PaddlePaddle
diff --git a/‎paddle/fluid/platform/device/gpu/gpu_info.cc
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+1Lines changed: 1 addition & 0 deletions b/‎paddle/fluid/platform/device/gpu/gpu_info.cc
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+1Lines changed: 1 addition & 0 deletions
diff --git a/‎paddle/phi/core/visit_type.h
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+1-1Lines changed: 1 addition & 1 deletion b/‎paddle/phi/core/visit_type.h
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+1-1Lines changed: 1 addition & 1 deletion
diff --git a/‎paddle/phi/kernels/CMakeLists.txt
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-2Lines changed: 0 additions & 2 deletions b/‎paddle/phi/kernels/CMakeLists.txt
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diff --git a/‎paddle/phi/kernels/funcs/dropout_impl.cu.h
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+9-17Lines changed: 9 additions & 17 deletions b/‎paddle/phi/kernels/funcs/dropout_impl.cu.h
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+9-17Lines changed: 9 additions & 17 deletions
diff --git a/‎paddle/phi/kernels/funcs/layer_norm_impl.cu.h
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+21-3Lines changed: 21 additions & 3 deletions b/‎paddle/phi/kernels/funcs/layer_norm_impl.cu.h
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+21-3Lines changed: 21 additions & 3 deletions
diff --git a/‎paddle/phi/kernels/fusion/gpu/fused_bias_dropout_residual_layer_norm_grad_kernel.cu
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+15-8Lines changed: 15 additions & 8 deletions b/‎paddle/phi/kernels/fusion/gpu/fused_bias_dropout_residual_layer_norm_grad_kernel.cu
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+15-8Lines changed: 15 additions & 8 deletions
diff --git a/‎paddle/phi/kernels/fusion/gpu/fused_bias_dropout_residual_layer_norm_kernel.cu
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+11-7Lines changed: 11 additions & 7 deletions b/‎paddle/phi/kernels/fusion/gpu/fused_bias_dropout_residual_layer_norm_kernel.cu
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+11-7Lines changed: 11 additions & 7 deletions
diff --git a/‎paddle/phi/kernels/fusion/gpu/fused_dropout_act_bias.h
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+6-2Lines changed: 6 additions & 2 deletions b/‎paddle/phi/kernels/fusion/gpu/fused_dropout_act_bias.h
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+6-2Lines changed: 6 additions & 2 deletions
diff --git a/‎paddle/phi/kernels/fusion/gpu/fused_dropout_add_grad_kernel.cu
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+4-13Lines changed: 4 additions & 13 deletions b/‎paddle/phi/kernels/fusion/gpu/fused_dropout_add_grad_kernel.cu
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+4-13Lines changed: 4 additions & 13 deletions
diff --git a/‎paddle/phi/kernels/fusion/gpu/fused_dropout_add_kernel.cu
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+4-13Lines changed: 4 additions & 13 deletions b/‎paddle/phi/kernels/fusion/gpu/fused_dropout_add_kernel.cu
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+4-13Lines changed: 4 additions & 13 deletions
@@ -217,6 +217,7 @@ class RecordedGpuMallocHelper {
     CUDADeviceGuard guard(dev_id_);
     gpuError_t result;
 #ifdef PADDLE_WITH_HIP
+    phi::backends::gpu::CUDAGraphCaptureModeGuard capture_mode_guard;
     if (UNLIKELY(malloc_managed_memory)) {
       result = hipMallocManaged(ptr, size);
     } else {
 
@@ -355,7 +355,7 @@ namespace phi {
                  "`");                                                        \
     }                                                                         \
   }()
-#if defined(PADDLE_WITH_XPU) || defined(PADDLE_WITH_HIP)
+#if defined(PADDLE_WITH_XPU)
 #define PD_VISIT_ALL_TYPES(TYPE, NAME, ...)                                    \
   [&] {                                                                        \
     const auto& __dtype__ = TYPE;                                              \
 
