[CodeStyle][Typos][O[1-2],P[1-3],R[1-2],S[1-3]] Fix typo(Opreator,opitimize,Parmas,Postional,precess,resuce,Reseve,socre,Simbol)

paddle/cinn/hlir/dialect/operator/transforms/pir_to_py_code_converter.cc

@@ -1523,7 +1523,7 @@ struct PirToPyCodeConverterHelper {
   std::string ConvertBlockSignatureAsArgs(const pir::Operation* op) {
     if (op->num_regions() == 0) return "";
     std::stringstream ss;
-    const auto& ConvertPostionalArgsAsQuotedString = [&](const auto& block) {
+    const auto& ConvertPositionalArgsAsQuotedString = [&](const auto& block) {
       std::stringstream ss;
       int idx = 0;
       for (const auto& value : block.args()) {
@@ -1547,7 +1547,7 @@ struct PirToPyCodeConverterHelper {
           if (j++ > 0) {
             ss << ",";
           }
-          ss << "[" << ConvertPostionalArgsAsQuotedString(block) << "]";
+          ss << "[" << ConvertPositionalArgsAsQuotedString(block) << "]";
         }
         ss << "]";
       }

paddle/fluid/distributed/collective/deep_ep/deep_ep.cpp

@@ -143,7 +143,7 @@ Buffer::Buffer(int rank,
 
   // Create 32 MiB workspace
   // Note(ZKK):  here we allocate more(2 * M2N_NUM_WORKSPACE) to support M2N!
-  // Later we will opitimize here!
+  // Later we will optimize here!
   CUDA_CHECK(
       cudaMalloc(&workspace, 2 * M2N_NUM_WORKSPACE * NUM_WORKSPACE_BYTES));
   CUDA_CHECK(cudaMemsetAsync(

paddle/phi/infermeta/ternary.cc

@@ -1658,7 +1658,7 @@ void MultiClassNMSInferMeta(const MetaTensor& bboxes,
               "The 2nd dimension of Input(BBoxes) must be equal to "
               "last dimension of Input(Scores), which represents the "
               "predicted bboxes."
-              "But received box_dims[1](%s) != socre_dims[2](%s)",
+              "But received box_dims[1](%s) != score_dims[2](%s)",
               box_dims[1],
               score_dims[2]));
     } else {

paddle/phi/kernels/funcs/dense_tensor_iterator.cc

@@ -204,7 +204,7 @@ void DenseTensorIterator::set_output_raw_strided(int64_t output_idx,
     }
     op.current_dtype = op.target_dtype;
   } else if (op.will_resize) {
-    PADDLE_THROW(common::errors::Fatal("Opreator Reize not Implemented!"));
+    PADDLE_THROW(common::errors::Fatal("Operator Resize not Implemented!"));
   }
 }
 

paddle/phi/kernels/funcs/fused_gemm_epilogue.h

@@ -461,7 +461,7 @@ void ComputeFusedGemmEpilogueForward(const phi::GPUContext& dev_ctx,
       sizeof(bias_data)));
 
   if (enable_auxiliary && activation != "none") {
-    // Note (Ming Huang): The initialization of ReseveSpace is happened in the
+    // Note (Ming Huang): The initialization of ReserveSpace is happened in the
     // dev_ctx.Alloc. Therefore, we set real date type up here.
     if (activation == "relu") {
       phi::DataType rs_type = phi::DataType::BOOL;

test/ir/pir/test_symbol_overload.py

@@ -36,7 +36,7 @@ def forward(self, x, y):
         return res
 
 
-class SimbolNet(nn.Layer):
+class SymbolNet(nn.Layer):
     def __init__(self):
         super().__init__()
 
@@ -61,7 +61,7 @@ def forward(self, x, y):
         return z1, z2, z3, z4
 
 
-class SimbolCompareNet(nn.Layer):
+class SymbolCompareNet(nn.Layer):
     def __init__(self):
         super().__init__()
 
