mirror of https://github.com/llvm/torch-mlir
784156a998
This finishes removing the dependence on the basicpy dialect! Changes: - Add `!torch.bool` type and replace use of `!basicpy.BoolType` in Torch-related code. - Rename BuiltinTensorize to BackendTypeConversion since now it handles bool conversions (and, when we add !torch.int and !torch.float, it will handle those as well), and generalize the related utilities (I also moved them to Torch/Transforms since they aren't really part of Torch/IR). - Add `torch.to_i1` and `torch.from_i1` ops for materializations - [cleanup] Reorganize `torch.constant.*` ops in TorchOps.td - Remove dependency of `torch` dialect on `basicpy` dialect and also `std` dialect. For `std`, we use some call related ops, but the `torch` dialect itself never produces them (we have passes that do though). This is fairly mechanical. Recommended review order: - New stuff in Torch/IR - New BuiltinTypeConversion files. - Mechnical fixups elsewhere. |
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| .. | ||
| GlobalizeObjectGraph | ||
| adjust-calling-conventions.mlir | ||
| canonicalize.mlir | ||
| finalizing-backend-type-conversion.mlir | ||
| func-backend-type-conversion.mlir | ||
| inline-global-slots.mlir | ||
| invalid.mlir | ||
| maximize-value-semantics.mlir | ||
| ops.mlir | ||
| prepare-for-globalize-object-graph.mlir | ||
| reduce-op-variants.mlir | ||
| refine-public-return.mlir | ||
| refine-types.mlir | ||