Skip to content

[mlir][tosa] Align check variables naming to use capitals #127830

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Feb 19, 2025
Merged

[mlir][tosa] Align check variables naming to use capitals #127830

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
42 changes: 21 additions & 21 deletions mlir/test/Dialect/Tosa/tosa-decompose-depthwise.mlir
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -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>
Expand All @@ -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>
}
4 changes: 2 additions & 2 deletions mlir/test/Dialect/Tosa/tosa-decompose-transpose-conv.mlir
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -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]]
Expand Down
18 changes: 9 additions & 9 deletions mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -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
Expand All @@ -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 ?
Expand All @@ -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 ?
Expand Down