@@ -106,7 +106,7 @@ def base_net(self):
     def symbol_net(self):
         main_program = paddle.static.Program()
         with paddle.static.program_guard(main_program):
-            net = SimbolNet()
+            net = SymbolNet()
             x = paddle.static.data('x', self.shape_x, dtype='float32')
             y = paddle.static.data('y', self.shape_y, dtype='float32')
             x.stop_gradient = False
@@ -164,7 +164,7 @@ def base_net(self):
     def symbol_net(self):
         main_program = paddle.static.Program()
         with paddle.static.program_guard(main_program):
-            net = SimbolCompareNet()
+            net = SymbolCompareNet()
             x = paddle.static.data('x', self.shape_x, dtype='float32')
             y = paddle.static.data('y', self.shape_y, dtype='float32')
 

test/legacy_test/test_audio_backend.py

@@ -22,9 +22,9 @@
 
 class TestAudioBackends(unittest.TestCase):
     def setUp(self):
-        self.initParmas()
+        self.initParams()
 
-    def initParmas(self):
+    def initParams(self):
         def get_wav_data(dtype: str, num_channels: int, num_frames: int):
             dtype_ = getattr(paddle, dtype)
             base = paddle.linspace(-1.0, 1.0, num_frames, dtype=dtype_) * 0.1

test/legacy_test/test_audio_functions.py

@@ -30,9 +30,9 @@ def parameterize(*params):
 class TestAudioFunctions(unittest.TestCase):
     def setUp(self):
         paddle.disable_static()
-        self.initParmas()
+        self.initParams()
 
-    def initParmas(self):
+    def initParams(self):
         def get_wav_data(dtype: str, num_channels: int, num_frames: int):
             dtype_ = getattr(paddle, dtype)
             base = paddle.linspace(-1.0, 1.0, num_frames, dtype=dtype_) * 0.1

test/legacy_test/test_audio_logmel_feature.py

@@ -29,9 +29,31 @@ def parameterize(*params):
 
 class TestFeatures(unittest.TestCase):
     def setUp(self):
-        self.initParmas()
+        self.initParams()
+
+    def initParams(self):
+        """
+        初始化音频特征提取测试参数。
+
+        初始化包括:
+        - 设置音频参数(fmin, top_db, duration等)
+        - 生成测试用的波形数据
+        - 将波形数据转换为numpy数组存储
+
+        Args:
+            无显式参数，通过self属性配置:
+            dtype: 音频数据类型，默认为"float32"
+            num_channels: 音频通道数，默认为1
+            sr: 采样率，默认为16000
+            duration: 音频时长(秒)，默认为0.5
+            fmin: 最小频率，默认为0.0
+            top_db: 最大分贝，默认为80.0
+
+        Returns:
+            无返回值，但会设置以下属性:
+            waveform: 生成的波形数据(numpy数组)
+        """
 
-    def initParmas(self):
         def get_wav_data(dtype: str, num_channels: int, num_frames: int):
             dtype_ = getattr(paddle, dtype)
             base = paddle.linspace(-1.0, 1.0, num_frames, dtype=dtype_) * 0.1

test/legacy_test/test_audio_mel_feature.py

@@ -28,9 +28,9 @@ def parameterize(*params):
 
 class TestFeatures(unittest.TestCase):
     def setUp(self):
-        self.initParmas()
+        self.initParams()
 
-    def initParmas(self):
+    def initParams(self):
         def get_wav_data(dtype: str, num_channels: int, num_frames: int):
             dtype_ = getattr(paddle, dtype)
             base = paddle.linspace(-1.0, 1.0, num_frames, dtype=dtype_) * 0.1

test/xpu/test_clip_op_xpu.py

@@ -266,7 +266,7 @@ def _executed_api(self, x, min=None, max=None):
 
 support_types = get_xpu_op_support_types('clip')
 for stype in support_types:
-    # TODO(lilujia): disable int32 and int64 test temporarily, as xdnn not support corresponding resuce_mean
+    # TODO(lilujia): disable int32 and int64 test temporarily, as xdnn not support corresponding reduce_mean
     if stype in ["int32", "int64"]:
         continue
     create_test_class(globals(), XPUTestClipOp, stype)