[mlir][tosa] Fix level check on unranked input tensor #140795
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This commit fixes a segfault that occurred on operators with unranked input tensors. Operator specific level checks performed before the rank check incorrectly assumed all inputs were shaped. Change-Id: Ib1e60f5bd59f1bd74c0276fe208383ef30dceb18
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@llvm/pr-subscribers-mlir-tosa @llvm/pr-subscribers-mlir Author: Luke Hutton (lhutton1) ChangesThis commit fixes a segfault that occurred on operators with unranked input tensors. Operator specific level checks performed before the rank check incorrectly assumed all inputs were shaped. Patch is 26.17 KiB, truncated to 20.00 KiB below, full version: https://github.com/llvm/llvm-project/pull/140795.diff 2 Files Affected:
diff --git a/mlir/lib/Dialect/Tosa/Transforms/TosaValidation.cpp b/mlir/lib/Dialect/Tosa/Transforms/TosaValidation.cpp
index feedc5057bea0..ddbd7391555d7 100644
--- a/mlir/lib/Dialect/Tosa/Transforms/TosaValidation.cpp
+++ b/mlir/lib/Dialect/Tosa/Transforms/TosaValidation.cpp
@@ -758,6 +758,10 @@ LogicalResult TosaValidation::applyLevelCheck(Operation *op) {
return success();
}
+ // check rank and sizes early so later checks can assume shaped operands
+ if (!levelCheckRanksAndSizes(op))
+ return failure();
+
// additional level checks from spec 0.70
if (!levelCheckPool<tosa::AvgPool2dOp>(op) ||
!levelCheckConv<tosa::Conv2DOp>(op) ||
@@ -770,10 +774,6 @@ LogicalResult TosaValidation::applyLevelCheck(Operation *op) {
return failure();
}
- if (!levelCheckRanksAndSizes(op)) {
- return failure();
- }
-
// level check MAX_TENSOR_LIST_SIZE
if (!levelCheckListSize(op)) {
return failure();
diff --git a/mlir/test/Dialect/Tosa/level_check.mlir b/mlir/test/Dialect/Tosa/level_check.mlir
index d24c1fa57883d..e7d0a0e1fa4ea 100644
--- a/mlir/test/Dialect/Tosa/level_check.mlir
+++ b/mlir/test/Dialect/Tosa/level_check.mlir
@@ -547,20 +547,20 @@ func.func @test_avgpool2d_stride_x(%arg0: tensor<1x32x8194x8xf32>, %arg1: tensor
// -----
-func.func @test_conv2d_dilation_y(%arg0: tensor<1x32x32x8xf32>, %arg1: tensor<16x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>) -> tensor<*xf32> {
+func.func @test_conv2d_dilation_y(%arg0: tensor<1x8192x8192x1xf32>, %arg1: tensor<16x1025x1024x1xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>) -> tensor<1x1x7170x16xf32> {
// expected-error@+1 {{'tosa.conv2d' op failed level check: dilation_y * KH <= MAX_KERNEL}}
- %0 = tosa.conv2d %arg0, %arg1, %arg2, %arg3, %arg3 {acc_type = f32, dilation = array<i64: 4097, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 1, 1>} :
- (tensor<1x32x32x8xf32>, tensor<16x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<*xf32>
- return %0 : tensor<*xf32>
+ %0 = tosa.conv2d %arg0, %arg1, %arg2, %arg3, %arg3 {acc_type = f32, dilation = array<i64: 8, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 1, 1>} :
+ (tensor<1x8192x8192x1xf32>, tensor<16x1025x1024x1xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x1x7170x16xf32>
+ return %0 : tensor<1x1x7170x16xf32>
}
// -----
-func.func @test_conv2d_dilation_x(%arg0: tensor<1x32x32x8xf32>, %arg1: tensor<16x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>) -> tensor<*xf32> {
+func.func @test_conv2d_dilation_x(%arg0: tensor<1x8192x8192x1xf32>, %arg1: tensor<16x1024x1025x1xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>) -> tensor<1x7170x1x16xf32> {
// expected-error@+1 {{'tosa.conv2d' op failed level check: dilation_x * KW <= MAX_KERNEL}}
- %0 = tosa.conv2d %arg0, %arg1, %arg2, %arg3, %arg3 {acc_type = f32, dilation = array<i64: 1, 4097>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 1, 1>} :
- (tensor<1x32x32x8xf32>, tensor<16x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<*xf32>
- return %0 : tensor<*xf32>
