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llvm-project/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_conversion.mlir
Andrzej Warzynski 23e5130ebf [mlir][test] Reland: Refactor SparseTensor CPU integration tests 
CHANGES SINCE THE ORIGINAL VERSION
----------------------------------
The default test set-up was extracted from
  * SparseTensor/CPU/lit.local.cfg.
and duplicated in all tests. This is to support downstream users that
don't use these local LIT config files.

SUMMARY OF CHANGES
------------------
This patch aims to reduce test duplication. This is a direct follow-up of:
  1. https://reviews.llvm.org/D155403 (test duplication), and
  2. https://reviews.llvm.org/D155405 (code re-use),

All SVE/VLA tests are now enabled _conditionally_ and refactored to use
`mlir-cpu-runner` rather than `lli`. The former helps with test
duplication and the latter with code re-use.

A few additional refactoring changes are included.

1. The reduce verbosity, long runtime library names like:

  %mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext

are replaced with:

  %mlir_c_runner_utils

2. In order to keep the code and the comments in sync, and to maintain
   consistency across the tests, the following:

  enable-runtime-library=true

is swapped with (and vice-versa):

  enable-runtime-library=false

Note that this change won't affect test coverage. Only few tests
required such update.

3. A VLS vectorization `RUN` line is added in tests where there was a
   VLA/VLS `RUN` line, but no VLS `RUN` line (with a few exceptions of
   tests that only contained one `RUN` line to begin with).

4. A few test variables are renamed/added. Most notable example:
  * %{options}` --> %{sparse_compiler_opts}

TEST RUNTIME IMPROVEMENT
------------------------
Tl;Dr This change improves test execution time by ~25%.

At the moment, the following `llvm-lit` invocation takes ~7.30s on my
AArch64 workstation (with SVE):

  llvm-lit  <llvm-project>/mlir/test/Integration/Dialect/SparseTensor/CPU/

This timing doesn't change no matter what the value of the following
CMake variable is (that should disable some tests):

  MLIR_RUN_ARM_SVE_TESTS

With this patch, the execution time will indeed depend on the value of
the above CMake variable:
  * with `MLIR_RUN_ARM_SVE_TESTS=true` the timing remains intact,
  * with `MLIR_RUN_ARM_SVE_TESTS=false` the timing drops to ~5.40s (~25%
    improvement).
This is expected:
  * on average there are 4 `RUN` lines per test,
  * _without this change_ (and with `MLIR_RUN_ARM_SVE_TESTS=false`) the
    4th `RUN` line would in most cases duplicate the 3rd `RUN` line,
  * _with this change) (and with `MLIR_RUN_ARM_SVE_TESTS=false`) the
    4th `RUN` line becomes empty.

PATCH SIZE
----------
While rather large and touching many files, most changes in this patch
are rather mechanical. All test configurations have been preserved and
only in a handful of cases new `RUN` lines added.

Differential Revision: https://reviews.llvm.org/D156625
2023-08-11 08:16:01 +00:00

