Replace framework:: DDim [fluid_ops] DDim (#66370)

co63oc · web-flow · commit b784ccb73378 · 2024-07-24T10:16:24.000+08:00
diff --git a/paddle/fluid/distributed/fleet_executor/dist_model.cc b/paddle/fluid/distributed/fleet_executor/dist_model.cc
@@ -46,7 +46,7 @@ bool LoadDataFromDistModelTensor(const DistModelTensor &input_data,
                                  phi::DenseTensor *input_tensor,
                                  const phi::Place &place) {
   VLOG(3) << "Loading data from DistModelTensor for " << input_data.name;
-  framework::DDim dims = common::make_ddim(input_data.shape);
+  phi::DDim dims = common::make_ddim(input_data.shape);
   void *input_tensor_ptr = nullptr;
   if (input_data.dtype == DistModelDataType::INT64) {
     input_tensor_ptr = input_tensor->mutable_data<int64_t>(dims, place);
diff --git a/paddle/fluid/distributed/test/brpc_service_dense_sgd_test.cc b/paddle/fluid/distributed/test/brpc_service_dense_sgd_test.cc
@@ -54,8 +54,7 @@ void InitTensorsOnClient(framework::Scope* scope,
   CreateVarsOnScope(scope, place);
 
   auto x_var = scope->Var("x")->GetMutable<phi::DenseTensor>();
-  float* x_ptr =
-      x_var->mutable_data<float>(framework::DDim({1, rows_numel}), *place);
+  float* x_ptr = x_var->mutable_data<float>(phi::DDim({1, rows_numel}), *place);
   for (int64_t i = 0; i < rows_numel; ++i)
     x_ptr[i] = static_cast<float>(1.0) * static_cast<float>(i);
 }
diff --git a/paddle/fluid/distributed/test/brpc_service_sparse_sgd_test.cc b/paddle/fluid/distributed/test/brpc_service_sparse_sgd_test.cc
@@ -57,15 +57,13 @@ void InitTensorsOnClient(framework::Scope* scope,
   CreateVarsOnScope(scope, place);
 
   auto x_var = scope->Var("x")->GetMutable<phi::DenseTensor>();
-  float* x_ptr =
-      x_var->mutable_data<float>(framework::DDim({1, rows_numel}), *place);
+  float* x_ptr = x_var->mutable_data<float>(phi::DDim({1, rows_numel}), *place);
   for (int64_t i = 0; i < rows_numel; ++i) x_ptr[i] = 1.0;
 
   auto g_size = rows_numel +
                 30;  // hard code here: key_num * (fea_dim + 3), show/clk/slot
   auto x_g_var = scope->Var("x@GRAD")->GetMutable<phi::DenseTensor>();
-  float* x_g_ptr =
-      x_g_var->mutable_data<float>(framework::DDim({1, g_size}), *place);
+  float* x_g_ptr = x_g_var->mutable_data<float>(phi::DDim({1, g_size}), *place);
   for (int64_t i = 0; i < g_size; ++i) x_g_ptr[i] = 1.0;
 }
 
diff --git a/paddle/fluid/framework/lod_tensor.cc b/paddle/fluid/framework/lod_tensor.cc
@@ -429,7 +429,7 @@ void MergeLoDTensor(phi::DenseTensor *target,
       false,
       phi::errors::InvalidArgument("The LoDTensors to be merged are empty."));
 
-  framework::DDim new_dim = lod_tensors[0]->dims();
+  phi::DDim new_dim = lod_tensors[0]->dims();
   proto::VarType::Type new_type = proto::VarType::FP32;
   phi::DataLayout new_layout = lod_tensors[0]->layout();
   for (auto *t : lod_tensors) {
diff --git a/paddle/fluid/framework/new_executor/collect_shape_manager.cc b/paddle/fluid/framework/new_executor/collect_shape_manager.cc
@@ -46,7 +46,7 @@ void CollectShapeManager::CollectShapeInfo(
 #endif
 #endif
 