@@ -209,11 +209,9 @@ if(WITH_ROCM)
     "gpu/lu_kernel.cu"
     "gpu/matrix_rank_kernel.cu"
     "gpu/matrix_rank_tol_kernel.cu"
-    "gpu/multiclass_nms3_kernel.cu"
     "gpu/put_along_axis_grad_kernel.cu"
     "gpu/put_along_axis_kernel.cu"
     "gpu/qr_kernel.cu"
-    "gpu/rms_norm_grad_kernel.cu"
     "gpu/svd_kernel.cu"
     "gpudnn/mha_cudnn_frontend.cu"
     "fusion/gpu/block_multi_head_attention_kernel.cu"
 
@@ -349,19 +349,6 @@ void DropoutFwGPUKernelDriver(
     } else {
       bool copy_in_kernel = GetSeedDataAndIncrement(
           dev_ctx, seed, is_fix_seed, seed_val, offset, &seed_data, &increment);
-#ifdef PADDLE_WITH_HIP
-      VectorizedRandomGenerator<T>
-          <<<grid_size, block_size, 0, stream>>>(0,
-                                                 size,
-                                                 seed_data,
-                                                 dropout_prob,
-                                                 x_data,
-                                                 mask_data,
-                                                 y_data,
-                                                 upscale_in_train,
-                                                 increment,
-                                                 main_offset);
-#else
       const phi::GPUContext* dev_ctx_p = &dev_ctx;
       auto gen_cuda = dev_ctx.GetGenerator();
       auto state_index = gen_cuda->GetStateIndex();
@@ -370,10 +357,11 @@ void DropoutFwGPUKernelDriver(
           parameterSetter = [offset, dev_ctx_p, state_index, is_fix_seed](
                                 phi::backends::gpu::gpuKernelParams& params) {
             if (!is_fix_seed) {
-              // we assume seed is null pointer
-              // seed copy to cpu is meaningless here
+          // we assume seed is null pointer
+          // seed copy to cpu is meaningless here
+#ifndef PADDLE_WITH_HIP
               assert(seed_tensor_ptr == nullptr);
-
+#endif
               auto gen_cuda = dev_ctx_p->GetGenerator();
               // ensure the generator use correct state index
               gen_cuda->SetStateIndex(state_index);
@@ -393,9 +381,14 @@ void DropoutFwGPUKernelDriver(
           cudaKernelCallback = [=](unsigned int id) {
             void* functionPtr =
                 reinterpret_cast<void*>(&(VectorizedRandomGenerator<T>));
+#ifdef PADDLE_WITH_HIP
+            hipFunction_t cudaFunc =
+                reinterpret_cast<hipFunction_t>(functionPtr);
+#else
             cudaFunction_t cudaFunc;
             PADDLE_ENFORCE_GPU_SUCCESS(
                 cudaGetFuncBySymbol(&cudaFunc, functionPtr));
+#endif
             VLOG(10) << "[cudaKernelCallback] cudaFunc = " << cudaFunc
                      << " functionPtr = " << functionPtr;
 
@@ -417,7 +410,6 @@ void DropoutFwGPUKernelDriver(
 
       VLOG(10) << "NON_CUDA_GRAPH seed = " << seed_data
                << ", increment = " << increment;
-#endif
     }
   } else {
     if (upscale_in_train) {
 
@@ -166,14 +166,14 @@ __inline__ __device__ double rsqrt_(const double val) {
   return ::rsqrt(val);
 }
 
-#if CUDA_ARCH_FP16_SUPPORTED(__CUDA_ARCH__)
+#if CUDA_ARCH_FP16_SUPPORTED(__CUDA_ARCH__) || defined(PADDLE_WITH_HIP)
 template <>
 __inline__ __device__ half rsqrt_(const half val) {
   return hrsqrt(val);
 }
 #endif
 
-#ifdef PADDLE_WITH_CUDA
+#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
 template <typename T,
           typename U,
           typename ScaleT = U,
@@ -254,7 +254,11 @@ __global__ __launch_bounds__(THREADS_PER_CTA) void fast_ln_fwd_kernel(
 
