Skip to content

Commit 1d829f6

Browse files
GeorgeARMGeorgeARM
authored
[mlir][tosa] Align check variables naming to use capitals (#127830)
Move in using capital letters for variable capture in LIT Signed-off-by: Georgios Pinitas <[email protected]>
1 parent ccd3def commit 1d829f6

File tree

3 files changed

+32
-32
lines changed

3 files changed

+32
-32
lines changed

‎mlir/test/Dialect/Tosa/tosa-decompose-depthwise.mlir‎

Lines changed: 21 additions & 21 deletions
Original file line numberDiff line numberDiff line change
@@ -31,22 +31,22 @@ func.func @depthwise_conv2d_as_mul(%arg0: tensor<4x10x10x2xf32>, %arg1: tensor<1
3131
// CHECK-LABEL: @depthwise_conv2d_as_mul_q
3232
func.func @depthwise_conv2d_as_mul_q(%arg0: tensor<4x10x10x2xi8>, %arg1: tensor<1x1x2x3xi8>, %arg2: tensor<6xi32>) -> tensor<4x10x10x6xi32> {
3333
// CHECK-DAG: %[[CONST0:.+]] = tosa.const_shape {value = dense<[4, 10, 10, 2, 1]> : tensor<5xindex>
34-
// CHECK-DAG: %[[iZp:.+]] = "tosa.const"() <{value = dense<7> : tensor<1x1x1x1x1xi32>}
35-
// CHECK-DAG: %[[wZp:.+]] = "tosa.const"() <{value = dense<11> : tensor<1x1x1x1xi32>}
34+
// CHECK-DAG: %[[INPUT_ZP:.+]] = "tosa.const"() <{value = dense<7> : tensor<1x1x1x1x1xi32>}
35+
// CHECK-DAG: %[[WEIGHT_ZP:.+]] = "tosa.const"() <{value = dense<11> : tensor<1x1x1x1xi32>}
3636
// CHECK-DAG: %[[CONST3:.+]] = tosa.const_shape {value = dense<[1, 1, 1, 2, 3]> : tensor<5xindex>
3737
// CHECK-DAG: %[[CONST4:.+]] = tosa.const_shape {value = dense<[4, 10, 10, 6]> : tensor<4xindex>
3838
// CHECK-DAG: %[[CONST5:.+]] = tosa.const_shape {value = dense<[1, 1, 1, 6]> : tensor<4xindex>
3939
// CHECK-DAG: %[[SHIFT:.*]] = "tosa.const"() <{value = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
40-
// CHECK: %[[rIn:.+]] = tosa.reshape %arg0, %[[CONST0]]
41-
// CHECK: %[[cIn:.+]] = tosa.cast %[[rIn]] : (tensor<4x10x10x2x1xi8>) -> tensor<4x10x10x2x1xi32>
42-
// CHECK: %[[cWe:.+]] = tosa.cast %arg1 : (tensor<1x1x2x3xi8>) -> tensor<1x1x2x3xi32>
43-
// CHECK: %[[sIn:.+]] = tosa.sub %[[cIn]], %[[iZp]]
44-
// CHECK: %[[sWe:.+]] = tosa.sub %[[cWe]], %[[wZp]]
45-
// CHECK: %[[resWe:.+]] = tosa.reshape %[[sWe]], %[[CONST3]]
46-
// CHECK: %[[mul:.+]] = tosa.mul %[[sIn]], %[[resWe]], %[[SHIFT]]
47-
// CHECK: %[[reO:.+]] = tosa.reshape %[[mul]], %[[CONST4]]
48-
// CHECK: %[[reArg2:.+]] = tosa.reshape %arg2, %[[CONST5]]
49-
// CHECK: %[[add:.+]] = tosa.add %[[reO]], %[[reArg2]]
40+
// CHECK: %[[RESHAPE_I:.+]] = tosa.reshape %arg0, %[[CONST0]]
41+
// CHECK: %[[CAST_I:.+]] = tosa.cast %[[RESHAPE_I]] : (tensor<4x10x10x2x1xi8>) -> tensor<4x10x10x2x1xi32>
42+
// CHECK: %[[CAST_W:.+]] = tosa.cast %arg1 : (tensor<1x1x2x3xi8>) -> tensor<1x1x2x3xi32>
43+
// CHECK: %[[SUB_I:.+]] = tosa.sub %[[CAST_I]], %[[INPUT_ZP]]
44+
// CHECK: %[[SUB_W:.+]] = tosa.sub %[[CAST_W]], %[[WEIGHT_ZP]]
45+
// CHECK: %[[RESHAPE_W:.+]] = tosa.reshape %[[SUB_W]], %[[CONST3]]
46+
