[mlir][tosa] Check negative output size in resize shape inference (#143382)

This commit adds a check to ensure that the calculated output height and
width, during shape inference, should be non-negative. An error is
output if this is the case.

Fixes: #142402
This commit is contained in:
Luke Hutton
2025-06-23 08:17:17 +01:00
committed by GitHub
parent 86beba9301
commit ddfc7cb61f
2 changed files with 24 additions and 2 deletions

View File

@@ -2533,16 +2533,26 @@ LogicalResult tosa::ResizeOp::inferReturnTypeComponents(
}
// Compute the output shape based on attributes: scale, offset, and border.
outputShape[1] =
const int64_t outputHeight =
(((inputHeight - 1) * scaleInt[0] - offsetInt[0] + borderInt[0]) /
scaleInt[1]) +
1;
outputShape[2] =
const int64_t outputWidth =
(((inputWidth - 1) * scaleInt[2] - offsetInt[1] + borderInt[1]) /
scaleInt[3]) +
1;
if (outputHeight < 0 || outputWidth < 0) {
return emitOptionalError(
location,
"calculated output height and width must be non-negative, "
"got height = ",
outputHeight, ", width = ", outputWidth);
}
outputShape[1] = outputHeight;
outputShape[2] = outputWidth;
inferredReturnShapes.push_back(ShapedTypeComponents(outputShape));
return success();
}

View File

@@ -1115,6 +1115,18 @@ func.func @resize_fp_power_of_two_upscale_offsetted(%arg0: tensor<1x50x48x1xf32>
// -----
// CHECK-LABEL: @resize_negative_output_dim
func.func @resize_negative_output_dim(%arg0: tensor<1x3x1x1xi8>) {
%scale = tosa.const_shape { values = dense<[1, 3, 1, 1]> : tensor<4xindex> } : () -> !tosa.shape<4>
%offset = tosa.const_shape { values = dense<[6, 1]> : tensor<2xindex> } : () -> !tosa.shape<2>
%border = tosa.const_shape { values = dense<[-15, 0]> : tensor<2xindex> } : () -> !tosa.shape<2>
// expected-error@+1 {{calculated output height and width must be non-negative, got height = -5, width = 0}}
%0 = tosa.resize %arg0, %scale, %offset, %border {mode = "NEAREST_NEIGHBOR"} : (tensor<1x3x1x1xi8>, !tosa.shape<4>, !tosa.shape<2>, !tosa.shape<2>) -> tensor<*xi8>
return
}
// -----
// CHECK-LABEL: @if_test_simple
func.func @if_test_simple(%arg0 : tensor<f32>, %arg1 : tensor<f32>, %arg2 : tensor<i1>) -> () {
%a = tosa.log %arg0 : (tensor<f32>) -> tensor<f32>