//--------------------------------------------------------------------------------------------------
// WHEN CREATING A NEW TEST, PLEASE JUST COPY & PASTE WITHOUT EDITS.
//
// Set-up that's shared across all tests in this directory. In principle, this
// config could be moved to lit.local.cfg. However, there are downstream users that
// do not use these LIT config files. Hence why this is kept inline.
//
// DEFINE: %{sparsifier_opts} = enable-runtime-library=true
// DEFINE: %{sparsifier_opts_sve} = enable-arm-sve=true %{sparsifier_opts}
// DEFINE: %{compile} = mlir-opt %s --sparsifier="%{sparsifier_opts}"
// DEFINE: %{compile_sve} = mlir-opt %s --sparsifier="%{sparsifier_opts_sve}"
// DEFINE: %{run_libs} = -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils
// DEFINE: %{run_libs_sve} = -shared-libs=%native_mlir_runner_utils,%native_mlir_c_runner_utils
// DEFINE: %{run_opts} = -e main -entry-point-result=void
// DEFINE: %{run} = mlir-cpu-runner %{run_opts} %{run_libs}
// DEFINE: %{run_sve} = %mcr_aarch64_cmd --march=aarch64 --mattr="+sve" %{run_opts} %{run_libs_sve}
//
// DEFINE: %{env} =
//--------------------------------------------------------------------------------------------------
// RUN: %{compile} | %{run} | FileCheck %s
//
// Do the same run, but now with direct IR generation.
// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false enable-buffer-initialization=true
// RUN: %{compile} | %{run} | FileCheck %s
//
// Do the same run, but now with direct IR generation and vectorization.
// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false enable-buffer-initialization=true vl=2 reassociate-fp-reductions=true enable-index-optimizations=true
// RUN: %{compile} | %{run} | FileCheck %s
//
// Do the same run, but now with direct IR generation and VLA vectorization.
// RUN: %if mlir_arm_sve_tests %{ %{compile_sve} | %{run_sve} | FileCheck %s %}
#CCC = #sparse_tensor.encoding<{
map = (d0, d1, d2) -> (d0 : compressed, d1 : compressed, d2 : compressed)
}>
#CDC = #sparse_tensor.encoding<{
map = (d0, d1, d2) -> (d0 : compressed, d1 : dense, d2 : compressed)
}>
#DCC = #sparse_tensor.encoding<{
map = (d0, d1, d2) -> (d0 : dense, d1 : compressed, d2 : compressed)
}>
#DDC = #sparse_tensor.encoding<{
map = (d0, d1, d2) -> (d0 : dense, d1 : dense, d2 : compressed)
}>
// Creates and returns 3-D buffer of size (%s1, %s2, %s3) filled with the value %f
func.func @alloc_3d_filled_f32(%s1 : index, %s2 : index, %s3 : index, %f : f32) -> tensor<?x?x?xf32> {
%buf = tensor.empty(%s1, %s2, %s3) : tensor<?x?x?xf32>
%ret = linalg.fill ins(%f : f32) outs(%buf : tensor<?x?x?xf32>) -> tensor<?x?x?xf32>
return %ret : tensor<?x?x?xf32>
}
func.func @conv_3d(%arg0: tensor<?x?x?xf32>, %arg1: tensor<?x?x?xf32>, %arg2: tensor<?x?x?xf32>) -> tensor<?x?x?xf32> {
%ret = linalg.conv_3d
ins (%arg0, %arg1: tensor<?x?x?xf32>, tensor<?x?x?xf32>)
outs (%arg2: tensor<?x?x?xf32>) -> tensor<?x?x?xf32>
return %ret : tensor<?x?x?xf32>
}
func.func @conv_3d_CCC(%arg0: tensor<?x?x?xf32, #CCC>, %arg1: tensor<?x?x?xf32>) -> tensor<?x?x?xf32, #CCC> {
%c6 = arith.constant 6 : index
%s = tensor.empty(%c6, %c6, %c6) : tensor<?x?x?xf32, #CCC>
%ret = linalg.conv_3d
ins (%arg0, %arg1: tensor<?x?x?xf32, #CCC>, tensor<?x?x?xf32>)
outs (%s: tensor<?x?x?xf32, #CCC>) -> tensor<?x?x?xf32, #CCC>
return %ret : tensor<?x?x?xf32, #CCC>
}
func.func @conv_3d_CDC(%arg0: tensor<?x?x?xf32, #CDC>, %arg1: tensor<?x?x?xf32>) -> tensor<?x?x?xf32, #CDC> {
%c6 = arith.constant 6 : index