-    framework::DDim dim = tensor.dims();
+    phi::DDim dim = tensor.dims();
     std::vector<int32_t> shape(dim.size());
     for (int i = 0; i < static_cast<int>(shape.size()); ++i)
       shape[i] = static_cast<int32_t>(dim[i]);
diff --git a/paddle/fluid/framework/operator.h b/paddle/fluid/framework/operator.h
@@ -590,7 +590,7 @@ class ExecutionContext : public phi::KernelContext {
 #endif
 
   template <typename T, typename DevContext>
-  phi::DenseTensor AllocateTmpTensor(const framework::DDim& dim,
+  phi::DenseTensor AllocateTmpTensor(const phi::DDim& dim,
                                      const DevContext& dev_ctx) const {
     phi::DenseTensor tmp;
     tmp.Resize(dim);
diff --git a/paddle/fluid/framework/tensor_util.cc b/paddle/fluid/framework/tensor_util.cc
@@ -803,7 +803,7 @@ void TensorFromDLPack(const ::DLTensor& dl_tensor, phi::DenseTensor* dst) {
             dl_tensor.shape + dl_tensor.ndim,
             std::back_inserter(vec));
 
-  framework::DDim vddim = common::make_ddim(vec);
+  phi::DDim vddim = common::make_ddim(vec);
 
   dst->Resize(vddim);
   ::DLDataType type = dl_tensor.dtype;
@@ -840,7 +840,7 @@ void TensorFromDLPack(const DLManagedTensor* src, phi::DenseTensor* dst) {
             src->dl_tensor.shape + src->dl_tensor.ndim,
             std::back_inserter(vec));
 
-  framework::DDim vddim = common::make_ddim(vec);
+  phi::DDim vddim = common::make_ddim(vec);
   dst->Resize(vddim);
   ::DLDataType type = src->dl_tensor.dtype;
 
diff --git a/paddle/fluid/imperative/infer_shape_context.h b/paddle/fluid/imperative/infer_shape_context.h
@@ -31,7 +31,7 @@ namespace imperative {
 
 template <typename VarType>
 class DygraphInferShapeContext : public framework::InferShapeContext {
-  using DDim = framework::DDim;
+  using DDim = phi::DDim;
 
  public:
   DygraphInferShapeContext(
diff --git a/paddle/fluid/inference/api/analysis_predictor.cc b/paddle/fluid/inference/api/analysis_predictor.cc
@@ -258,7 +258,7 @@ phi::Backend ConvertBackend(paddle_infer::PlaceType backend) {
 bool PaddleTensorToDenseTensor(const PaddleTensor &pt,
                                phi::DenseTensor *t,
                                const phi::Place &place) {
-  framework::DDim ddim = common::make_ddim(pt.shape);
+  phi::DDim ddim = common::make_ddim(pt.shape);
   void *input_ptr = nullptr;
   if (pt.dtype == PaddleDType::INT64) {
     input_ptr = t->mutable_data<int64_t>(ddim, place);
@@ -2853,7 +2853,7 @@ void AnalysisPredictor::HookCollectShapeRangeInfo() {
     if (!input_tensor.is_dense_tensor()) return;
     auto tensor =
         std::dynamic_pointer_cast<phi::DenseTensor>(input_tensor.impl()).get();
-    framework::DDim dim = tensor->dims();
+    phi::DDim dim = tensor->dims();
     std::vector<int32_t> shape(dim.size());
     for (int i = 0; i < static_cast<int>(shape.size()); ++i)
       shape[i] = static_cast<int32_t>(dim[i]);
diff --git a/paddle/fluid/inference/api/api_impl.cc b/paddle/fluid/inference/api/api_impl.cc
@@ -213,7 +213,7 @@ bool NativePaddlePredictor::SetFeed(const std::vector<PaddleTensor> &inputs,
 
