[mlir][sparse] Migrate tests to use new syntax #66543
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COO
lvlTypes = [ "compressed_nu", "singleton" ] to map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton)
lvlTypes = [ "compressed_nu_no", "singleton_no" ] to map = (d0, d1) -> (d0 : compressed(nonunique, nonordered), d1 : singleton(nonordered))
SortedCOO
lvlTypes = [ "compressed_nu", "singleton" ] to map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton)
BCOO
lvlTypes = [ "dense", "compressed_hi_nu", "singleton" ] to map = (d0, d1, d2) -> (d0 : dense, d1 : compressed(nonunique, high), d2 : singleton)
BCSR
lvlTypes = [ "compressed", "compressed", "dense", "dense" ], dimToLvl = affine_map<(d0, d1) -> (d0 floordiv 2, d1 floordiv 3, d0 mod 2, d1 mod 3)> to
map = ( i, j ) ->
( i floordiv 2 : compressed,
j floordiv 3 : compressed,
i mod 2 : dense,
j mod 3 : dense
)
Tensor and other supported formats(e.g. CCC, CDC, CCCC)
Currently, ELL and slice are not supported yet in the new syntax and the CHECK tests will be updated once printing is set to output the new syntax.
llvmbot
added
mlir:core
|
@llvm/pr-subscribers-mlir @llvm/pr-subscribers-mlir-gpu ChangesCOO SortedCOO BCOO BCSR Tensor and other supported formats(e.g. CCC, CDC, CCCC) Currently, ELL and slice are not supported yet in the new syntax and the CHECK tests will be updated once printing is set to output the new syntax.Patch is 51.38 KiB, truncated to 20.00 KiB below, full version: https://github.com/llvm/llvm-project/pull/66543.diff 58 Files Affected:
diff --git a/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorAttrDefs.td b/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorAttrDefs.td
index 8b79fbf726495ad..e671c5e323a09d9 100644
--- a/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorAttrDefs.td
+++ b/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorAttrDefs.td
@@ -200,7 +200,7 @@ def SparseTensorEncodingAttr : SparseTensor_Attr<"SparseTensorEncoding",
// Sorted Coordinate Scheme.
#SortedCOO = #sparse_tensor.encoding<{
- lvlTypes = [ "compressed_nu", "singleton" ]
+ map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton)
}>
... tensor<?x?xf64, #SortedCOO> ...
@@ -214,8 +214,12 @@ def SparseTensorEncodingAttr : SparseTensor_Attr<"SparseTensorEncoding",
// Block sparse row storage (2x3 blocks).
#BCSR = #sparse_tensor.encoding<{
- lvlTypes = [ "compressed", "compressed", "dense", "dense" ],
- dimToLvl = affine_map<(i, j) -> (i floordiv 2, j floordiv 3, i mod 2, j mod 3)>
+ map = ( i, j ) ->
+ ( i floordiv 2 : compressed,
+ j floordiv 3 : compressed,
+ i mod 2 : dense,
+ j mod 3 : dense
+ )
}>
... tensor<20x30xf32, #BCSR> ...