 #pragma unroll
     for (int it = 1; it < THREADS_PER_WARP; it *= 2) {
+#ifdef PADDLE_WITH_HIP
+      mu_local += __shfl_xor(mu_local, it);
+#else
       mu_local += __shfl_xor_sync(uint32_t(-1), mu_local, it);
+#endif
     }
     if (WARPS_N > 1) {
       if (lane == 0) {
@@ -290,7 +294,11 @@ __global__ __launch_bounds__(THREADS_PER_CTA) void fast_ln_fwd_kernel(
 
 #pragma unroll
     for (int it = 1; it < THREADS_PER_WARP; it *= 2) {
+#ifdef PADDLE_WITH_HIP
+      var_local += __shfl_xor(var_local, it);
+#else
       var_local += __shfl_xor_sync(uint32_t(-1), var_local, it);
+#endif
     }
 
     if (WARPS_N > 1) {
@@ -546,7 +554,7 @@ __inline__ __device__ void cuLoadAddStridedInputs(const int64_t i1_block,
   }
 }
 
-#ifdef PADDLE_WITH_CUDA
+#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
 template <bool IsFusedDropoutResidualLn,
           bool NeedDDropoutSrcPtr,
           typename T,
@@ -678,16 +686,26 @@ __global__ __launch_bounds__(THREADS_PER_CTA) void fused_ln_bwd_fast_kernel(
 #pragma unroll
       // row reduction among 32 threads.
       for (int it = 1; it < THREADS_PER_WARP; it *= 2) {
+#ifdef PADDLE_WITH_HIP
+        sum_loss1 += __shfl_xor(sum_loss1, it);
+        sum_loss2 += __shfl_xor(sum_loss2, it);
+#else
         sum_loss1 += __shfl_xor_sync(uint32_t(-1), sum_loss1, it);
         sum_loss2 += __shfl_xor_sync(uint32_t(-1), sum_loss2, it);
+#endif
       }
       sum_loss1 *= rn;
       sum_loss2 *= rn;
     } else {
 #pragma unroll
       for (int it = 16; it > 0; it /= 2) {
+#ifdef PADDLE_WITH_HIP
+        sum_loss1 += __shfl_down(sum_loss1, it);
+        sum_loss2 += __shfl_down(sum_loss2, it);
+#else
         sum_loss1 += __shfl_down_sync(uint32_t(-1), sum_loss1, it);
         sum_loss2 += __shfl_down_sync(uint32_t(-1), sum_loss2, it);
+#endif
       }
 
       if (lane == 0) {
 
@@ -11,7 +11,12 @@
 // 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.
-#ifndef PADDLE_WITH_HIP
+#ifdef PADDLE_WITH_HIP
+#include <hip/hip_fp16.h>
+#include <hip/hip_runtime.h>
+#include <hipcub/hipcub.hpp>
+namespace cub = hipcub;
+#else
 #include <cuda_fp16.h>
 #include <cub/cub.cuh>
 #endif
@@ -21,9 +26,7 @@
 #include "paddle/phi/core/kernel_registry.h"
 #include "paddle/phi/core/tensor_utils.h"
 #include "paddle/phi/kernels/funcs/layer_norm_impl.cu.h"
-#ifndef PADDLE_WITH_HIP
 #include "paddle/phi/kernels/fusion/gpu/fused_dropout_helper.h"
-#endif
 
 namespace phi {
 namespace fusion {
@@ -51,7 +54,6 @@ void FusedBiasDropoutResidualLnGradKernel(
     DenseTensor* bias_grad,
     DenseTensor* ln_scale_grad,
     DenseTensor* ln_bias_grad) {
-#ifndef PADDLE_WITH_HIP
   using U = LayerNormParamType<T>;
   auto* d_y_data = y_grad.data<T>();
   auto* ln_scale_data =
@@ -114,19 +116,24 @@ void FusedBiasDropoutResidualLnGradKernel(
       d_x_data,
       d_bias_data,
       d_residual_data);
-#else
-  PADDLE_THROW(phi::errors::Unimplemented(
-      "FusedBiasDropoutResidualLnGradKernel not surpport for rocm"));
-#endif
 }
 
