| // RUN: mlir-opt %s -split-input-file -test-single-fold | FileCheck %s |
| |
| // The tests in this file verify that fold() methods can handle complex |
| // optimization scenarios without requiring multiple folding iterations. |
| // This is important because: |
| // |
| // 1. OpBuilder::createOrFold() only calls fold() once, so operations must |
| // be fully optimized in that single call |
| // 2. Multiple rounds of folding would incur higher performance costs, |
| // so it's more efficient to complete all optimizations in one pass |
| // |
| // These tests ensure that folding implementations are robust and complete, |
| // avoiding situations where operations are left in intermediate states |
| // that could be further optimized. |
| |
| // CHECK-LABEL: fold_extract_in_single_pass |
| // CHECK-SAME: (%{{.*}}: vector<4xf16>, %[[ARG1:.+]]: f16) |
| func.func @fold_extract_in_single_pass(%arg0: vector<4xf16>, %arg1: f16) -> f16 { |
| %0 = vector.insert %arg1, %arg0 [1] : f16 into vector<4xf16> |
| %c1 = arith.constant 1 : index |
| // Verify that the fold is finished in a single pass even if the index is dynamic. |
| %1 = vector.extract %0[%c1] : f16 from vector<4xf16> |
| // CHECK: return %[[ARG1]] : f16 |
| return %1 : f16 |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: fold_insert_in_single_pass |
| func.func @fold_insert_in_single_pass() -> vector<2xf16> { |
| %cst = arith.constant dense<0.000000e+00> : vector<2xf16> |
| %c1 = arith.constant 1 : index |
| %c2 = arith.constant 2.5 : f16 |
| // Verify that the fold is finished in a single pass even if the index is dynamic. |
| // CHECK: arith.constant dense<[0.000000e+00, 2.500000e+00]> : vector<2xf16> |
| %0 = vector.insert %c2, %cst [%c1] : f16 into vector<2xf16> |
| return %0 : vector<2xf16> |
| } |