diff --git a/mlir/test/Dialect/SparseTensor/GPU/gpu_matvec_lib.mlir b/mlir/test/Dialect/SparseTensor/GPU/gpu_matvec_lib.mlir
index 4f25322df2c90dd..50ff81cb6ecd0a6 100644
--- a/mlir/test/Dialect/SparseTensor/GPU/gpu_matvec_lib.mlir
+++ b/mlir/test/Dialect/SparseTensor/GPU/gpu_matvec_lib.mlir
@@ -2,7 +2,7 @@
// RUN: --sparsification="enable-gpu-libgen" | FileCheck %s
#SortedCOO = #sparse_tensor.encoding<{
- lvlTypes = [ "compressed_nu", "singleton" ]
+ map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton)
}>
module {
diff --git a/mlir/test/Dialect/SparseTensor/codegen.mlir b/mlir/test/Dialect/SparseTensor/codegen.mlir
index c5061c40eb0b16b..f1317f23d656848 100644
--- a/mlir/test/Dialect/SparseTensor/codegen.mlir
+++ b/mlir/test/Dialect/SparseTensor/codegen.mlir
@@ -27,7 +27,7 @@
}>
#UCSR = #sparse_tensor.encoding<{
- lvlTypes = [ "dense", "compressed_no" ]
+ map = (d0, d1) -> (d0 : dense, d1 : compressed(nonordered))
}>
#CSC = #sparse_tensor.encoding<{
@@ -41,21 +41,19 @@
}>
#Dense3D = #sparse_tensor.encoding<{
- lvlTypes = [ "dense", "dense", "dense" ],
- dimToLvl = affine_map<(i, j, k) -> (k, i, j)>
+ map = (d0, d1, d2) -> (d2 : dense, d0 : dense, d1 : dense)
}>
#Coo = #sparse_tensor.encoding<{
- lvlTypes = [ "compressed_nu", "singleton" ]
+ map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton)
}>
#CooPNo = #sparse_tensor.encoding<{
- lvlTypes = [ "compressed_nu", "singleton_no" ],
- dimToLvl = affine_map<(i, j) -> (j, i)>
+ map = (d0, d1) -> (d1 : compressed(nonunique), d0 : singleton(nonordered))
}>
#ccoo = #sparse_tensor.encoding<{
- lvlTypes = [ "compressed", "compressed_nu", "singleton" ]
+ map = (d0, d1, d2) -> (d0 : compressed, d1 : compressed(nonunique), d2 : singleton)
}>
// CHECK-LABEL: func @sparse_nop(
diff --git a/mlir/test/Dialect/SparseTensor/codegen_sparse_alloc.mlir b/mlir/test/Dialect/SparseTensor/codegen_sparse_alloc.mlir
index 479642e5db4ed1e..50ad4a0a1ea247d 100644
--- a/mlir/test/Dialect/SparseTensor/codegen_sparse_alloc.mlir
+++ b/mlir/test/Dialect/SparseTensor/codegen_sparse_alloc.mlir
@@ -1,7 +1,7 @@
// RUN: mlir-opt %s --sparse-tensor-codegen --canonicalize --cse | FileCheck %s
#CSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed)}>
-#COO = #sparse_tensor.encoding<{ lvlTypes = ["compressed_nu", "singleton"]}>
+#COO = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton)}>
// CHECK-LABEL: func.func @sparse_alloc_copy_CSR(
// CHECK-SAME: %[[VAL_0:.*0]]: memref<?xindex>,
diff --git a/mlir/test/Dialect/SparseTensor/conversion.mlir b/mlir/test/Dialect/SparseTensor/conversion.mlir
index f8e30872a0756c7..64f66c5cb65eba9 100644
--- a/mlir/test/Dialect/SparseTensor/conversion.mlir
+++ b/mlir/test/Dialect/SparseTensor/conversion.mlir
@@ -25,8 +25,7 @@
}>
#SparseTensor = #sparse_tensor.encoding<{
- lvlTypes = ["dense", "compressed", "compressed"],
- dimToLvl = affine_map<(i,j,k) -> (k,i,j)>
+ map = (d0, d1, d2) -> (d2 : dense, d0 : compressed, d1 : compressed)
}>
// CHECK-LABEL: func @sparse_nop(
diff --git a/mlir/test/Dialect/SparseTensor/convert_dense2sparse.mlir b/mlir/test/Dialect/SparseTensor/convert_dense2sparse.mlir
index 4707b199222ad49..9fb1946d56263db 100644
--- a/mlir/test/Dialect/SparseTensor/convert_dense2sparse.mlir
+++ b/mlir/test/Dialect/SparseTensor/convert_dense2sparse.mlir
