[Mlir-commits] [mlir] [XeGPU] Add sg_map for scatter verification (PR #124300)
Artem Kroviakov
llvmlistbot at llvm.org
Thu Jan 30 05:50:05 PST 2025
https://github.com/akroviakov updated https://github.com/llvm/llvm-project/pull/124300
>From 8b52a276c1549f41d00aca6494a91e008ff9034d Mon Sep 17 00:00:00 2001
From: Artem Kroviakov <artem.kroviakov at intel.com>
Date: Thu, 30 Jan 2025 13:49:14 +0000
Subject: [PATCH] [MLIR][XeGPU] Add sg_map for scatter verification
---
.../include/mlir/Dialect/XeGPU/IR/XeGPUOps.td | 7 +-
mlir/lib/Dialect/XeGPU/IR/XeGPUOps.cpp | 47 ++++++++++-
mlir/test/Dialect/XeGPU/XeGPUOps.mlir | 62 ++++++++++++++-
mlir/test/Dialect/XeGPU/invalid.mlir | 77 +++++++++++++++++++
4 files changed, 183 insertions(+), 10 deletions(-)
diff --git a/mlir/include/mlir/Dialect/XeGPU/IR/XeGPUOps.td b/mlir/include/mlir/Dialect/XeGPU/IR/XeGPUOps.td
index a2bfa721f2515b..c2335eecc3781d 100644
--- a/mlir/include/mlir/Dialect/XeGPU/IR/XeGPUOps.td
+++ b/mlir/include/mlir/Dialect/XeGPU/IR/XeGPUOps.td
@@ -548,9 +548,7 @@ def XeGPU_PrefetchOp : XeGPU_Op<"prefetch", []> {
let hasVerifier = 1;
}
-def XeGPU_LoadGatherOp : XeGPU_Op<"load", [AllRanksMatch<["value", "TensorDesc"]>,
- AllElementTypesMatch<["value", "TensorDesc"]>,
- AllElementCountsMatch<["value", "TensorDesc"]>]> {
+def XeGPU_LoadGatherOp : XeGPU_Op<"load", [AllElementTypesMatch<["value", "TensorDesc"]>]> {
let summary = "load a set of scattered data points from memory.";
let description = [{ It (aka. load) load data per each work-item. The output
@@ -620,8 +618,7 @@ def XeGPU_LoadGatherOp : XeGPU_Op<"load", [AllRanksMatch<["value", "TensorDesc"]
let hasVerifier = 1;
}
-def XeGPU_StoreScatterOp : XeGPU_Op<"store", [AllElementCountsMatch<["value", "TensorDesc"]>,
- AllElementTypesMatch<["value", "TensorDesc"]>]> {
+def XeGPU_StoreScatterOp : XeGPU_Op<"store", [AllElementTypesMatch<["value", "TensorDesc"]>]> {
let summary = "store data to scattered memory locations.";
let description = [{ It (aka. store) stores data to scattered memory locations. The value is
typically a 1D vector. But when the chunk size of the TensorDesc is larger than 1, it will be
diff --git a/mlir/lib/Dialect/XeGPU/IR/XeGPUOps.cpp b/mlir/lib/Dialect/XeGPU/IR/XeGPUOps.cpp
index 15c435f1fa257b..58bb931b6fa1e8 100644
--- a/mlir/lib/Dialect/XeGPU/IR/XeGPUOps.cpp
+++ b/mlir/lib/Dialect/XeGPU/IR/XeGPUOps.cpp
@@ -453,7 +453,22 @@ LogicalResult CreateDescOp::verify() {
if (shape != tdescShape)
return emitOpError("Incorrect TensorDesc shape. ")
<< "Expected is " << makeString(shape) << "\n";
-
+ if (auto sgMap = tdescTy.getSGMapAttr()) {
+ // A work-item's slice of the TensorDesc with shape [sg_size] or
+ // [sg_size, chunk_size] will be [1] or [1, chunks_size] respectively,
+ // the mapping should reflect that.