320 lines
19 KiB
MLIR
Raw Blame History

//--------------------------------------------------------------------------------------------------
// 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: %{sparse_compiler_opts} = enable-runtime-library=true
// DEFINE: %{sparse_compiler_opts_sve} = enable-arm-sve=true %{sparse_compiler_opts}
// DEFINE: %{compile} = mlir-opt %s --sparse-compiler="%{sparse_compiler_opts}"
// DEFINE: %{compile_sve} = mlir-opt %s --sparse-compiler="%{sparse_compiler_opts_sve}"
// DEFINE: %{run_libs} = -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils
// DEFINE: %{run_opts} = -e entry -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}
//
// DEFINE: %{env} =
//--------------------------------------------------------------------------------------------------
// RUN: %{compile} | %{run} | FileCheck %s
//
// Do the same run, but now with direct IR generation.
// REDEFINE: %{sparse_compiler_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: %{sparse_compiler_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 %}
#Tensor1 = #sparse_tensor.encoding<{
lvlTypes = [ "compressed", "compressed", "compressed" ],
dimToLvl = affine_map<(i,j,k) -> (i,j,k)>
}>
#Tensor2 = #sparse_tensor.encoding<{
lvlTypes = [ "compressed", "compressed", "compressed" ],
dimToLvl = affine_map<(i,j,k) -> (j,k,i)>
}>
#Tensor3 = #sparse_tensor.encoding<{
lvlTypes = [ "compressed", "compressed", "compressed" ],
dimToLvl = affine_map<(i,j,k) -> (k,i,j)>
}>
//
// Integration test that tests conversions between sparse tensors.
//
module {
//
// Output utilities.
//
func.func @dumpf64(%arg0: memref<?xf64>) {
%c0 = arith.constant 0 : index
%d0 = arith.constant -1.0 : f64
%0 = vector.transfer_read %arg0[%c0], %d0: memref<?xf64>, vector<24xf64>
vector.print %0 : vector<24xf64>
return
}
func.func @dumpidx(%arg0: memref<?xindex>) {
%c0 = arith.constant 0 : index
%d0 = arith.constant 0 : index
%0 = vector.transfer_read %arg0[%c0], %d0: memref<?xindex>, vector<25xindex>
vector.print %0 : vector<25xindex>
return
}
//
// Main driver.
//
func.func @entry() {
%c0 = arith.constant 0 : index
%c1 = arith.constant 1 : index
%c2 = arith.constant 2 : index
//
// Initialize a 3-dim dense tensor.
//
%t = arith.constant dense<[
[ [ 1.0, 2.0, 3.0, 4.0 ],
[ 5.0, 6.0, 7.0, 8.0 ],
[ 9.0, 10.0, 11.0, 12.0 ] ],
[ [ 13.0, 14.0, 15.0, 16.0 ],
[ 17.0, 18.0, 19.0, 20.0 ],
[ 21.0, 22.0, 23.0, 24.0 ] ]
]> : tensor<2x3x4xf64>
//
// Convert dense tensor directly to various sparse tensors.
// tensor1: stored as 2x3x4
// tensor2: stored as 3x4x2
// tensor3: stored as 4x2x3
//
%1 = sparse_tensor.convert %t : tensor<2x3x4xf64> to tensor<2x3x4xf64, #Tensor1>
%2 = sparse_tensor.convert %t : tensor<2x3x4xf64> to tensor<2x3x4xf64, #Tensor2>
%3 = sparse_tensor.convert %t : tensor<2x3x4xf64> to tensor<2x3x4xf64, #Tensor3>
//
// Convert sparse tensor to various sparse tensors. Note that the result
// should always correspond to the direct conversion, since the sparse
// tensor formats have the ability to restore into the original ordering.
//
%a = sparse_tensor.convert %1 : tensor<2x3x4xf64, #Tensor1> to tensor<2x3x4xf64, #Tensor1>
%b = sparse_tensor.convert %2 : tensor<2x3x4xf64, #Tensor2> to tensor<2x3x4xf64, #Tensor1>
%c = sparse_tensor.convert %3 : tensor<2x3x4xf64, #Tensor3> to tensor<2x3x4xf64, #Tensor1>
