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diff --git a/‎paddle/fluid/pir/dialect/operator/interface/infer_symbolic_shape/multiary_infer_sym.cc
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+11Lines changed: 11 additions & 0 deletions b/‎paddle/fluid/pir/dialect/operator/interface/infer_symbolic_shape/multiary_infer_sym.cc
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diff --git a/‎paddle/fluid/pir/dialect/operator/interface/infer_symbolic_shape/multiary_infer_sym.h
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+1Lines changed: 1 addition & 0 deletions b/‎paddle/fluid/pir/dialect/operator/interface/infer_symbolic_shape/multiary_infer_sym.h
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diff --git a/‎paddle/phi/backends/dynload/cusolver.h
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+2Lines changed: 2 additions & 0 deletions b/‎paddle/phi/backends/dynload/cusolver.h
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diff --git a/‎paddle/phi/backends/dynload/lapack.h
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+22Lines changed: 22 additions & 0 deletions b/‎paddle/phi/backends/dynload/lapack.h
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+22Lines changed: 22 additions & 0 deletions
diff --git a/‎paddle/phi/backends/dynload/rocsolver.h
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+2Lines changed: 2 additions & 0 deletions b/‎paddle/phi/backends/dynload/rocsolver.h
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diff --git a/‎paddle/phi/kernels/cpu/lu_solve_grad_kernel.cc
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+23Lines changed: 23 additions & 0 deletions b/‎paddle/phi/kernels/cpu/lu_solve_grad_kernel.cc
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diff --git a/‎paddle/phi/kernels/cpu/lu_solve_kernel.cc
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+82Lines changed: 82 additions & 0 deletions b/‎paddle/phi/kernels/cpu/lu_solve_kernel.cc
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+82Lines changed: 82 additions & 0 deletions
diff --git a/‎paddle/phi/kernels/funcs/lapack/lapack_function.cc
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+27Lines changed: 27 additions & 0 deletions b/‎paddle/phi/kernels/funcs/lapack/lapack_function.cc
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diff --git a/‎paddle/phi/kernels/funcs/lapack/lapack_function.h
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+12Lines changed: 12 additions & 0 deletions b/‎paddle/phi/kernels/funcs/lapack/lapack_function.h
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+12Lines changed: 12 additions & 0 deletions
diff --git a/‎paddle/phi/kernels/gpu/lu_solve_grad_kernel.cu
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+22Lines changed: 22 additions & 0 deletions b/‎paddle/phi/kernels/gpu/lu_solve_grad_kernel.cu
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@@ -3473,6 +3473,17 @@ bool LstmOpInferSymbolicShape(pir::Operation *op,
 
   return true;
 }
+bool LuSolveOpInferSymbolicShape(
+    pir::Operation *op, pir::InferSymbolicShapeContext *infer_context) {
+  const auto &b_shape_or_data =
+      infer_context->GetShapeOrDataForValue(op->operand_source(0));
+  const std::vector<symbol::DimExpr> &b_shape = b_shape_or_data.shape();
+  infer_context->SetShapeOrDataForValue(
+      op->result(0),
+      symbol::ShapeOrDataDimExprs{symbol::TensorShapeOrDataDimExprs(b_shape)});
+
+  return true;
+}
 
 // bool MergedAdamOpInferSymbolicShape(pir::Operation *op,
 //                                     pir::InferSymbolicShapeContext
 
@@ -82,6 +82,7 @@ OP_DECLARE_INFER_SYMBOLIC_SHAPE(LinearInterp)
 OP_DECLARE_INFER_SYMBOLIC_SHAPE(LlmInt8Linear)
 OP_DECLARE_INFER_SYMBOLIC_SHAPE(Logspace)
 OP_DECLARE_INFER_SYMBOLIC_SHAPE(Lstm)
+OP_DECLARE_INFER_SYMBOLIC_SHAPE(LuSolve)
 OP_DECLARE_INFER_SYMBOLIC_SHAPE(MatchMatrixTensor)
 OP_DECLARE_INFER_SYMBOLIC_SHAPE(MaskedMultiheadAttention_)
 // OP_DECLARE_INFER_SYMBOLIC_SHAPE(MergedAdam)
 