+ if (sgMap.getWiData()[0] > 1)
+ return emitOpError("TensorDesc's SG map only supports multiple elements "
+ "contiguous along rows.");
+ if (chunkSize != static_cast<int>(sgMap.getWiData()[1]))
+ return emitOpError(
+ "TensorDesc's chunkSize must match WI's data mapping.");
+ if (int rank = tdescTy.getRank();
+ (sgMap.getWiLayout()[2 - rank] != tdescShape[0]))
+ return emitOpError("Detected a conflict between SG map's work-item "
+ "layout and TensorDesc shape. Check the index of "
+ "`subgroup_size` in WI layout map.");
+ }
return success();
}
@@ -512,10 +527,23 @@ LogicalResult LoadGatherOp::verify() {
if (tdescTy.getRank() == 2) {
if (!getTransposeAttr())
- return emitOpError("load_gather has to be transposed.");
+ return emitOpError("load of rank-2 tensor has to be transposed.");
transpose({1, 0}, tdescShape);
}
+ if (auto sgMap = tdescTy.getSGMapAttr()) {
+ auto valueVecTy = cast<VectorType>(valueTy);
+ const int32_t wiData =
+ sgMap.getWiData()[0] > 1 ? sgMap.getWiData()[0] : sgMap.getWiData()[1];
+ // All represent the same concept: a number of row elements to store.
+ if (valueVecTy.getNumElements() != wiData ||
+ valueVecTy.getNumElements() != tdescTy.getChunkSize()) {
+ return emitOpError("Chunk size, vector size and wi_data must match.");
+ }
+ // Work-item's slice (i.e., vector shape to load) is [1] or [1, chunk_size].
+ tdescShape[tdescTy.getRank() - 1] = 1;
+ }
+
if (valueShape != tdescShape)
return emitOpError("Unexpected result shape")
<< "(Expected shape: " << makeString(tdescShape)
@@ -551,10 +579,23 @@ LogicalResult StoreScatterOp::verify() {
if (tdescTy.getRank() == 2) {
if (!getTransposeAttr())
- return emitOpError("load_gather has to be transposed.");
+ return emitOpError("Store of a rank-2 tensor has to be transposed.");
transpose({1, 0}, tdescShape);
}
+ if (auto sgMap = tdescTy.getSGMapAttr()) {
+ auto valueVecTy = cast<VectorType>(valueTy);
+ const int32_t wiData =
+ sgMap.getWiData()[0] > 1 ? sgMap.getWiData()[0] : sgMap.getWiData()[1];
+ // All represent the same concept: a number of row elements to store.
+ if (valueVecTy.getNumElements() != wiData ||
+ valueVecTy.getNumElements() != tdescTy.getChunkSize()) {
+ return emitOpError("Chunk size, vector size and wi_data must match.");
+ }
+ // Work-item's slice (i.e., vector to store) is [1] or [1, chunk_size].
