!32644 [MD] fix doc issue2 in master

Merge pull request !32644 from liyong126/fix_doc_issue2

docs/api/api_python/dataset/mindspore.dataset.OBSMindDataset.rst

@@ -40,8 +40,6 @@
         - 如果线下训练，建议为每次训练设置 `BATCH_JOB_ID` 环境变量。
         - 分布式训练中，假如使用多个节点（服务器），则必须使用每个节点全部的8张卡。如果只有一个节点（服务器），则没有这样的限制。
 
-    .. include:: mindspore.dataset.Dataset.add_sampler.rst
-
     .. include:: mindspore.dataset.Dataset.rst
 
     .. include:: mindspore.dataset.Dataset.b.rst
@@ -50,6 +48,4 @@
 
     .. include:: mindspore.dataset.Dataset.d.rst
 
-    .. include:: mindspore.dataset.Dataset.use_sampler.rst
-
     .. include:: mindspore.dataset.Dataset.zip.rst

docs/api/api_python/mindrecord/mindspore.mindrecord.FileWriter.rst

@@ -9,7 +9,7 @@
     **参数：**
 
     - **file_name** (str) - 转换生成的MindRecord文件路径。
-    - **shard_num** (int，可选) - 生成MindRecord的文件个数。默认值：1。取值范围为[1, 1000]。
+    - **shard_num** (int，可选) - 生成MindRecord的文件个数。取值范围为[1, 1000]。默认值：1。
     - **overwrite** (bool，可选) - 当指定目录存在同名文件时是否覆盖写。默认值：False。
 
     **异常：**
@@ -52,7 +52,7 @@
         **参数：**
 
         - **content** (dict) - schema内容的字典。
-        - **desc** (str，可选) - schema的描述字符。默认值：None。
+        - **desc** (str，可选) - schema的描述。默认值：None。
 
         **返回：**
 
@@ -87,7 +87,7 @@
 
     .. py:method:: open_and_set_header()
 
-        打开MindRecord文件准备写入并且设置header。该函数仅用于并行写入，并在 `write_raw_data` 函数之前调用。
+        打开MindRecord文件准备写入并且设置描述其meta信息的头部，该函数仅用于并行写入，并在 `write_raw_data` 函数之前调用。
 
         **返回：**
 

docs/api/api_python/mindrecord/mindspore.mindrecord.MnistToMR.rst

@@ -5,7 +5,7 @@
 
     **参数：**
 
-    - **source** (str) - 包含t10k-images-idx3-ubyte.gz、train-images-idx3-ubyte.gz、t10k-labels-idx1-ubyte.gz和train-labels-idx1-ubyte.gz数据集文件的目录路径。
+    - **source** (str) - 数据集目录路径，其包含t10k-images-idx3-ubyte.gz、train-images-idx3-ubyte.gz、t10k-labels-idx1-ubyte.gz和train-labels-idx1-ubyte.gz数据集文件。
     - **destination** (str) - 转换生成的MindRecord文件路径，需提前创建目录并且目录下不能存在同名文件。
     - **partition_number** (int，可选) - 生成MindRecord的文件个数。默认值：1。
 

mindspore/python/mindspore/dataset/engine/datasets_standard_format.py

@@ -421,20 +421,8 @@ class OBSMindDataset(GeneratorDataset):
 
 
     def add_sampler(self, new_sampler):
-        """
-        Add a sampler for current dataset, it's not supported for OBSMindDataset.
-
-        Args:
-            new_sampler (Sampler): The sampler to be added as the parent sampler for current dataset.
-        """
         raise NotImplementedError("add_sampler is not supported for OBSMindDataset.")
 
 
     def use_sampler(self, new_sampler):
-        """
-        Make the current dataset use the new_sampler provided by other API, it's not supported for OBSMindDataset.
-
-        Args:
-            new_sampler (Sampler): The sampler to use for the current dataset.
-        """
         raise NotImplementedError("use_sampler is not supported for OBSMindDataset.")

mindspore/python/mindspore/dataset/engine/datasets_user_defined.py

@@ -135,7 +135,7 @@ def _convert_row(row):
     """
     if isinstance(row, dict):
         raise TypeError("Input data is expected to be " \
-                        "int, float, str, bytes, Numpy array, Tensor or list-or-tuple of them, but got dict.")
+                        "int, float, str, bytes, numpy.ndarray, Tensor or list/tuple of them, but got dict.")
 
