PaddlePaddle
diff --git a/‎paddle/cinn/api/README.md
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diff --git a/‎paddle/fluid/eager/auto_code_generator/eager_generator.cc
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diff --git a/‎paddle/fluid/eager/custom_operator/custom_operator_utils.cc
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+1-1Lines changed: 1 addition & 1 deletion b/‎paddle/fluid/eager/custom_operator/custom_operator_utils.cc
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diff --git a/‎paddle/fluid/eager/eager_layout_auto_tune.h
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diff --git a/‎paddle/fluid/eager/eager_tensor.h
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diff --git a/‎paddle/fluid/eager/pylayer/py_layer_node.cc
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diff --git a/‎paddle/fluid/eager/to_static/run_program_op_node.h
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+10-10Lines changed: 10 additions & 10 deletions b/‎paddle/fluid/eager/to_static/run_program_op_node.h
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diff --git a/‎paddle/fluid/eager/utils.h
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diff --git a/‎paddle/fluid/framework/details/broadcast_op_handle.cc
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diff --git a/‎paddle/fluid/framework/executor_cache.cc
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@@ -3,7 +3,7 @@ The classes in this directory are the interface of group fusion pass, you can us
 
 The Class and APIs are following:
 
-`OpGroup` : A set of op nodes, which will pass to cinn backend for generating kernel code. Two groups can fuse togather according to the rule of merging written in the passes.
+`OpGroup` : A set of op nodes, which will pass to cinn backend for generating kernel code. Two groups can fuse together according to the rule of merging written in the passes.
 
 `OpNode` : Map the op in the program.
 
@@ -35,11 +35,11 @@ The Class and APIs are following:
 |            | other methods are same with std::vector<int64_t> | |
 |  |  |  |
 | LightwareFusePassCtx | PickOpGroup() | Get the current group in the pass context |
-|                      | void EnableFuse(const OpGroup& first, const OpGroup& second) | Mark the two groups which can fuse togather |
+|                      | void EnableFuse(const OpGroup& first, const OpGroup& second) | Mark the two groups which can fuse together |
 |  | fuse_helper()     | Get the fuse_helper provided by pass context  |
 |  |  |  |
 | InputFusePassCtx   | PickConsumersWithSameInputs() | Get all consumer groups for input tensors of graph |
-|                      | void EnableFuse(const OpGroup& first, const OpGroup& second) | Mark the two groups which can fuse togather |
+|                      | void EnableFuse(const OpGroup& first, const OpGroup& second) | Mark the two groups which can fuse together |
 |  | fuse_helper()     | Get the fuse_helper provided by pass context  |
 |  |  |  |
 | FuseHelper | DetectCycleIfFuse(const OpGroup& first, const OpGroup& second) | Whether there is cycle in graph after fusing two groups |
@@ -2373,7 +2373,7 @@ static std::string GenerateSingleOpBase(
                   GradOut
 
           Its grad output "GradOut" corresponds to forward output "Out",
-          where there is a hiden inplace involved. So we find "GradOut"'s
+          where there is a hidden inplace involved. So we find "GradOut"'s
          index
          in
           grads, and perform the inplace operation by constructing outs =
@@ -2534,7 +2534,7 @@ static std::string GenerateSingleOpBase(
   std::string grad_attrs_str =
       paddle::string::Sprintf(ATTRS_TEMPLATE, attrs_name);
   if (fwd_op_type == "cast") {
-    // swtich in out dtype
+    // switch in out dtype
     const char* CAST_GRAD =
         "  auto temp_type = %s[\"in_dtype\"];\n"
         "  %s[\"in_dtype\"] = %s[\"out_dtype\"];\n"
 
@@ -406,7 +406,7 @@ static std::vector<std::vector<phi::DataType>> RunInferDtypeFunc(
               "Custom operator only supports `paddle::Vec(...)` inputs and "
               "cannot support `paddle::Vec(...)` output without setting "
               "InplaceMap. If you have to use `paddle::Vec(...)` output, "
-              "please indicate it by setting InplaceMap manully."));
+              "please indicate it by setting InplaceMap manually."));
       std::vector<phi::DataType> dtypes;
       auto duplicable_input_pair = ctx.InputRangeAt(inplace_reverse_map[i]);
       for (size_t j = duplicable_input_pair.first;
 
