Fix repalce_outputs_name replace_outputs_name (#61071)

co63oc · web-flow · commit 948a1add0aef · 2024-01-24T16:19:48.000+08:00
* Fix

* ci
diff --git a/paddle/fluid/framework/ir/fuse_adamw_op_pass.cc b/paddle/fluid/framework/ir/fuse_adamw_op_pass.cc
@@ -112,7 +112,7 @@ void InsertOpToGraph(const std::vector<std::vector<Node *>> &inout_node_vectors,
       fuse_adamw_op_desc.SetInput("SkipUpdate", {});
     }
 
-    for (auto &name : config.repalce_outputs_name) {
+    for (auto &name : config.replace_outputs_name) {
       fuse_adamw_op_desc.SetOutput(name, GetNodeNames(inout_node_vectors[i]));
       i++;
     }
@@ -151,7 +151,7 @@ void InsertOpToGraph(const std::vector<std::vector<Node *>> &inout_node_vectors,
         IR_NODE_LINK_TO(inout_node_vectors[j][k], fuse_adamw_node);
       }
       for (; j < config.replace_inputs_name.size() +
-                     config.repalce_outputs_name.size();
+                     config.replace_outputs_name.size();
            j++) {
         IR_NODE_LINK_TO(fuse_adamw_node, inout_node_vectors[j][k]);
       }
diff --git a/paddle/fluid/framework/ir/fuse_adamw_op_pass.h b/paddle/fluid/framework/ir/fuse_adamw_op_pass.h
@@ -52,7 +52,7 @@ struct AdamWConfig {
       "ParamOut", "Moment1Out", "Moment2Out", "Beta1PowOut", "Beta2PowOut"};
   const std::vector<std::string> replace_inputs_name = {
       "Params", "Grads", "Moments1", "Moments2", "Beta1Pows", "Beta2Pows"};
-  const std::vector<std::string> repalce_outputs_name = {"ParamsOut",
+  const std::vector<std::string> replace_outputs_name = {"ParamsOut",
                                                          "Moments1Out",
                                                          "Moments2Out",
                                                          "Beta1PowsOut",
diff --git a/paddle/fluid/inference/capi_exp/pd_tensor.cc b/paddle/fluid/inference/capi_exp/pd_tensor.cc
@@ -65,10 +65,10 @@ REPEAT_ALL_DATA_TYPE(PD_TENSOR_MUTABLE_DATA_IMPL)
     PADDLE_ENFORCE_NOT_NULL(size,                                              \
                             paddle::platform::errors::InvalidArgument(         \
                                 "The pointer of size shouldn't be nullptr"));  \
-    paddle_infer::PlaceType cxx_palce_type;                                    \
+    paddle_infer::PlaceType cxx_place_type;                                    \
     int cxx_size;                                                              \
-    type* data = tensor->data<type>(&cxx_palce_type, &cxx_size);               \
-    *place = paddle_infer::CvtFromCxxPlaceType(cxx_palce_type);                \
+    type* data = tensor->data<type>(&cxx_place_type, &cxx_size);               \
+    *place = paddle_infer::CvtFromCxxPlaceType(cxx_place_type);                \
     *size = static_cast<int32_t>(cxx_size);                                    \
     return data;                                                               \
   }
diff --git a/paddle/fluid/operators/cross_entropy_op.cc b/paddle/fluid/operators/cross_entropy_op.cc
@@ -252,7 +252,7 @@ CrossEntropy Operator.
 The input 'X' and 'Label' will first be logically flattened to 2-D matrixs.
 The matrix's second dimension(row length) is as same as the original last
 dimension, and the first dimension(column length) is the product of all other
-original dimensions. Then the softmax computation will take palce on each raw
+original dimensions. Then the softmax computation will take place on each raw
 of flattened matrixs.
 
 It supports both standard cross-entropy and soft-label cross-entropy loss
@@ -387,7 +387,7 @@ Hard-label CrossEntropy Operator.
 The input 'X' and 'Label' will first be logically flattened to 2-D matrixs.
 The matrix's second dimension(row length) is as same as the original last
 dimension, and the first dimension(column length) is the product of all other
-original dimensions. Then the softmax computation will take palce on each raw
+original dimensions. Then the softmax computation will take place on each raw
 of flattened matrixs.
 
 Only support hard label.
diff --git a/paddle/phi/README.md b/paddle/phi/README.md
@@ -670,7 +670,7 @@ In addition, only basic template adaptation has been implemented at present, and
 For the management of the new form of Kernel, described as follows:
 
 - `KernelFactory` is a global singleton data structure for managing Kernel. Similar to `OpKernelMap` of fluid, it is a two-level map. The first-level mapping finds the Kernel set according to the name, and the second-level mapping finds the specific Kernel according to the KernelKey.
-- `KernelKey` is similar to the original `OpKernelType`, but the `palce` and `library_type` fields are combined into one and called `Backend`, because the original `LibraryType` is a limited enumeration class, which is strongly related to place, the splitting increases the cost of understanding instead.
+- `KernelKey` is similar to the original `OpKernelType`, but the `place` and `library_type` fields are combined into one and called `Backend`, because the original `LibraryType` is a limited enumeration class, which is strongly related to place, the splitting increases the cost of understanding instead.
 - `Kernel` holds more information than the original `OpKernel`. In addition to the Function during execution, it also holds information about specific parameters, namely `KernelArgsDef`. For Tensor type input and output, it saves Tensor type information, Device, data Type, data layout. For Attribute type input and output, it saves type information.
 