@@ -15,8 +15,7 @@
}>
#SparseTensor = #sparse_tensor.encoding<{
- lvlTypes = ["dense", "compressed", "compressed"],
- dimToLvl = affine_map<(i,j,k) -> (k,i,j)>
+ map = (d0, d1, d2) -> (d2 : dense, d0 : compressed, d1 : compressed)
}>
// CHECK-LABEL: func @sparse_convert_1d(
diff --git a/mlir/test/Dialect/SparseTensor/convert_sparse2dense.mlir b/mlir/test/Dialect/SparseTensor/convert_sparse2dense.mlir
index 363a63eb8ed1eca..621235182c9a840 100644
--- a/mlir/test/Dialect/SparseTensor/convert_sparse2dense.mlir
+++ b/mlir/test/Dialect/SparseTensor/convert_sparse2dense.mlir
@@ -12,8 +12,7 @@
}>
#SparseTensor = #sparse_tensor.encoding<{
- lvlTypes = ["dense", "compressed", "compressed"],
- dimToLvl = affine_map<(i,j,k) -> (k,i,j)>
+ map = (d0, d1, d2) -> (d2 : dense, d0 : compressed, d1 : compressed)
}>
// CHECK-LABEL: func @sparse_convert_1d(
diff --git a/mlir/test/Dialect/SparseTensor/convert_sparse2sparse.mlir b/mlir/test/Dialect/SparseTensor/convert_sparse2sparse.mlir
index 296e1bf9030c624..b3eb50f1755dace 100644
--- a/mlir/test/Dialect/SparseTensor/convert_sparse2sparse.mlir
+++ b/mlir/test/Dialect/SparseTensor/convert_sparse2sparse.mlir
@@ -26,17 +26,16 @@
}>
#SortedCOO2D = #sparse_tensor.encoding<{
- lvlTypes = [ "compressed_nu", "singleton" ],
+ map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton),
}>
#SortedCOO3D = #sparse_tensor.encoding<{
- lvlTypes = [ "compressed_nu", "singleton_nu", "singleton" ]
+ map = (d0, d1, d2) -> (d0 : compressed(nonunique), d1 : singleton(nonunique), d2 : singleton)
}>
#TsssPermuted = #sparse_tensor.encoding<{
- lvlTypes = [ "compressed", "compressed", "compressed" ],
- dimToLvl = affine_map<(i,j,k) -> (k,i,j)>
+ map = (d0, d1, d2) -> (d2 : compressed, d0 : compressed, d1 : compressed)
}>
#COOSlice = #sparse_tensor.encoding<{
@@ -115,13 +114,13 @@ func.func @sparse_convert(%arg0: tensor<?xf32, #SparseVector64>) -> tensor<?xf32
}
#SparseSingleton64 = #sparse_tensor.encoding<{
- lvlTypes = ["singleton"],
+ map = (d0) -> (d0 : singleton),
posWidth = 64,
crdWidth = 64
}>
#SparseSingleton32 = #sparse_tensor.encoding<{
- lvlTypes = ["singleton"],
+ map = (d0) -> (d0 : singleton),
posWidth = 32,
crdWidth = 32
}>
diff --git a/mlir/test/Dialect/SparseTensor/invalid.mlir b/mlir/test/Dialect/SparseTensor/invalid.mlir
index 8e25cf06bcb6212..71e6eebb30261c8 100644
--- a/mlir/test/Dialect/SparseTensor/invalid.mlir
+++ b/mlir/test/Dialect/SparseTensor/invalid.mlir
@@ -32,7 +32,7 @@ func.func @invalid_pack_type(%values: tensor<6xf64>, %pos: tensor<2xi32>, %coord
// -----
-#SparseVector = #sparse_tensor.encoding<{lvlTypes = ["compressed_nu", "singleton"], posWidth=32, crdWidth=32}>
+#SparseVector = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton), posWidth=32, crdWidth=32}>
func.func @invalid_pack_type(%values: tensor<6xf64>, %pos: tensor<2xi32>, %coordinates: tensor<6x3xi32>)
-> tensor<100x2xf64, #SparseVector> {
@@ -68,7 +68,7 @@ func.func @invalid_unpack_type(%sp: tensor<100xf32, #SparseVector>, %values: ten
// -----
-#SparseVector = #sparse_tensor.encoding<{lvlTypes = ["compressed_nu", "singleton"], posWidth=32, crdWidth=32}>
+#SparseVector = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton), posWidth=32, crdWidth=32}>
