From 56ce6c36fa85515e4c05c253b617e9920fd09e4b Mon Sep 17 00:00:00 2001
From: jonyguo <guozhijian@huawei.com>
Date: Wed, 7 Sep 2022 17:12:17 +0800
Subject: [PATCH] reconstruct map parameters

---
 .../api_python/dataset/map_parameter_cn.png   | Bin 0 -> 2099 bytes
 .../api_python/dataset/map_parameter_en.png   | Bin 0 -> 2379 bytes
 .../dataset/map_parameter_pyfunc_cn.png       | Bin 0 -> 2926 bytes
 .../dataset/map_parameter_pyfunc_en.png       | Bin 0 -> 3246 bytes
 .../dataset/mindspore.dataset.Dataset.e.rst   |  25 ++++++++---
 .../mindspore/dataset/engine/datasets.py      |  40 +++++++++++++-----
 .../mindspore/dataset/engine/validators.py    |  16 ++++++-
 7 files changed, 62 insertions(+), 19 deletions(-)
 create mode 100644 docs/api/api_python/dataset/map_parameter_cn.png
 create mode 100644 docs/api/api_python/dataset/map_parameter_en.png
 create mode 100644 docs/api/api_python/dataset/map_parameter_pyfunc_cn.png
 create mode 100644 docs/api/api_python/dataset/map_parameter_pyfunc_en.png

diff --git a/docs/api/api_python/dataset/map_parameter_cn.png b/docs/api/api_python/dataset/map_parameter_cn.png
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diff --git a/docs/api/api_python/dataset/mindspore.dataset.Dataset.e.rst b/docs/api/api_python/dataset/mindspore.dataset.Dataset.e.rst
index 78ee119e465..fe734fd5558 100644
--- a/docs/api/api_python/dataset/mindspore.dataset.Dataset.e.rst
+++ b/docs/api/api_python/dataset/mindspore.dataset.Dataset.e.rst
@@ -1,4 +1,4 @@
-.. py:method:: map(operations, input_columns=None, output_columns=None, column_order=None, num_parallel_workers=None, python_multiprocessing=False, cache=None, callbacks=None, max_rowsize=16, offload=None)
+.. py:method:: map(operations, input_columns=None, output_columns=None, column_order=None, num_parallel_workers=None, **kwargs)
 
     给定一组数据增强列表，按顺序将数据增强作用在数据集对象上。
 
@@ -8,17 +8,30 @@
 
     最后一个数据增强的输出列的列名由 `output_columns` 指定，如果没有指定 `output_columns` ，输出列名与 `input_columns` 一致。
 