%s = tensor.empty(%c6, %c6, %c6) : tensor<?x?x?xf32, #CDC>
%ret = linalg.conv_3d
ins (%arg0, %arg1: tensor<?x?x?xf32, #CDC>, tensor<?x?x?xf32>)
outs (%s: tensor<?x?x?xf32, #CDC>) -> tensor<?x?x?xf32, #CDC>
return %ret : tensor<?x?x?xf32, #CDC>
}
func.func @conv_3d_DCC(%arg0: tensor<?x?x?xf32, #DCC>, %arg1: tensor<?x?x?xf32>) -> tensor<?x?x?xf32, #DCC> {
%c6 = arith.constant 6 : index
%s = tensor.empty(%c6, %c6, %c6) : tensor<?x?x?xf32, #DCC>
%ret = linalg.conv_3d
ins (%arg0, %arg1: tensor<?x?x?xf32, #DCC>, tensor<?x?x?xf32>)
outs (%s: tensor<?x?x?xf32, #DCC>) -> tensor<?x?x?xf32, #DCC>
return %ret : tensor<?x?x?xf32, #DCC>
}
func.func @conv_3d_DDC(%arg0: tensor<?x?x?xf32, #DDC>, %arg1: tensor<?x?x?xf32>) -> tensor<?x?x?xf32, #DDC> {
%c6 = arith.constant 6 : index
%s = tensor.empty(%c6, %c6, %c6) : tensor<?x?x?xf32, #DDC>
%ret = linalg.conv_3d
ins (%arg0, %arg1: tensor<?x?x?xf32, #DDC>, tensor<?x?x?xf32>)
outs (%s: tensor<?x?x?xf32, #DDC>) -> tensor<?x?x?xf32, #DDC>
return %ret : tensor<?x?x?xf32, #DDC>
}
func.func @main() {
%c0 = arith.constant 0 : index
%c1 = arith.constant 1 : index
%c3 = arith.constant 3 : index
%c6 = arith.constant 6 : index
%c8 = arith.constant 8 : index
%f10 = arith.constant 10.00000e+00 : f32
%val = arith.constant 2.00000e+00 : f32
%zero = arith.constant 0.00000e+00 : f32
%filter3D = call @alloc_3d_filled_f32(%c3, %c3, %c3, %val) : (index, index, index, f32) -> (tensor<?x?x?xf32>)
%in3D_tmp = call @alloc_3d_filled_f32(%c8, %c8, %c8, %val) : (index, index, index, f32) -> (tensor<?x?x?xf32>)
%in3D = tensor.insert %f10 into %in3D_tmp[%c0, %c3, %c0] : tensor<?x?x?xf32>
%out3D = call @alloc_3d_filled_f32(%c6, %c6, %c6, %zero) : (index, index, index, f32) -> (tensor<?x?x?xf32>)
%in3D_CCC = sparse_tensor.convert %in3D
: tensor<?x?x?xf32> to tensor<?x?x?xf32, #CCC>
%in3D_CDC = sparse_tensor.convert %in3D
: tensor<?x?x?xf32> to tensor<?x?x?xf32, #CDC>
%in3D_DCC = sparse_tensor.convert %in3D
: tensor<?x?x?xf32> to tensor<?x?x?xf32, #DCC>
%in3D_DDC = sparse_tensor.convert %in3D
: tensor<?x?x?xf32> to tensor<?x?x?xf32, #DDC>
%dense_ret = call @conv_3d(%in3D, %filter3D, %out3D) : (tensor<?x?x?xf32>, tensor<?x?x?xf32>, tensor<?x?x?xf32>) -> (tensor<?x?x?xf32>)
%CCC_ret = call @conv_3d_CCC(%in3D_CCC, %filter3D) : (tensor<?x?x?xf32, #CCC>, tensor<?x?x?xf32>) -> (tensor<?x?x?xf32, #CCC>)
%CDC_ret = call @conv_3d_CDC(%in3D_CDC, %filter3D) : (tensor<?x?x?xf32, #CDC>, tensor<?x?x?xf32>) -> (tensor<?x?x?xf32, #CDC>)
%DCC_ret = call @conv_3d_DCC(%in3D_DCC, %filter3D) : (tensor<?x?x?xf32, #DCC>, tensor<?x?x?xf32>) -> (tensor<?x?x?xf32, #DCC>)
%DDC_ret = call @conv_3d_DDC(%in3D_DDC, %filter3D) : (tensor<?x?x?xf32, #DDC>, tensor<?x?x?xf32>) -> (tensor<?x?x?xf32, #DDC>)
// CHECK:( ( ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 124, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 124, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 124, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ) ),
// CHECK-SAME: ( ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ) ),
// CHECK-SAME: ( ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ) ),
// CHECK-SAME: ( ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ) ),
// CHECK-SAME: ( ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ) ),
// CHECK-SAME: ( ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),
// CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ) ) )
%dense_v = vector.transfer_read %dense_ret[%c0, %c0, %c0], %zero
: tensor<?x?x?xf32>, vector<6x6x6xf32>
