| // RUN: mlir-opt %s -one-shot-bufferize="test-analysis-only analysis-heuristic=bottom-up-from-terminators" -split-input-file | FileCheck %s |
| |
| // CHECK-LABEL: func @simple_test( |
| func.func @simple_test(%lb: index, %ub: index, %step: index, %f1: f32, %f2: f32) -> (tensor<5xf32>, tensor<5xf32>) { |
| %c0 = arith.constant 0 : index |
| %p = arith.constant 0.0 : f32 |
| |
| // Make sure that ops that feed into region terminators bufferize in-place |
| // (if possible). |
| // Note: This test case fails to bufferize with a "top-down" or "bottom-up" |
| // heuristic. |
| |
| %0 = tensor.empty() : tensor<5xf32> |
| %1 = scf.for %iv = %lb to %ub step %step iter_args(%t = %0) -> (tensor<5xf32>) { |
| // CHECK: linalg.fill {__inplace_operands_attr__ = ["none", "false"]} |
| %2 = linalg.fill ins(%f1 : f32) outs(%t : tensor<5xf32>) -> tensor<5xf32> |
| // CHECK: linalg.fill {__inplace_operands_attr__ = ["none", "true"]} |
| %3 = linalg.fill ins(%f2 : f32) outs(%t : tensor<5xf32>) -> tensor<5xf32> |
| %4 = vector.transfer_read %2[%c0], %p : tensor<5xf32>, vector<5xf32> |
| vector.print %4 : vector<5xf32> |
| scf.yield %3 : tensor<5xf32> |
| } |
| |
| %5 = tensor.empty() : tensor<5xf32> |
| %6 = scf.for %iv = %lb to %ub step %step iter_args(%t = %0) -> (tensor<5xf32>) { |
| // CHECK: linalg.fill {__inplace_operands_attr__ = ["none", "true"]} |
| %7 = linalg.fill ins(%f1 : f32) outs(%t : tensor<5xf32>) -> tensor<5xf32> |
| // CHECK: linalg.fill {__inplace_operands_attr__ = ["none", "false"]} |
| %8 = linalg.fill ins(%f2 : f32) outs(%t : tensor<5xf32>) -> tensor<5xf32> |
| %9 = vector.transfer_read %8[%c0], %p : tensor<5xf32>, vector<5xf32> |
| vector.print %9 : vector<5xf32> |
| scf.yield %7 : tensor<5xf32> |
| } |
| |
| return %1, %6 : tensor<5xf32>, tensor<5xf32> |
| } |
