Commit Graph

7 Commits (30c519369ed7eabad0282d0f874500a9b41fcbbd)

Author SHA1 Message Date
Rob Suderman 6934ab81b0
Bump llvm/llvm-project@b6603e1bf1 (#3697)
Bump forward and refactor inline global slots to no longer track via
symlinks. This appears to make the tests past until we manage to remove
torchscript work.
2024-09-10 08:57:15 -07:00
Yuanqiang Liu 3225f20ab1
[Stablehlo] use index type as dim size, avoid to generate index_cast (#3526)
For example, the original IR is:
```
module attributes {torch.debug_module_name = "Matmul3D"} {
  func.func @forward(%arg0: tensor<?x?x?xf32>, %arg1: tensor<?x?x?xf32>) -> tensor<?x?x?xf32> {
    %c0 = arith.constant 0 : index
    %c1 = arith.constant 1 : index
    %c2 = arith.constant 2 : index
    %dim = tensor.dim %arg1, %c0 : tensor<?x?x?xf32>
    %0 = arith.index_cast %dim : index to i64
    %dim_0 = tensor.dim %arg1, %c1 : tensor<?x?x?xf32>
    %1 = arith.index_cast %dim_0 : index to i64
    %dim_1 = tensor.dim %arg1, %c2 : tensor<?x?x?xf32>
    %2 = arith.index_cast %dim_1 : index to i64
    %from_elements = tensor.from_elements %0, %1, %2 : tensor<3xi64>
    %3 = stablehlo.dynamic_broadcast_in_dim %arg1, %from_elements, dims = [0, 1, 2] : (tensor<?x?x?xf32>, tensor<3xi64>) -> tensor<?x?x?xf32>
    %4 = stablehlo.dot_general %arg0, %3, batching_dims = [0] x [0], contracting_dims = [2] x [1] : (tensor<?x?x?xf32>, tensor<?x?x?xf32>) -> tensor<?x?x?xf32>
    return %4 : tensor<?x?x?xf32>
  }
}
```
After using IndexType, the IR is:
```
module attributes {torch.debug_module_name = "Matmul3D"} {
  func.func @forward(%arg0: tensor<?x?x?xf32>, %arg1: tensor<?x?x?xf32>) -> tensor<?x?x?xf32> {
    %c0 = arith.constant 0 : index
    %c1 = arith.constant 1 : index
    %c2 = arith.constant 2 : index
    %dim = tensor.dim %arg1, %c0 : tensor<?x?x?xf32>
    %dim_0 = tensor.dim %arg1, %c1 : tensor<?x?x?xf32>
    %dim_1 = tensor.dim %arg1, %c2 : tensor<?x?x?xf32>
    %from_elements = tensor.from_elements %dim, %dim_0, %dim_1 : tensor<3xindex>
    %0 = stablehlo.dynamic_broadcast_in_dim %arg1, %from_elements, dims = [0, 1, 2] : (tensor<?x?x?xf32>, tensor<3xindex>) -> tensor<?x?x?xf32>
    %1 = stablehlo.dot_general %arg0, %0, batching_dims = [0] x [0], contracting_dims = [2] x [1] : (tensor<?x?x?xf32>, tensor<?x?x?xf32>) -> tensor<?x?x?xf32>
    return %1 : tensor<?x?x?xf32>
  }
}
```

The benefits of using IndexType on shape tensor:
* simplify the IR, avoid to generate `arith.index_cast`
* let backend compiler have a chance to decide the index width of shape
tensor
* let stablehlo backend have a chance to serialize dynamic shape IR by
[shape_legalize_to_stablehlo](https://github.com/openxla/stablehlo/blob/main/stablehlo/tests/shape_legalize_to_stablehlo.mlir)
2024-07-07 18:03:03 +08:00
Matthias Gehre 6678e1a256
TorchToLinalg: Try folding shape computations to keep static shapes when possible (#3475)
Before this PR, a statically shaped aten.convolution would generate
dynamically shaped linalg IR, and even `-canonicalize` would not be able
to fold it back into static shapes. This PR ensure that shape
calculations are folded on construction to directly generate statically
shaped linalg IR.

We achieve that by ensuring that `arith` ops involved in computing
shapes are created via `createOrFold`, so that later uses of
`getAsOpFoldResult` see constants instead of those ops.

For example
```
module {
  func.func @forward(%arg0: !torch.vtensor<[32,336,112,112],f32>,
                        %arg1: !torch.vtensor<[336,168,3,3],f32>, 
                        %arg2: !torch.vtensor<[336],f32>) 
                        -> !torch.vtensor<[32,336,56,56],f32> {
    %false = torch.constant.bool false
    %int2 = torch.constant.int 2
    %int1 = torch.constant.int 1
    %0 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<int>
    %1 = torch.prim.ListConstruct %int2, %int2 : (!torch.int, !torch.int) -> !torch.list<int>
    %2 = torch.prim.ListConstruct  : () -> !torch.list<int>
    %3 = torch.aten.convolution %arg0, %arg1, %arg2, %1, %0, %0, %false, %2, %int2 
    : !torch.vtensor<[32,336,112,112],f32>, !torch.vtensor<[336,168,3,3],f32>, !torch.vtensor<[336],f32>, !torch.list<int>,
      !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int
   -> !torch.vtensor<[32,336,56,56],f32>
    return %3 : !torch.vtensor<[32,336,56,56],f32>
  }
}
```
would result in
```
[...]
  %padded = tensor.pad %2 low[%14, %15, %16, %17] high[%14, %15, %16, %17] {
    ^bb0(%arg3: index, %arg4: index, %arg5: index, %arg6: index):
      tensor.yield %cst : f32
    } : tensor<32x336x112x112xf32> to tensor<?x?x?x?xf32>
[...]
  %45 = linalg.conv_2d_ngchw_gfchw {dilations = dense<1> : vector<2xi64>, strides = dense<2> : vector<2xi64>}
    ins(%expanded, %expanded_37 : tensor<?x2x?x?x?xf32>, tensor<2x168x168x3x3xf32>)
    outs(%expanded_44 : tensor<32x2x168x?x?xf32>) -> tensor<32x2x168x?x?xf32>
[...]
```
and with this PR all shapes are static.
2024-06-27 08:43:10 +02:00
Peiming Liu ba16bad8c7
[torch-mlir] bump stablehlo/llvm version (#3471)
Update to llvm/llvm-project@5207632f86
Update to openxla/stablehlo@d41390c3a7
2024-06-18 16:59:53 -07:00
Aart Bik 0aed231e21
[torch-mlir][conversion-test] cleanup trailing whitespace in mlir files (#2807) 2024-01-25 14:24:28 -08:00
Zhekun Zhang 1bd5747ca3
[StableHlo] Fix transposed convolution conversion (#2026)
* fix conv bwd

* fix

* fix group case

* clean up

---------

Co-authored-by: zhekun.zhang <zhekun.zhang@bytedance.com>
2023-04-13 11:24:39 -07:00
Yuanqiang Liu c86f46bd70
[test] rename TorchToMhlo to TorchToStablehlo (#1995) 2023-04-03 18:41:25 -07:00