update alloc usage (#45654)

paddle/fluid/operators/fused/fused_gemm_epilogue_op.cu

@@ -150,8 +150,10 @@ class FusedGemmEpilogueKernel : public framework::OpKernel<T> {
     // "enough". I just followed the settings from the NVIDIA MLPerf BERT code.
     size_t workspace_size = static_cast<size_t>(4) * 1024 * 1024;
     cudaStream_t stream = dev_ctx.stream();
-    memory::allocation::AllocationPtr workspace =
-        memory::Alloc(dev_ctx, workspace_size);
+    memory::allocation::AllocationPtr workspace = memory::Alloc(
+        dev_ctx.GetPlace(),
+        workspace_size,
+        phi::Stream(reinterpret_cast<phi::StreamId>(dev_ctx.stream())));
 
     double alpha64 = 1.0, beta64 = 0.0;
     float alpha32 = 1.0f, beta32 = 0.0f;
@@ -486,7 +488,10 @@ class FusedGemmEpilogueGradKernel : public framework::OpKernel<T> {
                 sizeof(aux_ld)));
       }
 
-      auto dx_workspace = memory::Alloc(dev_ctx, workspace_size);
+      auto dx_workspace = memory::Alloc(
+          dev_ctx.GetPlace(),
+          workspace_size,
+          phi::Stream(reinterpret_cast<phi::StreamId>(dev_ctx.stream())));
 
       auto* dx_data = dx->mutable_data<T>(ctx.GetPlace());
       const auto* y_data = y->data<T>();
@@ -605,7 +610,10 @@ class FusedGemmEpilogueGradKernel : public framework::OpKernel<T> {
                 sizeof(dbias_data)));
       }
 
-      auto dy_workspace = memory::Alloc(dev_ctx, workspace_size);
+      auto dy_workspace = memory::Alloc(
+          dev_ctx.GetPlace(),
+          workspace_size,
+          phi::Stream(reinterpret_cast<phi::StreamId>(dev_ctx.stream())));
       auto* dy_data = dy->mutable_data<T>(ctx.GetPlace());
       const auto* dout_data = dout->data<T>();
       const auto* x_data = x->data<T>();

paddle/fluid/operators/math/eigen_values_vectors.h

@@ -207,7 +207,10 @@ struct MatrixEighFunctor<phi::GPUContext, T> {
     auto vector_stride = dims[dim_size - 1] * dims[dim_size - 2];
     auto values_stride = dims[dim_size - 1];
     int lwork = 0;
-    auto info = memory::Alloc(dev_ctx, sizeof(int) * batch_size);
+    auto info = memory::Alloc(
+        dev_ctx.GetPlace(),
+        sizeof(int) * batch_size,
+        phi::Stream(reinterpret_cast<phi::StreamId>(dev_ctx.stream())));
     auto *info_ptr = reinterpret_cast<int *>(info->ptr());
 
     // When the input type is float32, and the feature value input dimension is
@@ -240,7 +243,10 @@ struct MatrixEighFunctor<phi::GPUContext, T> {
                 out_value,
                 &lwork);
     }
-    auto work = memory::Alloc(dev_ctx, sizeof(T) * lwork);
+    auto work = memory::Alloc(
+        dev_ctx.GetPlace(),
+        sizeof(T) * lwork,
+        phi::Stream(reinterpret_cast<phi::StreamId>(dev_ctx.stream())));
     auto *work_ptr = reinterpret_cast<T *>(work->ptr());
     for (auto i = 0; i < batch_size; i++) {
       auto *input_data = input_vector + i * vector_stride;

paddle/fluid/operators/sparse_attention_op.cu

@@ -522,7 +522,10 @@ void DotSdd(const phi::GPUContext& ctx,
       gpu_type,
       CUSPARSE_SDDMM_ALG_DEFAULT,
       &buffer_size);
-  auto d_buffer_ptr = paddle::memory::Alloc(ctx, buffer_size);
+  auto d_buffer_ptr = paddle::memory::Alloc(
+      ctx.GetPlace(),
+      buffer_size,
+      phi::Stream(reinterpret_cast<phi::StreamId>(ctx.stream())));
   void* d_buffer = static_cast<void*>(d_buffer_ptr->ptr());
 
   platform::dynload::cusparseSDDMM(handle,
@@ -616,7 +619,10 @@ void DotDsd(const phi::GPUContext& ctx,
                                              gpu_type,
                                              CUSPARSE_SPMM_ALG_DEFAULT,
                                              &buffer_size);
-  auto d_buffer_ptr = paddle::memory::Alloc(ctx, buffer_size);
+  auto d_buffer_ptr = paddle::memory::Alloc(
+      ctx.GetPlace(),
+      buffer_size,
+      phi::Stream(reinterpret_cast<phi::StreamId>(ctx.stream())));
   void* d_buffer = static_cast<void*>(d_buffer_ptr->ptr());
 
   platform::dynload::cusparseSpMM(handle,