Fix typos combile_ combine_ (#70241)

co63oc · web-flow · commit d82247adc904 · 2025-02-06T11:17:48.000+08:00
* Fix

* ci
diff --git a/paddle/fluid/inference/tensorrt/convert/batch_norm_op.cc b/paddle/fluid/inference/tensorrt/convert/batch_norm_op.cc
@@ -83,38 +83,38 @@ class BatchNormOpConverter : public OpConverter {
     auto* scale_data = scale_tensor.mutable_data<float>(phi::CPUPlace());
     auto* variance_data = variance_tensor.mutable_data<float>(phi::CPUPlace());
 
-    std::unique_ptr<phi::DenseTensor> combile_scale_tensor(
+    std::unique_ptr<phi::DenseTensor> combine_scale_tensor(
         new phi::DenseTensor());
-    std::unique_ptr<phi::DenseTensor> combile_bias_tensor(
+    std::unique_ptr<phi::DenseTensor> combine_bias_tensor(
         new phi::DenseTensor());
 
-    combile_scale_tensor->Resize(scale_tensor.dims());
-    combile_bias_tensor->Resize(bias_tensor.dims());
+    combine_scale_tensor->Resize(scale_tensor.dims());
+    combine_bias_tensor->Resize(bias_tensor.dims());
 
-    auto* combile_scale_data =
-        combile_scale_tensor->mutable_data<float>(phi::CPUPlace());
-    auto* combile_bias_data =
-        combile_bias_tensor->mutable_data<float>(phi::CPUPlace());
+    auto* combine_scale_data =
+        combine_scale_tensor->mutable_data<float>(phi::CPUPlace());
+    auto* combine_bias_data =
+        combine_bias_tensor->mutable_data<float>(phi::CPUPlace());
 
-    size_t ele_num = combile_scale_tensor->memory_size() / sizeof(float);
+    size_t ele_num = combine_scale_tensor->memory_size() / sizeof(float);
 
     for (size_t i = 0; i < ele_num; i++) {
       float scale = scale_data[i];
       float bias = bias_data[i];
       float mean = mean_data[i];
       float variance = variance_data[i];
-      combile_scale_data[i] = scale / sqrtf(variance + eps);
-      combile_bias_data[i] = bias - mean * combile_scale_data[i];
+      combine_scale_data[i] = scale / sqrtf(variance + eps);
+      combine_bias_data[i] = bias - mean * combine_scale_data[i];
     }
 
     TensorRTEngine::Weight scale_weights{
         nvinfer1::DataType::kFLOAT,
-        static_cast<void*>(combile_scale_data),
-        combile_scale_tensor->memory_size() / sizeof(float)};
+        static_cast<void*>(combine_scale_data),
+        combine_scale_tensor->memory_size() / sizeof(float)};
     TensorRTEngine::Weight shift_weights{
         nvinfer1::DataType::kFLOAT,
-        static_cast<void*>(combile_bias_data),
-        combile_bias_tensor->memory_size() / sizeof(float)};
+        static_cast<void*>(combine_bias_data),
+        combine_bias_tensor->memory_size() / sizeof(float)};
     TensorRTEngine::Weight power_weights{
         nvinfer1::DataType::kFLOAT, nullptr, 0};
 
@@ -152,9 +152,9 @@ class BatchNormOpConverter : public OpConverter {
                                  1);
 
     engine_->SetWeights(op_desc.Input("Bias").front(),
-                        std::move(combile_bias_tensor));
+                        std::move(combine_bias_tensor));
     engine_->SetWeights(op_desc.Input("Scale").front(),
-                        std::move(combile_scale_tensor));
+                        std::move(combine_scale_tensor));
     if (x_dim.nbDims < 4) {
       layer->getOutput(0)->setName(("BN: ScaleNd: " + output_name).c_str());
       layer->setName(("BN: ScaleNd: (Output: " + output_name + ")").c_str());
diff --git a/python/paddle/distributed/passes/auto_parallel_gradient_merge.py b/python/paddle/distributed/passes/auto_parallel_gradient_merge.py
@@ -383,7 +383,7 @@ def _pir_append_gradient_merge_backward_op(
         )
         new_gradient_merge_var_add_op.set_bool_attr("grad_merge_add", True)
 
-        # NOTE(zhangweilong): grad may in different device in auto_parallel, so need consider all_gather/all_recdue/split/... op
+        # NOTE(zhangweilong): grad may in different device in auto_parallel, so need consider all_gather/all_reduce/split/... op
         for used_grad_op in grad.all_used_ops():
             _move_used_grad_op(used_grad_op, grad)
 
diff --git a/python/paddle/distributed/passes/pass_utils.py b/python/paddle/distributed/passes/pass_utils.py
@@ -2107,7 +2107,7 @@ def _estimate_max_memory(
                     continue
 
                 var_info[var_name]["count"] -= 1
-                if var_name not in has_used_vars and not self._is_perisitable(
+                if var_name not in has_used_vars and not self._is_persistable(
                     var_name, var_info
                 ):
                     has_used_vars.add(var_name)
@@ -2122,7 +2122,7 @@ def _estimate_max_memory(
 
                 if self._is_last_used(var_name, var_info):
                     if (
-                        not self._is_perisitable(var_name, var_info)
+                        not self._is_persistable(var_name, var_info)
                         and var_name not in skip_gc_vars
                     ):
                         last_use_vars.append(var_name)
@@ -2242,7 +2242,7 @@ def _is_last_used(self, var_name, var_info):
 
         return var_info[var_name]["count"] == 0
 
-    def _is_perisitable(self, var_name, var_info):
+    def _is_persistable(self, var_name, var_info):
         if var_name not in var_info:
             return False
 

Original file line number	Diff line number	Diff line change
`@@ -383,7 +383,7 @@ def _pir_append_gradient_merge_backward_op(`
`383`	`383`	`)`
`384`	`384`	`new_gradient_merge_var_add_op.set_bool_attr("grad_merge_add", True)`
`385`	`385`
`386`		`- # NOTE(zhangweilong): grad may in different device in auto_parallel, so need consider all_gather/all_recdue/split/... op`
	`386`	`+ # NOTE(zhangweilong): grad may in different device in auto_parallel, so need consider all_gather/all_reduce/split/... op`
`387`	`387`	`for used_grad_op in grad.all_used_ops():`
`388`	`388`	`_move_used_grad_op(used_grad_op, grad)`
`389`	`389`