@@ -90,6 +90,8 @@ CUSOLVER_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_CUSOLVER_WRAP);
   __macro(cusolverDnSgesvdj);             \
   __macro(cusolverDnDgesvdj);             \
   __macro(cusolverDnSgetrf);              \
+  __macro(cusolverDnSgetrs);              \
+  __macro(cusolverDnDgetrs);              \
   __macro(cusolverDnDgetrf);              \
   __macro(cusolverDnCgetrf);              \
   __macro(cusolverDnZgetrf);              \
 
@@ -29,6 +29,26 @@ extern "C" void dgetrf_(
 extern "C" void sgetrf_(
     int *m, int *n, float *a, int *lda, int *ipiv, int *info);
 
+// getrs_
+extern "C" void sgetrs_(char *trans,
+                        int *n,
+                        int *nrhs,
+                        float *a,
+                        int *lda,
+                        int *ipiv,
+                        float *b,
+                        int *ldb,
+                        int *info);
+extern "C" void dgetrs_(char *trans,
+                        int *n,
+                        int *nrhs,
+                        double *a,
+                        int *lda,
+                        int *ipiv,
+                        double *b,
+                        int *ldb,
+                        int *info);
+
 // evd
 extern "C" void zheevd_(char *jobz,
                         char *uplo,
@@ -339,6 +359,8 @@ extern void *lapack_dso_handle;
 #define LAPACK_ROUTINE_EACH(__macro) \
   __macro(dgetrf_);                  \
   __macro(sgetrf_);                  \
+  __macro(sgetrs_);                  \
+  __macro(dgetrs_);                  \
   __macro(zheevd_);                  \
   __macro(cheevd_);                  \
   __macro(dsyevd_);                  \
 
@@ -45,6 +45,8 @@ extern void *rocsolver_dso_handle;
   __macro(rocsolver_dpotrs);            \
   __macro(rocsolver_cpotrs);            \
   __macro(rocsolver_zpotrs);            \
+  __macro(rocsolver_sgetrs);            \
+  __macro(rocsolver_dgetrs);            \
   __macro(rocsolver_sgetrf);            \
   __macro(rocsolver_dgetrf);            \
   __macro(rocsolver_cgetrf);            \
 
