PaddlePaddle
diff --git a/‎paddle/fluid/eager/accumulation/accumulation_node.cc
Copy file name to clipboard
+7-8Lines changed: 7 additions & 8 deletions b/‎paddle/fluid/eager/accumulation/accumulation_node.cc
Copy file name to clipboard
+7-8Lines changed: 7 additions & 8 deletions
diff --git a/‎paddle/fluid/eager/amp_auto_cast.h
Copy file name to clipboard
+2-4Lines changed: 2 additions & 4 deletions b/‎paddle/fluid/eager/amp_auto_cast.h
Copy file name to clipboard
+2-4Lines changed: 2 additions & 4 deletions
diff --git a/‎paddle/fluid/eager/api/generated/eager_generated/backwards/scale_node.cc
Copy file name to clipboard
+9-10Lines changed: 9 additions & 10 deletions b/‎paddle/fluid/eager/api/generated/eager_generated/backwards/scale_node.cc
Copy file name to clipboard
+9-10Lines changed: 9 additions & 10 deletions
diff --git a/‎paddle/fluid/eager/api/manual/eager_manual/forwards/multiply_fwd_func.cc
Copy file name to clipboard
+1-1Lines changed: 1 addition & 1 deletion b/‎paddle/fluid/eager/api/manual/eager_manual/forwards/multiply_fwd_func.cc
Copy file name to clipboard
+1-1Lines changed: 1 addition & 1 deletion
diff --git a/‎paddle/fluid/eager/api/utils/global_utils.cc
Copy file name to clipboard
+1-1Lines changed: 1 addition & 1 deletion b/‎paddle/fluid/eager/api/utils/global_utils.cc
Copy file name to clipboard
+1-1Lines changed: 1 addition & 1 deletion
diff --git a/‎paddle/fluid/eager/api/utils/hook_utils.cc
Copy file name to clipboard
+6-7Lines changed: 6 additions & 7 deletions b/‎paddle/fluid/eager/api/utils/hook_utils.cc
Copy file name to clipboard
+6-7Lines changed: 6 additions & 7 deletions
diff --git a/‎paddle/fluid/eager/auto_code_generator/eager_generator.cc
Copy file name to clipboard
+5-5Lines changed: 5 additions & 5 deletions b/‎paddle/fluid/eager/auto_code_generator/eager_generator.cc
Copy file name to clipboard
+5-5Lines changed: 5 additions & 5 deletions
diff --git a/‎paddle/fluid/eager/auto_code_generator/generator/python_c_gen.py
Copy file name to clipboard
+8-8Lines changed: 8 additions & 8 deletions b/‎paddle/fluid/eager/auto_code_generator/generator/python_c_gen.py
Copy file name to clipboard
+8-8Lines changed: 8 additions & 8 deletions
diff --git a/‎paddle/fluid/eager/autograd_meta.h
Copy file name to clipboard
+2-2Lines changed: 2 additions & 2 deletions b/‎paddle/fluid/eager/autograd_meta.h
Copy file name to clipboard
+2-2Lines changed: 2 additions & 2 deletions
diff --git a/‎paddle/fluid/eager/backward.cc
Copy file name to clipboard
+8-8Lines changed: 8 additions & 8 deletions b/‎paddle/fluid/eager/backward.cc
Copy file name to clipboard
+8-8Lines changed: 8 additions & 8 deletions
@@ -114,13 +114,12 @@ static void CopyOrAddTensor(paddle::Tensor* tensor,
           }
         }
       } else if (LIKELY(t.is_dist_tensor())) {
+        PADDLE_ENFORCE(tensor->is_dist_tensor(),
+                       phi::errors::Fatal("A DistTensor can only do gradient "
+                                          "merge with another DistTensor."));
         PADDLE_ENFORCE(
-            tensor->is_dist_tensor(),
-            paddle::platform::errors::Fatal("A DistTensor can only do gradient "
-                                            "merge with another DistTensor."));
-        PADDLE_ENFORCE(!t.is_custom_device(),
-                       paddle::platform::errors::Fatal(
-                           "DistTensor doesn't support custom device."));
+            !t.is_custom_device(),
+            phi::errors::Fatal("DistTensor doesn't support custom device."));
         auto t_dist =
             std::dynamic_pointer_cast<phi::distributed::DistTensor>(t.impl());
         paddle::Tensor t_values(
@@ -156,12 +155,12 @@ GradNodeAccumulation::operator()(
     bool is_new_grad) {
   VLOG(3) << "Running AD API Grad: GradNodeAccumulation";
   PADDLE_ENFORCE(grads.size() == 1,
-                 paddle::platform::errors::Fatal(
+                 phi::errors::Fatal(
                      "GradNodeAccumulation should take exactly 1 grad tensor"
                      "However received: %d slot.",
                      grads.size()));
   PADDLE_ENFORCE(grads[0].size() == 1,
-                 paddle::platform::errors::Fatal(
+                 phi::errors::Fatal(
                      "GradNodeAccumulation should take exactly 1 grad tensor"
                      "However received: %d in slot %d .",
                      grads[0].size(),
 
