[ROCM] fix softmax_with_cross_entropy_op (#31982)

paddle/fluid/operators/math/cross_entropy.cu

@@ -66,18 +66,23 @@ class CrossEntropyFunctor<platform::CUDADeviceContext, T> {
 
     int batch_size = prob->dims()[0];
     int class_num = prob->dims()[1];
+#ifdef __HIPCC__
+    constexpr int kMaxBlockDim = 256;
+#else
+    constexpr int kMaxBlockDim = 512;
+#endif
 
     if (softLabel) {
       const T* label_data = labels->data<T>();
-      int block = class_num > 512
-                      ? 512
+      int block = class_num > kMaxBlockDim
+                      ? kMaxBlockDim
                       : pow(2, static_cast<int>(std::log2(class_num)));
 
       SoftCrossEntropyKernel<T><<<batch_size, block, 0, ctx.stream()>>>(
           loss_data, prob_data, label_data, class_num);
     } else {
       const int64_t* label_data = labels->data<int64_t>();
-      int block = 512;
+      int block = kMaxBlockDim;
       int grid = (batch_size + block - 1) / block;
       CrossEntropyKernel<T><<<grid, block, 0, ctx.stream()>>>(
           loss_data, prob_data, label_data, batch_size, class_num,

paddle/fluid/operators/math/softmax.cu

@@ -54,10 +54,11 @@ void SoftmaxCUDNNFunctor<T>::operator()(
       xDesc.descriptor<T>(layout, cudnn_tensor_dims);
   miopenTensorDescriptor_t cudnn_y_desc =
       xDesc.descriptor<T>(layout, cudnn_tensor_dims);
-  PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::miopenSoftmaxForward(
+  PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::miopenSoftmaxForward_V2(
       context.cudnn_handle(), CudnnDataType<T>::kOne(), cudnn_x_desc,
       X->data<T>(), CudnnDataType<T>::kZero(), cudnn_y_desc,
-      Y->mutable_data<T>(context.GetPlace())));
+      Y->mutable_data<T>(context.GetPlace()), MIOPEN_SOFTMAX_ACCURATE,
+      MIOPEN_SOFTMAX_MODE_INSTANCE));
 #else
   cudnnTensorDescriptor_t cudnn_x_desc =
       xDesc.descriptor<T>(layout, cudnn_tensor_dims);
@@ -96,11 +97,12 @@ void SoftmaxGradCUDNNFunctor<T>::operator()(
       dxDesc.descriptor<T>(layout, cudnn_tensor_dims);
   miopenTensorDescriptor_t cudnn_ygrad_desc =
       dyDesc.descriptor<T>(layout, cudnn_tensor_dims);
-  PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::miopenSoftmaxBackward(
+  PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::miopenSoftmaxBackward_V2(
       context.cudnn_handle(), CudnnDataType<T>::kOne(), cudnn_y_desc,
       Y->data<T>(), cudnn_ygrad_desc, YGrad->data<T>(),
       CudnnDataType<T>::kZero(), cudnn_xgrad_desc,
-      XGrad->mutable_data<T>(context.GetPlace())));
+      XGrad->mutable_data<T>(context.GetPlace()), MIOPEN_SOFTMAX_ACCURATE,
+      MIOPEN_SOFTMAX_MODE_INSTANCE));
 #else
   cudnnTensorDescriptor_t cudnn_y_desc =
       yDesc.descriptor<T>(layout, cudnn_tensor_dims);

paddle/fluid/operators/softmax_with_cross_entropy_op.cu

@@ -672,7 +672,11 @@ template <typename T>
 static void SoftmaxWithCrossEntropyFusedKernel(
     const T* logits_data, const T* labels_data, T* softmax_data, T* loss_data,
     int64_t n, int64_t d, int axis_dim, gpuStream_t stream) {
+#ifdef __HIPCC__
+  constexpr int kMaxBlockDim = 256;
+#else
   constexpr int kMaxBlockDim = 512;
+#endif
   int64_t block_dim = axis_dim >= kMaxBlockDim
                           ? kMaxBlockDim
                           : (1 << static_cast<int>(std::log2(axis_dim)));

paddle/fluid/platform/dynload/miopen.h

@@ -116,7 +116,9 @@ extern void EnforceCUDNNLoaded(const char* fn_name);
   __macro(miopenPoolingForward);                          \
   __macro(miopenPoolingBackward);                         \
   __macro(miopenSoftmaxBackward);                         \
+  __macro(miopenSoftmaxBackward_V2);                      \
   __macro(miopenSoftmaxForward);                          \
+  __macro(miopenSoftmaxForward_V2);                       \
   __macro(miopenCreateDropoutDescriptor);                 \
   __macro(miopenDestroyDropoutDescriptor);                \
   __macro(miopenRestoreDropoutDescriptor);                \