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build_tools/ci/cpu_comparison/test_files/three_matmuls.mlir
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// This test shows arbitory matmuls that would have producer consumer relationships | ||
// across different dispatches running on CI. | ||
|
||
// These lines are strictly required by the script which generates input data: | ||
// | ||
// input 32x32xf32 | ||
// input 32x32xf32 | ||
// input 32x4xf32 | ||
// input 4x32xf32 | ||
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||
!A_TYPE = tensor<32x32xf32> | ||
!B_TYPE = tensor<32x4xf32> | ||
!C_TYPE = tensor <4x32xf32> | ||
!D_TYPE = tensor <4x4xf32> | ||
func.func @two_mm(%lhs : !A_TYPE, | ||
%rhs : !A_TYPE, %rhs_2 : !B_TYPE, %lhs_2 : !C_TYPE) -> !D_TYPE { | ||
%empty = tensor.empty() : !A_TYPE | ||
%empty_2 = tensor.empty() : !B_TYPE | ||
%empty_3 = tensor.empty() : !D_TYPE | ||
%cst = arith.constant 0.0 : f32 | ||
%fill = linalg.fill ins(%cst : f32) outs(%empty : !A_TYPE) -> !A_TYPE | ||
%fill_2 = linalg.fill ins(%cst : f32) outs(%empty_2 : !B_TYPE) -> !B_TYPE | ||
%fill_3 = linalg.fill ins(%cst : f32) outs(%empty_3 : !D_TYPE) -> !D_TYPE | ||
%2 = linalg.matmul ins(%lhs, %rhs : !A_TYPE, !A_TYPE) | ||
outs(%fill : !A_TYPE) -> !A_TYPE | ||
%3 = linalg.matmul ins(%2, %rhs_2 : !A_TYPE, !B_TYPE) | ||
outs(%fill_2 : !B_TYPE) -> !B_TYPE | ||
%4 = linalg.matmul ins(%lhs_2, %3 : !C_TYPE, !B_TYPE) | ||
outs(%fill_3 : !D_TYPE) -> !D_TYPE | ||
return %4 : !D_TYPE | ||
} |
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