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// RUN: mlir-opt %s -one-shot-bufferize="allow-unknown-ops allow-return-allocs-from-loops" -split-input-file -verify-diagnostics
func.func @inconsistent_memory_space_scf_if(%c: i1) -> tensor<10xf32> {
// Yielding tensors with different memory spaces. Such IR cannot be
// bufferized.
%0 = bufferization.alloc_tensor() {memory_space = 0 : ui64} : tensor<10xf32>
%1 = bufferization.alloc_tensor() {memory_space = 1 : ui64} : tensor<10xf32>
// expected-error @+1 {{inconsistent memory space on then/else branches}}
%r = scf.if %c -> tensor<10xf32> {
// expected-error @+1 {{failed to bufferize op}}
scf.yield %0 : tensor<10xf32>
} else {
scf.yield %1 : tensor<10xf32>
}
func.return %r : tensor<10xf32>
}
// -----
func.func @execute_region_multiple_yields(%t: tensor<5xf32>) -> tensor<5xf32> {
// expected-error @below{{op op without unique scf.yield is not supported}}
%0 = scf.execute_region -> tensor<5xf32> {
scf.yield %t : tensor<5xf32>
^bb1(%arg1 : tensor<5xf32>):
scf.yield %arg1 : tensor<5xf32>
}
func.return %0 : tensor<5xf32>
}
// -----
func.func @execute_region_no_yield(%t: tensor<5xf32>) -> tensor<5xf32> {
// expected-error @below{{op op without unique scf.yield is not supported}}
%0 = scf.execute_region -> tensor<5xf32> {
cf.br ^bb0(%t : tensor<5xf32>)
^bb0(%arg0 : tensor<5xf32>):
cf.br ^bb1(%arg0: tensor<5xf32>)
^bb1(%arg1 : tensor<5xf32>):
cf.br ^bb0(%arg1: tensor<5xf32>)
}
func.return %0 : tensor<5xf32>
}
// -----
func.func @inconsistent_memory_space_scf_for(%lb: index, %ub: index, %step: index) -> tensor<10xf32> {
%0 = bufferization.alloc_tensor() {memory_space = 0 : ui64} : tensor<10xf32>
%1 = bufferization.alloc_tensor() {memory_space = 1 : ui64} : tensor<10xf32>
// expected-error @below{{init_arg and yielded value bufferize to inconsistent memory spaces}}
%2 = scf.for %iv = %lb to %ub step %step iter_args(%arg = %0) -> tensor<10xf32> {
// expected-error @below {{failed to bufferize op}}
scf.yield %1 : tensor<10xf32>
}
return %2 : tensor<10xf32>
}
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