// CHECK: %[[MUL:.+]] = tosa.mul %[[SUB_I]], %[[RESHAPE_W]], %[[SHIFT]]
47+
// CHECK: %[[RESHAPE_O:.+]] = tosa.reshape %[[MUL]], %[[CONST4]]
48+
// CHECK: %[[RESHAPE_ARG2:.+]] = tosa.reshape %arg2, %[[CONST5]]
49+
// CHECK: %[[ADD:.+]] = tosa.add %[[RESHAPE_O]], %[[RESHAPE_ARG2]]
5050
%input_zp = "tosa.const"() {value = dense<7> : tensor<1xi8>} : () -> tensor<1xi8>
5151
%weight_zp = "tosa.const"() {value = dense<11> : tensor<1xi8>} : () -> tensor<1xi8>
5252
%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<
5858
// CHECK-LABEL: @depthwise_conv2d_as_mul_padded
5959
func.func @depthwise_conv2d_as_mul_padded(%arg0: tensor<4x10x10x2xf32>, %arg1: tensor<1x1x2x3xf32>, %arg2: tensor<6xf32>) -> tensor<4x12x12x6xf32> {
6060
// CHECK-DAG: %[[CONST0:.+]] = tosa.const_shape {value = dense<[4, 10, 10, 2, 1]> : tensor<5xindex>}
61-
// CHECK-DAG: %[[pad:.+]] = tosa.const_shape {value = dense<[0, 0, 1, 1, 1, 1, 0, 0, 0, 0]> : tensor<10xindex>} : () -> !tosa.shape<10>
62-
// CHECK-DAG: %[[zero:.+]] = "tosa.const"() <{value = dense<0.000000e+00> : tensor<f32>}
61+
// CHECK-DAG: %[[PAD:.+]] = tosa.const_shape {value = dense<[0, 0, 1, 1, 1, 1, 0, 0, 0, 0]> : tensor<10xindex>} : () -> !tosa.shape<10>
62+
// CHECK-DAG: %[[ZERO:.+]] = "tosa.const"() <{value = dense<0.000000e+00> : tensor<f32>}
6363
// CHECK-DAG: %[[CONST3:.+]] = tosa.const_shape {value = dense<[1, 1, 1, 2, 3]> : tensor<5xindex>}
6464
// CHECK-DAG: %[[CONST4:.+]] = tosa.const_shape {value = dense<[4, 12, 12, 6]> : tensor<4xindex>}
6565
// CHECK-DAG: %[[CONST5:.+]] = tosa.const_shape {value = dense<[1, 1, 1, 6]> : tensor<4xindex>}
6666
// CHECK-DAG: %[[SHIFT:.*]] = "tosa.const"() <{value = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
67-
// CHECK: %[[reIn:.+]] = tosa.reshape %arg0, %[[CONST0]]
68-
// CHECK: %[[padded:.+]] = tosa.pad %[[reIn]], %[[pad]], %[[zero]] : (tensor<4x10x10x2x1xf32>, !tosa.shape<10>, tensor<f32>) -> tensor<4x12x12x2x1xf32>
69-
// CHECK: %[[reArg1:.+]] = tosa.reshape %arg1, %[[CONST3]]
70-
// CHECK: %[[mul:.+]] = tosa.mul %[[padded]], %[[reArg1]], %[[SHIFT]]
71-
// CHECK: %[[reOut:.+]] = tosa.reshape %[[mul]], %[[CONST4]]
72-
// CHECK: %[[reArg2:.+]] = tosa.reshape %arg2, %[[CONST5]]
73-
// CHECK: %[[add:.+]] = tosa.add %[[reOut]], %[[reArg2]]
67+
// CHECK: %[[RESHAPE_I:.+]] = tosa.reshape %arg0, %[[CONST0]]
68+
// CHECK: %[[PAD_I:.+]] = tosa.pad %[[RESHAPE_I]], %[[PAD]], %[[ZERO]] : (tensor<4x10x10x2x1xf32>, !tosa.shape<10>, tensor<f32>) -> tensor<4x12x12x2x1xf32>
69+
// CHECK: %[[RESHAPE_ARG1:.+]] = tosa.reshape %arg1, %[[CONST3]]
70+
// CHECK: %[[MUL:.+]] = tosa.mul %[[PAD_I]], %[[RESHAPE_ARG1]], %[[SHIFT]]
71+
// CHECK: %[[RESHAPE_O:.+]] = tosa.reshape %[[MUL]], %[[CONST4]]
72+
// CHECK: %[[RESHAPE_ARG2:.+]] = tosa.reshape %arg2, %[[CONST5]]
73+
// CHECK: %[[ADD:.+]] = tosa.add %[[RESHAPE_O]], %[[RESHAPE_ARG2]]
7474
%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>
7575
return %0 : tensor<4x12x12x6xf32>
7676
}

