[clang] [mlir][sparse] Change tests to use new syntax for ELL and slice (PR #67569)

[Yinying Li via cfe-commits]

https://github.com/yinying-lisa-li closed 
https://github.com/llvm/llvm-project/pull/67569
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[clang] [mlir][sparse] Change tests to use new syntax for ELL and slice (PR #67569)

[Yinying Li via cfe-commits]

@@ -240,8 +240,9 @@ def SparseTensorEncodingAttr : 
SparseTensor_Attr<"SparseTensorEncoding",
 // CSR slice (offset = 0, size = 4, stride = 1 on the first dimension;
 // offset = 0, size = 8, and a dynamic stride on the second dimension).
 #CSR_SLICE = #sparse_tensor.encoding<{
-  lvlTypes = [ "dense", "compressed" ],
-  dimSlices = [ (0, 4, 1), (0, 8, ?) ]
+  map = (d0 : #sparse_tensor,

yinying-lisa-li wrote:

Yeah, it's a bit hard to comprehend. But for now, let's keep it this way and we 
could optimize it later once the migrate is done.

https://github.com/llvm/llvm-project/pull/67569
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[clang] [mlir][sparse] Change tests to use new syntax for ELL and slice (PR #67569)

[Aart Bik via cfe-commits]

@@ -240,8 +240,9 @@ def SparseTensorEncodingAttr : 
SparseTensor_Attr<"SparseTensorEncoding",
 // CSR slice (offset = 0, size = 4, stride = 1 on the first dimension;
 // offset = 0, size = 8, and a dynamic stride on the second dimension).
 #CSR_SLICE = #sparse_tensor.encoding<{
-  lvlTypes = [ "dense", "compressed" ],
-  dimSlices = [ (0, 4, 1), (0, 8, ?) ]
+  map = (d0 : #sparse_tensor,

aartbik wrote:

can we use "i" and "j" in the documentation? it of course does not matter and 
we will print it back with d0/d1 most likey (as all the affine stuff), but I 
want to make the doc very user friendly ;-)

https://github.com/llvm/llvm-project/pull/67569
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[clang] [mlir][sparse] Change tests to use new syntax for ELL and slice (PR #67569)

[Yinying Li via cfe-commits]

https://github.com/yinying-lisa-li updated 
https://github.com/llvm/llvm-project/pull/67569

>From 0f1db4000d971192e0b2b027746cdd37083bf87f Mon Sep 17 00:00:00 2001
From: Yinying Li 
Date: Wed, 27 Sep 2023 14:51:34 +
Subject: [PATCH] [mlir][sparse] Change tests to use new syntax for ELL and
 slice

Examples:

#ELL = #sparse_tensor.encoding<{
  lvlTypes = [ "dense", "dense", "compressed" ],
  dimToLvl = affine_map<(i,j)[c] -> (c*4*i, i, j)>
}>
to
#ELL = #sparse_tensor.encoding<{
  map = [s0](d0, d1) -> (d0 * (s0 * 4) : dense, d0 : dense, d1 : compressed)
}>

#CSR_SLICE = #sparse_tensor.encoding<{
  lvlTypes = [ "dense", "compressed" ],
  dimSlices = [ (1, 4, 1), (1, 4, 2) ]
}>
to
#CSR_SLICE = #sparse_tensor.encoding<{
  map = (d0 : #sparse_tensor, d1 : #sparse_tensor) -> (d0 : dense, d1 : compressed)
}>
---
 .../SparseTensor/IR/SparseTensorAttrDefs.td   |  5 ++--
 mlir/test/CAPI/sparse_tensor.c|  3 +--
 .../SparseTensor/convert_sparse2sparse.mlir   |  3 +--
 mlir/test/Dialect/SparseTensor/invalid.mlir   |  9 +++
 .../SparseTensor/invalid_encoding.mlir|  3 +--
 .../Dialect/SparseTensor/pre_rewriting.mlir   |  3 +--
 mlir/test/Dialect/SparseTensor/roundtrip.mlir | 15 
 .../SparseTensor/roundtrip_encoding.mlir  | 20 +++-
 .../SparseTensor/sparse_extract_slice.mlir|  3 +--
 .../Dialect/SparseTensor/sparse_foreach.mlir  |  6 ++---
 .../CPU/sparse_foreach_slices.mlir| 12 --
 .../SparseTensor/CPU/sparse_matmul_slice.mlir | 24 +++
 12 files changed, 33 insertions(+), 73 deletions(-)

