注释

src/mindspore2022/tests/dataset_mock.py

@@ -1,3 +1,6 @@
+这段代码是一个Python类的实现，名为`MindData`，它是一个用于模拟MindSpore框架中数据集处理的桩（Stub）。下面是对这段代码的逐行注释：
+
+```python
 # Copyright 2020 Huawei Technologies Co., Ltd
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
@@ -12,77 +15,94 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ============================================================================
+
 '''Remove after MindData merge to MindSpore '''
 import numpy as np
 
 from mindspore import Tensor
 
-
 class MindData:
     """ Stub for MindData """
-
+    # 构造函数，初始化MindData类的实例
     def __init__(self, size=1, batch_size=None, repeat_count=1,
                  np_types=None, output_shapes=None, input_indexs=()):
-        self._size = size
+        self._size = size  # 数据集的大小
-        self._batch_size = batch_size
+        self._batch_size = batch_size  # 批处理大小
-        self._repeat_count = repeat_count
+        self._repeat_count = repeat_count  # 重复次数
-        self._np_types = np_types
+        self._np_types = np_types  # NumPy数据类型
-        self._output_shapes = output_shapes
+        self._output_shapes = output_shapes  # 输出形状
-        self._input_indexs = input_indexs
+        self._input_indexs = input_indexs  # 输入索引
-        self._iter_num = 0
+        self._iter_num = 0  # 迭代次数计数器
-        self.dynamic_setting = [False, None]
+        self.dynamic_setting = [False, None]  # 动态设置标志和值
-
+
+    # 获取数据集大小
     def get_dataset_size(self):
         return self._size
 
+    # 获取重复次数
     def get_repeat_count(self):
         return self._repeat_count
 
+    # 获取批处理大小
     def get_batch_size(self):
         return self._batch_size
 
+    # 获取输出数据类型
     def output_types(self):
         return self._np_types
 
+    # 获取输出形状
     def output_shapes(self):
         return self._output_shapes
 
+    # 输入索引属性
     @property
     def input_indexs(self):
         return self._input_indexs
 
+    # 设备队列设置
     def device_que(self, send_epoch_end=True, create_data_info_queue=False):
         self.queue_name = '6ba41974-209e-11ea-88b0-a24efeb2c736'
         self.send_epoch_end = send_epoch_end
         return self
 
+    # 创建元组迭代器
     def create_tuple_iterator(self, num_epochs=-1, do_copy=True):
         return self.__iter__()
 
+    # 发送数据
     def send(self, num_epochs=-1):
         pass
 
+    # 停止发送数据
     def stop_send(self):
         pass
 
+    # 释放资源
     def release(self):
         pass
 
+    # 继续发送数据
     def continue_send(self):
         pass
 
+    # 获取数据信息
     def get_data_info(self):
         pass
 
+    # 动态最小最大形状
     def dynamic_min_max_shapes(self):
         pass
 
+    # 获取长度
     def __len__(self):
         return self._size
 
+    # 迭代器
     def __iter__(self):
         return self
 
+    # 获取下一个元素
     def __next__(self):
         if self._size < self._iter_num:
             raise StopIteration
@@ -90,11 +110,13 @@ class MindData:
         next_value = []
         for shape, typ in zip(self._output_shapes, self._np_types):
             next_value.append(Tensor(np.ndarray(shape, typ)))
-
         return tuple(next_value)
 
+    # 下一个元素
     def next(self):
         return self.__next__()
 
+    # 重置迭代器
     def reset(self):
         self._iter_num = 0
+