@@ -24,10 +24,8 @@ static inline bool NeedCast(const paddle::Tensor& tensor,
                             const phi::DataType& dst_dtype) {
   auto place = tensor.place();
   auto data_type = tensor.dtype();
-  if (paddle::platform::is_gpu_place(place) ||
-      paddle::platform::is_cuda_pinned_place(place) ||
-      paddle::platform::is_xpu_place(place) ||
-      paddle::platform::is_custom_place(place)) {
+  if (phi::is_gpu_place(place) || phi::is_cuda_pinned_place(place) ||
+      phi::is_xpu_place(place) || phi::is_custom_place(place)) {
     // CudaPinnedPlace is added for varbase created by dataloader
     if ((data_type == phi::DataType::FLOAT32 ||
          data_type == phi::DataType::FLOAT16 ||
 
@@ -85,7 +85,7 @@ static void ScaleDeviceDispatch(const phi::DenseTensor& dense_tensor,
       break;
     }
     default: {
-      PADDLE_THROW(paddle::platform::errors::Fatal(
+      PADDLE_THROW(phi::errors::Fatal(
           "Detected unsupported data type."
           "Only Float64, Float32, Int64, Int32 are supported for now."));
       break;
@@ -113,17 +113,16 @@ void ScaleAPI(const paddle::Tensor& x,
   // Handle Device Context
   const phi::Place& expected_kernel_place =
       Controller::Instance().GetExpectedPlace();
-  paddle::platform::DeviceContextPool& pool =
-      paddle::platform::DeviceContextPool::Instance();
+  phi::DeviceContextPool& pool = phi::DeviceContextPool::Instance();
 
   if (expected_kernel_place == phi::CPUPlace()) {
     auto* dev_ctx =
         dynamic_cast<phi::CPUContext*>(pool.Get(expected_kernel_place));
     if (!dev_ctx) {
-      PADDLE_THROW(paddle::platform::errors::Fatal(
-          "Cannot convert device_context to phi::CPUContext."
-          "This indicates backend mismatch."
-          "Pleas double check your expected place"));
+      PADDLE_THROW(
+          phi::errors::Fatal("Cannot convert device_context to phi::CPUContext."
+                             "This indicates backend mismatch."
+                             "Pleas double check your expected place"));
     }
     ScaleDeviceDispatch<phi::CPUContext>(*dense_tensor.get(),
                                          *dev_ctx,
@@ -137,7 +136,7 @@ void ScaleAPI(const paddle::Tensor& x,
     auto* dev_ctx =
         dynamic_cast<phi::GPUContext*>(pool.Get(expected_kernel_place));
     if (!dev_ctx) {
-      PADDLE_THROW(paddle::platform::errors::Fatal(
+      PADDLE_THROW(phi::errors::Fatal(
           "Cannot convert device_context to CUDADeviceContext."
           "This indicates backend mismatch."
           "Pleas double check your expected place"));
@@ -150,7 +149,7 @@ void ScaleAPI(const paddle::Tensor& x,
                                          dense_out.get());
 #endif
   } else {
-    PADDLE_THROW(paddle::platform::errors::Fatal(
+    PADDLE_THROW(phi::errors::Fatal(
         "Detected unsupported backend."
         "Only CPU and CUDA Backend are supported for now."
         "Please double check if your backend falls into the above two "
@@ -177,7 +176,7 @@ GradNodeScale::operator()(
   VLOG(6) << "grad size is: " << grads.size();
   PADDLE_ENFORCE(
       ((grads.size() == 1) && (grads[0].size() == 1)),
-      paddle::platform::errors::Fatal(
+      phi::errors::Fatal(
           "ScaleGradNode takes exactly 1 grad tensor."
           "However received: %d",
           "This indicates an issue with Eager Dygraph Backward logic",
 