‎mlir/test/Dialect/Tosa/tosa-decompose-transpose-conv.mlir‎

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -120,8 +120,8 @@ func.func @transpose_conv2d_strided_quantized(%arg0: tensor<2x17x15x3xi8>, %arg1
120120
// CHECK-DAG: %[[CONV_NEW_SHAPE:.*]] = tosa.const_shape {value = dense<[2, 18, 16, 2, 3, 5]> : tensor<6xindex>}
121121
// CHECK-DAG: %[[RESHAPE_OUT_1:.+]] = tosa.reshape %[[CONV]], %[[CONV_NEW_SHAPE]]
122122
// CHECK-DAG: %[[TRANS_OUT:.+]] = tosa.transpose %[[RESHAPE_OUT_1]], %[[TRANS2]]
123-
// CHECK-DAG: %[[TEANS_NEW_SHAPE:.+]] = tosa.const_shape {value = dense<[2, 36, 48, 5]> : tensor<4xindex>}
124-
// CHECK-DAG: %[[RESHAPE_OUT_2:.+]] = tosa.reshape %[[TRANS_OUT]], %[[TEANS_NEW_SHAPE]]
123+
// CHECK-DAG: %[[TRANS_NEW_SHAPE:.+]] = tosa.const_shape {value = dense<[2, 36, 48, 5]> : tensor<4xindex>}
124+
// CHECK-DAG: %[[RESHAPE_OUT_2:.+]] = tosa.reshape %[[TRANS_OUT]], %[[TRANS_NEW_SHAPE]]
125125
// CHECK-DAG: %[[SLICE:.+]] = tosa.slice %[[RESHAPE_OUT_2]], %[[START]], %[[SIZE]]
126126
// CHECK-DAG: %[[ARG2_NEW_SHAPE:.+]] = tosa.const_shape {value = dense<[1, 1, 1, 5]> : tensor<4xindex>}
127127
// CHECK-DAG: %[[RESHAPE_ARG2:.+]] = tosa.reshape %arg2, %[[ARG2_NEW_SHAPE]]