+ %0 = tosa.conv2d %arg0, %arg1, %arg2, %arg3, %arg3 {acc_type = f32, dilation = array<i64: 1, 8>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 1, 1>} :
+ (tensor<1x8192x8192x1xf32>, tensor<16x1024x1025x1xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x7170x1x16xf32>
+ return %0 : tensor<1x7170x1x16xf32>
}
// -----
@@ -601,200 +601,201 @@ func.func @test_conv2d_pad_right(%arg0: tensor<1x32x32x8xf32>, %arg1: tensor<16x
// -----
-func.func @test_conv2d_stride_y(%arg0: tensor<1x32x32x8xf32>, %arg1: tensor<16x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>) -> tensor<*xf32> {
+func.func @test_conv2d_stride_y(%arg0: tensor<1x8194x33x8xf32>, %arg1: tensor<16x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>) -> tensor<1x2x33x16xf32> {
// expected-error@+1 {{'tosa.conv2d' op failed level check: stride <= MAX_STRIDE}}
%0 = tosa.conv2d %arg0, %arg1, %arg2, %arg3, %arg3 {acc_type = f32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 8193, 1>} :
- (tensor<1x32x32x8xf32>, tensor<16x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<*xf32>
- return %0 : tensor<*xf32>
+ (tensor<1x8194x33x8xf32>, tensor<16x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x2x33x16xf32>
+ return %0 : tensor<1x2x33x16xf32>
}
// -----
-func.func @test_conv2d_stride_x(%arg0: tensor<1x32x32x8xf32>, %arg1: tensor<16x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>) -> tensor<*xf32> {
+func.func @test_conv2d_stride_x(%arg0: tensor<1x33x8194x8xf32>, %arg1: tensor<16x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>) -> tensor<1x33x2x16xf32> {
// expected-error@+1 {{'tosa.conv2d' op failed level check: stride <= MAX_STRIDE}}
%0 = tosa.conv2d %arg0, %arg1, %arg2, %arg3, %arg3 {acc_type = f32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 1, 8193>} :
- (tensor<1x32x32x8xf32>, tensor<16x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<*xf32>
- return %0 : tensor<*xf32>
+ (tensor<1x33x8194x8xf32>, tensor<16x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x33x2x16xf32>
+ return %0 : tensor<1x33x2x16xf32>
}
// -----
-func.func @test_conv3d_dilation_d(%arg0: tensor<1x1x32x32x8xf32>, %arg1: tensor<16x2x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<*xf32> {
+func.func @test_conv3d_dilation_d(%arg0: tensor<1x8192x1x1x8xf32>, %arg1: tensor<16x1025x1x1x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x1x2x2x16xf32> {
// expected-error@+1 {{'tosa.conv3d' op failed level check: dilation_d * KD <= MAX_KERNEL}}
- %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 4097, 1, 1>, pad = array<i64: 0, 1, 0, 1, 0, 1>, stride = array<i64: 1, 1, 1>} :
- (tensor<1x1x32x32x8xf32>, tensor<16x2x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<*xf32>
- return %0 : tensor<*xf32>
+ %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 8, 1, 1>, pad = array<i64: 0, 1, 0, 1, 0, 1>, stride = array<i64: 1, 1, 1>} :
+ (tensor<1x8192x1x1x8xf32>, tensor<16x1025x1x1x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x1x2x2x16xf32>
+ return %0 : tensor<1x1x2x2x16xf32>
}
// -----
-func.func @test_conv3d_dilation_y(%arg0: tensor<1x1x32x32x8xf32>, %arg1: tensor<16x2x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<*xf32> {
+func.func @test_conv3d_dilation_y(%arg0: tensor<1x1x8192x1x8xf32>, %arg1: tensor<16x1x1025x1x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x2x1x2x16xf32> {
// expected-error@+1 {{'tosa.conv3d' op failed level check: dilation_y * KH <= MAX_KERNEL}}
- %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 1, 4097, 1>, pad = array<i64: 0, 1, 0, 1, 0, 1>, stride = array<i64: 1, 1, 1>} :
- (tensor<1x1x32x32x8xf32>, tensor<16x2x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<*xf32>
- return %0 : tensor<*xf32>
+ %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 1, 8, 1>, pad = array<i64: 0, 1, 0, 1, 0, 1>, stride = array<i64: 1, 1, 1>} :