   for (size_t i = 0; i < inputs.size(); ++i) {
     auto &input = feed_tensors_[i];
-    framework::DDim ddim = common::make_ddim(inputs[i].shape);
+    phi::DDim ddim = common::make_ddim(inputs[i].shape);
     void *input_ptr = nullptr;
     if (inputs[i].dtype == PaddleDType::INT64) {
       input_ptr = input.mutable_data<int64_t>(ddim, place_);
diff --git a/paddle/fluid/inference/tensorrt/convert/emb_eltwise_layernorm.cc b/paddle/fluid/inference/tensorrt/convert/emb_eltwise_layernorm.cc
@@ -27,7 +27,7 @@ class EmbEltwiseLayerNormOpConverter : public OpConverter {
     VLOG(4) << "convert EmbEltwiseLayerNorm op to tensorrt layer";
     // get the presistable var's data
     auto GetWeight = [&](const std::string& var_name,
-                         framework::DDim* dim) -> TensorRTEngine::Weight {
+                         phi::DDim* dim) -> TensorRTEngine::Weight {
       auto* temp_var = scope.FindVar(var_name);
       auto* temp_tensor = temp_var->GetMutable<phi::DenseTensor>();
       *dim = temp_tensor->dims();
@@ -48,8 +48,8 @@ class EmbEltwiseLayerNormOpConverter : public OpConverter {
     std::vector<nvinfer1::Weights> input_embs;
     std::vector<int> emb_sizes;
     TensorRTEngine::Weight weight;
-    framework::DDim emb_dims;
-    framework::DDim bias_dims, scale_dims;
+    phi::DDim emb_dims;
+    phi::DDim bias_dims, scale_dims;
     TensorRTEngine::Weight bias_weight, scale_weight;
 
     int64_t bias_size = common::product(bias_dims);
diff --git a/paddle/fluid/inference/tensorrt/convert/group_norm_op.cc b/paddle/fluid/inference/tensorrt/convert/group_norm_op.cc
@@ -42,7 +42,7 @@ class GroupNormOpConverter : public OpConverter {
 
     // get the presistable var's data
     auto GetWeight = [&](const std::string& var_name,
-                         framework::DDim* dims) -> TensorRTEngine::Weight {
+                         phi::DDim* dims) -> TensorRTEngine::Weight {
       auto* temp_var = scope.FindVar(var_name);
       auto* temp_tensor = temp_var->GetMutable<phi::DenseTensor>();
       (*dims) = temp_tensor->dims();
@@ -51,8 +51,8 @@ class GroupNormOpConverter : public OpConverter {
       return weight;
     };
 
-    framework::DDim scale_dims;
-    framework::DDim bias_dims;
+    phi::DDim scale_dims;
+    phi::DDim bias_dims;
     auto scale_weights = GetWeight(scale_name, &scale_dims);
     auto bias_weights = GetWeight(bias_name, &bias_dims);
     bool with_fp16 = engine_->WithFp16() && !engine_->disable_trt_plugin_fp16();
diff --git a/paddle/fluid/inference/tensorrt/convert/preln_emb_eltwise_layernorm.cc b/paddle/fluid/inference/tensorrt/convert/preln_emb_eltwise_layernorm.cc
@@ -25,7 +25,7 @@ class PrelnEmbEltwiseLayerNormOpConverter : public OpConverter {
     VLOG(4) << "convert PrelnEmbEltwiseLayerNorm op to tensorrt layer";
     // get the presistable var's data
     auto GetWeight = [&](const std::string& var_name,
-                         framework::DDim* dim) -> TensorRTEngine::Weight {
+                         phi::DDim* dim) -> TensorRTEngine::Weight {
       auto* temp_var = scope.FindVar(var_name);
       auto* temp_tensor = temp_var->GetMutable<phi::DenseTensor>();
       *dim = temp_tensor->dims();
@@ -56,8 +56,8 @@ class PrelnEmbEltwiseLayerNormOpConverter : public OpConverter {
     std::vector<nvinfer1::Weights> input_embs;
     std::vector<int> emb_sizes;
     TensorRTEngine::Weight weight;
-    framework::DDim emb_dims;
-    framework::DDim bias_dims, scale_dims;
+    phi::DDim emb_dims;
+    phi::DDim bias_dims, scale_dims;
     TensorRTEngine::Weight bias_weight, scale_weight;
 
     int64_t bias_size = common::product(bias_dims);
diff --git a/paddle/fluid/inference/tensorrt/convert/preln_groupnorm_act_op.cc b/paddle/fluid/inference/tensorrt/convert/preln_groupnorm_act_op.cc
@@ -43,7 +43,7 @@ class PrelnGroupnormActOpConverter : public OpConverter {
 