@@ -172,7 +172,7 @@ paddle::Tensor multiply_ad_func(const paddle::Tensor& x,
 #ifdef PADDLE_WITH_CUSTOM_DEVICE
     if (check_if_support_elementwise_mul_mem_opt(x.place().GetDeviceType())) {
 #else
-    if (paddle::platform::is_gpu_place(x.place())) {
+    if (phi::is_gpu_place(x.place())) {
 #endif
       if (x_autograd_meta != nullptr && x_autograd_meta->StopGradient() &&
           y_autograd_meta != nullptr && !y_autograd_meta->StopGradient()) {
 
@@ -36,7 +36,7 @@ bool Controller::UseLayoutAutoTune() {
   bool use_autotune = false;
 #if defined(PADDLE_WITH_CUDA)
   auto place = tracer_->ExpectedPlace();
-  bool is_gpu_place = paddle::platform::is_gpu_place(place);
+  bool is_gpu_place = phi::is_gpu_place(place);
   if (is_gpu_place) {
     use_autotune = tracer_->UseLayoutAutoTune();
   }
 
@@ -38,18 +38,17 @@ void RegisterReduceHookForTensor(const paddle::Tensor& tensor,
   if (EagerUtils::IsLeafTensor(tensor)) {
     VLOG(6) << "Register ReduceHook for leaf tensor";
     std::shared_ptr<GradNodeBase> grad_node = EagerUtils::grad_node(tensor);
-    PADDLE_ENFORCE(
-        grad_node.get() != nullptr,
-        paddle::platform::errors::Fatal("Detected NULL grad_node,"
-                                        "Leaf tensor should have had grad_node "
-                                        "with type: GradNodeAccumulation"));
+    PADDLE_ENFORCE(grad_node.get() != nullptr,
+                   phi::errors::Fatal("Detected NULL grad_node,"
+                                      "Leaf tensor should have had grad_node "
+                                      "with type: GradNodeAccumulation"));
     auto accumulation_grad_node =
         std::dynamic_pointer_cast<GradNodeAccumulation>(grad_node);
     accumulation_grad_node->RegisterReduceHook(
         std::make_shared<CppVoidHook>(hook));
   } else {
-    PADDLE_THROW(paddle::platform::errors::Fatal(
-        "Only can register reduce hook for leaf Tensor."));
+    PADDLE_THROW(
+        phi::errors::Fatal("Only can register reduce hook for leaf Tensor."));
   }
 }
 
 
@@ -729,7 +729,7 @@ static void PurifyGradNodeGenerationInfo(const proto::OpProto& op_proto,
 
               PADDLE_ENFORCE(
                   grad_outs->count(grad_output_name) > 0,
-                  paddle::platform::errors::Fatal(
+                  phi::errors::Fatal(
                       "Unable to find gradient output name in grad_outs."));
               // grad_outs
               grad_outs->erase(grad_output_name);
@@ -767,7 +767,7 @@ static void PurifyGradNodeGenerationInfo(const proto::OpProto& op_proto,
 
               PADDLE_ENFORCE(
                   grad_ins->count(grad_input_name) > 0,
-                  paddle::platform::errors::Fatal(
+                  phi::errors::Fatal(
                       "Unable to find gradient input name in grad_ins."));
               // grad_ins
               grad_ins->erase(grad_input_name);
@@ -1685,7 +1685,7 @@ static std::pair<std::string, std::string> GenerateForwardFunctionContents(
       PADDLE_ENFORCE_NE(
           forward_inplace_map[output_name],
           "",
-          paddle::platform::errors::InvalidArgument(
+          phi::errors::InvalidArgument(
               "Inplace op %s has no input corresponding to output %s.",
               op_type,
               output_name));
@@ -2388,7 +2388,7 @@ static std::string GenerateSingleOpBase(
       */
       if (!fwd_inputs_name_pos_map.count(fwd_name)) {
         PADDLE_ENFORCE(fwd_outputs_name_pos_map.count(fwd_name),
-                       paddle::platform::errors::Fatal(
+                       phi::errors::Fatal(
                            "fwd_name not found in fwd_inputs_name_pos_map nor "
                            "fwd_outputs_name_pos_map"));
 