func.func @invalid_unpack_type(%sp: tensor<100x2xf64, #SparseVector>, %values: tensor<6xf64>, %pos: tensor<2xi32>, %coordinates: tensor<6x3xi32>) {
// expected-error@+1 {{input/output trailing COO level-ranks don't match}}
@@ -270,7 +270,7 @@ func.func @sparse_get_md(%arg0: !sparse_tensor.storage_specifier<#SparseVector>)
// -----
-#COO = #sparse_tensor.encoding<{lvlTypes = ["compressed_nu", "singleton"]}>
+#COO = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton)}>
func.func @sparse_get_md(%arg0: !sparse_tensor.storage_specifier<#COO>) -> index {
// expected-error@+1 {{requested position memory size on a singleton level}}
@@ -658,7 +658,7 @@ func.func @invalid_concat_dim(%arg0: tensor<2x4xf64, #DC>,
#C = #sparse_tensor.encoding<{map = (d0) -> (d0 : compressed)}>
#DC = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : dense, d1 : compressed)}>
-#DCC = #sparse_tensor.encoding<{lvlTypes = ["dense", "compressed", "compressed"]}>
+#DCC = #sparse_tensor.encoding<{map = (d0, d1, d2) -> (d0 : dense, d1 : compressed, d2 : compressed)}>
func.func @invalid_concat_rank_mismatch(%arg0: tensor<2xf64, #C>,
%arg1: tensor<3x4xf64, #DC>,
%arg2: tensor<4x4x4xf64, #DCC>) -> tensor<9x4xf64, #DC> {
diff --git a/mlir/test/Dialect/SparseTensor/pre_rewriting.mlir b/mlir/test/Dialect/SparseTensor/pre_rewriting.mlir
index 1245cb0eeed3c55..5aa4acaf863937f 100644
--- a/mlir/test/Dialect/SparseTensor/pre_rewriting.mlir
+++ b/mlir/test/Dialect/SparseTensor/pre_rewriting.mlir
@@ -5,7 +5,7 @@
}>
#SortedCOO = #sparse_tensor.encoding<{
- lvlTypes = [ "compressed_nu", "singleton" ]
+ map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton)
}>
#DCSR = #sparse_tensor.encoding<{
diff --git a/mlir/test/Dialect/SparseTensor/rewriting_for_codegen.mlir b/mlir/test/Dialect/SparseTensor/rewriting_for_codegen.mlir
index 0312758722bea82..913059e2197f12d 100644
--- a/mlir/test/Dialect/SparseTensor/rewriting_for_codegen.mlir
+++ b/mlir/test/Dialect/SparseTensor/rewriting_for_codegen.mlir
@@ -10,7 +10,7 @@
}>
#COO = #sparse_tensor.encoding<{
- lvlTypes = [ "compressed_nu", "singleton" ]
+ map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton)
}>
// CHECK-LABEL: func.func @sparse_new(
diff --git a/mlir/test/Dialect/SparseTensor/roundtrip.mlir b/mlir/test/Dialect/SparseTensor/roundtrip.mlir
index d3f07fd298d72e9..d1262cb7aea02df 100644
--- a/mlir/test/Dialect/SparseTensor/roundtrip.mlir
+++ b/mlir/test/Dialect/SparseTensor/roundtrip.mlir
@@ -77,7 +77,7 @@ func.func @sparse_convert_1d_to_sparse(%arg0: tensor<64xf32>) -> tensor<64xf32,
// -----
-#SparseTensor = #sparse_tensor.encoding<{ lvlTypes = [ "dense", "dense", "compressed" ] }>
+#SparseTensor = #sparse_tensor.encoding<{ map = (d0, d1, d2) -> (d0 : dense, d1 : dense, d2 : compressed) }>
// CHECK-LABEL: func @sparse_convert_3d_from_sparse(
// CHECK-SAME: %[[A:.*]]: tensor<8x8x8xf64, #{{.*}}>)
@@ -103,7 +103,7 @@ func.func @sparse_positions(%arg0: tensor<128xf64, #SparseVector>) -> memref<?xi
// -----
-#COO = #sparse_tensor.encoding<{lvlTypes = ["compressed_nu", "singleton"]}>
+#COO = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton)}>
// CHECK-LABEL: func @sparse_indices_buffer(
// CHECK-SAME: %[[A:.*]]: tensor<?x?xf64, #{{.*}}>)
diff --git a/mlir/test/Dialect/SparseTensor/roundtrip_encoding.mlir b/mlir/test/Dialect/SparseTensor/roundtrip_encoding.mlir