 }  // namespace fusion
 }  // namespace phi
 
+#ifdef PADDLE_WITH_HIP
+PD_REGISTER_KERNEL(fused_bias_dropout_residual_layer_norm_grad,
+                   GPU,
+                   ALL_LAYOUT,
+                   phi::fusion::FusedBiasDropoutResidualLnGradKernel,
+                   float,
+                   phi::dtype::float16) {}
+#else
 PD_REGISTER_KERNEL(fused_bias_dropout_residual_layer_norm_grad,
                    GPU,
                    ALL_LAYOUT,
                    phi::fusion::FusedBiasDropoutResidualLnGradKernel,
                    float,
                    double,
                    phi::dtype::float16) {}
+#endif
@@ -17,9 +17,7 @@
 #include "paddle/phi/core/kernel_registry.h"
 #include "paddle/phi/core/tensor_utils.h"
 #include "paddle/phi/kernels/funcs/layer_norm_impl.cu.h"
-#ifndef PADDLE_WITH_HIP
 #include "paddle/phi/kernels/fusion/gpu/fused_dropout_helper.h"
-#endif
 
 namespace phi {
 namespace fusion {
@@ -42,7 +40,6 @@ void FusedBiasDropoutResidualLnKernel(
     DenseTensor* dropout_mask_out,
     DenseTensor* ln_mean,
     DenseTensor* ln_variance) {
-#ifndef PADDLE_WITH_HIP
   using U = phi::funcs::LayerNormParamType<T>;
   auto* x_data = x.data<T>();
   auto* bias_data = (bias.get_ptr() == nullptr) ? nullptr : bias->data<T>();
@@ -95,14 +92,20 @@ void FusedBiasDropoutResidualLnKernel(
       y_data,
       ln_mean_data,
       ln_var_data);
-#else
-  PADDLE_THROW(phi::errors::Unimplemented(
-      "FusedBiasDropoutResidualLnKernel not support for rocm"));
-#endif
 }
 }  // namespace fusion
 }  // namespace phi
 
+#ifdef PADDLE_WITH_HIP
+PD_REGISTER_KERNEL(fused_bias_dropout_residual_layer_norm,
+                   GPU,
+                   ALL_LAYOUT,
+                   phi::fusion::FusedBiasDropoutResidualLnKernel,
+                   float,
+                   phi::dtype::float16) {
+  kernel->OutputAt(1).SetDataType(phi::DataType::UINT8);
+}
+#else
 PD_REGISTER_KERNEL(fused_bias_dropout_residual_layer_norm,
                    GPU,
                    ALL_LAYOUT,
@@ -112,3 +115,4 @@ PD_REGISTER_KERNEL(fused_bias_dropout_residual_layer_norm,
                    phi::dtype::float16) {
   kernel->OutputAt(1).SetDataType(phi::DataType::UINT8);
 }
+#endif
@@ -35,7 +35,11 @@ struct GeluFunctor {
 template <typename T>
 struct FastGeluFunctor {
   inline __device__ T operator()(const T x) const {
+#ifdef PADDLE_WITH_HIP
+    assert(0 && "ROCM does not support FastGelu");
+#else
     return phi::GeluFwd<T, true>(x);
+#endif
   }
 };
 
@@ -92,8 +96,8 @@ __global__ void FusedDropoutActBias(
   int row_id = blockIdx.y;
   int idx = row_id * cols + col_id;
 
-  curandStatePhilox4_32_10_t state;
-  curand_init(seed, idx, increment, &state);
+  GPURAND(StatePhilox4_32_10_t) state;
+  GPURAND(_init)(seed, idx, increment, &state);
 
   const T factor =
       phi::fusion::GetFactor<T>(dropout_prob, is_upscale_in_train, is_test);
 
