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qingshui · Jan 12, 2024 · 2809f5f · 2809f5f
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diff --git a/paddle/phi/kernels/gpu/matmul_grad_kernel.cu b/paddle/phi/kernels/gpu/matmul_grad_kernel.cu
@@ -14,60 +14,8 @@ limitations under the License. */
 
 #include "paddle/phi/common/complex.h"
 #include "paddle/phi/core/kernel_registry.h"
-#include "paddle/phi/kernels/funcs/blas/blaslt_impl.cu.h"
 #include "paddle/phi/kernels/impl/matmul_grad_kernel_impl.h"
 #include "paddle/phi/kernels/matmul_grad_kernel.h"
-namespace phi {
-template <>
-void MatMul<phi::GPUContext, float>(const phi::GPUContext& dev_ctx,
-                                    const DenseTensor& a,
-                                    bool trans_a,
-                                    const DenseTensor& b,
-                                    bool trans_b,
-                                    DenseTensor* out) {
-  dev_ctx.template Alloc<float>(out);
-#if (defined(PADDLE_WITH_CUDA) && CUDA_VERSION >= 11060)
-  if (a.dims().size() == 2 && b.dims().size() == 2) {
-    auto& x_dims = a.dims();  // M * K
-    auto& y_dims = b.dims();  // K * N
-    const int M = trans_a ? x_dims[1] : x_dims[0];
-    const int K = trans_a ? x_dims[0] : x_dims[1];
-    const int N = trans_b ? y_dims[0] : y_dims[1];
-    phi::funcs::LinearWithCublasLt<float>::Run(
-        dev_ctx,
-        &a,       // x
-        &b,       // y
-        out,      // out
-        nullptr,  // bias
-        nullptr,
-        M,  // M  bsz_seqf
-        N,  // N  output_size
-        K,  // K  input_size
-        trans_a,
-        trans_b,
-        phi::funcs::MatmulFusedType::kMatmul);
-    return;
-  }
-#endif
-  auto blas = phi::funcs::GetBlas<phi::GPUContext, float>(dev_ctx);
-  auto mat_dim_a = phi::funcs::CreateMatrixDescriptor(a.dims(), 0, trans_a);
-  auto mat_dim_b = phi::funcs::CreateMatrixDescriptor(b.dims(), 0, trans_b);
-  if (a.dims().size() == 3 && b.dims().size() <= 2) {
-    // the transpose_X must be false, if is true, the transpose cost much time
-    if (!trans_a) {
-      mat_dim_a.height_ *= mat_dim_a.batch_size_;
-      mat_dim_a.batch_size_ = 0;
-    }
-  }
-  blas.MatMul(a.data<float>(),
-              mat_dim_a,
-              b.data<float>(),
-              mat_dim_b,
-              static_cast<float>(1),
-              dev_ctx.template Alloc<float>(out),
-              static_cast<float>(false));
-}
-}  // namespace phi
 
 PD_REGISTER_KERNEL(matmul_grad,
                    GPU,

diff --git a/paddle/phi/kernels/gpu/matmul_kernel.cu b/paddle/phi/kernels/gpu/matmul_kernel.cu
@@ -15,48 +15,9 @@ limitations under the License. */
 #include "paddle/phi/backends/gpu/gpu_context.h"
 #include "paddle/phi/common/complex.h"
 #include "paddle/phi/core/kernel_registry.h"
-#include "paddle/phi/kernels/funcs/blas/blaslt_impl.cu.h"
 #include "paddle/phi/kernels/impl/matmul_kernel_impl.h"
 #include "paddle/phi/kernels/matmul_kernel.h"
 
-namespace phi {
-template <>
-void MatMulFunction<phi::GPUContext, float>(const phi::GPUContext& dev_ctx,
-                                            const DenseTensor& X,
-                                            const DenseTensor& Y,
-                                            DenseTensor* Out,
-                                            bool trans_x,
-                                            bool trans_y) {
-#if (defined(PADDLE_WITH_CUDA) && CUDA_VERSION >= 11060)
-  if (X.dims().size() == 2 && Y.dims().size() == 2) {
-    auto& x_dims = X.dims();  // M * K
-    auto& y_dims = Y.dims();  // K * N
-    const int M = trans_x ? x_dims[1] : x_dims[0];
-    const int K = trans_x ? x_dims[0] : x_dims[1];
-    const int N = trans_y ? y_dims[0] : y_dims[1];
-    phi::funcs::LinearWithCublasLt<float>::Run(
-        dev_ctx,
-        &X,       // x
-        &Y,       // y
-        Out,      // out
-        nullptr,  // bias
-        nullptr,
-        M,  // M  bsz_seqf
-        N,  // N  output_size
-        K,  // K  input_size
-        trans_x,
-        trans_y,
-        phi::funcs::MatmulFusedType::kMatmul);
-    return;
-  }
-#endif
-  const std::vector<std::int64_t> x_dims = vectorize(X.dims());
-  const std::vector<std::int64_t> y_dims = vectorize(Y.dims());
-  MatMulFunction<phi::GPUContext, float>(
-      dev_ctx, X, Y, x_dims, y_dims, Out, trans_x, trans_y, false);
-}
-}  // namespace phi
-
 PD_REGISTER_KERNEL(matmul,
                    GPU,
                    ALL_LAYOUT,