diff --git a/docs/msadapter/docs/source_zh_cn/api.rst b/docs/msadapter/docs/source_zh_cn/api.rst
index 9137473e6454f84e80808f130286f631b3c6c414..21ac65550d65147a804db81c9f956da29974d160 100644
--- a/docs/msadapter/docs/source_zh_cn/api.rst
+++ b/docs/msadapter/docs/source_zh_cn/api.rst
@@ -129,56 +129,6 @@ Dataloader中的pin_memory参数仅支持设置为False
             return data.pin_memory(device)
     TypeError: pin_memory() takes 1 positional argument but 2 were given
 
-不支持tensor.backward()操作
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-示例代码：
-
-.. code-block::
-
-    import torch
-    x = torch.randn(2,)
-    x.backward()
-
-报错信息如下：
-
-.. code-block::
-
-    Traceback (most recent call last):
-        File "/path/to/your/demo.py", line XX, in <module>
-            x.backward()
-        File "/path/to/your/torch/_tensor.py", line 325, in backward
-            raise ValueError('not support Tensor.backward yet.')
-    ValueError: not support Tensor.backward yet.
-
-不支持to(device)操作
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-示例代码：
-
-.. code-block::
-
-    import torch
-    x = torch.randn(2,)
-    device = "cuda"
-    x.to(device)
-
-报错信息如下：
-
-.. code-block::
-
-    Traceback (most recent call last):
-        File "/path/to/your/demo.py", line XX, in <module>
-            x.to(device)
-        File "/path/to/your/mindspore/common/tensor.py", line 3018, in to
-            return self if self.dtype == dtype else self._to(dtype)
-    TypeError: _to(): argument 'dtype' (position 1) must be mstype, not str.
-
-    ----------------------------------------------------
-    - C++ Call Stack: (For framework developers)
-    ----------------------------------------------------
-    mindspore/ccsrc/pynative/op_function/converter.cc:657 Parse
-
 MindSpore导出的ckpt文件无法被直接加载到PyTorch模型中
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
diff --git a/docs/msadapter/docs/source_zh_cn/msadapter_user_guide/constraints.md b/docs/msadapter/docs/source_zh_cn/msadapter_user_guide/constraints.md
index c1fd89fa8b419fdba25d9c4fb5c42f8d6bcda204..a4b718d54f2138d4485d131b5aee77cf0d0461eb 100755
--- a/docs/msadapter/docs/source_zh_cn/msadapter_user_guide/constraints.md
+++ b/docs/msadapter/docs/source_zh_cn/msadapter_user_guide/constraints.md
@@ -4,63 +4,12 @@
 
 本文介绍MindSpore和PyTorch实现上的主要区别：
 
-1. 微分机制
-2. Dispatch机制
-3. Storage机制
-4. 静态编译机制
+1. Dispatch机制
+2. Storage机制
+3. 静态编译机制
 
 这些机制的不同，导致用户需要手动修改代码，或者部分功能暂时不支持。
 
-## 微分机制
-
-PyTorch 使用的是动态计算图，运算在代码执行时立即计算，正反向计算图在每次前向传播时动态构建。PyTorch微分为命令式反向微分，更符合面对对象编程的使用习惯。
-
-MindSpore使用函数式自动微分的设计理念，提供更接近于数学语义的自动微分接口。MindSpore的微分可以简单理解为函数包装了一个模型，接口是一个函数，而PyTorch的接口是模型。
-
-详情参考[MindSpore函数式微分](https://www.mindspore.cn/tutorials/zh-CN/master/beginner/autograd.html)。
-
-由于两者底层设计的不同，MSAdapter不支持以下相关接口：
-
-- torch.Tensor.backward()
-- torch.autograd.*
-
-部分相关接口PyTorch原始用法如下：
-
-```python
-loss.backward()
-```
-
-```python
-loss.backward(gradient_tensor)
-```
-
-由于计算图的实现差异（包含命令式微分与函数式微分的差异），**原始正向计算以及反向计算需要用户手动进行如下修改**：
-
-原始PyTorch写法：
-
-```python
-outputs = model(inputs)
-loss = criterion(outputs, labels)
-loss.backward()
-```
-
-MSAdapter修改后的写法：
-
-```python
-import mindspore
-def forward_fn(inputs, labels):
-    outputs = model(inputs)
-    loss = criterion(outputs, labels)
-    return loss
-grad_fn = mindspore.value_and_grad(forward_fn, None, weights=model.trainable_params())
-
-loss, grads = grad_fn(inputs, labels)
-```
-
-mindspore.value_and_grad的第二个参数为grad_position，定义对于哪些输入进行求导。当用户设置为None的时候必须定义weights。详细定义可以参考[mindspore.value_and_grad](https://www.mindspore.cn/docs/zh-CN/master/api_python/mindspore/mindspore.value_and_grad.html)。
-
-MSAdapter只需要调用grad_fn就能够一次性调用正向计算加反向计算。
-
 ## Dispatch机制
 
