// RUN: mlir-opt %s -one-shot-bufferize="allow-return-allocs bufferize-function-boundaries" -drop-equivalent-buffer-results -split-input-file | FileCheck %s
// Run fuzzer with different seeds.
// RUN: mlir-opt %s -one-shot-bufferize="allow-return-allocs test-analysis-only analysis-fuzzer-seed=23 bufferize-function-boundaries" -split-input-file -o /dev/null
// RUN: mlir-opt %s -one-shot-bufferize="allow-return-allocs test-analysis-only analysis-fuzzer-seed=59 bufferize-function-boundaries" -split-input-file -o /dev/null
// RUN: mlir-opt %s -one-shot-bufferize="allow-return-allocs test-analysis-only analysis-fuzzer-seed=91 bufferize-function-boundaries" -split-input-file -o /dev/null
// Test bufferization using memref types that have no layout map.
// RUN: mlir-opt %s -one-shot-bufferize="allow-return-allocs unknown-type-conversion=identity-layout-map bufferize-function-boundaries" -split-input-file -o /dev/null
// CHECK-DAG: #[[$map_1d_dyn:.*]] = affine_map<(d0)[s0, s1] -> (d0 * s1 + s0)>
// CHECK-LABEL: func @insert_slice_fun
// CHECK-SAME: %[[A0:[a-zA-Z0-9]*]]: memref<?xf32, #[[$map_1d_dyn]]>,
// CHECK-SAME: %[[A1:[a-zA-Z0-9]*]]: memref<?xf32, #[[$map_1d_dyn]]>,
// CHECK-SAME: %[[t0:[a-zA-Z0-9]*]]: memref<4xf32, #[[$map_1d_dyn]]>,
// CHECK-SAME: %[[t1:[a-zA-Z0-9]*]]: memref<4xf32, #[[$map_1d_dyn]]>
func.func @insert_slice_fun(
%A0 : tensor<?xf32> {bufferization.writable = false},
%A1 : tensor<?xf32> {bufferization.writable = true},
%t0 : tensor<4xf32> {bufferization.writable = false},
%t1 : tensor<4xf32> {bufferization.writable = true})
-> (tensor<?xf32>, tensor<?xf32>, tensor<?xf32>, tensor<?xf32>)
{
// Alloc and copy the whole result tensor. Copy the tensor.extract_slice.
// CHECK: %[[REALLOC3:.*]] = memref.alloc
// CHECK: memref.copy %[[A0]], %[[REALLOC3]]
// CHECK: %[[SV_A0:.*]] = memref.subview %[[REALLOC3]]
// CHECK: memref.copy %[[t0]], %[[SV_A0]]
%r0 = tensor.insert_slice %t0 into %A0[0][4][1] : tensor<4xf32> into tensor<?xf32>
// Alloc and copy the whole result tensor. Copy the tensor.extract_slice.
// CHECK: %[[REALLOC2:.*]] = memref.alloc
// CHECK: memref.copy %[[A0]]
// CHECK: %[[SV_A0_2:.*]] = memref.subview %[[REALLOC2]]
// CHECK: memref.copy %[[t1]], %[[SV_A0_2]]
%r1 = tensor.insert_slice %t1 into %A0[0][4][1] : tensor<4xf32> into tensor<?xf32>
// Still alloc the large tensor because %A1 is read after. Copy the tensor.extract_slice.
// CHECK: %[[REALLOC1:.*]] = memref.alloc
// CHECK: memref.copy %[[A1]]
// CHECK: %[[SV_A1:.*]] = memref.subview %[[REALLOC1]]
// CHECK: memref.copy %[[t0]], %[[SV_A1]]
%r2 = tensor.insert_slice %t0 into %A1[0][4][1] : tensor<4xf32> into tensor<?xf32>
// Do not realloc the large tensor. Copy the tensor.extract_slice.
// CHECK-NOT: alloc
// CHECK: %[[SV_A1_2:.*]] = memref.subview %[[A1]]
// CHECK: memref.copy %[[t1]], %[[SV_A1_2]]
%r3 = tensor.insert_slice %t1 into %A1[0][4][1] : tensor<4xf32> into tensor<?xf32>
// CHECK: return %[[REALLOC3]], %[[REALLOC2]], %[[REALLOC1]] :
// CHECK-SAME: memref<?xf32>, memref<?xf32>, memref<?xf32>
return %r0, %r1, %r2, %r3: tensor<?xf32>, tensor<?xf32>, tensor<?xf32>, tensor<?xf32>
}
// -----
// CHECK-DAG: #[[$map_1d_dyn:.*]] = affine_map<(d0)[s0, s1] -> (d0 * s1 + s0)>
// CHECK-LABEL: func @insert_slice_fun
// CHECK-SAME: %[[A:[a-zA-Z0-9]*]]: memref<?xf32, #[[$map_1d_dyn]]>
// CHECK-SAME: %[[t:[a-zA-Z0-9]*]]: memref<4xf32, #[[$map_1d_dyn]]>
func.func @insert_slice_fun(
%A : tensor<?xf32> {bufferization.writable = true},
%t : tensor<4xf32> {bufferization.writable = false})
-> tensor<?xf32>
{
%f0 = arith.constant 0.0 : f32
// CHECK-NOT: alloc
// CHECK: %[[SV_A:.*]] = memref.subview %[[A]]
// CHECK: memref.copy %[[t]], %[[SV_A]]
%r0 = tensor.insert_slice %t into %A[0][4][1] : tensor<4xf32> into tensor<?xf32>
/// Overwrite A inplace.