%d = sparse_tensor.convert %1 : tensor<2x3x4xf64, #Tensor1> to tensor<2x3x4xf64, #Tensor2>
%e = sparse_tensor.convert %2 : tensor<2x3x4xf64, #Tensor2> to tensor<2x3x4xf64, #Tensor2>
%f = sparse_tensor.convert %3 : tensor<2x3x4xf64, #Tensor3> to tensor<2x3x4xf64, #Tensor2>
%g = sparse_tensor.convert %1 : tensor<2x3x4xf64, #Tensor1> to tensor<2x3x4xf64, #Tensor3>
%h = sparse_tensor.convert %2 : tensor<2x3x4xf64, #Tensor2> to tensor<2x3x4xf64, #Tensor3>
%i = sparse_tensor.convert %3 : tensor<2x3x4xf64, #Tensor3> to tensor<2x3x4xf64, #Tensor3>
//
// Check number_of_entries.
//
// CHECK-COUNT-12: 24
%nv1 = sparse_tensor.number_of_entries %1 : tensor<2x3x4xf64, #Tensor1>
%nv2 = sparse_tensor.number_of_entries %2 : tensor<2x3x4xf64, #Tensor2>
%nv3 = sparse_tensor.number_of_entries %3 : tensor<2x3x4xf64, #Tensor3>
%nav = sparse_tensor.number_of_entries %a : tensor<2x3x4xf64, #Tensor1>
%nbv = sparse_tensor.number_of_entries %b : tensor<2x3x4xf64, #Tensor1>
%ncv = sparse_tensor.number_of_entries %c : tensor<2x3x4xf64, #Tensor1>
%ndv = sparse_tensor.number_of_entries %d : tensor<2x3x4xf64, #Tensor2>
%nev = sparse_tensor.number_of_entries %e : tensor<2x3x4xf64, #Tensor2>
%nfv = sparse_tensor.number_of_entries %f : tensor<2x3x4xf64, #Tensor2>
%ngv = sparse_tensor.number_of_entries %g : tensor<2x3x4xf64, #Tensor3>
%nhv = sparse_tensor.number_of_entries %h : tensor<2x3x4xf64, #Tensor3>
%niv = sparse_tensor.number_of_entries %i : tensor<2x3x4xf64, #Tensor3>
vector.print %nv1 : index
vector.print %nv2 : index
vector.print %nv3 : index
vector.print %nav : index
vector.print %nbv : index
vector.print %ncv : index
vector.print %ndv : index
vector.print %nev : index
vector.print %nfv : index
vector.print %ngv : index
vector.print %nhv : index
vector.print %niv : index
//
// Check values.
//
// CHECK: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24 )
// CHECK-NEXT: ( 1, 13, 2, 14, 3, 15, 4, 16, 5, 17, 6, 18, 7, 19, 8, 20, 9, 21, 10, 22, 11, 23, 12, 24 )
// CHECK-NEXT: ( 1, 5, 9, 13, 17, 21, 2, 6, 10, 14, 18, 22, 3, 7, 11, 15, 19, 23, 4, 8, 12, 16, 20, 24 )
// CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24 )
// CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24 )
// CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24 )
// CHECK-NEXT: ( 1, 13, 2, 14, 3, 15, 4, 16, 5, 17, 6, 18, 7, 19, 8, 20, 9, 21, 10, 22, 11, 23, 12, 24 )
// CHECK-NEXT: ( 1, 13, 2, 14, 3, 15, 4, 16, 5, 17, 6, 18, 7, 19, 8, 20, 9, 21, 10, 22, 11, 23, 12, 24 )
// CHECK-NEXT: ( 1, 13, 2, 14, 3, 15, 4, 16, 5, 17, 6, 18, 7, 19, 8, 20, 9, 21, 10, 22, 11, 23, 12, 24 )
// CHECK-NEXT: ( 1, 5, 9, 13, 17, 21, 2, 6, 10, 14, 18, 22, 3, 7, 11, 15, 19, 23, 4, 8, 12, 16, 20, 24 )
// CHECK-NEXT: ( 1, 5, 9, 13, 17, 21, 2, 6, 10, 14, 18, 22, 3, 7, 11, 15, 19, 23, 4, 8, 12, 16, 20, 24 )
// CHECK-NEXT: ( 1, 5, 9, 13, 17, 21, 2, 6, 10, 14, 18, 22, 3, 7, 11, 15, 19, 23, 4, 8, 12, 16, 20, 24 )
//
%v1 = sparse_tensor.values %1 : tensor<2x3x4xf64, #Tensor1> to memref<?xf64>
%v2 = sparse_tensor.values %2 : tensor<2x3x4xf64, #Tensor2> to memref<?xf64>
%v3 = sparse_tensor.values %3 : tensor<2x3x4xf64, #Tensor3> to memref<?xf64>
%av = sparse_tensor.values %a : tensor<2x3x4xf64, #Tensor1> to memref<?xf64>
%bv = sparse_tensor.values %b : tensor<2x3x4xf64, #Tensor1> to memref<?xf64>
