Integrate LLVM at llvm/llvm-project@7752fec6 #18177
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Signed-off-by: hanhanW <[email protected]>
Abbreviated Benchmark Summary@ commit a7057b33695a46ea551c12173d37e9f4bf451106 (vs. base 5a48912c52f65ead960bec9bfde5a836d1b02ab2) Data-Tiling Comparison TableClick to show
No improved or regressed benchmarks 🏖️ No improved or regressed compilation metrics 🏖️ For more information: |
hanhanW
changed the title
Signed-off-by: hanhanW <[email protected]>
ScottTodd
approved these changes
Aug 9, 2024
It looks a LLVM failure.. looking |
Signed-off-by: hanhanW <[email protected]>
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Confirmed that llvm/llvm-project#102198 is the issue locally. I'll try to create a repro and signal it in upstream. |
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To repro it in IREE: func.func private @generate_2D_source(%height : index, %width : index) -> tensor<?x?xi32> {
%init_source = tensor.empty(%height, %width) : tensor<?x?xi32>
%source = linalg.generic {
indexing_maps = [affine_map<(d0, d1) -> (d0, d1)>],
iterator_types = ["parallel", "parallel"]}
outs(%init_source : tensor<?x?xi32>) {
^bb0(%b0 : i32):
%outer = linalg.index 0 : index
%inner = linalg.index 1 : index
%strided = arith.muli %outer, %width : index
%linearized = arith.addi %inner, %strided : index
%linearized_i32 = arith.index_cast %linearized : index to i32
linalg.yield %linearized_i32 : i32
} -> tensor<?x?xi32>
// This blocks the fusion for inputs and testing ops.
%0 = util.optimization_barrier %source : tensor<?x?xi32>
%1 = flow.tensor.tie_shape %0 : tensor<?x?xi32>{%height, %width}
return %1 : tensor<?x?xi32>
}
func.func @static_pack_pad_transpose_outer_dims_large() {
%height = arith.constant 100 : index
%width = arith.constant 250 : index
%0 = call @generate_2D_source(%height, %width) : (index, index) -> tensor<?x?xi32>
%source = tensor.cast %0 : tensor<?x?xi32> to tensor<100x250xi32>
%padding_value = arith.constant 42 : i32
%init_pack = tensor.empty() : tensor<16x4x32x16xi32>
%pack = tensor.pack %source padding_value(%padding_value : i32)
outer_dims_perm = [1, 0] inner_dims_pos = [0, 1] inner_tiles = [32, 16] into %init_pack
: tensor<100x250xi32> -> tensor<16x4x32x16xi32>
%pad = tensor.pad %source low[0, 0] high[28, 6] {
^bb0(%b0 : index, %b1 : index):
tensor.yield %padding_value : i32
} : tensor<100x250xi32> to tensor<128x256xi32>
%reshape = tensor.expand_shape %pad [[0, 1], [2, 3]] output_shape [4, 32, 16, 16] : tensor<128x256xi32> into tensor<4x32x16x16xi32>
%init_transpose = tensor.empty() : tensor<16x4x32x16xi32>
%transpose = linalg.transpose
ins(%reshape : tensor<4x32x16x16xi32>)
outs(%init_transpose : tensor<16x4x32x16xi32>)
permutation = [2, 0, 1, 3]
check.expect_eq(%pack, %transpose) : tensor<16x4x32x16xi32>
return
} |
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Here is the LLVM module before translate it to ISA: https://gist.github.com/hanhanW/b806883680dd028ed82943b84483c2b8 And it failed in which calls iree/compiler/plugins/target/ROCM/ROCMTarget.cpp Lines 191 to 203 in 5a48912 @MaheshRavishankar @kuhar how do we reproduce the failure using LLVM tools? I think we can ask for a revert if we can provide such repro to the author. |
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