vector.print %dense_v : vector<6x6x6xf32>
//
// CHECK: ---- Sparse Tensor ----
// CHECK-NEXT: nse = 216
// CHECK-NEXT: dim = ( 6, 6, 6 )
// CHECK-NEXT: lvl = ( 6, 6, 6 )
// CHECK-NEXT: pos[0] : ( 0, 6 )
// CHECK-NEXT: crd[0] : ( 0, 1, 2, 3, 4, 5 )
// CHECK-NEXT: pos[1] : ( 0, 6, 12, 18, 24, 30, 36 )
// CHECK-NEXT: crd[1] : ( 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5,
// CHECK-SAME: 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5 )
// CHECK-NEXT: pos[2] : ( 0, 6, 12, 18, 24, 30, 36, 42, 48, 54, 60, 66, 72, 78,
// CHECK-SAME: 84, 90, 96, 102, 108, 114, 120, 126, 132, 138, 144, 150,
// CHECK-SAME: 156, 162, 168, 174, 180, 186, 192, 198, 204, 210, 216 )
// CHECK-NEXT: crd[2] : ( 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0,
// CHECK-SAME: 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,
// CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2,
// CHECK-SAME: 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3,
// CHECK-SAME: 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4,
// CHECK-SAME: 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5,
// CHECK-SAME: 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0,
// CHECK-SAME: 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,
// CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2,
// CHECK-SAME: 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3,
// CHECK-SAME: 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4,
// CHECK-SAME: 5, 0, 1, 2, 3, 4, 5 )
// CHECK-NEXT: values : ( 108, 108, 108, 108, 108, 108, 124, 108, 108, 108, 108, 108,
// CHECK-SAME: 124, 108, 108, 108, 108, 108, 124, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108 )
// CHECK-NEXT: ----
//
sparse_tensor.print %CCC_ret : tensor<?x?x?xf32, #CCC>
//
// CHECK: ---- Sparse Tensor ----
// CHECK-NEXT: nse = 216
// CHECK-NEXT: dim = ( 6, 6, 6 )
// CHECK-NEXT: lvl = ( 6, 6, 6 )
// CHECK-NEXT: pos[0] : ( 0, 6 )
// CHECK-NEXT: crd[0] : ( 0, 1, 2, 3, 4, 5 )
// CHECK-NEXT: pos[2] : ( 0, 6, 12, 18, 24, 30, 36, 42, 48, 54, 60, 66, 72, 78, 84,
// CHECK-SAME: 90, 96, 102, 108, 114, 120, 126, 132, 138, 144, 150, 156,
// CHECK-SAME: 162, 168, 174, 180, 186, 192, 198, 204, 210, 216 )
// CHECK-NEXT: crd[2] : ( 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,
// CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3,
// CHECK-SAME: 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5,
// CHECK-SAME: 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,
// CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3,
// CHECK-SAME: 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5,
// CHECK-SAME: 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,
// CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3,
// CHECK-SAME: 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5,
// CHECK-SAME: 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,
// CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5 )
// CHECK-NEXT: values : ( 108, 108, 108, 108, 108, 108, 124, 108, 108, 108, 108, 108,
// CHECK-SAME: 124, 108, 108, 108, 108, 108, 124, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108 )
// CHECK-NEXT: ----
//
sparse_tensor.print %CDC_ret : tensor<?x?x?xf32, #CDC>
//
// CHECK: ---- Sparse Tensor ----
// CHECK-NEXT: nse = 216
// CHECK-NEXT: dim = ( 6, 6, 6 )
// CHECK-NEXT: lvl = ( 6, 6, 6 )
// CHECK-NEXT: pos[2] : ( 0, 6, 12, 18, 24, 30, 36, 42, 48, 54, 60, 66, 72, 78, 84, 90,
// CHECK-SAME: 96, 102, 108, 114, 120, 126, 132, 138, 144, 150, 156, 162,