@@ -2600,7 +2600,7 @@ static std::string GenerateSingleOpBase(
       num_appended_outputs++;
     } else {
       PADDLE_ENFORCE(fwd_outputs_name_pos_map.count(fwd_name),
-                     paddle::platform::errors::Fatal(
+                     phi::errors::Fatal(
                          "fwd_name not found in fwd_inputs_name_pos_map nor "
                          "fwd_outputs_name_pos_map"));
     }
 
@@ -145,30 +145,30 @@ def FindParsingFunctionFromAttributeType(atype):
 
 FUNCTION_SET_DEVICE_TEMPLATE = """{}
     SetPythonStack();
-    if (paddle::platform::is_gpu_place(place)) {{
+    if (phi::is_gpu_place(place)) {{
 #if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
       phi::backends::gpu::SetDeviceId(place.device);
       VLOG(4) <<"CurrentDeviceId: " << phi::backends::gpu::GetCurrentDeviceId() << " from " << (int)place.device;
 #else
-      PADDLE_THROW(paddle::platform::errors::PreconditionNotMet(
+      PADDLE_THROW(phi::errors::PreconditionNotMet(
         "PaddlePaddle should compile with GPU if use CUDAPlace."));
 #endif
     }}
-    if (paddle::platform::is_custom_place(place)) {{
+    if (phi::is_custom_place(place)) {{
 #if defined(PADDLE_WITH_CUSTOM_DEVICE)
       phi::DeviceManager::SetDevice(place);
       VLOG(4) <<"CurrentDeviceId: " << phi::DeviceManager::GetDevice(place.GetDeviceType()) << " from " << (int)place.device;
 #else
-      PADDLE_THROW(paddle::platform::errors::PreconditionNotMet(
+      PADDLE_THROW(phi::errors::PreconditionNotMet(
         "PaddlePaddle should compile with CUSTOM_DEVICE if use CustomPlace."));
 #endif
     }}
-    if (paddle::platform::is_xpu_place(place)) {{
+    if (phi::is_xpu_place(place)) {{
 #if defined(PADDLE_WITH_XPU)
       phi::backends::xpu::SetXPUDeviceId(place.device);
       VLOG(4) <<"CurrentDeviceId: " << phi::backends::xpu::GetXPUCurrentDeviceId() << " from " << (int)place.device;
 #else
-      PADDLE_THROW(paddle::platform::errors::PreconditionNotMet(
+      PADDLE_THROW(phi::errors::PreconditionNotMet(
         "PaddlePaddle should compile with XPU if use XPUPlace."));
 #endif
     }}
@@ -205,11 +205,11 @@ def FindParsingFunctionFromAttributeType(atype):
 
 void BindFinalStateEagerOpFunctions(pybind11::module *module) {{
   if (PyModule_AddFunctions(module->ptr(), EagerFinalStateMethods) < 0) {{
-    PADDLE_THROW(platform::errors::Fatal ("Add functions to core.eager.ops failed!"));
+    PADDLE_THROW(phi::errors::Fatal ("Add functions to core.eager.ops failed!"));
   }}
 
   if (PyModule_AddFunctions(module->ptr(), CustomEagerFinalStateMethods) < 0) {{
-    PADDLE_THROW(platform::errors::Fatal ("Add functions to core.eager.ops failed!"));
+    PADDLE_THROW(phi::errors::Fatal ("Add functions to core.eager.ops failed!"));
   }}
 }}
 
 
@@ -71,7 +71,7 @@ class AutogradMeta : public AbstractAutogradMeta {
   const paddle::Tensor& Grad() const {
     PADDLE_ENFORCE_NOT_NULL(
         grad_.get(),
-        paddle::platform::errors::InvalidArgument(
+        phi::errors::InvalidArgument(
             "Should Not get NULL from Grad pointer, since "
             "we should have default Tensor once we init AutoGradMeta. "
             "if you got this error may indicates framework error in "
@@ -86,7 +86,7 @@ class AutogradMeta : public AbstractAutogradMeta {
   void SetGradNode(const std::shared_ptr<GradNodeBase>& grad_node) {
     PADDLE_ENFORCE_NOT_NULL(
         grad_node.get(),
-        paddle::platform::errors::InvalidArgument(
+        phi::errors::InvalidArgument(
             "Should Not set NULL as GradNode pointer, since "
             "our default Edge and autogradMeta has nullptr for "
             "grad node. Set Nullptr will lead error."));
 