index 1cc5c0e3f61527e..60367b43a6ee0e4 100644
--- a/mlir/test/Dialect/SparseTensor/roundtrip_encoding.mlir
+++ b/mlir/test/Dialect/SparseTensor/roundtrip_encoding.mlir
@@ -85,8 +85,12 @@ func.func private @sparse_sorted_coo(tensor<10x10xf64, #SortedCOO>)
// -----
#BCSR = #sparse_tensor.encoding<{
- lvlTypes = [ "compressed", "compressed", "dense", "dense" ],
- dimToLvl = affine_map<(i, j) -> (i floordiv 2, j floordiv 3, i mod 2, j mod 3)>
+ map = ( i, j ) ->
+ ( i floordiv 2 : compressed,
+ j floordiv 3 : compressed,
+ i mod 2 : dense,
+ j mod 3 : dense
+ )
}>
// CHECK-LABEL: func private @sparse_bcsr(
diff --git a/mlir/test/Dialect/SparseTensor/sorted_coo.mlir b/mlir/test/Dialect/SparseTensor/sorted_coo.mlir
index e4bc55fcdb06298..95c410a08b0e408 100644
--- a/mlir/test/Dialect/SparseTensor/sorted_coo.mlir
+++ b/mlir/test/Dialect/SparseTensor/sorted_coo.mlir
@@ -1,7 +1,7 @@
// RUN: mlir-opt %s -sparsification --canonicalize | FileCheck %s
#SortedCOO = #sparse_tensor.encoding<{
- lvlTypes = [ "compressed_nu", "singleton" ]
+ map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton)
}>
#trait_scale = {
diff --git a/mlir/test/Dialect/SparseTensor/sparse_2d.mlir b/mlir/test/Dialect/SparseTensor/sparse_2d.mlir
index 44c731e9302749a..00bf4ea440628cd 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_2d.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_2d.mlir
@@ -1050,7 +1050,7 @@ func.func @cmp_ss_ss(%arga: tensor<32x16xf32, #Tss>, %argb: tensor<32x16xf32, #T
}
#BatchedVector = #sparse_tensor.encoding<{
- lvlTypes = [ "dense", "compressed_hi" ],
+ map = (d0, d1) -> (d0 : dense, d1 : compressed(high))
}>
// CHECK-LABEL: func.func @sub_ss_batched(
// CHECK-SAME: %[[VAL_0:.*]]: tensor<2x3xf64, #{{.*}}>>,
diff --git a/mlir/test/Dialect/SparseTensor/sparse_3d.mlir b/mlir/test/Dialect/SparseTensor/sparse_3d.mlir
index 9019b9984d8f680..3513bc48ffc0e38 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_3d.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_3d.mlir
@@ -3,14 +3,14 @@
#Td = #sparse_tensor.encoding<{ map = (d0) -> (d0 : dense) }>
-#Tddd = #sparse_tensor.encoding<{ lvlTypes = [ "dense", "dense", "dense" ] }>
-#Tdds = #sparse_tensor.encoding<{ lvlTypes = [ "dense", "dense", "compressed" ] }>
-#Tdsd = #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed", "dense" ] }>
-#Tdss = #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed", "compressed" ] }>
-#Tsdd = #sparse_tensor.encoding<{ lvlTypes = [ "compressed", "dense", "dense" ] }>
-#Tsds = #sparse_tensor.encoding<{ lvlTypes = [ "compressed", "dense", "compressed" ] }>
-#Tssd = #sparse_tensor.encoding<{ lvlTypes = [ "compressed", "compressed", "dense" ] }>
-#Tsss = #sparse_tensor.encoding<{ lvlTypes = [ "compressed", "compressed", "compressed" ] }>
+#Tddd = #sparse_tensor.encoding<{ map = (d0, d1, d2) -> (d0 : dense, d1 : dense, d2 : dense) }>
+#Tdds = #sparse_tensor.encoding<{ map = (d0, d1, d2) -> (d0 : dense, d1 : dense, d2 : compressed) }>
+#Tdsd = #sparse_tensor.encoding<{ map = (d0, d1, d2) -> (d0 : dense, d1 : compressed, d2 : dense) }>
+#Tdss = #sparse_tensor.encoding<{ map = (d0, d1, d2) -> (d0 : dense, d1 : compressed, d2 : compressed) }>
+#Tsdd = #sparse_tensor.encoding<{ map = (d0, d1, d2) -> (d0 : compressed, d1 : dense, d2 : dense) }>