@@ -0,0 +1,23 @@
+// Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     https://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "paddle/phi/backends/cpu/cpu_context.h"
+#include "paddle/phi/core/kernel_registry.h"
+
+#include "paddle/phi/kernels/impl/lu_solve_grad_kernel_impl.h"
+#include "paddle/phi/kernels/lu_solve_grad_kernel.h"
+
+// Register the CPU backward kernel
+PD_REGISTER_KERNEL(
+    lu_solve_grad, CPU, ALL_LAYOUT, phi::LuSolveGradKernel, float, double) {}
@@ -0,0 +1,82 @@
+// Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     https://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "paddle/phi/kernels/lu_solve_kernel.h"
+#include "paddle/phi/backends/cpu/cpu_context.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/funcs/lapack/lapack_function.h"
+#include "paddle/phi/kernels/impl/lu_kernel_impl.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void LuSolveKernel(const Context& dev_ctx,
+                   const DenseTensor& b,
+                   const DenseTensor& lu,
+                   const DenseTensor& pivots,
+                   const std::string& trans,
+                   DenseTensor* out) {
+  // Get lu matrix dimensions
+  auto lu_dims = lu.dims();
+  // Get x matrix dimensions
+  auto x_dims = b.dims();
+
+  // Allocate output tensor
+  dev_ctx.template Alloc<T>(out);
+  // Copy RHS data to output (will be overwritten with solution)
+  *out = Transpose2DTo6D<Context, T>(dev_ctx, b);
+  DenseTensor tem_lu = Transpose2DTo6D<Context, T>(dev_ctx, lu);
+
+  // Prepare LAPACK parameters
+  char trans_char = (trans == "N") ? 'N' : ((trans == "T") ? 'T' : 'C');
+  int n_int = lu_dims[lu_dims.size() - 1];
+  int nrhs_int = x_dims[x_dims.size() - 1];
+  int lda = std::max(1, n_int);  // Leading dimension of A (LU matrix)
+  int ldb = std::max(1, n_int);  // Leading dimension of B (RHS/solution matrix)
+  int info = 0;
+
+  auto outdims = out->dims();
+  auto outrank = outdims.size();
+  int batchsize = product(common::slice_ddim(outdims, 0, outrank - 2));
+  auto out_data = out->data<T>();
+  auto lu_data = tem_lu.data<T>();
+  auto pivots_data =
+      reinterpret_cast<int*>(const_cast<int*>(pivots.data<int>()));
+
+  for (int i = 0; i < batchsize; i++) {
+    auto* out_data_item = &out_data[i * lda * nrhs_int];
+    auto* lu_data_item = &lu_data[i * ldb * n_int];
+    auto* pivots_data_item = &pivots_data[i * n_int];
+    phi::funcs::lapackLuSolve<T>(trans_char,
+                                 n_int,
+                                 nrhs_int,
+                                 lu_data_item,
+                                 lda,
+                                 pivots_data_item,
+                                 out_data_item,
+                                 ldb,
+                                 &info);
+    PADDLE_ENFORCE_EQ(
+        info,
+        0,
+        phi::errors::PreconditionNotMet(
+            "LU solve failed with error code %d. Check if matrix is singular.",
+            info));
+  }
+  *out = Transpose2DTo6D<Context, T>(dev_ctx, *out);
+}
+}  // namespace phi
+
+PD_REGISTER_KERNEL(
+    lu_solve, CPU, ALL_LAYOUT, phi::LuSolveKernel, float, double) {}
@@ -30,6 +30,33 @@ void lapackLu<float>(int m, int n, float *a, int lda, int *ipiv, int *info) {
   dynload::sgetrf_(&m, &n, a, &lda, ipiv, info);
 }
 
+// lu_solve
+template <>
+void lapackLuSolve<double>(char trans,
+                           int n,
+                           int nrhs,
+                           double *a,
+                           int lda,
+                           int *ipiv,
+                           double *b,
+                           int ldb,
+                           int *info) {
+  dynload::dgetrs_(&trans, &n, &nrhs, a, &lda, ipiv, b, &ldb, info);
+}
+
+template <>
+void lapackLuSolve<float>(char trans,
+                          int n,
+                          int nrhs,
+                          float *a,
+                          int lda,
+                          int *ipiv,
+                          float *b,
+                          int ldb,
+                          int *info) {
+  dynload::sgetrs_(&trans, &n, &nrhs, a, &lda, ipiv, b, &ldb, info);
+}
+
 // eigh
 template <>
 void lapackEigh<float>(char jobz,
 
@@ -21,6 +21,18 @@ namespace funcs {
 template <typename T>
 void lapackLu(int m, int n, T *a, int lda, int *ipiv, int *info);
 
+// Lu_solve
+template <typename T>
+void lapackLuSolve(char trans,
+                   int n,
+                   int nrhs,
+                   T *a,
+                   int lda,
+                   int *ipiv,
+                   T *b,
+                   int ldb,
+                   int *info);
+
 // Eigh
 template <typename T, typename ValueType = T>
 void lapackEigh(char jobz,
 
@@ -0,0 +1,22 @@
+// Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     https://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "paddle/phi/backends/gpu/gpu_context.h"
+#include "paddle/phi/core/kernel_registry.h"
+
+#include "paddle/phi/kernels/impl/lu_solve_grad_kernel_impl.h"
+#include "paddle/phi/kernels/lu_solve_grad_kernel.h"
+
+PD_REGISTER_KERNEL(
+    lu_solve_grad, GPU, ALL_LAYOUT, phi::LuSolveGradKernel, float, double) {}