+ (tensor<1x1x8192x1x8xf32>, tensor<16x1x1025x1x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x2x1x2x16xf32>
+ return %0 : tensor<1x2x1x2x16xf32>
}
// -----
-func.func @test_conv3d_dilation_x(%arg0: tensor<1x1x32x32x8xf32>, %arg1: tensor<16x2x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<*xf32> {
+func.func @test_conv3d_dilation_x(%arg0: tensor<1x1x1x8192x8xf32>, %arg1: tensor<16x1x1x1025x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x2x2x1x16xf32> {
// expected-error@+1 {{'tosa.conv3d' op failed level check: dilation_x * KW <= MAX_KERNEL}}
- %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 1, 1, 4097>, pad = array<i64: 0, 1, 0, 1, 0, 1>, stride = array<i64: 1, 1, 1>} :
- (tensor<1x1x32x32x8xf32>, tensor<16x2x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<*xf32>
- return %0 : tensor<*xf32>
+ %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 1, 1, 8>, pad = array<i64: 0, 1, 0, 1, 0, 1>, stride = array<i64: 1, 1, 1>} :
+ (tensor<1x1x1x8192x8xf32>, tensor<16x1x1x1025x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x2x2x1x16xf32>
+ return %0 : tensor<1x2x2x1x16xf32>
}
// -----
-func.func @test_conv3d_pad_d0(%arg0: tensor<1x1x32x32x8xf32>, %arg1: tensor<16x2x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<*xf32> {
+func.func @test_conv3d_pad_d0(%arg0: tensor<1x1x32x32x8xf32>, %arg1: tensor<16x2x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x8194x32x32x16xf32> {
// expected-error@+1 {{'tosa.conv3d' op failed level check: pad <= MAX_KERNEL}}
%0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 8193, 1, 0, 1, 0, 1>, stride = array<i64: 1, 1, 1>} :
- (tensor<1x1x32x32x8xf32>, tensor<16x2x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<*xf32>
- return %0 : tensor<*xf32>
+ (tensor<1x1x32x32x8xf32>, tensor<16x2x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x8194x32x32x16xf32>
+ return %0 : tensor<1x8194x32x32x16xf32>
}
// -----
-func.func @test_conv3d_pad_d1(%arg0: tensor<1x1x32x32x8xf32>, %arg1: tensor<16x2x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<*xf32> {
+func.func @test_conv3d_pad_d1(%arg0: tensor<1x1x32x32x8xf32>, %arg1: tensor<16x2x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x8194x32x32x16xf32> {
// expected-error@+1 {{'tosa.conv3d' op failed level check: pad <= MAX_KERNEL}}
%0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 1, 8193, 0, 1, 0, 1>, stride = array<i64: 1, 1, 1>} :
- (tensor<1x1x32x32x8xf32>, tensor<16x2x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<*xf32>
- return %0 : tensor<*xf32>
+ (tensor<1x1x32x32x8xf32>, tensor<16x2x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x8194x32x32x16xf32>
+ return %0 : tensor<1x8194x32x32x16xf32>
}
// -----
-func.func @test_conv3d_pad_top(%arg0: tensor<1x1x32x32x8xf32>, %arg1: tensor<16x2x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<*xf32> {
+func.func @test_conv3d_pad_top(%arg0: tensor<1x1x32x32x8xf32>, %arg1: tensor<16x2x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x1x8225x32x16xf32> {
// expected-error@+1 {{'tosa.conv3d' op failed level check: pad <= MAX_KERNEL}}
%0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 1, 8193, 1, 0, 1>, stride = array<i64: 1, 1, 1>} :
- (tensor<1x1x32x32x8xf32>, tensor<16x2x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<*xf32>
- return %0 : tensor<*xf32>
+ (tensor<1x1x32x32x8xf32>, tensor<16x2x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x1x8225x32x16xf32>
+ return %0 : tensor<1x1x8225x32x16xf32>
}
// -----
-func.func @test_conv3d_pad_bottom(%arg0: tensor<1x1x32x32x8xf32>, %arg1: tensor<16x2x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<*xf32> {
+func.func @test_conv3d_pad_bottom(%arg0: tensor<1x1x32x32x8xf32>, %arg1: tensor<16x2x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x1x8224x32x16xf32> {
// expected-error@+1 {{'tosa.conv3d' op failed level check: pad <= MAX_KERNEL}}