+ tdescShape[tdescTy.getRank() - 1] = 1;
+ }
+
if (valueShape != tdescShape)
return emitOpError("Unexpected value shape")
<< "(Expected shape: " << makeString(tdescShape)
diff --git a/mlir/test/Dialect/XeGPU/XeGPUOps.mlir b/mlir/test/Dialect/XeGPU/XeGPUOps.mlir
index d7174a489888a4..dcd6b01974cf30 100644
--- a/mlir/test/Dialect/XeGPU/XeGPUOps.mlir
+++ b/mlir/test/Dialect/XeGPU/XeGPUOps.mlir
@@ -163,11 +163,69 @@ gpu.func @test_create_tdesc_vc_1(%src: memref<?xf32, 3>) {
gpu.func @test_create_tdesc_vc_with_sg_map(%src: ui64) {
//CHECK: %[[cst:.*]] = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
%0 = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
- //CHECK: %[[R0:.*]] = xegpu.create_tdesc %[[arg0]], %[[cst]] : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2 : i64>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 1]>>
- %1 = xegpu.create_tdesc %src, %0 : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 1]>>
+ //CHECK: %[[R0:.*]] = xegpu.create_tdesc %[[arg0]], %[[cst]] : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2 : i64>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>
+ %1 = xegpu.create_tdesc %src, %0 : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>
gpu.return
}
+// CHECK: gpu.func @test_load_with_sg_map(%[[arg0:.*]]: ui64) {
+gpu.func @test_load_with_sg_map(%src: ui64) {
+ //CHECK: %[[cst:.*]] = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
+ %0 = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
+ //CHECK: %[[cst1:.*]] = arith.constant dense<true> : vector<4xi1>
+ %1 = arith.constant dense<1>: vector<4xi1>
+ //CHECK: %[[R0:.*]] = xegpu.create_tdesc %[[arg0]], %[[cst]] : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2 : i64>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>
+ %2 = xegpu.create_tdesc %src, %0 : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>
+ //CHECK: %[[R1:.*]] = xegpu.load %[[R0]], %[[cst1]] <{l1_hint = #xegpu.cache_hint<cached>, l2_hint = #xegpu.cache_hint<uncached>, transpose}> : !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2 : i64>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>, vector<4xi1> -> vector<2x1xf32>
+ %3 = xegpu.load %2, %1 <{l1_hint = #xegpu.cache_hint<cached>, l2_hint = #xegpu.cache_hint<uncached>, transpose}> : !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>, vector<4xi1> -> vector<2x1xf32>
+ gpu.return
+}
+
+// CHECK: gpu.func @test_load_with_sg_map_2(%[[arg0:.*]]: ui64) {
+gpu.func @test_load_with_sg_map_2(%src: ui64) {
+ //CHECK: %[[cst:.*]] = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
+ %0 = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
+ //CHECK: %[[cst1:.*]] = arith.constant dense<true> : vector<4xi1>
+ %1 = arith.constant dense<1>: vector<4xi1>
+ //CHECK: %[[R0:.*]] = xegpu.create_tdesc %[[arg0]], %[[cst]] : ui64, vector<4xindex> -> !xegpu.tensor_desc<4xf32, #xegpu.scatter_tdesc_attr<>, #xegpu.sg_map<wi_layout = [1, 4], wi_data = [1, 1]>>
+ %2 = xegpu.create_tdesc %src, %0 : ui64, vector<4xindex> -> !xegpu.tensor_desc<4xf32, #xegpu.scatter_tdesc_attr<>, #xegpu.sg_map<wi_layout = [1, 4], wi_data = [1, 1]>>
+ //CHECK: %[[R1:.*]] = xegpu.load %[[R0]], %[[cst1]] <{l1_hint = #xegpu.cache_hint<cached>, l2_hint = #xegpu.cache_hint<uncached>}> : !xegpu.tensor_desc<4xf32, #xegpu.scatter_tdesc_attr<>, #xegpu.sg_map<wi_layout = [1, 4], wi_data = [1, 1]>>, vector<4xi1> -> vector<1xf32>
+ %3 = xegpu.load %2, %1 <{l1_hint = #xegpu.cache_hint<cached>, l2_hint = #xegpu.cache_hint<uncached>}> : !xegpu.tensor_desc<4xf32, #xegpu.scatter_tdesc_attr<>, #xegpu.sg_map<wi_layout = [1, 4], wi_data = [1, 1]>>, vector<4xi1> -> vector<1xf32>
+ gpu.return
+}
+