// CHECK-SAME: 168, 174, 180, 186, 192, 198, 204, 210, 216 )
// CHECK-NEXT: crd[2] : ( 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,
// CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3,
// CHECK-SAME: 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5,
// CHECK-SAME: 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,
// CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3,
// CHECK-SAME: 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5,
// CHECK-SAME: 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,
// CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3,
// CHECK-SAME: 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5,
// CHECK-SAME: 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,
// CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5 )
// CHECK-NEXT: values : ( 108, 108, 108, 108, 108, 108, 124, 108, 108, 108, 108, 108,
// CHECK-SAME: 124, 108, 108, 108, 108, 108, 124, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108 )
// CHECK-NEXT: ----
//
sparse_tensor.print %DDC_ret : tensor<?x?x?xf32, #DDC>
//
// CHECK: ---- Sparse Tensor ----
// CHECK-NEXT: nse = 216
// CHECK-NEXT: dim = ( 6, 6, 6 )
// CHECK-NEXT: lvl = ( 6, 6, 6 )
// CHECK-NEXT: pos[1] : ( 0, 6, 12, 18, 24, 30, 36 )
// CHECK-NEXT: crd[1] : ( 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,
// CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5 )
// CHECK-NEXT: pos[2] : ( 0, 6, 12, 18, 24, 30, 36, 42, 48, 54, 60, 66, 72, 78, 84, 90,
// CHECK-SAME: 96, 102, 108, 114, 120, 126, 132, 138, 144, 150, 156, 162,
// CHECK-SAME: 168, 174, 180, 186, 192, 198, 204, 210, 216 )
// CHECK-NEXT: crd[2] : ( 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,
// CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3,
// CHECK-SAME: 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5,
// CHECK-SAME: 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,
// CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3,
// CHECK-SAME: 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5,
// CHECK-SAME: 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,
// CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3,
// CHECK-SAME: 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5,
// CHECK-SAME: 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,
// CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5 )
// CHECK-NEXT: values : ( 108, 108, 108, 108, 108, 108, 124, 108, 108, 108, 108, 108,
// CHECK-SAME: 124, 108, 108, 108, 108, 108, 124, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,
// CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108 )
// CHECK-NEXT: ----
//
sparse_tensor.print %DCC_ret : tensor<?x?x?xf32, #DCC>
// Free the resources
bufferization.dealloc_tensor %in3D : tensor<?x?x?xf32>
bufferization.dealloc_tensor %filter3D : tensor<?x?x?xf32>
bufferization.dealloc_tensor %out3D : tensor<?x?x?xf32>
bufferization.dealloc_tensor %in3D_CDC : tensor<?x?x?xf32, #CDC>
bufferization.dealloc_tensor %in3D_CCC : tensor<?x?x?xf32, #CCC>
bufferization.dealloc_tensor %in3D_DDC : tensor<?x?x?xf32, #DDC>
bufferization.dealloc_tensor %in3D_DCC : tensor<?x?x?xf32, #DCC>
bufferization.dealloc_tensor %CCC_ret : tensor<?x?x?xf32, #CCC>
bufferization.dealloc_tensor %CDC_ret : tensor<?x?x?xf32, #CDC>
bufferization.dealloc_tensor %DDC_ret : tensor<?x?x?xf32, #DDC>
bufferization.dealloc_tensor %DCC_ret : tensor<?x?x?xf32, #DCC>
return
}
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