%0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 1, 0, 8193, 0, 1>, stride = array<i64: 1, 1, 1>} :
- (tensor<1x1x32x32x8xf32>, tensor<16x2x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<*xf32>
- return %0 : tensor<*xf32>
+ (tensor<1x1x32x32x8xf32>, tensor<16x2x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x1x8224x32x16xf32>
+ return %0 : tensor<1x1x8224x32x16xf32>
}
// -----
-func.func @test_conv3d_pad_left(%arg0: tensor<1x1x32x32x8xf32>, %arg1: tensor<16x2x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<*xf32> {
+func.func @test_conv3d_pad_left(%arg0: tensor<1x1x32x32x8xf32>, %arg1: tensor<16x2x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x1x32x8225x16xf32> {
// expected-error@+1 {{'tosa.conv3d' op failed level check: pad <= MAX_KERNEL}}
%0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 1, 0, 1, 8193, 1>, stride = array<i64: 1, 1, 1>} :
- (tensor<1x1x32x32x8xf32>, tensor<16x2x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<*xf32>
- return %0 : tensor<*xf32>
+ (tensor<1x1x32x32x8xf32>, tensor<16x2x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x1x32x8225x16xf32>
+ return %0 : tensor<1x1x32x8225x16xf32>
}
// -----
-func.func @test_conv3d_pad_right(%arg0: tensor<1x1x32x32x8xf32>, %arg1: tensor<16x2x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<*xf32> {
+func.func @test_conv3d_pad_right(%arg0: tensor<1x1x32x32x8xf32>, %arg1: tensor<16x2x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x1x32x8224x16xf32> {
// expected-error@+1 {{'tosa.conv3d' op failed level check: pad <= MAX_KERNEL}}
%0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 1, 0, 1, 0, 8193>, stride = array<i64: 1, 1, 1>} :
- (tensor<1x1x32x32x8xf32>, tensor<16x2x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<*xf32>
- return %0 : tensor<*xf32>
+ (tensor<1x1x32x32x8xf32>, tensor<16x2x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x1x32x8224x16xf32>
+ return %0 : tensor<1x1x32x8224x16xf32>
}
// -----
-func.func @test_conv3d_stride_d(%arg0: tensor<1x1x32x32x8xf32>, %arg1: tensor<16x2x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<*xf32> {
+func.func @test_conv3d_stride_d(%arg0: tensor<1x1x32x32x8xf32>, %arg1: tensor<16x2x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x1x32x32x16xf32>{
// expected-error@+1 {{'tosa.conv3d' op failed level check: stride <= MAX_STRIDE}}
%0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 1, 0, 1, 0, 1>, stride = array<i64: 8193, 1, 1>} :
- (tensor<1x1x32x32x8xf32>, tensor<16x2x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<*xf32>
- return %0 : tensor<*xf32>
+ (tensor<1x1x32x32x8xf32>, tensor<16x2x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x1x32x32x16xf32>
+ return %0 : tensor<1x1x32x32x16xf32>
}
// -----
-func.func @test_conv3d_stride_y(%arg0: tensor<1x1x32x32x8xf32>, %arg1: tensor<16x2x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<*xf32> {
+func.func @test_conv3d_stride_y(%arg0: tensor<1x1x8194x32x8xf32>, %arg1: tensor<16x2x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x1x2x32x16xf32> {
// expected-error@+1 {{'tosa.conv3d' op failed level check: stride <= MAX_STRIDE}}
%0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 1, 0, 1, 0, 1>, stride = array<i64: 1, 8193, 1>} :
- (tensor<1x1x32x32x8xf32>, tensor<16x2x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<*xf32>
- return %0 : tensor<*xf32>
+ (tensor<1x1x8194x32x8xf32>, tensor<16x2x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x1x2x32x16xf32>
+ return %0 : tensor<1x1x2x32x16xf32>
}
// -----
-func.func @test_conv3d_stride_x(%arg0: tensor<1x1x32x32x8xf32>, %arg1: tensor<16x2x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<*xf32> {
+func.func @test_conv3d_stride_x(%arg0: tensor<1x1x32x8194x8xf32>, %arg1: tensor<16x2x2x2x8xf32>, %arg2: tensor<16xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x1x32x2x16xf32> {