+#Tsds = #sparse_tensor.encoding<{ map = (d0, d1, d2) -> (d0 : compressed, d1 : dense, d2 : compressed) }>
+#Tssd = #sparse_tensor.encoding<{ map = (d0, d1, d2) -> (d0 : compressed, d1 : compressed, d2 : dense) }>
+#Tsss = #sparse_tensor.encoding<{ map = (d0, d1, d2) -> (d0 : compressed, d1 : compressed, d2 : compressed) }>
#trait3 = {
indexing_maps = [
diff --git a/mlir/test/Dialect/SparseTensor/sparse_broadcast.mlir b/mlir/test/Dialect/SparseTensor/sparse_broadcast.mlir
index 3af4614dfe93e6a..ae5b941259f6515 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_broadcast.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_broadcast.mlir
@@ -1,7 +1,7 @@
// RUN: mlir-opt %s --sparsification --canonicalize --cse | FileCheck %s
#DCSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : compressed, d1 : compressed) }>
-#SparseTensor = #sparse_tensor.encoding<{ lvlTypes = [ "compressed", "compressed", "compressed" ] }>
+#SparseTensor = #sparse_tensor.encoding<{ map = (d0, d1, d2) -> (d0 : compressed, d1 : compressed, d2 : compressed) }>
#trait = {
indexing_maps = [
diff --git a/mlir/test/Dialect/SparseTensor/sparse_foreach.mlir b/mlir/test/Dialect/SparseTensor/sparse_foreach.mlir
index baa30c9457d2dce..822cfb0148f249a 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_foreach.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_foreach.mlir
@@ -141,7 +141,7 @@ func.func @foreach_print_slice(%A: tensor<4x4xf64, #CSR_SLICE>) {
}
#BCOO = #sparse_tensor.encoding<{
- lvlTypes = [ "dense", "compressed_hi_nu", "singleton" ],
+ map = (d0, d1, d2) -> (d0 : dense, d1 : compressed(nonunique, high), d2 : singleton)
}>
// CHECK-LABEL: func.func @foreach_bcoo(
diff --git a/mlir/test/Dialect/SparseTensor/sparse_nd.mlir b/mlir/test/Dialect/SparseTensor/sparse_nd.mlir
index 742d42be3f8c584..d05cebd55ce3128 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_nd.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_nd.mlir
@@ -5,8 +5,10 @@
// but an acyclic iteration graph using sparse constraints only.
#SparseTensor = #sparse_tensor.encoding<{
- lvlTypes = [ "dense", "dense", "dense", "compressed",
- "compressed", "dense", "dense", "dense" ]
+ map = (d0, d1, d2, d3,
+ d4, d5, d6, d7) -> (d0 : dense, d1 : dense, d2 : dense,
+ d3 : compressed, d4 : compressed, d5 : dense,
+ d6 : dense, d7 : dense)
}>
#trait_mul = {
diff --git a/mlir/test/Dialect/SparseTensor/sparse_out.mlir b/mlir/test/Dialect/SparseTensor/sparse_out.mlir
index 128c290e966b92d..97d8da213423d9e 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_out.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_out.mlir
@@ -9,7 +9,7 @@
}>
#SparseTensor = #sparse_tensor.encoding<{
- lvlTypes = [ "compressed", "compressed", "compressed" ]
+ map = (d0, d1, d2) -> (d0 : compressed, d1 : compressed, d2 : compressed)
}>
#trait_scale_inpl = {
diff --git a/mlir/test/Dialect/SparseTensor/sparse_pack.mlir b/mlir/test/Dialect/SparseTensor/sparse_pack.mlir
index 45906f498356700..8caf75636277762 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_pack.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_pack.mlir
@@ -1,7 +1,7 @@
// RUN: mlir-opt %s --canonicalize --post-sparsification-rewrite="enable-runtime-library=false" --sparse-tensor-codegen -cse --canonicalize | FileCheck %s