 #### 2.3.5 Kernel Compilation and Dependencies
diff --git a/paddle/phi/infermeta/unary.cc b/paddle/phi/infermeta/unary.cc
@@ -426,7 +426,7 @@ void CastInferMeta(const MetaTensor& x, DataType out_dtype, MetaTensor* out) {
   out->set_dims(x.dims());
   out->set_layout(x.layout());
   out->share_lod(x);
-  // In inpalce case, setting the dtype of out will reset the dtype of x at the
+  // In inplace case, setting the dtype of out will reset the dtype of x at the
   // same time, which will cause bugs, so move the dtype setting of out to the
   // kernel
   if (!(out->is_same_tensor(x))) {
diff --git a/paddle/phi/kernels/gpu/gaussian_kernel.cu b/paddle/phi/kernels/gpu/gaussian_kernel.cu
@@ -77,7 +77,7 @@ void GaussianKernel(const Context& dev_ctx,
 }
 
 template <typename T, typename Context>
-void GaussianInpalceKernel(const Context& dev_ctx,
+void GaussianInplaceKernel(const Context& dev_ctx,
                            const DenseTensor& x,
                            float mean,
                            float std,
@@ -110,10 +110,10 @@ PD_REGISTER_KERNEL(gaussian,
                    float,
                    double) {}
 
-PD_REGISTER_KERNEL(gaussian_inpalce,
+PD_REGISTER_KERNEL(gaussian_inplace,
                    GPU,
                    ALL_LAYOUT,
-                   phi::GaussianInpalceKernel,
+                   phi::GaussianInplaceKernel,
                    phi::dtype::float16,
                    phi::dtype::bfloat16,
                    float,
diff --git a/python/paddle/distributed/fleet/recompute/recompute_hybrid.py b/python/paddle/distributed/fleet/recompute/recompute_hybrid.py
@@ -150,7 +150,7 @@ def forward(
 
                 # In new dygraph mode, in some cases a subset of outputs is identity to the subset of inputs,
                 #  which is inplace operating. When the inputs' stop_gradient is True, an
-                #  error will occurs because the stop_gradient=True and inpalce-op are not
+                #  error will occurs because the stop_gradient=True and inplace-op are not
                 #  supported in the same time. The solution is to mark the inputs non_differentiable
                 #  if its stop_gradient is True.
                 # Note:
diff --git a/python/paddle/incubate/distributed/utils/io/dist_load.py b/python/paddle/incubate/distributed/utils/io/dist_load.py
@@ -39,7 +39,7 @@ def load(path, **configs):
             DO NOT use them. Default None.
             The following options are currently supported:
                 (1) place: where to place the loaded state dict.
-                     If the state dict is too large, the palce should be set 'cpu'.
+                     If the state dict is too large, the place should be set 'cpu'.
             Note:
                 Other config value may cause some error.Please don't use any more config options.
     Returns:
diff --git a/python/paddle/incubate/distributed/utils/io/dist_save.py b/python/paddle/incubate/distributed/utils/io/dist_save.py
@@ -364,7 +364,7 @@ def _grouped_gather_data_dict(state_data_dict, dst, group, max_size):
     logger.debug("all gathered ...")
 
     if dist.get_rank() in dst:
-        # convert numpy.ndarray to Tensor in cpu palce
+        # convert numpy.ndarray to Tensor in cpu place
         place = paddle.CPUPlace()
         for k in output_state.keys():
             output_state[k] = paddle.to_tensor(output_state[k], place=place)
diff --git a/test/legacy_test/test_inplace.py b/test/legacy_test/test_inplace.py
@@ -351,7 +351,7 @@ def inplace_api_processing(self, var):
 
     def test_continuous_inplace_backward(self):
         # The api that only relies on input to calculate the gradient will copy input before
-        # the inpalce calculation, so here supports continuous inpalce backward calculation.
+        # the inplace calculation, so here supports continuous inplace backward calculation.
         grad_var_a, grad_var_a_inplace = 0, 1
         with paddle.base.dygraph.guard():
             var_a = paddle.to_tensor(self.input_var_numpy).astype(self.dtype)

Original file line number	Diff line number	Diff line change
`@@ -112,7 +112,7 @@ void InsertOpToGraph(const std::vector<std::vector<Node *>> &inout_node_vectors,`
`112`	`112`	`fuse_adamw_op_desc.SetInput("SkipUpdate", {});`
`113`	`113`	`}`
`114`	`114`
`115`		`- for (auto &name : config.repalce_outputs_name) {`
	`115`	`+ for (auto &name : config.replace_outputs_name) {`
`116`	`116`	`fuse_adamw_op_desc.SetOutput(name, GetNodeNames(inout_node_vectors[i]));`
`117`	`117`	`i++;`
`118`	`118`	`}`
`@@ -151,7 +151,7 @@ void InsertOpToGraph(const std::vector<std::vector<Node *>> &inout_node_vectors,`
`151`	`151`	`IR_NODE_LINK_TO(inout_node_vectors[j][k], fuse_adamw_node);`
`152`	`152`	`}`
`153`	`153`	`for (; j < config.replace_inputs_name.size() +`
`154`		`- config.repalce_outputs_name.size();`
	`154`	`+ config.replace_outputs_name.size();`
`155`	`155`	`j++) {`
`156`	`156`	`IR_NODE_LINK_TO(fuse_adamw_node, inout_node_vectors[j][k]);`
`157`	`157`	`}`