// CHECK: linalg.fill ins({{.*}}{{.*}}outs(%[[A]]
%r1 = linalg.fill ins(%f0 : f32) outs(%r0 : tensor<?xf32>) -> tensor<?xf32>
// CHECK: return
// CHECK-NOT: tensor
return %r1: tensor<?xf32>
}
// -----
// CHECK-DAG: #[[$map_1d_dyn:.*]] = affine_map<(d0)[s0, s1] -> (d0 * s1 + s0)>
// CHECK-LABEL: func @insert_slice_fun
// CHECK-SAME: %[[A:[a-zA-Z0-9]*]]: memref<?xf32, #[[$map_1d_dyn]]>
// CHECK-SAME: %[[t:[a-zA-Z0-9]*]]: memref<4xf32, #[[$map_1d_dyn]]>
func.func @insert_slice_fun(
%A : tensor<?xf32> {bufferization.writable = true},
%t : tensor<4xf32> {bufferization.writable = false})
-> tensor<?xf32>
{
%f0 = arith.constant 0.0 : f32
// CHECK: linalg.fill ins({{.*}}{{.*}}outs(%[[A]]
%r0 = linalg.fill ins(%f0 : f32) outs(%A : tensor<?xf32>) -> tensor<?xf32>
// CHECK-NOT: alloc
// CHECK: %[[SV_A:.*]] = memref.subview %[[A]]
/// Overwrite A inplace by copying into the subview.
// CHECK: memref.copy %[[t]], %[[SV_A]]
%r1 = tensor.insert_slice %t into %r0[0][4][1] : tensor<4xf32> into tensor<?xf32>
// CHECK: return
// CHECK-NOT: tensor
return %r1: tensor<?xf32>
}
// -----
// CHECK-DAG: #[[$map_1d_dyn:.*]] = affine_map<(d0)[s0, s1] -> (d0 * s1 + s0)>
// CHECK-LABEL: func @insert_slice_fun_not_inplace
// CHECK-SAME: %[[A:[a-zA-Z0-9]*]]: memref<?xf32, #[[$map_1d_dyn]]>
// CHECK-SAME: %[[t:[a-zA-Z0-9]*]]: memref<4xf32, #[[$map_1d_dyn]]>
func.func @insert_slice_fun_not_inplace(
%A : tensor<?xf32> {bufferization.writable = false},
%t : tensor<4xf32> {bufferization.writable = false})
-> tensor<?xf32>
{
// CHECK: %[[ALLOC:.*]] = memref.alloc(%{{.*}}) {alignment = 128 : i64} : memref<?xf32>
// CHECK: memref.copy %[[A]], %[[ALLOC]] : memref<?xf32{{.*}} to memref<?xf32>
// CHECK: %[[SV:.*]] = memref.subview %[[ALLOC]][0] [4] [1] : memref<?xf32> to memref<4xf32>
// CHECK: memref.copy %[[t]], %[[SV]] : memref<4xf32, #map> to memref<4xf32>
%r0 = tensor.insert_slice %t into %A[0][4][1] : tensor<4xf32> into tensor<?xf32>
// CHECK: return %{{.*}} : memref<?xf32>
return %r0: tensor<?xf32>
}
// -----
// CHECK-LABEL: func @tensor_cast_not_in_place(
// CHECK-SAME: %[[A:.*]]: memref<?xf32{{.*}}>, %[[B:.*]]: memref<?xf32{{.*}}>
// CHECK: %[[alloc:.*]] = memref.alloc
// CHECK: memref.copy %[[A]], %[[alloc]]
// CHECK: %[[subview:.*]] = memref.subview %[[A]][{{.*}}] [4] [1] : {{.*}} to memref<4xf32
// CHECK: memref.copy %[[alloc]], %[[subview]]
func.func @tensor_cast_not_in_place(
%A : tensor<?xf32> {bufferization.writable = true},
%B : tensor<?xf32> {bufferization.writable = false}, %idx: index)
-> (tensor<?xf32>)
{
%r0 = tensor.cast %A : tensor<?xf32> to tensor<4xf32>
%r1 = tensor.insert_slice %r0 into %A[%idx][4][1] : tensor<4xf32> into tensor<?xf32>
return %r1 : tensor<?xf32>
}
// -----
// CHECK-LABEL: func @insert_op
// CHECK-SAME: %[[t1:.*]]: memref<?xf32, {{.*}}>, %[[s:.*]]: f32, %[[i:.*]]: index
func.func @insert_op(%t1 : tensor<?xf32> {bufferization.writable = true},
%s : f32, %i : index) -> tensor<?xf32> {
// CHECK: memref.store %[[s]], %[[t1]][%[[i]]]
%0 = tensor.insert %s into %t1[%i] : tensor<?xf32>
// CHECK: return
return %0 : tensor<?xf32>
}
// -----
// A regression test to make sure that we handle rank-reducing extract_slice
// correctly.