@@ -90,7 +90,7 @@ inline std::shared_ptr<EagerLayoutTransformer> EagerLayoutAutotune(
     const std::string& op_name,
     const paddle::small_vector<std::vector<paddle::Tensor>,
                                kSlotSmallVectorSize>& tensors_vector,
-    paddle::experimental::IntArray* padddings,
+    paddle::experimental::IntArray* paddings,
     std::string* attr) {
   // for pad
   if ((DesiredLayout() == phi::DataLayout::UNDEFINED)) {
 
@@ -285,7 +285,7 @@ class EagerVariable final {
   template <typename VarType>
   void ConstructVariableFromTensor(const paddle::Tensor& tensor) {
     auto* framework_tensor = var_.GetMutable<VarType>();
-    // Contruct phi::DenseTensor from egr::EagerVariable
+    // Construct phi::DenseTensor from egr::EagerVariable
     auto tensor_dense = std::dynamic_pointer_cast<VarType>(tensor.impl());
 
     PADDLE_ENFORCE_EQ(
@@ -308,7 +308,7 @@ class EagerVariable final {
   template <typename VarType>
   void ConstructVariableFromCompatTensor(const paddle::Tensor& tensor) {
     auto* framework_holder = var_.GetMutable<VarType>();
-    // Contruct phi::DenseTensor from egr::EagerVariable
+    // Construct phi::DenseTensor from egr::EagerVariable
     auto* compat_tensor =
         static_cast<VariableCompatTensor*>(tensor.impl().get());
     PADDLE_ENFORCE_NOT_NULL(compat_tensor,
 
@@ -150,7 +150,7 @@ GradNodePyLayer::operator()(
       PyObject_GetAttrString(reinterpret_cast<PyObject*>(ctx), "backward");
   if (!backward_fn) {
     PADDLE_THROW(paddle::platform::errors::InvalidArgument(
-        "Get backward function faild."));
+        "Get backward function failed."));
   }
   bool need_grad_tmp = egr::Controller::Instance().HasGrad();
   egr::Controller::Instance().SetHasGrad(create_graph && need_grad_tmp);
 
@@ -116,7 +116,7 @@ static void CheckOutputVarStatus(const paddle::framework::Variable &src_var,
     PADDLE_ENFORCE_EQ(phi::SelectedRows::classof(&src_tensor),
                       true,
                       paddle::platform::errors::InvalidArgument(
-                          "The output tensodfr %s get from "
+                          "The output tensor %s get from "
                           "RunProgram(Grad)Op's internal scope holds "
                           "wrong type. Expect type is SelectedRows",
                           name));
@@ -721,13 +721,13 @@ inline void RunProgramAPI(
     if (in_pir_pt_mode) {
       // build new ir program
       auto ir_program =
-          paddle::framework::ConstructFowardIrProgram(forward_global_block,
-                                                      backward_global_block,
-                                                      output_names,
-                                                      x,
-                                                      input_names,
-                                                      params,
-                                                      place);
+          paddle::framework::ConstructForwardIrProgram(forward_global_block,
+                                                       backward_global_block,
+                                                       output_names,
+                                                       x,
+                                                       input_names,
+                                                       params,
+                                                       place);
       interpreter_core = paddle::framework::CreatePirInterpreterCoreInfoToCache(
           std::move(ir_program),
           place,
@@ -1208,7 +1208,7 @@ class GradNodeRunProgram : public egr::GradNodeBase {
     if (!(*executed_)) {
       auto *out_scope_vec = &step_scope_;
       VLOG(4) << "~GradNodeRunProgram: " << this;
-      // Normally out_scope_vec.size() == 1. for safty, we add for-loop here.
+      // Normally out_scope_vec.size() == 1. for safety, we add for-loop here.
       for (size_t i = 0; i < out_scope_vec->size(); ++i) {
         paddle::framework::Scope *global_inner_scope = out_scope_vec->at(i);
         global_inner_scope->SetCanReused(true);
@@ -1394,7 +1394,7 @@ class PirGradNodeRunProgram : public egr::GradNodeBase {
     if (!(*executed_)) {
       auto *out_scope_vec = &step_scope_;
       VLOG(4) << "~PirGradNodeRunProgram";
-      // Normally out_scope_vec.size() == 1. for safty, we add for-loop here.
+      // Normally out_scope_vec.size() == 1. for safety, we add for-loop here.
       for (size_t i = 0; i < out_scope_vec->size(); ++i) {
         paddle::framework::Scope *global_inner_scope = out_scope_vec->at(i);
         global_inner_scope->SetCanReused(true);
 