     // get the presistable var's data
     auto GetWeight = [&](const std::string& var_name,
-                         framework::DDim* dims) -> TensorRTEngine::Weight {
+                         phi::DDim* dims) -> TensorRTEngine::Weight {
       auto* temp_var = scope.FindVar(var_name);
       auto* temp_tensor = temp_var->GetMutable<phi::DenseTensor>();
       (*dims) = temp_tensor->dims();
@@ -52,8 +52,8 @@ class PrelnGroupnormActOpConverter : public OpConverter {
       return weight;
     };
 
-    framework::DDim scale_dims;
-    framework::DDim bias_dims;
+    phi::DDim scale_dims;
+    phi::DDim bias_dims;
     auto scale_weights = GetWeight(scale_name, &scale_dims);
     auto bias_weights = GetWeight(bias_name, &bias_dims);
     bool with_fp16 = engine_->WithFp16() && !engine_->disable_trt_plugin_fp16();
diff --git a/paddle/fluid/inference/tensorrt/convert/preln_residual_bias.cc b/paddle/fluid/inference/tensorrt/convert/preln_residual_bias.cc
@@ -34,7 +34,7 @@ class PrelnResidualBiasOpConverter : public OpConverter {
     inputs.push_back(input1);
     inputs.push_back(input2);
     auto get_persistable_data = [&](const std::string& arg_name,
-                                    framework::DDim* dims) -> float* {
+                                    phi::DDim* dims) -> float* {
       std::string var_name = op_desc.Input(arg_name).front();
       auto* temp_var = scope.FindVar(var_name);
       auto* temp_tensor = temp_var->GetMutable<phi::DenseTensor>();
@@ -43,7 +43,7 @@ class PrelnResidualBiasOpConverter : public OpConverter {
           engine_->GetFp32TrtWeight(var_name, *temp_tensor).get().values));
       return temp_data;
     };
-    framework::DDim bias_dims, scale_dims, ele_bias_dims;
+    phi::DDim bias_dims, scale_dims, ele_bias_dims;
     auto* bias = get_persistable_data("LnBias", &bias_dims);
     auto* scale = get_persistable_data("LnScale", &scale_dims);
     auto const& vars = op_desc.Inputs(false);
diff --git a/paddle/fluid/inference/tensorrt/convert/preln_skip_layernorm.cc b/paddle/fluid/inference/tensorrt/convert/preln_skip_layernorm.cc
@@ -40,7 +40,7 @@ class PrelnSkipLayerNormOpConverter : public OpConverter {
     inputs.push_back(input2);
 
     auto get_persistable_data = [&](const std::string& arg_name,
-                                    framework::DDim* dims) -> float* {
+                                    phi::DDim* dims) -> float* {
       std::string var_name = op_desc.Input(arg_name).front();
       auto* temp_var = scope.FindVar(var_name);
       auto* temp_tensor = temp_var->GetMutable<phi::DenseTensor>();
@@ -51,7 +51,7 @@ class PrelnSkipLayerNormOpConverter : public OpConverter {
       return temp_data;
     };
 
-    framework::DDim bias_dims, scale_dims;
+    phi::DDim bias_dims, scale_dims;
     auto* bias = get_persistable_data("Bias", &bias_dims);
     auto* scale = get_persistable_data("Scale", &scale_dims);
     int bias_size = common::product(bias_dims);
diff --git a/paddle/fluid/inference/tensorrt/convert/prompt_tuning_emb_eltwise_layernorm.cc b/paddle/fluid/inference/tensorrt/convert/prompt_tuning_emb_eltwise_layernorm.cc
@@ -27,7 +27,7 @@ class PromptTuningEmbEltwiseLayerNormOpConverter : public OpConverter {
                "tensorrt layer";
     // get the presistable var's data
     auto GetWeight = [&](const std::string& var_name,
-                         framework::DDim* dim) -> TensorRTEngine::Weight {
+                         phi::DDim* dim) -> TensorRTEngine::Weight {
       auto* temp_var = scope.FindVar(var_name);
       auto* temp_tensor = temp_var->GetMutable<phi::DenseTensor>();
       *dim = temp_tensor->dims();
@@ -49,8 +49,8 @@ class PromptTuningEmbEltwiseLayerNormOpConverter : public OpConverter {
     std::vector<nvinfer1::Weights> input_embs;
     std::vector<int> emb_sizes;
     TensorRTEngine::Weight weight;
-    framework::DDim emb_dims;
-    framework::DDim bias_dims, scale_dims;
+    phi::DDim emb_dims;
+    phi::DDim bias_dims, scale_dims;
     TensorRTEngine::Weight bias_weight, scale_weight;
 
