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torch-mlir/test/E2E/e2e-constants.mlir

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Rework reference shape lowering based on upstream shape dialect changes. * Primarily, the upstream shape dialect now uses tensor<?xindex> for non-erroring, immediate shape calculations (and will return this for shape_of of a tensor or memref). * In addition, upstream passes do not yet exist for fully lowering to standard ops, so the passes here need to be extended to handle this new convention. * This should be seen as an intermediate state, necessary to integrate a new LLVM version and needs more work and cleanup for generality. * There is a good deal of awkwardness in these conversions. The hope is that additional upstream work will yield better defined conversion paths once out of this intermediate state.
2020-08-03 13:06:12 +08:00
// RUN: npcomp-opt <%s -pass-pipeline=e2e-lowering-pipeline | FileCheck %s --dump-input=fail
// RUN: npcomp-opt <%s -pass-pipeline=e2e-lowering-pipeline{optimize} | FileCheck %s --dump-input=fail
// -----
// CHECK-LABEL: func @global_add
func @global_add() -> tensor<2xf32> attributes {iree.module.export} {
%cst = constant dense<[3.000000e+00, 4.000000e+00]> : tensor<2xf32>
%cst_0 = constant dense<[1.000000e+00, 2.000000e+00]> : tensor<2xf32>
%0 = "tcf.add"(%cst, %cst_0) : (tensor<2xf32>, tensor<2xf32>) -> tensor<2xf32>
%1 = "tcf.add"(%cst_0, %0) : (tensor<2xf32>, tensor<2xf32>) -> tensor<2xf32>
return %1 : tensor<2xf32>
}