%cv = sparse_tensor.values %c : tensor<2x3x4xf64, #Tensor1> to memref<?xf64>
%dv = sparse_tensor.values %d : tensor<2x3x4xf64, #Tensor2> to memref<?xf64>
%ev = sparse_tensor.values %e : tensor<2x3x4xf64, #Tensor2> to memref<?xf64>
%fv = sparse_tensor.values %f : tensor<2x3x4xf64, #Tensor2> to memref<?xf64>
%gv = sparse_tensor.values %g : tensor<2x3x4xf64, #Tensor3> to memref<?xf64>
%hv = sparse_tensor.values %h : tensor<2x3x4xf64, #Tensor3> to memref<?xf64>
%iv = sparse_tensor.values %i : tensor<2x3x4xf64, #Tensor3> to memref<?xf64>
call @dumpf64(%v1) : (memref<?xf64>) -> ()
call @dumpf64(%v2) : (memref<?xf64>) -> ()
call @dumpf64(%v3) : (memref<?xf64>) -> ()
call @dumpf64(%av) : (memref<?xf64>) -> ()
call @dumpf64(%bv) : (memref<?xf64>) -> ()
call @dumpf64(%cv) : (memref<?xf64>) -> ()
call @dumpf64(%dv) : (memref<?xf64>) -> ()
call @dumpf64(%ev) : (memref<?xf64>) -> ()
call @dumpf64(%fv) : (memref<?xf64>) -> ()
call @dumpf64(%gv) : (memref<?xf64>) -> ()
call @dumpf64(%hv) : (memref<?xf64>) -> ()
call @dumpf64(%iv) : (memref<?xf64>) -> ()
//
// Check coordinates.
//
// CHECK-NEXT: ( 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
// CHECK-NEXT: ( 0, 1, 2, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
// CHECK-NEXT: ( 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0 )
// CHECK-NEXT: ( 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
// CHECK-NEXT: ( 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
// CHECK-NEXT: ( 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0 )
// CHECK-NEXT: ( 0, 1, 2, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
// CHECK-NEXT: ( 0, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
// CHECK-NEXT: ( 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0 )
// CHECK-NEXT: ( 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
// CHECK-NEXT: ( 0, 1, 2, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
// CHECK-NEXT: ( 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0 )
// CHECK-NEXT: ( 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
// CHECK-NEXT: ( 0, 1, 2, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
// CHECK-NEXT: ( 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0 )
// CHECK-NEXT: ( 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
// CHECK-NEXT: ( 0, 1, 2, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
// CHECK-NEXT: ( 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0 )
// CHECK-NEXT: ( 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
// CHECK-NEXT: ( 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
// CHECK-NEXT: ( 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0 )
// CHECK-NEXT: ( 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
// CHECK-NEXT: ( 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
// CHECK-NEXT: ( 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0 )
// CHECK-NEXT: ( 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
// CHECK-NEXT: ( 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
// CHECK-NEXT: ( 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0 )
// CHECK-NEXT: ( 0, 1, 2, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
// CHECK-NEXT: ( 0, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
// CHECK-NEXT: ( 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0 )