     int64_t bias_size = common::product(bias_dims);
diff --git a/paddle/fluid/inference/tensorrt/convert/skip_groupnorm_act_op.cc b/paddle/fluid/inference/tensorrt/convert/skip_groupnorm_act_op.cc
@@ -40,7 +40,7 @@ class SkipGroupnormActOpConverter : public OpConverter {
 
     // get the presistable var's data
     auto GetWeight = [&](const std::string& var_name,
-                         framework::DDim* dims) -> TensorRTEngine::Weight {
+                         phi::DDim* dims) -> TensorRTEngine::Weight {
       auto* temp_var = scope.FindVar(var_name);
       auto* temp_tensor = temp_var->GetMutable<phi::DenseTensor>();
       (*dims) = temp_tensor->dims();
@@ -49,8 +49,8 @@ class SkipGroupnormActOpConverter : public OpConverter {
       return weight;
     };
 
-    framework::DDim scale_dims;
-    framework::DDim bias_dims;
+    phi::DDim scale_dims;
+    phi::DDim bias_dims;
     auto scale_weights = GetWeight(scale_name, &scale_dims);
     auto bias_weights = GetWeight(bias_name, &bias_dims);
     bool with_fp16 = engine_->WithFp16() && !engine_->disable_trt_plugin_fp16();
diff --git a/paddle/fluid/inference/tensorrt/trt_int8_calibrator.cc b/paddle/fluid/inference/tensorrt/trt_int8_calibrator.cc
@@ -39,7 +39,7 @@ TRTInt8Calibrator::TRTInt8Calibrator(
     std::string input_name = it.first;
     int data_size = it.second;
     int num_ele = data_size / sizeof(int16_t);
-    framework::DDim data_shape = common::make_ddim({num_ele});
+    phi::DDim data_shape = common::make_ddim({num_ele});
     temp_tensor.Resize(data_shape);
     data_buffers_[input_name] = std::pair<void*, size_t>(
         static_cast<void*>(temp_tensor.mutable_data<int16_t>(place)),
diff --git a/paddle/fluid/platform/profiler.cc b/paddle/fluid/platform/profiler.cc
@@ -81,7 +81,7 @@ RecordOpInfoSupplement::RecordOpInfoSupplement(
   if (IsEnabled() == false) {
     return;
   }
-  std::map<std::string, std::vector<framework::DDim>> input_shapes;
+  std::map<std::string, std::vector<phi::DDim>> input_shapes;
   std::map<std::string, std::vector<framework::proto::VarType::Type>> dtypes;
   for (const auto &input : ctx.inputs) {
     input_shapes[input.first] = shape_ctx.GetInputsDim(input.first);
@@ -103,7 +103,7 @@ RecordOpInfoSupplement::RecordOpInfoSupplement(
   if (IsEnabled() == false) {
     return;
   }
-  std::map<std::string, std::vector<framework::DDim>> input_shapes;
+  std::map<std::string, std::vector<phi::DDim>> input_shapes;
   std::map<std::string, std::vector<framework::proto::VarType::Type>> dtypes;
   for (auto input_name_char : kernel_signature.input_names) {
     std::string input_name(input_name_char);
diff --git a/paddle/fluid/platform/profiler/common_event.h b/paddle/fluid/platform/profiler/common_event.h
@@ -36,7 +36,7 @@ struct OperatorSupplementOriginEvent {
       std::function<void *(size_t)> arena_allocator,
       uint64_t timestamp_ns,
       const std::string &type_name,
-      const std::map<std::string, std::vector<framework::DDim>> &input_shapes,
+      const std::map<std::string, std::vector<phi::DDim>> &input_shapes,
       const std::map<std::string, std::vector<framework::proto::VarType::Type>>
           &dtypes,
       const framework::AttributeMap &attributes,
@@ -54,7 +54,7 @@ struct OperatorSupplementOriginEvent {
   uint64_t timestamp_ns;
   const char *op_type = nullptr;  // not owned, designed for performance
   // input shapes
-  std::map<std::string, std::vector<framework::DDim>> input_shapes;
+  std::map<std::string, std::vector<phi::DDim>> input_shapes;
   std::map<std::string, std::vector<framework::proto::VarType::Type>> dtypes;
   // op attributes
   framework::AttributeMap attributes;
diff --git a/paddle/phi/kernels/gpu/depthwise_conv.h b/paddle/phi/kernels/gpu/depthwise_conv.h
@@ -1235,10 +1235,10 @@ class DepthwiseConvFunctor<phi::GPUContext, T, fuse_relu_before_conv> {
 
