torch-mlir/test/Conversion/TorchToLinalg
zjgarvey d0933b0eb6
[TorchToLinalg] Fix possible OOB access in Interpolate lowering (#3570)
Following up from the discussion in
<https://github.com/llvm/torch-mlir/pull/3550>, I've edited the lowering
to prevent OOB extracts in a more direct fashion (i.e., just clamping
directly).

I don't think this affects the lit tests at all, but I've tested the
changes in our external test suite at
<https://github.com/nod-ai/SHARK-TestSuite/tree/main/>. I found the
issue when I was unexpectedly getting `nan`'s along the output image
border for a resize test there.
2024-08-02 13:55:37 -05:00
..
basic.mlir Change linalg.matmul_unsigned to linalg.matmul with unsigned type_fn (#3587) 2024-08-02 11:32:24 -07:00
broadcast.mlir [TorchToLinalg] Improve broadcast lowerings in strict symbolic modes (#2505) 2023-10-05 15:15:26 -04:00
convolution.mlir [TorchToLinalg] Fix Quantized Convolution Accumulator Type (#3459) 2024-06-20 13:54:20 -07:00
elementwise.mlir TorchToLinalg: Try folding shape computations to keep static shapes when possible (#3475) 2024-06-27 08:43:10 +02:00
flatten.mlir Integrate llvm-project at dabdec1001dc368373dd581cf72f37a440873ce3 (#3300) 2024-05-08 14:43:06 -04:00
gridsampler.mlir [onnx] Gridsampler addition of nearest mode (#3320) 2024-05-10 11:42:10 -07:00
pooling.mlir TorchToLinalg: Try folding shape computations to keep static shapes when possible (#3475) 2024-06-27 08:43:10 +02:00
resize.mlir [TorchToLinalg] Fix possible OOB access in Interpolate lowering (#3570) 2024-08-02 13:55:37 -05:00
sparse.mlir [torch-mlir] bump stablehlo/llvm version (#3471) 2024-06-18 16:59:53 -07:00
unsqueeze.mlir Integrate llvm-project at dabdec1001dc368373dd581cf72f37a440873ce3 (#3300) 2024-05-08 14:43:06 -04:00
view.mlir Add support for multiple dynamic reassociation dims for unflatten.int (#3504) 2024-06-28 09:59:51 -07:00
view_strict.mlir TorchToLinalg: Try folding shape computations to keep static shapes when possible (#3475) 2024-06-27 08:43:10 +02:00