Fix markdown anchors

docs/apis/data_en.md

@@ -128,7 +128,7 @@ The requirements of `SegDataset` for the file list are as follows:
 
 Remote sensing images come from various sources and their data formats are very complicated. PaddleRS provides a unified interface for reading remote sensing images of different types and formats. At present, PaddleRS can read common file formats such as .png, .jpg, .bmp, and .npy, as well as handle GeoTiff, img, and other image formats commonly used in remote sensing.
 
-Depending on the practical demands, the user can choose `paddlers.transforms.decode_image()` or `paddlers.transforms.DecodeImg` to read data. `DecodeImg` is one of [Data transformation operators](#data-transformation-operators), can be combined with other operators. `decode_image` is the encapsulation of `DecodeImg` operator, which is convenient use in the way of function calls.
+Depending on the practical demands, the user can choose `paddlers.transforms.decode_image()` or `paddlers.transforms.DecodeImg` to read data. `DecodeImg` is one of [data transformation operators](#data-transformation-operators), can be combined with other operators. `decode_image` is the encapsulation of `DecodeImg` operator, which is convenient use in the way of function calls.
 
 The parameter list of `decode_image()` function is as follows:
 
@@ -148,7 +148,7 @@ The return format is as follows:
 - If `read_geo_info` is `False`, the image ([h, w, c] arrangement) is returned in the format of `numpy.ndarray`.
 - If `read_geo_info` is `True`, return a tuple consisting of two elements. The first element is the image data, and the second element is a dictionary containing the geographic information of the image, such as the geotransform information and geographic projection information.
 
-## Data Transformation Operator
+## Data Transformation Operators
 
 In PaddleRS a series of classes are defined that, when instantiated, perform certain data preprocessing or data augmentation operations by calling the `__call__` method. PaddleRS calls these classes data preprocessing/data augmentation operators, and collectively **Data Transform Operators**. All data transformation operators inherit from the parent class[`Transform`](https://github.com/PaddlePaddle/PaddleRS/blob/develop/paddlers/transforms/operators.py).
 

docs/apis/infer_en.md

@@ -230,7 +230,7 @@ Input parameter list:
 |`repeats`|`int`|Number of repetitions used to assess model reasoning and pre- and post-processing speed. If it is greater than `1`, repeats the prediction and averages the time.|`1`|
 |`quiet`|`bool`|If `True`, no timing information will be printed.|`False`|
 
-`Predictor.predict()`returns exactly the same format as the graph inference API. For details, please refer to [Dynamic Graph Inference API](#dynamic-graph-inference-apis).
+`Predictor.predict()`returns exactly the same format as the graph inference API. For details, please refer to [Dynamic Graph Inference APIs](#dynamic-graph-inference-apis).
 
 ### `Predictor.slider_predict()`
 

docs/intro/transforms_cn.md

@@ -31,11 +31,3 @@ PaddleRS对不同遥感任务需要的数据预处理/数据增强（合称为
 | ResizeByShort        | 调整输入影像大小，保持纵横比不变（根据短边计算缩放系数）。 | 所有任务 | ... |
 | SelectBand           | 对输入影像进行波段选择。 | 所有任务 | ... |
 | ...                  | ... | ... | ... |
-
-## 组合算子
-
-在实际的模型训练过程中，常常需要组合多种数据预处理与数据增强策略。PaddleRS提供了`paddlers.transforms.Compose`以便捷地组合多个数据变换算子，使这些算子能够串行执行。关于`paddlers.transforms.Compose`的具体用法请参见[API说明](../apis/data_cn.md)。
-
-## 构造算子
-
-参见[此文档](transforms_cons_params_cn.md)。

docs/intro/transforms_en.md

@@ -31,11 +31,3 @@ PaddleRS has organically integrated the data preprocessing/data augmentation (co
 | ResizeByShort        | Resize the input image, keeping the aspect ratio unchanged (calculate the scaling factor according to the short edge). | All tasks | ... |
 | SelectBand           | Select the band of the input image. | All tasks | ... |
 | ...                  | ... | ... | ... |
-
-## Combinatorial Operator
-
-During the model training process, it is often necessary to combine a variety of data preprocessing and data augmentation strategies. PaddleRS provides `paddlers.transforms.Compose` to easily combine multiple data transformation operators so that they can be executed serially. For the specific usage of the `paddlers.transforms.Compose` please see [API Description](../apis/data_en.md).
-
-## Operator Construction
-
-See [this document](transforms_cons_params_en.md).