+// CHECK: gpu.func @test_store_with_sg_map(%[[arg0:.*]]: ui64) {
+gpu.func @test_store_with_sg_map(%src: ui64) {
+ //CHECK: %[[cst:.*]] = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
+ %0 = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
+ //CHECK: %[[cst1:.*]] = arith.constant dense<true> : vector<4xi1>
+ %1 = arith.constant dense<1>: vector<4xi1>
+ //CHECK: %[[cst2:.*]] = arith.constant dense<2.900000e+00> : vector<2x1xf32>
+ %2 = arith.constant dense<2.9>: vector<2x1xf32>
+ //CHECK: %[[R0:.*]] = xegpu.create_tdesc %[[arg0]], %[[cst]] : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2 : i64>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>
+ %3 = xegpu.create_tdesc %src, %0 : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>
+ //CHECK: xegpu.store %[[cst2]], %[[R0]], %[[cst1]] <{l1_hint = #xegpu.cache_hint<write_back>, l2_hint = #xegpu.cache_hint<uncached>, transpose}> : vector<2x1xf32>, !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2 : i64>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>, vector<4xi1>
+ xegpu.store %2, %3, %1 <{l1_hint = #xegpu.cache_hint<write_back>, l2_hint = #xegpu.cache_hint<uncached>, transpose}> : vector<2x1xf32>, !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>, vector<4xi1>
+ gpu.return
+}
+
+// CHECK: gpu.func @test_store_with_sg_map_2(%[[arg0:.*]]: ui64) {
+gpu.func @test_store_with_sg_map_2(%src: ui64) {
+ //CHECK: %[[cst:.*]] = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
+ %0 = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
+ //CHECK: %[[cst1:.*]] = arith.constant dense<true> : vector<4xi1>
+ %1 = arith.constant dense<1>: vector<4xi1>
+ //CHECK: %[[cst2:.*]] = arith.constant dense<2.900000e+00> : vector<1xf32>
+ %2 = arith.constant dense<2.9>: vector<1xf32>
+ //CHECK: %[[R0:.*]] = xegpu.create_tdesc %[[arg0]], %[[cst]] : ui64, vector<4xindex> -> !xegpu.tensor_desc<4xf32, #xegpu.scatter_tdesc_attr<>, #xegpu.sg_map<wi_layout = [1, 4], wi_data = [1, 1]>>
+ %3 = xegpu.create_tdesc %src, %0 : ui64, vector<4xindex> -> !xegpu.tensor_desc<4xf32, #xegpu.scatter_tdesc_attr<>, #xegpu.sg_map<wi_layout = [1, 4], wi_data = [1, 1]>>
+ //CHECK: xegpu.store %[[cst2]], %[[R0]], %[[cst1]] <{l1_hint = #xegpu.cache_hint<write_back>, l2_hint = #xegpu.cache_hint<uncached>}> : vector<1xf32>, !xegpu.tensor_desc<4xf32, #xegpu.scatter_tdesc_attr<>, #xegpu.sg_map<wi_layout = [1, 4], wi_data = [1, 1]>>, vector<4xi1>
+ xegpu.store %2, %3, %1 <{l1_hint = #xegpu.cache_hint<write_back>, l2_hint = #xegpu.cache_hint<uncached>}> : vector<1xf32>, !xegpu.tensor_desc<4xf32, #xegpu.scatter_tdesc_attr<>, #xegpu.sg_map<wi_layout = [1, 4], wi_data = [1, 1]>>, vector<4xi1>
+ gpu.return
+}
+
+
+
// CHECK: gpu.func @test_prefetch_vc(%[[arg0:.*]]: ui64) {
gpu.func @test_prefetch_vc(%src: ui64) {
//CHECK: %[[cst:.*]] = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
diff --git a/mlir/test/Dialect/XeGPU/invalid.mlir b/mlir/test/Dialect/XeGPU/invalid.mlir
index 7816bff0582f81..201f72120cf2c5 100644
--- a/mlir/test/Dialect/XeGPU/invalid.mlir
+++ b/mlir/test/Dialect/XeGPU/invalid.mlir
@@ -170,6 +170,83 @@ func.func @test_prefetch_vc_2(%src: ui64) {
return
}
+// -----
+func.func @test_create_tdesc_sg_map_1(%src: ui64) {
+ %cst = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
+ // expected-error at +1 {{Detected a conflict between SG map's work-item layout and TensorDesc shape. Check the index of `subgroup_size` in WI layout map}}
+ %1 = xegpu.create_tdesc %src, %cst : ui64, vector<4xindex> -> !xegpu.tensor_desc<4xf32, #xegpu.scatter_tdesc_attr<>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 1]>>
+ return
+}
+
+// -----
+func.func @test_create_tdesc_sg_map_2(%src: ui64) {
