External functions have no body, so they cannot be analyzed. Assume conservatively that each tensor bbArg may be aliasing with each tensor result. Furthermore, assume that each function arg is read and written-to after bufferization. This default behavior can be controlled with `bufferization.access` (similar to `bufferization.memory_layout`) in test cases.
Also fix a bug in the dialect attribute verifier, which did not run for region argument attributes.
Differential Revision: https://reviews.llvm.org/D139517
bufferization.to_memref ops are not supported in One-Shot Analysis. They often trigger a failed assertion that can be confusing. Instead, scan for to_memref ops before running the analysis and immediately abort with a proper error message.
Differential Revision: https://reviews.llvm.org/D132027
bufferization.writable is used in most cases instead. All remaining test cases are updated. Some code that is no longer needed is deleted.
Differential Revision: https://reviews.llvm.org/D129739
No longer pass static dim sizes as an attribute. This was redundant and required extra checks in the verifier. This change also makes the op symmetrical to memref::AllocOp.
Differential Revision: https://reviews.llvm.org/D126178
This change adds a new op `alloc_tensor` to the bufferization dialect. During bufferization, this op is always lowered to a buffer allocation (unless it is "eliminated" by a pre-processing pass). It is useful to have such an op in tensor land, because it allows users to model tensor SSA use-def chains (which drive bufferization decisions) and because tensor SSA use-def chains can be analyzed by One-Shot Bufferize, while memref values cannot.
This change also replaces all uses of linalg.init_tensor in bufferization-related code with bufferization.alloc_tensor.
linalg.init_tensor and bufferization.alloc_tensor are similar, but the purpose of the former one is just to carry a shape. It does not indicate a memory allocation.
linalg.init_tensor is not suitable for modelling SSA use-def chains for bufferization purposes, because linalg.init_tensor is marked as not having side effects (in contrast to alloc_tensor). As such, it is legal to move linalg.init_tensor ops around/CSE them/etc. This is not desirable for alloc_tensor; it represents an explicit buffer allocation while still in tensor land and such allocations should not suddenly disappear or get moved around when running the canonicalizer/CSE/etc.
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Differential Revision: https://reviews.llvm.org/D126003
This was leftover from when the standard dialect was destroyed, and
when FuncOp moved to the func dialect. Now that these transitions
have settled a bit we can drop these.
Most updates were handled using a simple regex: replace `^( *)func` with `$1func.func`
Differential Revision: https://reviews.llvm.org/D124146
This commit relaxes the rules around ops that define a value but do not specify the tensor's contents. (The only such op at the moment is init_tensor.)
When such a tensor is written in a loop, it should not cause out-of-place bufferization.
Differential Revision: https://reviews.llvm.org/D124849
* Move Module Bufferization to the bufferization dialect. The implementation is split into `OneShotModuleBufferize.cpp` and `FuncBufferizableOpInterfaceImpl.cpp`, so that the external model implementation can be easily moved to the func dialect in the future.
* Split and clean up test cases. A few test cases are still remaining in Linalg and will be updated separately.
* `linalg.inplaceable` is renamed to `bufferization.writable` to accurately reflect its current usage.
* Attributes and their verifiers are moved from the Linalg dialect to the Bufferization dialect.
* Expand documentation.
* Add a new flag to One-Shot Bufferize to allow for function boundary bufferization.
Differential Revision: https://reviews.llvm.org/D122229