‎mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir‎

Lines changed: 9 additions & 9 deletions
Original file line numberDiff line numberDiff line change
@@ -501,9 +501,9 @@ func.func @test_slice(%arg0 : tensor<?xi32>) -> () {
501501

502502
// CHECK-LABEL: @test_slice_size_minus_one
503503
func.func @test_slice_size_minus_one(%arg0 : tensor<?x8x8x8xi32>) -> () {
504-
// CHECK: %[[Start:.+]] = tosa.const_shape
505-
// CHECK: %[[Size:.+]] = tosa.const_shape
506-
// CHECK: %[[VAL:.+]] = tosa.slice %arg0, %[[Start]], %[[Size]] : (tensor<?x8x8x8xi32>, !tosa.shape<4>, !tosa.shape<4>) -> tensor<?x7x?x?xi32>
504+
// CHECK: %[[START:.+]] = tosa.const_shape
505+
// CHECK: %[[SIZE:.+]] = tosa.const_shape
506+
// CHECK: %[[VAL:.+]] = tosa.slice %arg0, %[[START]], %[[SIZE]] : (tensor<?x8x8x8xi32>, !tosa.shape<4>, !tosa.shape<4>) -> tensor<?x7x?x?xi32>
507507
// this checks following
508508
// dim 0: size=-1, input dim=? => inferred output dim is ?
509509
// 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>) -> () {
519519

520520
// CHECK-LABEL: @test_slice_size_out_of_bound
521521
func.func @test_slice_size_out_of_bound(%arg0 : tensor<8x8x8x?xi32>) -> () {
522-
// CHECK: %[[Start:.+]] = tosa.const_shape
523-
// CHECK: %[[Size:.+]] = tosa.const_shape
524-
// CHECK: %[[VAL:.+]] = tosa.slice %arg0, %[[Start]], %[[Size]] : (tensor<8x8x8x?xi32>, !tosa.shape<4>, !tosa.shape<4>) -> tensor<?x?x?x4xi32>
522+
// CHECK: %[[START:.+]] = tosa.const_shape
523+
// CHECK: %[[SIZE:.+]] = tosa.const_shape
524+
// CHECK: %[[VAL:.+]] = tosa.slice %arg0, %[[START]], %[[SIZE]] : (tensor<8x8x8x?xi32>, !tosa.shape<4>, !tosa.shape<4>) -> tensor<?x?x?x4xi32>
525525
// this checks following
526526
// dim 0: size=0 => inferred output dim is ?
527527
// dim 1: size=-2 => inferred output dim is ?
@@ -537,9 +537,9 @@ func.func @test_slice_size_out_of_bound(%arg0 : tensor<8x8x8x?xi32>) -> () {
537537

538538
// CHECK-LABEL: @test_slice_start_out_of_bound
539539
func.func @test_slice_start_out_of_bound(%arg0 : tensor<8x8x8x?xi32>) -> () {
540-
// CHECK: %[[Start:.+]] = tosa.const_shape
541-
// CHECK: %[[Size:.+]] = tosa.const_shape
542-
// CHECK: %[[VAL:.+]] = tosa.slice %arg0, %[[Start]], %[[Size]] : (tensor<8x8x8x?xi32>, !tosa.shape<4>, !tosa.shape<4>) -> tensor<?x?x?x4xi32>
540+
// CHECK: %[[START:.+]] = tosa.const_shape
541+
// CHECK: %[[SIZE:.+]] = tosa.const_shape
542+
// CHECK: %[[VAL:.+]] = tosa.slice %arg0, %[[START]], %[[SIZE]] : (tensor<8x8x8x?xi32>, !tosa.shape<4>, !tosa.shape<4>) -> tensor<?x?x?x4xi32>
543543
// this checks following
544544
// dim 0: start=-1 => inferred output dim is ?
545545
// dim 1: start=8 => inferred output dim is ?

0 commit comments

Comments
 (0)