| // RUN: mlir-opt %s -one-shot-bufferize="must-infer-memory-space" -split-input-file -verify-diagnostics |
| |
| func.func @inconsistent_memory_space_arith_select(%c: i1) -> tensor<10xf32> { |
| // Selecting 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 @+2 {{inconsistent memory space on true/false operands}} |
| // expected-error @+1 {{failed to bufferize op}} |
| %r = arith.select %c, %0, %1 : tensor<10xf32> |
| func.return %r : tensor<10xf32> |
| } |
| |
| // ----- |
| |
| func.func @unknown_memory_space(%idx: index, %v: i32) -> tensor<3xi32> { |
| // expected-error @+2 {{could not infer memory space}} |
| // expected-error @+1 {{failed to bufferize op}} |
| %cst = arith.constant dense<[5, 1000, 20]> : tensor<3xi32> |
| %0 = tensor.insert %v into %cst[%idx] : tensor<3xi32> |
| return %0 : tensor<3xi32> |
| } |