// expected-error@+1 {{'tosa.conv3d' op failed level check: stride <= MAX_STRIDE}}
%0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 1, 0, 1, 0, 1>, stride = array<i64: 1, 1, 8193>} :
- (tensor<1x1x32x32x8xf32>, tensor<16x2x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<*xf32>
- return %0 : tensor<*xf32>
+ (tensor<1x1x32x8194x8xf32>, tensor<16x2x2x2x8xf32>, tensor<16xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x1x32x2x16xf32>
+ return %0 : tensor<1x1x32x2x16xf32>
}
// -----
-func.func @test_depthwise_conv2d_dilation_y(%arg0: tensor<1x32x32x8xf32>, %arg1: tensor<2x2x8x8xf32>, %arg2: tensor<64xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<*xf32> {
+func.func @test_depthwise_conv2d_dilation_y(%arg0: tensor<1x8192x8192x4xf32>, %arg1: tensor<1025x16x4x1xf32>, %arg2: tensor<4xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x1x8178x4xf32> {
// expected-error@+1 {{'tosa.depthwise_conv2d' op failed level check: dilation_y * KH <= MAX_KERNEL}}
- %0 = tosa.depthwise_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 4097, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 1, 1>} :
- (tensor<1x32x32x8xf32>, tensor<2x2x8x8xf32>, tensor<64xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<*xf32>
- return %0 : tensor<*xf32>
+ %0 = tosa.depthwise_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 8, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 1, 1>} :
+ (tensor<1x8192x8192x4xf32>, tensor<1025x16x4x1xf32>, tensor<4xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x1x8178x4xf32>
+ return %0 : tensor<1x1x8178x4xf32>
}
// -----
-func.func @test_depthwise_conv2d_dilation_x(%arg0: tensor<1x32x32x8xf32>, %arg1: tensor<2x2x8x8xf32>, %arg2: tensor<64xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<*xf32> {
+func.func @test_depthwise_conv2d_dilation_x(%arg0: tensor<1x8192x8192x4xf32>, %arg1: tensor<16x1025x4x1xf32>, %arg2: tensor<4xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x8178x1x4xf32> {
// expected-error@+1 {{'tosa.depthwise_conv2d' op failed level check: dilation_x * KW <= MAX_KERNEL}}
- %0 = tosa.depthwise_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 1, 4097>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 1, 1>} :
- (tensor<1x32x32x8xf32>, tensor<2x2x8x8xf32>, tensor<64xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<*xf32>
- return %0 : tensor<*xf32>
+ %0 = tosa.depthwise_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 1, 8>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 1, 1>} :
+ (tensor<1x8192x8192x4xf32>, tensor<16x1025x4x1xf32>, tensor<4xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x8178x1x4xf32>
+ return %0 : tensor<1x8178x1x4xf32>
}
// -----
-func.func @test_depthwise_conv2d_pad_top(%arg0: tensor<1x32x32x8xf32>, %arg1: tensor<2x2x8x8xf32>, %arg2: tensor<64xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<*xf32> {
+func.func @test_depthwise_conv2d_pad_top(%arg0: tensor<1x32x32x8xf32>, %arg1: tensor<2x2x8x8xf32>, %arg2: tensor<64...
[truncated]
|
|
LGTM |
leandron
approved these changes
May 22, 2025
sivan-shani
pushed a commit
to sivan-shani/llvm-project
that referenced
this pull request
Jun 3, 2025
This commit fixes a segfault that occurred on operators with unranked input tensors. Operator specific level checks performed before the rank check incorrectly assumed all inputs were shaped.
ajaden-codes
pushed a commit
to Jaddyen/llvm-project
that referenced
this pull request
Jun 6, 2025
This commit fixes a segfault that occurred on operators with unranked input tensors. Operator specific level checks performed before the rank check incorrectly assumed all inputs were shaped.
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This commit fixes a segfault that occurred on operators with unranked input tensors. Operator specific level checks performed before the rank check incorrectly assumed all inputs were shaped.