#COO = #sparse_tensor.encoding<{
- lvlTypes = ["compressed_nu", "singleton"],
+ map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton),
crdWidth=32
}>
diff --git a/mlir/test/Dialect/SparseTensor/sparse_perm.mlir b/mlir/test/Dialect/SparseTensor/sparse_perm.mlir
index 438f2c496d89157..26712f2c7b001b3 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_perm.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_perm.mlir
@@ -2,8 +2,7 @@
// RUN: mlir-opt %s -sparsification | FileCheck %s
#X = #sparse_tensor.encoding<{
- lvlTypes = [ "dense", "dense", "dense" ],
- dimToLvl = affine_map<(i,j,k) -> (k,i,j)>
+ map = (d0, d1, d2) -> (d2 : dense, d0 : dense, d1 : dense)
}>
#trait = {
diff --git a/mlir/test/Dialect/SparseTensor/sparse_perm_lower.mlir b/mlir/test/Dialect/SparseTensor/sparse_perm_lower.mlir
index 2e3d723889cdd76..fd8aaf28697e42d 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_perm_lower.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_perm_lower.mlir
@@ -4,8 +4,7 @@
// RUN: FileCheck %s --check-prefix=CHECK-MIR
#X = #sparse_tensor.encoding<{
- lvlTypes = [ "dense", "dense", "dense" ],
- dimToLvl = affine_map<(i,j,k) -> (k,i,j)>
+ map = (d0, d1, d2) -> (d2 : dense, d0 : dense, d1 : dense)
}>
#trait = {
diff --git a/mlir/test/Dialect/SparseTensor/sparse_reshape_dot.mlir b/mlir/test/Dialect/SparseTensor/sparse_reshape_dot.mlir
index 43cf36fc0ac72aa..395a915f32806e8 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_reshape_dot.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_reshape_dot.mlir
@@ -4,8 +4,8 @@
//
// RUN: mlir-opt %s --linalg-generalize-named-ops --sparsification --cse --canonicalize | FileCheck %s
-#COO_2D = #sparse_tensor.encoding<{ lvlTypes = [ "compressed_nu", "singleton" ], posWidth = 32, crdWidth = 32 }>
-#COO_3D = #sparse_tensor.encoding<{ lvlTypes = [ "compressed_nu", "singleton_nu", "singleton" ], posWidth = 32, crdWidth = 32 }>
+#COO_2D = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton), posWidth = 32, crdWidth = 32 }>
+#COO_3D = #sparse_tensor.enco...
[truncated]
|
aartbik
approved these changes
Sep 15, 2023
ZijunZhaoCCK
pushed a commit
to ZijunZhaoCCK/llvm-project
that referenced
this pull request
Sep 19, 2023
**COO**
`lvlTypes = [ "compressed_nu", "singleton" ]` to `map = (d0, d1) -> (d0
: compressed(nonunique), d1 : singleton)`
`lvlTypes = [ "compressed_nu_no", "singleton_no" ]` to `map = (d0, d1)
-> (d0 : compressed(nonunique, nonordered), d1 : singleton(nonordered))`
**SortedCOO**
`lvlTypes = [ "compressed_nu", "singleton" ]` to `map = (d0, d1) -> (d0
: compressed(nonunique), d1 : singleton)`
**BCOO**
`lvlTypes = [ "dense", "compressed_hi_nu", "singleton" ]` to `map = (d0,
d1, d2) -> (d0 : dense, d1 : compressed(nonunique, high), d2 :
singleton)`
**BCSR**
`lvlTypes = [ "compressed", "compressed", "dense", "dense" ], dimToLvl =
affine_map<(d0, d1) -> (d0 floordiv 2, d1 floordiv 3, d0 mod 2, d1 mod
3)>` to
`map = ( i, j ) ->
( i floordiv 2 : compressed,
j floordiv 3 : compressed,
i mod 2 : dense,
j mod 3 : dense
)`
**Tensor and other supported formats(e.g. CCC, CDC, CCCC)**
Currently, ELL and slice are not supported yet in the new syntax and the
CHECK tests will be updated once printing is set to output the new
syntax.