+    - 如果使用的是 `mindspore` `dataset` 提供的数据增强（
+      `vision类 <https://www.mindspore.cn/docs/zh-CN/master/api_python/mindspore.dataset.vision.html>`_，
+      `nlp类 <https://www.mindspore.cn/docs/zh-CN/master/api_python/mindspore.dataset.text.html>`_，
+      `audio类 <https://www.mindspore.cn/docs/zh-CN/master/api_python/mindspore.dataset.audio.html>`_），请使用如下参数：
+
+      .. image:: map_parameter_cn.png
+
+    - 如果使用的是自定义PyFunc数据增强，请使用如下参数：
+
+      .. image:: map_parameter_pyfunc_cn.png
+
     参数：
         - **operations** (Union[list[TensorOperation], list[functions]]) - 一组数据增强操作，支持数据集增强算子或者用户自定义的Python Callable对象。map操作将按顺序将一组数据增强作用在数据集对象上。
         - **input_columns** (Union[str, list[str]], 可选) - 第一个数据增强操作的输入数据列。此列表的长度必须与 `operations` 列表中第一个数据增强的预期输入列数相匹配。默认值：None。表示所有数据列都将传递给第一个数据增强操作。
         - **output_columns** (Union[str, list[str]], 可选) - 最后一个数据增强操作的输出数据列。如果 `input_columns` 长度不等于 `output_columns` 长度，则必须指定此参数。列表的长度必须必须与最后一个数据增强的输出列数相匹配。默认值：None，输出列将与输入列具有相同的名称。
         - **column_order** (Union[str, list[str]], 可选) - 指定传递到下一个数据集操作的数据列的顺序。如果 `input_columns` 长度不等于 `output_columns` 长度，则必须指定此参数。注意：参数的列名不限定在 `input_columns` 和 `output_columns` 中指定的列，也可以是上一个操作输出的未被处理的数据列。默认值：None，按照原输入顺序排列。
         - **num_parallel_workers** (int, 可选) - 指定map操作的多进程/多线程并发数，加快处理速度。默认值：None，将使用 `set_num_parallel_workers` 设置的并发数。
-        - **python_multiprocessing** (bool, 可选) - 启用Python多进程模式加速map操作。当传入的 `operations` 计算量很大时，开启此选项可能会有较好效果。默认值：False。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
-        - **callbacks** (DSCallback, list[DSCallback], 可选) - 要调用的Dataset回调函数列表。默认值：None。
-        - **max_rowsize** (int, 可选) - 指定在多进程之间复制数据时，共享内存分配的最大空间，仅当 `python_multiprocessing` 为True时，该选项有效。默认值：16，单位为MB。
-        - **offload** (bool, 可选) - 是否进行异构硬件加速，详情请阅读 `数据准备异构加速 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/dataset_offload.html>`_ 。默认值：None。
+        - **\*\*kwargs** - 其他参数。
+
+          - python_multiprocessing (bool, 可选) - 启用Python多进程模式加速map操作。当传入的 `operations` 计算量很大时，开启此选项可能会有较好效果。默认值：False。
+          - max_rowsize (int, 可选) - 指定在多进程之间复制数据时，共享内存分配的最大空间，仅当 `python_multiprocessing` 为True时，该选项有效。默认值：16，单位为MB。
+          - cache (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+          - callbacks (DSCallback, list[DSCallback], 可选) - 要调用的Dataset回调函数列表。默认值：None。
+          - offload (bool, 可选) - 是否进行异构硬件加速，详情请阅读 `数据准备异构加速 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/dataset_offload.html>`_ 。默认值：None。
 
     .. note::
         - `operations` 参数接收 `TensorOperation` 类型的数据处理操作，以及用户定义的Python函数(PyFuncs)。
diff --git a/mindspore/python/mindspore/dataset/engine/datasets.py b/mindspore/python/mindspore/dataset/engine/datasets.py
index 60372faec96..348cc0067ce 100644
--- a/mindspore/python/mindspore/dataset/engine/datasets.py
+++ b/mindspore/python/mindspore/dataset/engine/datasets.py
@@ -767,8 +767,7 @@ class Dataset:
 
     @check_map
     def map(self, operations, input_columns=None, output_columns=None, column_order=None,
-            num_parallel_workers=None, python_multiprocessing=False, cache=None, callbacks=None,
-            max_rowsize=16, offload=None):
+            num_parallel_workers=None, **kwargs):
         """
         Apply each operation in operations to this dataset.
 
@@ -780,6 +779,18 @@ class Dataset:
         The columns outputted by the very last operation will be assigned names specified by
         `output_columns`, and if not specified, the column name of output column is same as that of `input_columns`.
 
