6 Commits

Author SHA1 Message Date
gysit
e9085d0d25 [mlir][OpDSL] Rename function to make signedness explicit (NFC).
The revision renames the following OpDSL functions:
```
TypeFn.cast -> TypeFn.cast_signed
BinaryFn.min -> BinaryFn.min_signed
BinaryFn.max -> BinaryFn.max_signed
```
The corresponding enum values on the C++ side are renamed accordingly:
```
#linalg.type_fn<cast> -> #linalg.type_fn<cast_signed>
#linalg.binary_fn<min> -> #linalg.binary_fn<min_signed>
#linalg.binary_fn<max> -> #linalg.binary_fn<max_signed>
```

Depends On D120110

Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D120562
2022-03-01 08:15:53 +00:00
gysit
15757ea80a [mlir][OpDSL] Add TypeFn class.
This revision introduces a the `TypeFn` class that similar to the `PrimFn` class contains an extensible set of type conversion functions. Having the same mechanism for both type conversion functions and arithmetic functions improves code consistency. Additionally, having an explicit function class and function name is a prerequisite to specify a conversion or arithmetic function via attribute. In a follow up commits, we will introduce function attributes to make OpDSL operations more generic. In particular, the goal is to handle signed and unsigned computation in one operations. Today, there is a linalg.matmul and a linalg.matmul_unsigned.

The commit implements the following changes:
- Introduce the class of type conversion functions `TypeFn`
- Replace the hardwired cast and cast_unsigned ops by the `TypeFn` counterparts
- Adapt the python and C++ code generation paths to support the new cast operations

Example:
```
cast(U, A[D.m, D.k])
```
changes to
```
TypeFn.cast(U, A[D.m, D.k])
```

Depends On D115237

Reviewed By: stellaraccident

Differential Revision: https://reviews.llvm.org/D115239
2022-01-07 12:26:47 +00:00
Tobias Gysi
4361bd9b7b [mlir][linalg][python] Explicit shape and dimension order in OpDSL.
Extend the OpDSL syntax with an optional `domain` function to specify an explicit dimension order. The extension is needed to provide more control over the dimension order instead of deducing it implicitly depending on the formulation of the tensor comprehension. Additionally, the patch also ensures the symbols are ordered according to the operand definitions of the operation.

Differential Revision: https://reviews.llvm.org/D105117
2021-06-30 08:59:39 +00:00
Tobias Gysi
78dc1e4978 [mlir][linalg][python] Add shape-only tensor support to OpDSL.
Add an index_dim annotation to specify the shape to loop mapping of shape-only tensors. A shape-only tensor serves is not accessed withing the body of the operation but is required to span the iteration space of certain operations such as pooling.

Differential Revision: https://reviews.llvm.org/D104767
2021-06-24 14:11:15 +00:00
Tobias Gysi
31f888ea9a [mlir][linalg][python] Add attribute support to the OpDSL.
Extend the OpDSL with index attributes. After tensors and scalars, index attributes are the third operand type. An index attribute represents a compile-time constant that is limited to index expressions. A use cases are the strides and dilations defined by convolution and pooling operations.

The patch only updates the OpDSL. The C++ yaml codegen is updated by a followup patch.

Differential Revision: https://reviews.llvm.org/D104711
2021-06-24 09:40:32 +00:00
Stella Laurenzo
9f3f6d7bd8 Move MLIR python sources to mlir/python.
* NFC but has some fixes for CMake glitches discovered along the way (things not cleaning properly, co-mingled depends).
* Includes previously unsubmitted fix in D98681 and a TODO to fix it more appropriately in a smaller followup.

Differential Revision: https://reviews.llvm.org/D101493
2021-05-03 18:36:48 +00:00