Previous PRs: llvm#66146, llvm#66309, llvm#66443
zahiraam
pushed a commit
to tahonermann/llvm-project
that referenced
this pull request
Oct 24, 2023
**COO**
`lvlTypes = [ "compressed_nu", "singleton" ]` to `map = (d0, d1) -> (d0
: compressed(nonunique), d1 : singleton)`
`lvlTypes = [ "compressed_nu_no", "singleton_no" ]` to `map = (d0, d1)
-> (d0 : compressed(nonunique, nonordered), d1 : singleton(nonordered))`
**SortedCOO**
`lvlTypes = [ "compressed_nu", "singleton" ]` to `map = (d0, d1) -> (d0
: compressed(nonunique), d1 : singleton)`
**BCOO**
`lvlTypes = [ "dense", "compressed_hi_nu", "singleton" ]` to `map = (d0,
d1, d2) -> (d0 : dense, d1 : compressed(nonunique, high), d2 :
singleton)`
**BCSR**
`lvlTypes = [ "compressed", "compressed", "dense", "dense" ], dimToLvl =
affine_map<(d0, d1) -> (d0 floordiv 2, d1 floordiv 3, d0 mod 2, d1 mod
3)>` to
`map = ( i, j ) ->
( i floordiv 2 : compressed,
j floordiv 3 : compressed,
i mod 2 : dense,
j mod 3 : dense
)`
**Tensor and other supported formats(e.g. CCC, CDC, CCCC)**
Currently, ELL and slice are not supported yet in the new syntax and the
CHECK tests will be updated once printing is set to output the new
syntax.
Previous PRs: llvm#66146, llvm#66309, llvm#66443
zahiraam
pushed a commit
to tahonermann/llvm-project
that referenced
this pull request
Oct 24, 2023
**COO**
`lvlTypes = [ "compressed_nu", "singleton" ]` to `map = (d0, d1) -> (d0
: compressed(nonunique), d1 : singleton)`
`lvlTypes = [ "compressed_nu_no", "singleton_no" ]` to `map = (d0, d1)
-> (d0 : compressed(nonunique, nonordered), d1 : singleton(nonordered))`
**SortedCOO**
`lvlTypes = [ "compressed_nu", "singleton" ]` to `map = (d0, d1) -> (d0
: compressed(nonunique), d1 : singleton)`
**BCOO**
`lvlTypes = [ "dense", "compressed_hi_nu", "singleton" ]` to `map = (d0,
d1, d2) -> (d0 : dense, d1 : compressed(nonunique, high), d2 :
singleton)`
**BCSR**
`lvlTypes = [ "compressed", "compressed", "dense", "dense" ], dimToLvl =
affine_map<(d0, d1) -> (d0 floordiv 2, d1 floordiv 3, d0 mod 2, d1 mod
3)>` to
`map = ( i, j ) ->
( i floordiv 2 : compressed,
j floordiv 3 : compressed,
i mod 2 : dense,
j mod 3 : dense
)`
**Tensor and other supported formats(e.g. CCC, CDC, CCCC)**
Currently, ELL and slice are not supported yet in the new syntax and the
CHECK tests will be updated once printing is set to output the new
syntax.
Previous PRs: llvm#66146, llvm#66309, llvm#66443
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COO
lvlTypes = [ "compressed_nu", "singleton" ]tomap = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton)lvlTypes = [ "compressed_nu_no", "singleton_no" ]tomap = (d0, d1) -> (d0 : compressed(nonunique, nonordered), d1 : singleton(nonordered))SortedCOO
lvlTypes = [ "compressed_nu", "singleton" ]tomap = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton)BCOO
lvlTypes = [ "dense", "compressed_hi_nu", "singleton" ]tomap = (d0, d1, d2) -> (d0 : dense, d1 : compressed(nonunique, high), d2 : singleton)BCSR
lvlTypes = [ "compressed", "compressed", "dense", "dense" ], dimToLvl = affine_map<(d0, d1) -> (d0 floordiv 2, d1 floordiv 3, d0 mod 2, d1 mod 3)>tomap = ( i, j ) -> ( i floordiv 2 : compressed, j floordiv 3 : compressed, i mod 2 : dense, j mod 3 : dense )Tensor and other supported formats(e.g. CCC, CDC, CCCC)
Currently, ELL and slice are not supported yet in the new syntax and the CHECK tests will be updated once printing is set to output the new syntax.
Previous PRs: #66146, #66309, #66443