 `torch.dispatch` 是 PyTorch 中用于拦截和自定义张量操作的机制。它允许开发者在张量运算被调用时插入自己的逻辑，无论是为了调试、性能优化，还是实现特定领域的功能增强。这个特性是在 PyTorch 1.7中引入的，并且为高级用户提供了强大的能力来扩展PyTorch的功能。
diff --git a/docs/msadapter/docs/source_zh_cn/msadapter_user_guide/install.md b/docs/msadapter/docs/source_zh_cn/msadapter_user_guide/install.md
index c478bbeaa5e3fc7195ed3b72f9e45e6233b90fb9..fd4522993c69b62f164698593b01249938de22a1 100755
--- a/docs/msadapter/docs/source_zh_cn/msadapter_user_guide/install.md
+++ b/docs/msadapter/docs/source_zh_cn/msadapter_user_guide/install.md
@@ -18,8 +18,8 @@ pip install mindspore
 - 如果用户希望直接使用源码，设置如下环境环境变量：
 
     ``` bash
-    git clone https://openi.pcl.ac.cn/OpenI/MSAdapter
-    export $PYTHONPATH=your_workspace/MSAdapter/mindtorch
+    export PYTHONPATH=${your_workspace}/msadapter/:$PYTHONPATH
+    export PYTHONPATH=${your_workspace}/msadapter/msa_thirdparty:$PYTHONPATH
     ```
 
     其中，your_workspace是git clone下载的目录。此方法不会影响用户的PyTorch使用。
@@ -27,9 +27,12 @@ pip install mindspore
 - 如果用户希望以Python安装包编译的形式使用，进入MSAdapter目录，进行源码编译操作：
 
     ```bash
-    git clone https://openi.pcl.ac.cn/OpenI/MSAdapter
-    cd MSAdapter
-    pip install .
+    git clone https://gitee.com/mindspore/msadapter.git
+    cd msadapter
+    bash scripts/build.sh
+    pip install ${your_workspace}/msadapter/dist/*.whl
+    export PYTHONPATH=/*/site-packages/msa_thirdparty:$PYTHONPATH
+    # /*/site-packages 指python环境下的安装包路径，可以使用pip show msadapter获取。
     ```
 
     直接安装会覆盖原始PyTorch的使用，如果希望同时使用PyTorch和MSAdapter，可以考虑直接使用源码。
diff --git a/docs/msadapter/docs/source_zh_cn/msadapter_user_guide/quick_start.md b/docs/msadapter/docs/source_zh_cn/msadapter_user_guide/quick_start.md
index 7d5449c5632261fdbce4aff5489e6fdeae358ef2..fa53fcc1f527c279d2dc4d950a5241e4526b271e 100755
--- a/docs/msadapter/docs/source_zh_cn/msadapter_user_guide/quick_start.md
+++ b/docs/msadapter/docs/source_zh_cn/msadapter_user_guide/quick_start.md
@@ -6,13 +6,8 @@
 
 模型适配详细步骤如下：
 
-1. 导入依赖包
-2. 模型定义
-3. 参数解析
-4. 数据下载与预处理
-5. 模型构建
-6. 定义损失函数
-7. 训练
+1. 使能MSAdapter
+2. 训练
 
