[all-commits] [llvm/llvm-project] 66f84c: [mlir][tensor] Extend the logic to generalise tens...

[Andrzej Warzyński via All-commits]

  Branch: refs/heads/main
  Home:   https://github.com/llvm/llvm-project
  Commit: 66f84c8b8a762832af39e91370018f8f8307a0fc
      https://github.com/llvm/llvm-project/commit/66f84c8b8a762832af39e91370018f8f8307a0fc
  Author: Andrzej Warzyński <andrzej.warzynski at arm.com>
  Date:   2024-10-02 (Wed, 02 Oct 2024)

  Changed paths:
    M mlir/include/mlir/Dialect/Tensor/Utils/Utils.h
    M mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp
    M mlir/lib/Dialect/Tensor/Utils/Utils.cpp
    M mlir/test/Dialect/Linalg/generalize-tensor-pack.mlir

  Log Message:
  -----------
  [mlir][tensor] Extend the logic to generalise tensor.pack (#109815)

Extends the logic to generalise tensor.pack (into e.g. tensor.pad +
tensor.transpose) so that it also works when one of the inner tile sizes
is scalable (i.e. a multiple of `vector.vscale`). For example:
```mlir
  %c8 = arith.constant 8 : index
  %vscale = vector.vscale
  %c8_vscale = arith.muli %vscale, %c8 : index
  %0 = tensor.pack %input
      padding_value(%pad : f32)
      inner_dims_pos = [0, 1]
      inner_tiles = [%c8_vscale, 2]
      into %output : tensor<5x1xf32> -> tensor<1x1x?x2xf32>
}
```
is generalised as:
```mlir
  %c8 = arith.constant 8 : index
  %vscale = vector.vscale
  %c8_vscale = arith.muli %vscale, %c8 : index
  %0 = affine.apply #map()[%c8_vscale, %c5]
  %padded = tensor.pad %arg0 low[0, 0] high[%0, 1] {
  ^bb0(%arg3: index, %arg4: index):
    tensor.yield %arg2 : f32
  } : tensor<5x1xf32> to tensor<?x2xf32>
```

At the Tensor level, we model scalability using dynamic shapes and this
change basically extends the relevant logic so that it also works for
dynamic shapes.



To unsubscribe from these emails, change your notification settings at https://github.com/llvm/llvm-project/settings/notifications