@@ -202,18 +202,6 @@ void FusedDropoutAddGradKernel(const Context& dev_ctx,
                        ? NoMaskBwFunctor<T, float>(1.0f - dropout_rate)
                        : NoMaskBwFunctor<T, float>(1.0f - dropout_rate, 1.0f);
 
-#ifdef PADDLE_WITH_HIP
-    VectorizedDropoutBackward<T, NoMaskBwFunctor<T, float>>
-        <<<grid_size, block_size, 0, stream>>>(0,
-                                               numel,
-                                               seed_data,  //  idx: 2 need save
-                                               x_grad_data,
-                                               y_grad_data,
-                                               out_grad_data,
-                                               increment,  //  idx: 6 need save
-                                               main_offset,
-                                               functor);
-#else
     // we assume seed/offset is same across iterations
     // seed_offset_data should preserved by cudaGraph pool
     const phi::GPUContext* dev_ctx_p = &dev_ctx;
@@ -233,9 +221,13 @@ void FusedDropoutAddGradKernel(const Context& dev_ctx,
         cudaKernelCallback = [=](unsigned int id) {
           void* functionPtr = reinterpret_cast<void*>(
               &(VectorizedDropoutBackward<T, NoMaskBwFunctor<T, float>>));
+#ifdef PADDLE_WITH_HIP
+          hipFunction_t cudaFunc = reinterpret_cast<hipFunction_t>(functionPtr);
+#else
           cudaFunction_t cudaFunc;
           PADDLE_ENFORCE_GPU_SUCCESS(
               cudaGetFuncBySymbol(&cudaFunc, functionPtr));
+#endif
           VLOG(10) << "[cudaKernelCallback] cudaFunc = " << cudaFunc
                    << " functionPtr = " << functionPtr;
 
@@ -257,7 +249,6 @@ void FusedDropoutAddGradKernel(const Context& dev_ctx,
 
     VLOG(10) << "NON_CUDA_GRAPH seed = " << seed_data
              << ", increment = " << increment;
-#endif
   }
 }
 
 
@@ -186,18 +186,6 @@ void FusedDropoutAddKernel(const Context& dev_ctx,
     auto dst_functor =
         NoMaskFwFunctor<T, float>(1.0f - dropout_rate, upscale_in_train);
 
-#ifdef PADDLE_WITH_HIP
-    VectorizedDropoutForward<T, NoMaskFwFunctor<T, float>>
-        <<<grid_size, block_size, 0, stream>>>(0,
-                                               numel,
-                                               seed_data,  // need save
-                                               x_data,
-                                               y_data,
-                                               out_data,
-                                               increment,  // need save
-                                               main_offset,
-                                               dst_functor);
-#else
     // we assume seed/offset is same across iterations
     // seed_offset_data should preserved by cudaGraph pool
     const phi::GPUContext* dev_ctx_p = &dev_ctx;
@@ -237,9 +225,13 @@ void FusedDropoutAddKernel(const Context& dev_ctx,
         cudaKernelCallback = [=](unsigned int id) {
           void* functionPtr = reinterpret_cast<void*>(
               &(VectorizedDropoutForward<T, NoMaskFwFunctor<T, float>>));
+#ifdef PADDLE_WITH_HIP
+          hipFunction_t cudaFunc = reinterpret_cast<hipFunction_t>(functionPtr);
+#else
           cudaFunction_t cudaFunc;
           PADDLE_ENFORCE_GPU_SUCCESS(
               cudaGetFuncBySymbol(&cudaFunc, functionPtr));
+#endif
           VLOG(10) << "[cudaKernelCallback] cudaFunc = " << cudaFunc
                    << " functionPtr = " << functionPtr;
 
@@ -260,7 +252,6 @@ void FusedDropoutAddKernel(const Context& dev_ctx,
 
     VLOG(10) << "NON_CUDA_GRAPH seed = " << seed_data
              << ", increment = " << increment;
-#endif
   } else {
     using MT = typename phi::dtype::MPTypeTrait<T>::Type;
     MT factor = static_cast<MT>(1.0f - dropout_rate);