+        - If you use transformations (
+          `vision transform <https://www.mindspore.cn/docs/en/master/api_python/mindspore.dataset.vision.html>`_,
+          `nlp transform <https://www.mindspore.cn/docs/en/master/api_python/mindspore.dataset.text.html>`_,
+          `audio transform <https://www.mindspore.cn/docs/en/master/api_python/mindspore.dataset.audio.html>`_)
+          provided by mindspore dataset, please use the following parameters:
+
+          .. image:: map_parameter_en.png
+
+        - If you use user-defined transform as PyFunc (Python Func), please use the following parameters:
+
+          .. image:: map_parameter_pyfunc_en.png
+
         Args:
             operations (Union[list[TensorOperation], list[functions]]): List of operations to be
                 applied on the dataset. Operations are applied in the order they appear in this list.
@@ -798,14 +809,21 @@ class Dataset:
                 Caution: the list here is not just the columns specified in parameter input_columns and output_columns.
             num_parallel_workers (int, optional): Number of threads used to process the dataset in
                 parallel (default=None, the value from the configuration will be used).
-            python_multiprocessing (bool, optional): Parallelize Python operations with multiple worker processes. This
-                option could be beneficial if the Python operation is computational heavy (default=False).
-            cache (DatasetCache, optional): Use tensor caching service to speed up dataset processing.
-                (default=None, which means no cache is used).
-            callbacks (DSCallback, list[DSCallback], optional): List of Dataset callbacks to be called (Default=None).
-            max_rowsize (int, optional): Maximum size of row in MB that is used for shared memory allocation to copy
-               data between processes.  This is only used if python_multiprocessing is set to True (Default=16).
-            offload (bool, optional): Flag to indicate whether offload is used (Default=None).
+            **kwargs:
+
+                - python_multiprocessing (bool, optional): Parallelize Python operations with multiple worker processes.
+                  This option could be beneficial if the Python operation is computational heavy (default=False).
+
+                - max_rowsize (int, optional): Maximum size of row in MB that is used for shared memory allocation to
+                  copy data between processes.  This is only used if python_multiprocessing is set to True (Default=16).
+
+                - cache (DatasetCache, optional): Use tensor caching service to speed up dataset processing.
+                  (default=None, which means no cache is used).
+
+                - callbacks (DSCallback, list[DSCallback], optional): List of Dataset callbacks to be called
+                  (Default=None).
+
+                - offload (bool, optional): Flag to indicate whether offload is used (Default=None).
 
         Note:
             - Input `operations` accepts TensorOperations defined in mindspore.dataset part, plus user-defined
@@ -914,7 +932,7 @@ class Dataset:
                            "Please use '.project' operation instead.")
 
         return MapDataset(self, operations, input_columns, output_columns, column_order, num_parallel_workers,
-                          python_multiprocessing, cache, callbacks, max_rowsize, offload)
+                          **kwargs)
 
     @check_filter
     def filter(self, predicate, input_columns=None, num_parallel_workers=None):
diff --git a/mindspore/python/mindspore/dataset/engine/validators.py b/mindspore/python/mindspore/dataset/engine/validators.py
index d6396d0650d..06e8d92282a 100644
--- a/mindspore/python/mindspore/dataset/engine/validators.py
+++ b/mindspore/python/mindspore/dataset/engine/validators.py
@@ -1316,16 +1316,28 @@ def check_shuffle(method):
     return new_method
 
 
+def get_map_kwargs_from_dict(param_dict):
+    """get map operation kwargs parameters."""
+    if param_dict is not None:
+        python_multiprocessing = param_dict.get("python_multiprocessing", False)
+        max_rowsize = param_dict.get("max_rowsize", 16)
+        cache = param_dict.get("cache", None)
+        callbacks = param_dict.get("callbacks", None)
+        offload = param_dict.get("offload", None)
+    return python_multiprocessing, max_rowsize, cache, callbacks, offload
+
+
 def check_map(method):
     """check the input arguments of map."""
 
     @wraps(method)
     def new_method(self, *args, **kwargs):
         from mindspore.dataset.callback import DSCallback
-        [operations, input_columns, output_columns, column_order, num_parallel_workers, python_multiprocessing, cache,
-         callbacks, max_rowsize, offload], _ = \
+        [operations, input_columns, output_columns, column_order, num_parallel_workers, param_dict], _ = \
             parse_user_args(method, *args, **kwargs)
 
+        (python_multiprocessing, max_rowsize, cache, callbacks, offload) = get_map_kwargs_from_dict(param_dict)
+
         # check whether network computing operator exist in input operations(python function)
         # check used variable and function document whether contain computing operator
         from types import FunctionType