Update parse grammar support tensor get item and set item by tensor index.

docs/source_en/constraints_on_network_construction.md

@@ -103,12 +103,28 @@ The index operation includes `tuple` and` Tensor`. The following focuses on the
 - Boolean constant index: index is `True`, index is `False` is not supported temporarily.
   - Value: `tensor_x[True]`.
   - Assignment: Not supported yet.
+  
 - Tensor index: index is `Tensor`
-  - Value: Not supported yet.
-  - Assignment: `tensor_x[index] = u`, `index` only supports `Tensor` of type` bool`.
+   - Value: `tensor_x [index]`, `index` must be `Tensor` of type `int32`, the element value range is `[0, tensor_x.shape[0])`.
+   - Assignment: `tensor_x [index] = U`.
+      - `tensor_x` data type must be one of the following: `float16`, `float32`, `int8`, `uint8`.
+      - `index` must be `Tensor` of type `int32`, the element value range is `[0, tensor_x.shape [0])`.
+      - `U` can be `Number`, `Tensor`, `Tuple` only containing `Number`, `Tuple` only containing `Tensor`.
+        - Single `Number` or every `Number` in  `Tuple` must be the same type as `tensor_x`, ie
+          When the data type of `tensor_x` is `uint8` or `int8`, the `Number` type should be `int`;
+          When the data type of `tensor_x` is `float16` or `float32`, the `Number` type should be `float`.
+        - Single `Tensor` or every `Tensor in Tuple` must be consistent with the data type of `tensor_x`,
+          when single `Tensor`, the `shape` should be equal to or broadcast as `index.shape + tensor_x.shape [1:]`.
+        - `Tuple` containing `Number` must meet requirement:
+          `len (Tuple) = (index.shape + tensor_x.shape [1:]) [-1]`.
+        - `Tuple` containing `Tensor` must meet requirements:
+          the `shape` of each `Tensor` should be the same,
+          `(len (Tuple),) + Tensor.shape` should be equal to or broadcast as `index.shape + tensor_x.shape [1:]`.
+
 - None constant index: index is `None`
   - Value: `tensor_x[None]`, results are consistent with numpy.
   - Assignment: Not supported yet.
+
 - tuple index: index is `tuple`
   - The tuple element is a slice:
     - Value: for example `tensor_x[::,: 4, 3: 0: -1]`.
@@ -126,7 +142,7 @@ In addition, tuple also supports slice value operation, `tuple_x [start: stop: s
 ### Unsupported Syntax
 
 Currently, the following syntax is not supported in network constructors: 
- `break`, `continue`, `pass`, `raise`, `yield`, `async for`, `with`, `async with`, `assert`, `import`, and `await`.
+ `raise`, `yield`, `async for`, `with`, `async with`, `assert`, `import`, and `await`.
 
 ## Network Definition Constraints
 

docs/source_zh_cn/constraints_on_network_construction.md

@@ -102,8 +102,22 @@
   - 取值：`tensor_x[True]`。
   - 赋值：暂不支持。
 - Tensor索引：index为`Tensor`
-  - 取值：暂不支持。
-  - 赋值：`tensor_x[index]=u`，`index`仅支持`bool`类型的`Tensor`。
+  - 取值：`tensor_x[index]`，`index`必须是`int32`类型的`Tensor`，元素取值范围在`[0, tensor_x.shape[0])`。
+  - 赋值：`tensor_x[index]=U`。
+    - `tensor_x`的数据类型必须是下面一种： `float16`，`float32`，`int8`，`uint8`。
+    - `index`必须是`int32`类型的`Tensor`，元素取值范围在`[0, tensor_x.shape[0])`。
+    - `U`可以是`Number`，`Tensor`，只包含`Number`的`Tuple`，只包含`Tensor`的`Tuple`。
+      - 单个`Number`和`Tuple`里的每个`Number`必须与`tensor_x`的数据类型属于同一类，即
+        当`tensor_x`的数据类型是`uint8`或者`int8`时，`Number`类型应该是`int`；
+        当`tensor_x`的数据类型是`float16`或者`float32`时，`Number`类型应该是`float`。
+      - 单个`Tensor`和`Tuple`里的每个`Tensor`必须与`tensor_x`的数据类型一致，
+        单个`Tensor`时，其`shape`需等于或者可广播为`index.shape + tensor_x.shape[1:]`。
+      - 包含`Number`的`Tuple`需满足下面条件：
+        `len(Tuple) = (index.shape + tensor_x.shape[1:])[-1]`。
+      - 包含`Tensor`的`Tuple`需满足下面条件：
+        每个`Tensor`的`shape`一样；
+        `(len(Tuple),) + Tensor.shape`等于或者可广播为`index.shape + tensor_x.shape[1:]`。
+      
 - None常量索引：index为`None`
   - 取值：`tensor_x[None]`，结果与numpy保持一致。
   - 赋值：暂不支持。
@@ -124,7 +138,7 @@
 ### 不支持的语法
 
 目前在网络构造函数里面暂不支持以下语法： 
- `break`、 `continue`、 `pass`、 `raise`、 `yield`、 `async for`、 `with`、 `async with`、 `assert`、 `import`、 `await`。
+ `raise`、 `yield`、 `async for`、 `with`、 `async with`、 `assert`、 `import`、 `await`。
 
 ## 网络定义约束