// CHECK-NEXT: ( 0, 1, 2, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
// CHECK-NEXT: ( 0, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
// CHECK-NEXT: ( 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0 )
// CHECK-NEXT: ( 0, 1, 2, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
// CHECK-NEXT: ( 0, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
// CHECK-NEXT: ( 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0 )
//
%v10 = sparse_tensor.coordinates %1 { level = 0 : index } : tensor<2x3x4xf64, #Tensor1> to memref<?xindex>
%v11 = sparse_tensor.coordinates %1 { level = 1 : index } : tensor<2x3x4xf64, #Tensor1> to memref<?xindex>
%v12 = sparse_tensor.coordinates %1 { level = 2 : index } : tensor<2x3x4xf64, #Tensor1> to memref<?xindex>
%v20 = sparse_tensor.coordinates %2 { level = 0 : index } : tensor<2x3x4xf64, #Tensor2> to memref<?xindex>
%v21 = sparse_tensor.coordinates %2 { level = 1 : index } : tensor<2x3x4xf64, #Tensor2> to memref<?xindex>
%v22 = sparse_tensor.coordinates %2 { level = 2 : index } : tensor<2x3x4xf64, #Tensor2> to memref<?xindex>
%v30 = sparse_tensor.coordinates %3 { level = 0 : index } : tensor<2x3x4xf64, #Tensor3> to memref<?xindex>
%v31 = sparse_tensor.coordinates %3 { level = 1 : index } : tensor<2x3x4xf64, #Tensor3> to memref<?xindex>
%v32 = sparse_tensor.coordinates %3 { level = 2 : index } : tensor<2x3x4xf64, #Tensor3> to memref<?xindex>
%a10 = sparse_tensor.coordinates %a { level = 0 : index } : tensor<2x3x4xf64, #Tensor1> to memref<?xindex>
%a11 = sparse_tensor.coordinates %a { level = 1 : index } : tensor<2x3x4xf64, #Tensor1> to memref<?xindex>
%a12 = sparse_tensor.coordinates %a { level = 2 : index } : tensor<2x3x4xf64, #Tensor1> to memref<?xindex>
%b10 = sparse_tensor.coordinates %b { level = 0 : index } : tensor<2x3x4xf64, #Tensor1> to memref<?xindex>
%b11 = sparse_tensor.coordinates %b { level = 1 : index } : tensor<2x3x4xf64, #Tensor1> to memref<?xindex>
%b12 = sparse_tensor.coordinates %b { level = 2 : index } : tensor<2x3x4xf64, #Tensor1> to memref<?xindex>
%c10 = sparse_tensor.coordinates %c { level = 0 : index } : tensor<2x3x4xf64, #Tensor1> to memref<?xindex>
%c11 = sparse_tensor.coordinates %c { level = 1 : index } : tensor<2x3x4xf64, #Tensor1> to memref<?xindex>
%c12 = sparse_tensor.coordinates %c { level = 2 : index } : tensor<2x3x4xf64, #Tensor1> to memref<?xindex>
%d20 = sparse_tensor.coordinates %d { level = 0 : index } : tensor<2x3x4xf64, #Tensor2> to memref<?xindex>
%d21 = sparse_tensor.coordinates %d { level = 1 : index } : tensor<2x3x4xf64, #Tensor2> to memref<?xindex>
%d22 = sparse_tensor.coordinates %d { level = 2 : index } : tensor<2x3x4xf64, #Tensor2> to memref<?xindex>
%e20 = sparse_tensor.coordinates %e { level = 0 : index } : tensor<2x3x4xf64, #Tensor2> to memref<?xindex>
%e21 = sparse_tensor.coordinates %e { level = 1 : index } : tensor<2x3x4xf64, #Tensor2> to memref<?xindex>
%e22 = sparse_tensor.coordinates %e { level = 2 : index } : tensor<2x3x4xf64, #Tensor2> to memref<?xindex>
%f20 = sparse_tensor.coordinates %f { level = 0 : index } : tensor<2x3x4xf64, #Tensor2> to memref<?xindex>
%f21 = sparse_tensor.coordinates %f { level = 1 : index } : tensor<2x3x4xf64, #Tensor2> to memref<?xindex>
%f22 = sparse_tensor.coordinates %f { level = 2 : index } : tensor<2x3x4xf64, #Tensor2> to memref<?xindex>