+ %cst = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
+ // expected-error at +1 {{TensorDesc's SG map only supports multiple elements contiguous along rows}}
+ %1 = xegpu.create_tdesc %src, %cst : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [1, 4], wi_data = [2, 1]>>
+ return
+}
+
+// -----
+func.func @test_create_tdesc_sg_map_3(%src: ui64) {
+ %cst = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
+ // expected-error at +1 {{TensorDesc's chunkSize must match WI's data mapping}}
+ %1 = xegpu.create_tdesc %src, %cst : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x3xf32, #xegpu.scatter_tdesc_attr<chunk_size = 3>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>
+ return
+}
+
+// -----
+func.func @test_load_gather_sg_map_1(%src: ui64) {
+ %0 = arith.constant dense<1>: vector<4xi1>
+ %cst = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
+ %1 = xegpu.create_tdesc %src, %cst : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>
+ // expected-error at +1 {{Unexpected result shape(Expected shape: [2, 1], Given shape: [1, 2])}}
+ %2 = xegpu.load %1, %0 <{l1_hint = #xegpu.cache_hint<cached>, transpose}> : !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>, vector<4xi1> -> vector<1x2xf32>
+ return
+}
+
+// -----
+func.func @test_load_gather_sg_map_2(%src: ui64) {
+ %0 = arith.constant dense<1>: vector<4xi1>
+ %cst = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
+ %1 = xegpu.create_tdesc %src, %cst : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>
+ // expected-error at +1 {{Unexpected result shape(Expected shape: [2, 1], Given shape: [2])}}
+ %2 = xegpu.load %1, %0 <{l1_hint = #xegpu.cache_hint<cached>, transpose}> : !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>, vector<4xi1> -> vector<2xf32>
+ return
+}
+
+// -----
+func.func @test_load_gather_sg_map_3(%src: ui64) {
+ %0 = arith.constant dense<1>: vector<4xi1>
+ %cst = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
+ %1 = xegpu.create_tdesc %src, %cst : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>
+ // expected-error at +1 {{Chunk size, vector size and wi_data must match}}
+ %2 = xegpu.load %1, %0 <{l1_hint = #xegpu.cache_hint<cached>, transpose}> : !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>, vector<4xi1> -> vector<1xf32>
+ return
+}
+
+
+// -----
+func.func @test_store_scatter_sg_map_1(%src: ui64) {
+ %0 = arith.constant dense<1>: vector<4xi1>
+ %cst = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
+ %val = arith.constant dense<2.9>: vector<1x2xf32>
+ %1 = xegpu.create_tdesc %src, %cst : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>
+ // expected-error at +1 {{Unexpected value shape(Expected shape: [2, 1], Given shape: [1, 2])}}
+ xegpu.store %val, %1, %0 <{l1_hint = #xegpu.cache_hint<cached>, transpose}> : vector<1x2xf32>, !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>, vector<4xi1>
+ return
+}
+
+// -----
+func.func @test_store_scatter_sg_map_2(%src: ui64) {
+ %0 = arith.constant dense<1>: vector<4xi1>
+ %cst = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
+ %val = arith.constant dense<2.9>: vector<2xf32>
+ %1 = xegpu.create_tdesc %src, %cst : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>
+ // expected-error at +1 {{Unexpected value shape(Expected shape: [2, 1], Given shape: [2])}}
+ xegpu.store %val, %1, %0 <{l1_hint = #xegpu.cache_hint<cached>, transpose}> : vector<2xf32>, !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>, vector<4xi1>
+ return
+}
+
// -----
func.func @test_load_gather_vc_1(%src: memref<24x32xf16>) {
%0 = arith.constant dense<1>: vector<4xi1>
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