mirror of https://github.com/llvm/torch-mlir
1c7c362e29
This involved adding a `tcp.splatted` op to splat a dynamically sized init tensor. See rationale in TCPOps.td docs. One interesting observation is that when lowering tcf.matmul to linalg.matmul, we need to both 1) create the error checks and 2) calculate a shape transfer function to create the init tensors. Previously, 2) was deferred to bufferizing tcp.matmul later. I'm not sure if this is a conflation of concerns or not. For now, it's not a big burden. |
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|---|---|---|
| .. | ||
| ATenToTCF | ||
| BasicpyToIREEVM | ||
| BasicpyToStd | ||
| NumpyToTCF | ||
| TCFToLinalg | ||
| TCFToStd | ||
| TCFToTCP | ||
| CMakeLists.txt | ||
| Passes.h | ||
| Passes.td | ||