[CodeStyle][Typos][S-[10-14]] Fix typo

Author: sphcode

_typos.toml

@@ -28,18 +28,13 @@ datas = "datas"
 feeded = "feeded"
 
 # These words need to be fixed
-schedual = "schedual"
-secenarios = "secenarios"
-sematic = "sematic"
-seperator = "seperator"
 setted = "setted"
 shoule = "shoule"
 similary = "similary"
 simplier = "simplier"
 skiped = "skiped"
 softwares = "softwares"
 specail = "specail"
-sperated = "sperated"
 splited = "splited"
 splitted = "splitted"
 stirng = "stirng"

ci_scripts/check_api_docs_en.py

@@ -14,7 +14,7 @@
         "py_files",
         str,
         None,
-        "api python files, sperated by space",
+        "api python files, separated by space",
     ],
     [
         "--api_info_file",

ci_scripts/check_api_parameters.py

@@ -33,7 +33,7 @@ def add_path(path):
 
 arguments = [
     # flags, dest, type, default, help
-    ["--rst-files", "rst_files", str, None, "api rst files, sperated by space"],
+    ["--rst-files", "rst_files", str, None, "api rst files, separated by space"],
     ["--api-info", "api_info_file", str, None, "api_info_all.json filename"],
 ]
 

docs/design/ir/overview.md

@@ -15,7 +15,7 @@ Usually, the `gap` is bridged by
 * Has a simple way to verify and debug each transformation.
 
 * Flexible to add, remove or customize transformations to fit
-the requirements of various algorithms (models) and hardware secenarios.
+the requirements of various algorithms (models) and hardware scenarios.
 
 Some other events also push us to a better unified pattern.
 

docs/design/motivation/api.md

@@ -71,7 +71,7 @@ paddle.train(topology, parameters, reader=read_ranking_model_data)
 
 # Inference using fA (or fB or fC, as they share their parameters).
 [testA, testB, testQ] = read_ranking_model_data()
-print "The sematic-vector of testA: ", paddle.infer(fA, parameters, testA)
+print "The semantic-vector of testA: ", paddle.infer(fA, parameters, testA)
 ```
 
 

docs/guides/model_convert/convert_from_pytorch/deprecated/validate_mapping_files_deprecated.py

@@ -527,7 +527,7 @@ def process_mapping_index(index_path, item_processor, context={}):
 
     column_names = []
     column_count = -1
-    table_seperator_pattern = re.compile(r"^ *\|(?P<group> *-+ *\|)+ *$")
+    table_separator_pattern = re.compile(r"^ *\|(?P<group> *-+ *\|)+ *$")
 
     expect_column_names = [
         "序号",
@@ -571,22 +571,22 @@ def process_mapping_index(index_path, item_processor, context={}):
 
         elif state == IndexParserState.table_sep_ignore:
             if (
-                not table_seperator_pattern.match(line)
+                not table_separator_pattern.match(line)
                 or len(columns) != column_count
             ):
                 raise Exception(
-                    f"Table seperator not match at line {i + 1}: {line}"
+                    f"Table separator not match at line {i + 1}: {line}"
                 )
             if not item_processor(line, i, state, output, context):
                 break
             state = IndexParserState.table_row_ignore
         elif state == IndexParserState.table_sep:
             if (
-                not table_seperator_pattern.match(line)
+                not table_separator_pattern.match(line)
                 or len(columns) != column_count
             ):
                 raise Exception(
-                    f"Table seperator not match at line {i + 1}: {line}"
+                    f"Table separator not match at line {i + 1}: {line}"
                 )
             if not item_processor(line, i, state, output, context):
                 break

docs/guides/model_convert/convert_from_pytorch/tools/get_api_difference_info.py

@@ -497,7 +497,7 @@ def process_mapping_index(index_path, item_processor, context={}):
 
     column_names = []
     column_count = -1
-    table_seperator_pattern = re.compile(r"^ *\|(?P<group> *-+ *\|)+ *$")
+    table_separator_pattern = re.compile(r"^ *\|(?P<group> *-+ *\|)+ *$")
 
     expect_column_names = [
         "序号",
@@ -541,22 +541,22 @@ def process_mapping_index(index_path, item_processor, context={}):
 
         elif state == IndexParserState.table_sep_ignore:
             if (
-                not table_seperator_pattern.match(line)
+                not table_separator_pattern.match(line)
                 or len(columns) != column_count
             ):
                 raise Exception(
-                    f"Table seperator not match at line {i + 1}: {line}"
+                    f"Table separator not match at line {i + 1}: {line}"
                 )
             if not item_processor(line, i, state, output, context):
                 break
             state = IndexParserState.table_row_ignore
         elif state == IndexParserState.table_sep:
             if (
-                not table_seperator_pattern.match(line)
+                not table_separator_pattern.match(line)
                 or len(columns) != column_count
             ):
                 raise Exception(
-                    f"Table seperator not match at line {i + 1}: {line}"
+                    f"Table separator not match at line {i + 1}: {line}"
                 )
             if not item_processor(line, i, state, output, context):
                 break

docs/practices/time_series/stock_forecast.ipynb

@@ -1348,7 +1348,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": null,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2022-12-16T06:18:50.396897Z",
@@ -1424,7 +1424,7 @@
     "\n",
     "model = paddle.Model(LSTM(num_classes, input_size, hidden_size, num_layers))\n",
     "\n",
-    "lr_schedual = paddle.optimizer.lr.CosineAnnealingDecay(\n",
+    "lr_scheduler = paddle.optimizer.lr.CosineAnnealingDecay(\n",
     "    learning_rate=learning_rate, T_max=num_epochs, verbose=False\n",
     ")\n",
     "# 设置优化器，学习率，并且把模型参数给优化器\n",

docs/practices/time_series/temperature_forecast.ipynb

@@ -946,7 +946,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": null,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2022-12-07T17:42:50.203156Z",
@@ -971,12 +971,12 @@
     "labels = InputSpec([None, 72, 1], \"float32\", \"x\")\n",
     "model = paddle.Model(Encoder(future, fea_num), inputs, labels)\n",
     "\n",
-    "lr_schedual = paddle.optimizer.lr.CosineAnnealingDecay(\n",
+    "lr_scheduler = paddle.optimizer.lr.CosineAnnealingDecay(\n",
     "    learning_rate=learning_rate, T_max=epoch_num, verbose=False\n",
     ")\n",
     "# 设置优化器，学习率，并且把模型参数给优化器\n",
     "opt = paddle.optimizer.Adam(\n",
-    "    learning_rate=lr_schedual,\n",
+    "    learning_rate=lr_scheduler,\n",
     "    parameters=model.parameters(),\n",
     "    beta1=0.9,\n",
     "    beta2=0.999,\n",