     # convert single item to np.array
     prim_type = (int, float, str, bytes, np.ndarray, Tensor)
@@ -147,7 +147,7 @@ def _convert_row(row):
         else:
             item = np.array(row, copy=False)
             if item.dtype == 'object':
-                raise TypeError("Data type of the input or converted Numpy array is expected to be " \
+                raise TypeError("Data type of the input or its converted Numpy array is expected to be " \
                                 "int or float or str, but got {}.".format(item.dtype))
         return tuple([item])
 
@@ -161,12 +161,12 @@ def _convert_row(row):
         elif isinstance(x, Tensor):      # mindspore.Tensor
             value.append(x.asnumpy())
         elif isinstance(x, dict):
-            raise TypeError("The {}st item of input data is expected to be " \
-                            "int, float, str, bytes, Numpy array, Tensor, but got dict.".format(idx))
+            raise TypeError("The {}th item of input data is expected to be " \
+                            "int, float, str, bytes, numpy.ndarray, Tensor, but got dict.".format(idx))
         else:
             item = np.array(x, copy=False)
             if item.dtype == 'object':
-                raise TypeError("Data type of {}st item of the input or converted Numpy array is expected to be " \
+                raise TypeError("Data type of {}th item of the input or its converted Numpy array is expected to be " \
                                 "int or float or str, but got {}.".format(idx, item.dtype))
             value.append(item)
     return tuple(value)

mindspore/python/mindspore/dataset/engine/obs/config_loader.py

@@ -47,7 +47,7 @@ class _Config:
             return self._convert_type(key)
         if key in self.config:
             return self.config[key]
-        raise RuntimeError("Variable {} can not found in configuration file or environment variables.".format(key))
+        raise RuntimeError("Variable {} can not be found in configuration file or environment variables.".format(key))
 
     def __setattr__(self, key, value):
         if key == 'config':

mindspore/python/mindspore/mindrecord/filewriter.py

@@ -42,8 +42,8 @@ class FileWriter:
 
     Args:
         file_name (str): File name of MindRecord file.
-        shard_num (int, optional): The Number of MindRecord files. Default: 1.
-            It should be between [1, 1000].
+        shard_num (int, optional): The Number of MindRecord files.
+            It should be between [1, 1000]. Default: 1.
         overwrite (bool, optional): Whether to overwrite if the file already exists. Default: False.
 
     Raises:
@@ -273,7 +273,7 @@ class FileWriter:
 
     def open_and_set_header(self):
         """
-        Open writer and set header. The function is only used for parallel \
+        Open writer and set header which stores meta information. The function is only used for parallel \
         writing and is called before the `write_raw_data`.
 
         Returns:

tests/ut/python/dataset/test_datasets_generator.py

@@ -641,7 +641,7 @@ def test_generator_error_1():
         data1 = ds.GeneratorDataset(generator_np, ["data"])
         for _ in data1:
             pass
-    assert "Data type of 1st item of the input or converted Numpy array is expected" in str(info.value)
+    assert "Data type of 1th item of the input or its converted Numpy array is expected" in str(info.value)
 
 
 def test_generator_error_2():
@@ -653,7 +653,7 @@ def test_generator_error_2():
         data1 = ds.GeneratorDataset(generator_np, ["data"])
         for _ in data1:
             pass
-    assert "Data type of 1st item of the input or converted Numpy array is expected" in str(info.value)
+    assert "Data type of 1th item of the input or its converted Numpy array is expected" in str(info.value)
 
 
 def test_generator_error_3():
@@ -1360,7 +1360,7 @@ def test_generator_single_input_6():
             data1 = ds.GeneratorDataset(data, ["data"], shuffle=False)
             for _ in data1.create_dict_iterator(num_epochs=1, output_numpy=True):  # each data is a dictionary
                 pass
-        assert " Data type of the input or converted Numpy array is expected" in str(info.value)
+        assert " Data type of the input or its converted Numpy array is expected" in str(info.value)
 
     assert_generator_single_input_6(generator_nested_np)
     assert_generator_single_input_6(RandomAccessDatasetInner())