 ## PyTorch用例
 
@@ -86,219 +81,35 @@ if __name__ == "__main__":
 
 接下来，对应PyTorch的完整流程，说明如何使用MSAdapter完成相同的任务。
 
-### 1. 导入依赖包
+### 1. 使能MSAdapter
 
-MSAdapter已经兼容PyTorch的各类子模块，无需修改。
+MSAdapter已经兼容PyTorch的各类子模块，这里使能MSAdapter有两种方式第一种是微调脚本切换后端，第二种是环境变量切换。
 
-```python
-import torch
-import torch.nn as nn
-import torch.optim as optim
-from torch.utils.data import DataLoader
-from torchvision import datasets, transforms
-```
-
-### 2. 模型定义
-
-MSAdapter已经兼容torch.nn.Module，无需修改。
-
-```python
-class ToyModel(nn.Module):
-    def __init__(self):
-        super(ToyModel, self).__init__()
-        self.net1 = nn.Linear(784, 64)
-        self.relu = nn.ReLU()
-        self.net2 = nn.Linear(64, 10)
-    def forward(self, x):
-        return self.net2(self.relu(self.net1(x)))
-```
-
-### 3. 参数解析
-
-argparse是常规Python，与深度学习无关，无需修改。
-
-### 4. 数据下载与预处理
-
-MSAdapter已经兼容基础数据集相关接口，无需修改。
-
-```python
-def data_process(inputs, labels):
-    inputs = inputs.view(inputs.size(0), -1)
-    return inputs, labels
-
-# 预处理函数
-transform = transforms.Compose([
-    transforms.ToTensor(),
-    transforms.Normalize((0.5,), (0.5,))
-])
-train_dataset = datasets.MNIST(root='./data', train=True, download=True, transform=transform)
-# 加载数据集
-train_loader = DataLoader(train_dataset, batch_size=args.batch_size, shuffle=True)
-```
-
-### 5. 模型构建
-
-MSAdapter在torch.nn.Module.to()调用上与PyTorch有差别。
-
-```python
-model = ToyModel().to('cuda')
-```
-
-由于MSAdapter暂时不支持torch.nn.Module.to接口，需要转换为如下方式，MSAdapter默认将模型放置于NPU上。若用户希望将模型或者张量搬运至CPU，则需要调用.cpu()接口。
-
-修改如下：
-
-```python
-model = ToyModel()
-```
-
-### 6. 定义损失函数
-
-MSAdapter的损失函数使用方式与PyTorch一致，无需修改。
-
-```python
-criterion = nn.CrossEntropyLoss()
-optimizer = optim.Adam(model.parameters(), lr=args.learning_rate)
-```
-
-### 7. 训练
-
-MSAdapter在torch.Tensor.to()、正向计算、反向微分计算的调用上与PyTorch有差别，需要修改代码。
-
-```python
-for epoch in range(args.epochs):
-    model.train()
-    for inputs, labels in train_loader:
-        inputs, labels = data_process(inputs, labels)
-        inputs, labels = inputs.to('cuda'), labels.to('cuda')  # Tensor.to()问题
-        optimizer.zero_grad()
-        outputs = model(inputs) # 前向调用不同
-        loss = criterion(outputs, labels).to('cuda') # Tensor.to()问题
-        loss.backward() # 反向调用不同
-        optimizer.step()
-        step += 1
-```
-
-#### torch.Tensor.to()
-
-与步骤5类似，由于MSAdapter暂时不支持torch.nn.Tensor.to接口，需要转换为如下方式。注意：MSAdapter默认将模型放置于NPU上。
-
-```python
-inputs, labels = inputs.to('cuda'), labels.to('cuda')
-loss = criterion(outputs, labels).to('cuda')
-```
-
-修改如下：
-
-```python
-# inputs, labels无需显示指定NPU
-loss = criterion(outputs, labels)
-```
-
-#### 前向与反向计算
+#### 1.1 微调脚本切换后端
 