%g30 = sparse_tensor.coordinates %g { level = 0 : index } : tensor<2x3x4xf64, #Tensor3> to memref<?xindex>
%g31 = sparse_tensor.coordinates %g { level = 1 : index } : tensor<2x3x4xf64, #Tensor3> to memref<?xindex>
%g32 = sparse_tensor.coordinates %g { level = 2 : index } : tensor<2x3x4xf64, #Tensor3> to memref<?xindex>
%h30 = sparse_tensor.coordinates %h { level = 0 : index } : tensor<2x3x4xf64, #Tensor3> to memref<?xindex>
%h31 = sparse_tensor.coordinates %h { level = 1 : index } : tensor<2x3x4xf64, #Tensor3> to memref<?xindex>
%h32 = sparse_tensor.coordinates %h { level = 2 : index } : tensor<2x3x4xf64, #Tensor3> to memref<?xindex>
%i30 = sparse_tensor.coordinates %i { level = 0 : index } : tensor<2x3x4xf64, #Tensor3> to memref<?xindex>
%i31 = sparse_tensor.coordinates %i { level = 1 : index } : tensor<2x3x4xf64, #Tensor3> to memref<?xindex>
%i32 = sparse_tensor.coordinates %i { level = 2 : index } : tensor<2x3x4xf64, #Tensor3> to memref<?xindex>
call @dumpidx(%v10) : (memref<?xindex>) -> ()
call @dumpidx(%v11) : (memref<?xindex>) -> ()
call @dumpidx(%v12) : (memref<?xindex>) -> ()
call @dumpidx(%v20) : (memref<?xindex>) -> ()
call @dumpidx(%v21) : (memref<?xindex>) -> ()
call @dumpidx(%v22) : (memref<?xindex>) -> ()
call @dumpidx(%v30) : (memref<?xindex>) -> ()
call @dumpidx(%v31) : (memref<?xindex>) -> ()
call @dumpidx(%v32) : (memref<?xindex>) -> ()
call @dumpidx(%a10) : (memref<?xindex>) -> ()
call @dumpidx(%a11) : (memref<?xindex>) -> ()
call @dumpidx(%a12) : (memref<?xindex>) -> ()
call @dumpidx(%b10) : (memref<?xindex>) -> ()
call @dumpidx(%b11) : (memref<?xindex>) -> ()
call @dumpidx(%b12) : (memref<?xindex>) -> ()
call @dumpidx(%c10) : (memref<?xindex>) -> ()
call @dumpidx(%c11) : (memref<?xindex>) -> ()
call @dumpidx(%c12) : (memref<?xindex>) -> ()
call @dumpidx(%d20) : (memref<?xindex>) -> ()
call @dumpidx(%d21) : (memref<?xindex>) -> ()
call @dumpidx(%d22) : (memref<?xindex>) -> ()
call @dumpidx(%e20) : (memref<?xindex>) -> ()
call @dumpidx(%e21) : (memref<?xindex>) -> ()
call @dumpidx(%e22) : (memref<?xindex>) -> ()
call @dumpidx(%f20) : (memref<?xindex>) -> ()
call @dumpidx(%f21) : (memref<?xindex>) -> ()
call @dumpidx(%f22) : (memref<?xindex>) -> ()
call @dumpidx(%g30) : (memref<?xindex>) -> ()
call @dumpidx(%g31) : (memref<?xindex>) -> ()
call @dumpidx(%g32) : (memref<?xindex>) -> ()
call @dumpidx(%h30) : (memref<?xindex>) -> ()
call @dumpidx(%h31) : (memref<?xindex>) -> ()
call @dumpidx(%h32) : (memref<?xindex>) -> ()
call @dumpidx(%i30) : (memref<?xindex>) -> ()
call @dumpidx(%i31) : (memref<?xindex>) -> ()
call @dumpidx(%i32) : (memref<?xindex>) -> ()
// Release the resources.
bufferization.dealloc_tensor %1 : tensor<2x3x4xf64, #Tensor1>
bufferization.dealloc_tensor %2 : tensor<2x3x4xf64, #Tensor2>
bufferization.dealloc_tensor %3 : tensor<2x3x4xf64, #Tensor3>
bufferization.dealloc_tensor %b : tensor<2x3x4xf64, #Tensor1>
bufferization.dealloc_tensor %c : tensor<2x3x4xf64, #Tensor1>
bufferization.dealloc_tensor %d : tensor<2x3x4xf64, #Tensor2>
bufferization.dealloc_tensor %f : tensor<2x3x4xf64, #Tensor2>
bufferization.dealloc_tensor %g : tensor<2x3x4xf64, #Tensor3>
bufferization.dealloc_tensor %h : tensor<2x3x4xf64, #Tensor3>
return
}
}
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