@@ -43,7 +43,7 @@ std::unordered_map<GradNodeBase*, int> getInDegreeMap(
 
     PADDLE_ENFORCE_NOT_NULL(
         node,
-        paddle::platform::errors::Fatal(
+        phi::errors::Fatal(
             "We got null node when we traverse the backward graph, and this "
             "should not happened please check your code and contact us."));
     // Find and append next nodes
@@ -75,7 +75,7 @@ void EnforceGradNodeHasInput(GradNodeBase* node) {
   PADDLE_ENFORCE_NE(
       node->IsTensorWrappersCleared(),
       true,
-      paddle::platform::errors::Fatal(
+      phi::errors::Fatal(
           "The TensorWrappers of %s do not exist. This may be because:\n"
           "You calculate backward twice for the same subgraph without "
           "setting retain_graph=True. Please set retain_graph=True in the "
@@ -91,7 +91,7 @@ void DuplicateCheck(const std::vector<paddle::Tensor>& inputs, bool is_input) {
     PADDLE_ENFORCE_EQ(
         visited_ins.count(auto_grad_meta),
         0,
-        paddle::platform::errors::AlreadyExists(
+        phi::errors::AlreadyExists(
             "%s contain duplicate tensor %s, please check %s carefully.",
             msg,
             in.name(),
@@ -183,7 +183,7 @@ std::vector<paddle::Tensor> RunBackward(
     if (!grad_tensors.empty() && grad_tensors[i].initialized()) {
       PADDLE_ENFORCE(
           grad_tensors.size() == tensors.size(),
-          paddle::platform::errors::Fatal(
+          phi::errors::Fatal(
               "Detected size mismatch between tensors and grad_tensors"
               "grad_tensors should either have "
               "size = 0 or same size as tensors."));
@@ -265,7 +265,7 @@ std::vector<paddle::Tensor> RunBackward(
     PADDLE_ENFORCE_NE(
         node_input_buffer_iter,
         node_input_buffers_dict.end(),
-        paddle::platform::errors::Fatal(
+        phi::errors::Fatal(
             "Unable to find next node in the GradTensorHolder \n"
             "Trying to run Node without configuring its GradTensorHolder."));
 
@@ -315,7 +315,7 @@ std::vector<paddle::Tensor> RunBackward(
     const paddle::small_vector<std::vector<GradSlotMeta>, kSlotSmallVectorSize>&
         metas = node->OutputMeta();
     PADDLE_ENFORCE(metas.size() == grad_output_tensors.size() || metas.empty(),
-                   paddle::platform::errors::Fatal(
+                   phi::errors::Fatal(
                        "Number of edges should be either empty ( for leaf node "
                        ") or the same as number of output grad tensors, but we "
                        "got edges size is: %d, grad_output size is: %d",
@@ -346,7 +346,7 @@ std::vector<paddle::Tensor> RunBackward(
         PADDLE_ENFORCE_LT(
             j,
             grad_output_tensors[i].size(),
-            paddle::platform::errors::Fatal(
+            phi::errors::Fatal(
                 "Rank of grad_output_tensors should be less than "
                 "grad_output_tensors[i].size(), which is: %d. This error may "
                 "indicate autoprune or autograd api error. ",
@@ -388,7 +388,7 @@ std::vector<paddle::Tensor> RunBackward(
 
         PADDLE_ENFORCE(
             node_in_degree_map[next_node] >= 0,
-            paddle::platform::errors::Fatal(
+            phi::errors::Fatal(
                 "Detected in-degree value smaller than zero. For Node: %s"
                 "Node's in-degree cannot be negative.",
                 next_node->name()));
Original file line number	Diff line number	Diff line change
`@@ -36,7 +36,7 @@ bool Controller::UseLayoutAutoTune() {`
`36`	`36`	`bool use_autotune = false;`
`37`	`37`	`#if defined(PADDLE_WITH_CUDA)`
`38`	`38`	`auto place = tracer_->ExpectedPlace();`
`39`		`- bool is_gpu_place = paddle::platform::is_gpu_place(place);`
	`39`	`+ bool is_gpu_place = phi::is_gpu_place(place);`
`40`	`40`	`if (is_gpu_place) {`
`41`	`41`	`use_autotune = tracer_->UseLayoutAutoTune();`
`42`	`42`	`}`