mirror of https://github.com/llvm/torch-mlir
d310bb12bd
Currently, the op `torch.tensor_static_info_cast` will not get canonicalized away if the result type has any shape or dtype information. This is because `isValidSubtype` only returns true when the tensor types being compared are exactly the same or the supertype has no shape and dtype information. Being unable to canonicalize away the `torch.tensor_static_info_cast` gets in the way of further optimizations, such as shape propagation. This commit improves `isValidSubtype` by adding logic that compares the shapes and dtypes of the two tensor types to determine of one type is indeed a valid subtype of the other. Fixes https://github.com/llvm/torch-mlir/issues/1926 |
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| .. | ||
| GlobalizeObjectGraph | ||
| adjust-calling-conventions.mlir | ||
| canonicalize.mlir | ||
| decompose-complex-ops-legal.mlir | ||
| decompose-complex-ops.mlir | ||
| drop-abstract-interp-calculations.mlir | ||
| erase-module-initializer.mlir | ||
| inline-global-slots-analysis.mlir | ||
| inline-global-slots-transform.mlir | ||
| invalid.mlir | ||
| lower-to-backend-contract-error.mlir | ||
| maximize-value-semantics.mlir | ||
| ops.mlir | ||
| prepare-for-globalize-object-graph.mlir | ||
| reduce-op-variants-error.mlir | ||
| reduce-op-variants.mlir | ||
| refine-public-return.mlir | ||
| refine-types-branch.mlir | ||
| refine-types-ops.mlir | ||
| refine-types.mlir | ||
| reify-dtype-calculations.mlir | ||
| reify-shape-calculations.mlir | ||
| simplify-dtype-calculations.mlir | ||
| simplify-shape-calculations.mlir | ||
| torch-function-to-torch-backend-pipeline.mlir | ||
| verify-backend-contract-error.mlir | ||