diff --git a/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorAttrDefs.td 
b/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorAttrDefs.td
index e6577aed063ca7f..58e09f0d5e1803b 100644
--- a/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorAttrDefs.td
+++ b/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorAttrDefs.td
@@ -228,8 +228,9 @@ def SparseTensorEncodingAttr : 
SparseTensor_Attr<"SparseTensorEncoding",
 // CSR slice (offset = 0, size = 4, stride = 1 on the first dimension;
 // offset = 0, size = 8, and a dynamic stride on the second dimension).
 #CSR_SLICE = #sparse_tensor.encoding<{
-  lvlTypes = [ "dense", "compressed" ],
-  dimSlices = [ (0, 4, 1), (0, 8, ?) ]
+  map = (d0 : #sparse_tensor,
+ d1 : #sparse_tensor) ->
+(d0 : dense, d1 : compressed)
 }>
 ... tensor ...
 
diff --git a/mlir/test/CAPI/sparse_tensor.c b/mlir/test/CAPI/sparse_tensor.c
index 30ef1557e73302f..33ee8e784096a18 100644
--- a/mlir/test/CAPI/sparse_tensor.c
+++ b/mlir/test/CAPI/sparse_tensor.c
@@ -25,8 +25,7 @@ static int testRoundtripEncoding(MlirContext ctx) {
   // clang-format off
   const char *originalAsm =
 "#sparse_tensor.encoding<{ "
-"lvlTypes = [ \"dense\", \"compressed\", \"compressed\"], "
-"dimToLvl = affine_map<(d0, d1)[s0] -> (s0, d0, d1)>, "
+"map = [s0](d0, d1) -> (s0 : dense, d0 : compressed, d1 : compressed), "
 "posWidth = 32, crdWidth = 64 }>";
   // clang-format on
   MlirAttribute originalAttr =
diff --git a/mlir/test/Dialect/SparseTensor/convert_sparse2sparse.mlir 
b/mlir/test/Dialect/SparseTensor/convert_sparse2sparse.mlir
index 54cdfc690952d9a..2a2619daf493654 100644
--- a/mlir/test/Dialect/SparseTensor/convert_sparse2sparse.mlir
+++ b/mlir/test/Dialect/SparseTensor/convert_sparse2sparse.mlir
@@ -39,8 +39,7 @@
 }>
 
 #COOSlice = #sparse_tensor.encoding<{
-  lvlTypes = [ "compressed_nu", "singleton" ],
-  dimSlices = [ (2, 2, 1), (12, 13, 1) ]
+  map = (d0 : #sparse_tensor, d1 : #sparse_tensor) -> (d0 : compressed(nonunique), d1 : singleton)
 }>
 
 // CHECK-LABEL: func @sparse_nop_convert(
diff --git a/mlir/test/Dialect/SparseTensor/invalid.mlir 
b/mlir/test/Dialect/SparseTensor/invalid.mlir
index c0e813dcde7c57e..2a13f208fa225d3 100644
--- a/mlir/test/Dialect/SparseTensor/invalid.mlir
+++ b/mlir/test/Dialect/SparseTensor/invalid.mlir
@@ -201,8 +201,7 @@ func.func @mismatch_values_types(%arg0: tensor) -> memref<
 // -
 
 #CSR_SLICE = #sparse_tensor.encoding<{
-  lvlTypes = [ "dense", "compressed" ],
-  dimSlices = [ (1, 4, 1), (1, 4, 2) ]
+  map = (d0 : #sparse_tensor, d1 : #sparse_tensor) -> (d0 : dense, d1 : compressed)
 }>
 
 func.func @sparse_slice_offset(%arg0: tensor<2x8xf64, #CSR_SLICE>) -> index {
@@ -214,8 +213,7 @@ func.func @sparse_slice_offset(%arg0: tensor<2x8xf64, 
#CSR_SLICE>) -> index {
 // -
 
 #CSR_SLICE = #sparse_tensor.encoding<{
-  lvlTypes = [ "dense", "compressed" ],
-  dimSlices = [ (1, 4, 1), (1, 4, 2) ]
+  map = (d0 : #sparse_tensor, d1 : #sparse_tensor) -> (d0 : dense, d1 : compressed)
 }>
 
 func.func @sparse_slice_stride(%arg0: tensor<2x8xf64, #CSR_SLICE>) -> index {
@@ -400,8 +398,7 @@ func.func @invalid_out_dense(%arg0: tensor<10xf64>, %arg1: 
!llvm.ptr) {
 // -
 
 #CSR = #sparse_tensor.encoding<{
-  lvlTypes = ["dense", "compressed"],
-  dimSlices = [ (1, 4, 1), (1, 4, 2) ]
+  map = (d0 :