@@ -27,9 +27,9 @@ class TensorWrapper;
 
 /**
  * EagerUtils is utils used to do some static conversion or autograd
- * members access, this class is desinged to be a full static functional
+ * members access, this class is designed to be a full static functional
  * utils class
- * **/
+ **/
 
 template <typename ElementType>
 class IterHelper {
@@ -194,7 +194,7 @@ class TEST_API EagerUtils {
   static std::vector<paddle::Tensor> RecoverTensorWrapper(
       std::vector<TensorWrapper>* tw);
 
-  // Intermidate needed remove this once we don't need legacy
+  // Intermediate needed remove this once we don't need legacy
   // Inner Method
   static std::shared_ptr<egr::EagerVariable> TrySyncToVar(
       const paddle::Tensor& tensor);
 
@@ -151,7 +151,7 @@ void BroadcastOpHandle::BroadcastOneVar(
     }
 #else
     PADDLE_THROW(
-        platform::errors::PreconditionNotMet("Not compiled with NCLL."));
+        platform::errors::PreconditionNotMet("Not compiled with NCCL."));
 #endif
   } else {
 #if defined(PADDLE_WITH_XPU_BKCL)
 
@@ -386,7 +386,7 @@ std::unique_ptr<::pir::Program> ApplyIrPass(::pir::Program *program,
   return ir_res;
 }
 
-std::unique_ptr<::pir::Program> ConstructFowardIrProgram(
+std::unique_ptr<::pir::Program> ConstructForwardIrProgram(
     const paddle::framework::BlockDesc *forward_global_block,
     const paddle::framework::BlockDesc *backward_global_block,
     const std::vector<std::string> &output_names,
Original file line number	Diff line number	Diff line change
`@@ -150,7 +150,7 @@ GradNodePyLayer::operator()(`
`150`	`150`	`PyObject_GetAttrString(reinterpret_cast<PyObject*>(ctx), "backward");`
`151`	`151`	`if (!backward_fn) {`
`152`	`152`	`PADDLE_THROW(paddle::platform::errors::InvalidArgument(`
`153`		`- "Get backward function faild."));`
	`153`	`+ "Get backward function failed."));`
`154`	`154`	`}`
`155`	`155`	`bool need_grad_tmp = egr::Controller::Instance().HasGrad();`
`156`	`156`	`egr::Controller::Instance().SetHasGrad(create_graph && need_grad_tmp);`
Original file line number	Diff line number	Diff line change
`@@ -151,7 +151,7 @@ void BroadcastOpHandle::BroadcastOneVar(`
`151`	`151`	`}`
`152`	`152`	`#else`
`153`	`153`	`PADDLE_THROW(`
`154`		`- platform::errors::PreconditionNotMet("Not compiled with NCLL."));`
	`154`	`+ platform::errors::PreconditionNotMet("Not compiled with NCCL."));`
`155`	`155`	`#endif`
`156`	`156`	`} else {`
`157`	`157`	`#if defined(PADDLE_WITH_XPU_BKCL)`
Original file line number	Diff line number	Diff line change
`@@ -386,7 +386,7 @@ std::unique_ptr<::pir::Program> ApplyIrPass(::pir::Program *program,`
`386`	`386`	`return ir_res;`
`387`	`387`	`}`
`388`	`388`
`389`		`-std::unique_ptr<::pir::Program> ConstructFowardIrProgram(`
	`389`	`+std::unique_ptr<::pir::Program> ConstructForwardIrProgram(`
`390`	`390`	`const paddle::framework::BlockDesc *forward_global_block,`
`391`	`391`	`const paddle::framework::BlockDesc *backward_global_block,`
`392`	`392`	`const std::vector<std::string> &output_names,`