From 6fbb1e0e0e6119f2a3b70771f107590b06c4e76d Mon Sep 17 00:00:00 2001
From: xumengjuan1 <xumengjuan1@huawei.com>
Date: Wed, 6 Apr 2022 10:20:53 +0800
Subject: [PATCH] modify doc

---
 mindspore/python/mindspore/communication/_comm_helper.py  | 5 +++--
 .../python/mindspore/dataset/vision/py_transforms.py      | 8 ++++----
 .../python/mindspore/mindrecord/tools/tfrecord_to_mr.py   | 2 +-
 mindspore/python/mindspore/ops/operations/random_ops.py   | 4 ++--
 4 files changed, 10 insertions(+), 9 deletions(-)

diff --git a/mindspore/python/mindspore/communication/_comm_helper.py b/mindspore/python/mindspore/communication/_comm_helper.py
index 9fe7d7428e2..05b3c51c083 100644
--- a/mindspore/python/mindspore/communication/_comm_helper.py
+++ b/mindspore/python/mindspore/communication/_comm_helper.py
@@ -97,8 +97,9 @@ DEFAULT_BACKEND = Backend("hccl")
 class GlobalComm:
     """
     World communication information. The GlobalComm is a global class. The members contain:
-        BACKEND: The communication library used, using HCCL/NCCL.
-        WORLD_COMM_GROUP: Global communication domain.
+
+    - BACKEND: The communication library used, using HCCL/NCCL.
+    - WORLD_COMM_GROUP: Global communication domain.
     """
     BACKEND = DEFAULT_BACKEND
     WORLD_COMM_GROUP = HCCL_WORLD_COMM_GROUP
diff --git a/mindspore/python/mindspore/dataset/vision/py_transforms.py b/mindspore/python/mindspore/dataset/vision/py_transforms.py
index 578cd3b3c3b..f6a43bd7822 100644
--- a/mindspore/python/mindspore/dataset/vision/py_transforms.py
+++ b/mindspore/python/mindspore/dataset/vision/py_transforms.py
@@ -878,12 +878,12 @@ class RandomAffine(py_transforms.PyTensorOperation):
         shear (Union[float, Sequence[float, float], Sequence[float, float, float, float]], optional):
             Range of shear factor to select from.
             If float is provided, a shearing parallel to X axis with a factor selected from
-            (-`shear`, `shear`) will be applied.
+            (- `shear` , `shear` ) will be applied.
             If Sequence[float, float] is provided, a shearing parallel to X axis with a factor selected
-            from (`shear`[0], `shear`[1]) will be applied.
+            from ( `shear` [0], `shear` [1]) will be applied.
             If Sequence[float, float, float, float] is provided, a shearing parallel to X axis with a factor selected
-            from (`shear`[0], `shear`[1]) and a shearing parallel to Y axis with a factor selected from
-            (`shear`[2], `shear`[3]) will be applied. Default: None, means no shearing.
+            from ( `shear` [0], `shear` [1]) and a shearing parallel to Y axis with a factor selected from
+            ( `shear` [2], `shear` [3]) will be applied. Default: None, means no shearing.
         resample (Inter, optional): Method of interpolation. It can be Inter.BILINEAR, Inter.NEAREST
             or Inter.BICUBIC. If the input PIL Image is in mode of "1" or "P", Inter.NEAREST will be
             used directly. Default: Inter.NEAREST.
diff --git a/mindspore/python/mindspore/mindrecord/tools/tfrecord_to_mr.py b/mindspore/python/mindspore/mindrecord/tools/tfrecord_to_mr.py
index 6245bb26093..98f17b995cb 100644
--- a/mindspore/python/mindspore/mindrecord/tools/tfrecord_to_mr.py
+++ b/mindspore/python/mindspore/mindrecord/tools/tfrecord_to_mr.py
@@ -75,7 +75,7 @@ class TFRecordToMR:
         source (str): TFRecord file to be transformed.
         destination (str): MindRecord file path to transform into, ensure that no file with the same name
             exists in the directory.
-        feature_dict (dict[str, `FixedLenFeature <https://www.tensorflow.org/api_docs/python/tf/io/FixedLenFeature>`_ ]): Dictionary
+        feature_dict (dict[str, `FixedLenFeature <https://www.tensorflow.org/api_docs/python/tf/io/FixedLenFeature>`_]): Dictionary
             that states the feature type, and `VarLenFeature <https://www.tensorflow.org/api_docs/python/tf/io/VarLenFeature>`_
             is not supported.
         bytes_fields (list[str], optional): The bytes fields which are in `feature_dict` and can be images bytes.
diff --git a/mindspore/python/mindspore/ops/operations/random_ops.py b/mindspore/python/mindspore/ops/operations/random_ops.py
index 3907ddf75b2..db3b68a3d8b 100644
--- a/mindspore/python/mindspore/ops/operations/random_ops.py
+++ b/mindspore/python/mindspore/ops/operations/random_ops.py
@@ -748,8 +748,8 @@ class LogUniformCandidateSampler(PrimitiveWithInfer):
     Outputs:
         Tuple of 3 Tensors.
 
-        - **sampled_candidates** (Tensor) - A Tensor with shape :math:`(num\_sampled,)` and
-        the same type as `true_classes`.
+        - **sampled_candidates** (Tensor) - A Tensor with shape :math:`(num\_sampled,)`
+          and the same type as `true_classes`.
         - **true_expected_count** (Tensor) - A Tensor with the same shape as `true_classes and` type float32.
         - **sampled_expected_count** (Tensor) - A Tensor with the same shape as `sampled_candidates` and type float32.