// CHECK-LABEL: func @rank_reducing
func.func @rank_reducing(
%i: index, %j: index,
%arg0: tensor<8x18x32xf32>)
-> tensor<?x1x6x8xf32> {
%c1 = arith.constant 1 : index
%c6 = arith.constant 6 : index
%c8 = arith.constant 8 : index
%c32 = arith.constant 32 : index
%c0 = arith.constant 0 : index
%0 = bufferization.alloc_tensor() : tensor<4x1x6x8xf32>
%1 = tensor.cast %0 : tensor<4x1x6x8xf32> to tensor<?x1x6x8xf32>
%2 = bufferization.alloc_tensor() : tensor<1x6x8xf32>
%5 = scf.for %arg7 = %c0 to %c32 step %c8 iter_args(%arg8 = %1) -> (tensor<?x1x6x8xf32>) {
%7 = affine.apply affine_map<(d0) -> (d0 ceildiv 8)>(%arg7)
%8 = tensor.extract_slice %arg0[%i, %j, %arg7] [1, 6, 8] [1, 1, 1] : tensor<8x18x32xf32> to tensor<1x6x8xf32>
%9 = scf.for %arg9 = %c0 to %c6 step %c1 iter_args(%arg10 = %2) -> (tensor<1x6x8xf32>) {
%11 = tensor.extract_slice %8[0, %arg9, 0] [1, 1, 8] [1, 1, 1] : tensor<1x6x8xf32> to tensor<1x1x8xf32>
%12 = tensor.insert_slice %11 into %arg10[0, %arg9, 0] [1, 1, 8] [1, 1, 1] : tensor<1x1x8xf32> into tensor<1x6x8xf32>
scf.yield %12 : tensor<1x6x8xf32>
}
%10 = tensor.insert_slice %9 into %arg8[%7, 0, 0, 0] [1, 1, 6, 8] [1, 1, 1, 1] : tensor<1x6x8xf32> into tensor<?x1x6x8xf32>
scf.yield %10 : tensor<?x1x6x8xf32>
}
return %5: tensor<?x1x6x8xf32>
}
// -----
// CHECK: #[[$MAP0:.*]] = affine_map<(d0)[s0, s1] -> (d0 * s1 + s0)>
// CHECK: #[[$MAP1:.*]] = affine_map<(d0, d1)[s0, s1, s2] -> (d0 * s1 + s0 + d1 * s2)>
// CHECK-LABEL: func.func @rank_reducing_parallel_insert_slice
func.func @rank_reducing_parallel_insert_slice(%in: tensor<100xf32>, %out: tensor<200x100xf32>) {
%c1 = arith.constant 1 : index
%num_threads = arith.constant 100 : index
// CHECK: scf.foreach_thread {{.*}} {
%result = scf.foreach_thread (%thread_idx) in (%num_threads) -> tensor<200x100xf32> {
%1 = tensor.extract_slice %in[%thread_idx][1][1] : tensor<100xf32> to tensor<1xf32>
scf.foreach_thread.perform_concurrently {
// CHECK: memref.subview %{{.*}}[%{{.*}}] [1] [1] : memref<100xf32, #[[$MAP0]]> to memref<1xf32, #[[$MAP0]]>
// CHECK: memref.subview %{{.*}}[1, %{{.*}}] [1, 1] [1, 1] : memref<200x100xf32, #[[$MAP1]]> to memref<1xf32, #[[$MAP0]]>
tensor.parallel_insert_slice %1 into %out[1, %thread_idx][1, 1][1, 1] :
tensor<1xf32> into tensor<200x100xf32>
}
}
// CHECK: }
return
}
// -----
// CHECK-LABEL: func @dealloc_generate_buffer
func.func @dealloc_generate_buffer(%arg: tensor<*xf32>, %sz: index, %idx: index)
-> index
{
// CHECK: memref.alloc
// CHECK: scf.parallel
// CHECK: memref.load
// CHECK: memref.dealloc
%0 = tensor.generate %sz {
^bb0(%i : index):
%elem = tensor.dim %arg, %i : tensor<*xf32>
tensor.yield %elem : index
} : tensor<?xindex>
%r = tensor.extract %0[%idx] : tensor<?xindex>
return %r : index
}