     phi::DenseTensor filter_hwc;
     if (data_layout == DataLayout::kNHWC) {
-      framework::DDim filter_hwc_dims({filter.dims()[2],
-                                       filter.dims()[3],
-                                       filter.dims()[0],
-                                       filter.dims()[1]});
+      phi::DDim filter_hwc_dims({filter.dims()[2],
+                                 filter.dims()[3],
+                                 filter.dims()[0],
+                                 filter.dims()[1]});
       filter_hwc.Resize(filter_hwc_dims);
       context.template Alloc<T>(&filter_hwc);
       std::vector<int> perm_axis({2, 3, 0, 1});
@@ -1403,10 +1403,10 @@ class DepthwiseConvInputGradFunctor<phi::GPUContext, T, fuse_relu_before_conv> {
 
     phi::DenseTensor filter_hwc;
     if (data_layout == DataLayout::kNHWC) {
-      framework::DDim filter_hwc_dims({filter.dims()[2],
-                                       filter.dims()[3],
-                                       filter.dims()[0],
-                                       filter.dims()[1]});
+      phi::DDim filter_hwc_dims({filter.dims()[2],
+                                 filter.dims()[3],
+                                 filter.dims()[0],
+                                 filter.dims()[1]});
       filter_hwc.Resize(filter_hwc_dims);
       context.template Alloc<T>(&filter_hwc);
       std::vector<int> perm_axis({2, 3, 0, 1});
@@ -1635,10 +1635,10 @@ class DepthwiseConvFilterGradFunctor<phi::GPUContext,
     } else {                                                                   \
       phi::DenseTensor filter_grad_hwc;                                        \
       if (c_filter != -1) {                                                    \
-        framework::DDim filter_grad_hwc_dims({filter_grad->dims()[2],          \
-                                              filter_grad->dims()[3],          \
-                                              filter_grad->dims()[0],          \
-                                              filter_grad->dims()[1]});        \
+        phi::DDim filter_grad_hwc_dims({filter_grad->dims()[2],                \
+                                        filter_grad->dims()[3],                \
+                                        filter_grad->dims()[0],                \
+                                        filter_grad->dims()[1]});              \
         filter_grad_hwc.Resize(filter_grad_hwc_dims);                          \
         context.template Alloc<T>(&filter_grad_hwc);                           \
         phi::funcs::SetConstant<phi::GPUContext, T> set_zero;                  \

Original file line number	Diff line number	Diff line change
`@@ -54,8 +54,7 @@ void InitTensorsOnClient(framework::Scope* scope,`
`54`	`54`	`CreateVarsOnScope(scope, place);`
`55`	`55`
`56`	`56`	`auto x_var = scope->Var("x")->GetMutable<phi::DenseTensor>();`
`57`		`- float* x_ptr =`
`58`		`- x_var->mutable_data<float>(framework::DDim({1, rows_numel}), *place);`
	`57`	`+ float* x_ptr = x_var->mutable_data<float>(phi::DDim({1, rows_numel}), *place);`
`59`	`58`	`for (int64_t i = 0; i < rows_numel; ++i)`
`60`	`59`	`x_ptr[i] = static_cast<float>(1.0) * static_cast<float>(i);`
`61`	`60`	`}`