]] : (tensor<8x8x8x?xi32>, !tosa.shape<4>, !tosa.shape<4>) -> tensor<?x?x?x4xi32>
+ // CHECK: %[[START:.+]] = tosa.const_shape
+ // CHECK: %[[SIZE:.+]] = tosa.const_shape
+ // CHECK: %[[VAL:.+]] = tosa.slice %arg0, %[[START]], %[[SIZE]] : (tensor<8x8x8x?xi32>, !tosa.shape<4>, !tosa.shape<4>) -> tensor<?x?x?x4xi32>
// this checks following
// dim 0: size=0 => inferred output dim is ?
// dim 1: size=-2 => inferred output dim is ?
@@ -537,9 +537,9 @@ func.func @test_slice_size_out_of_bound(%arg0 : tensor<8x8x8x?xi32>) -> () {
// CHECK-LABEL: @test_slice_start_out_of_bound
func.func @test_slice_start_out_of_bound(%arg0 : tensor<8x8x8x?xi32>) -> () {
- // CHECK: %[[Start:.+]] = tosa.const_shape
- // CHECK: %[[Size:.+]] = tosa.const_shape
- // CHECK: %[[VAL:.+]] = tosa.slice %arg0, %[[Start]], %[[Size]] : (tensor<8x8x8x?xi32>, !tosa.shape<4>, !tosa.shape<4>) -> tensor<?x?x?x4xi32>
+ // CHECK: %[[START:.+]] = tosa.const_shape
+ // CHECK: %[[SIZE:.+]] = tosa.const_shape
+ // CHECK: %[[VAL:.+]] = tosa.slice %arg0, %[[START]], %[[SIZE]] : (tensor<8x8x8x?xi32>, !tosa.shape<4>, !tosa.shape<4>) -> tensor<?x?x?x4xi32>
// this checks following
// dim 0: start=-1 => inferred output dim is ?
// dim 1: start=8 => inferred output dim is ?
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Move in using capital letters for variable capture in LIT