-由于MSAdapter使用了函数式微分，正向反向计算均要调用函数，所以需要将PyTorch模型封装为函数。用户除了修改代码，还需要导入MindSpore。
+这种方式的前提是我们已经安装了MSAdapter，具体安装流程可以参考安装章节。需要在脚本前加一行，来切换后端，具体修改如下：
 
 ```python
-outputs = model(inputs) # 前向调用不同
-loss = criterion(outputs, labels).to('cuda') # Tensor.to()问题不在此重述
-loss.backward() # 反向调用不同
-```
-
-修改如下：
-
-1. 预定义正向计算函数和反向计算函数
-
-    ```python
-    import mindspore
-    def forward_fn(inputs, labels):
-        outputs = model(inputs)
-        loss = criterion(outputs, labels)
-        return loss
-    grad_fn = mindspore.value_and_grad(forward_fn, None, weights=model.trainable_params())
-    ```
-
-2. 替换原始的PyTorch计算过程
-
-    ```python
-    loss, grads = grad_fn(inputs, labels)
-    ```
-
-## MSAdapter适配后代码
-
-此处提供MSAdapter可运行的代码：
-
-```python
-import argparse
+import msadapter # 改为mindspore后端执行
 import torch
-import torch_npu
 import torch.nn as nn
 import torch.optim as optim
 from torch.utils.data import DataLoader
 from torchvision import datasets, transforms
-import mindspore
-
-class ToyModel(nn.Module):
-    def __init__(self):
-        super(ToyModel, self).__init__()
-        self.net1 = nn.Linear(784, 64)
-        self.relu = nn.ReLU()
-        self.net2 = nn.Linear(64, 10)
-
-    def forward(self, x):
-        return self.net2(self.relu(self.net1(x)))
-
-def parse_args():
-    parser = argparse.ArgumentParser(description="command line arguments")
-    parser.add_argument('--batch_size', type=int, default=64)
-    parser.add_argument('--epochs', type=int, default=1)
-    parser.add_argument('--learning_rate', type=float, default=0.0001)
-    return parser.parse_args()
-
-def data_process(inputs, labels):
-    inputs = inputs.view(inputs.size(0), -1)
-    return inputs, labels
-
-def main():
-    # 获取传参
-    args = parse_args()
-    transform = transforms.Compose([
-        transforms.ToTensor(),
-        transforms.Normalize((0.5,), (0.5,))
-    ])
-    train_dataset = datasets.MNIST(root='./data', train=True, download=True, transform=transform)
-    # 加载数据集
-    train_loader = DataLoader(train_dataset, batch_size=args.batch_size, shuffle=True)
-    # 将模型转移到NPU上
-    model = ToyModel()
-    # 定义损失函数
-    criterion = nn.CrossEntropyLoss()
-    optimizer = optim.Adam(model.parameters(), lr=args.learning_rate)
-    step = 0
+```
 
-    def forward_fn(inputs, labels):
-        outputs = model(inputs)
-        loss = criterion(outputs, labels)
-        return loss
-    grad_fn = mindspore.value_and_grad(forward_fn, None, weights=model.trainable_params())
+#### 1.2 环境变量切换
 
-    for epoch in range(args.epochs):
-        model.train()
-        for inputs, labels in train_loader:
-            # 数据预处理，将数据集的数据转成需要的shape
-            inputs, labels = data_process(inputs, labels)
+这种方式要求我们下载源码，将源码路径加入到环境变量中来使能MSAdapter流程。
 
-            optimizer.zero_grad()
-            loss, grads = grad_fn(inputs, labels)
-            optimizer.step()
+```bash
+export PYTHONPATH=${work_dir}/msadapter/:$PYTHONPATH
+export PYTHONPATH=${work_dir}/msadapter/msa_thirdparty:$PYTHONPATH
+```
 
-            # 添加每个step的打印，用户可自行修改
-            print(f"step = {step}, loss : {loss}")
-            step += 1
+### 2. 训练
 
-if __name__ == "__main__":
-    main()
-```
+当前MSAdapter微分机制这部分已与torch对齐，无需用户去做调整。根据使能MSAdapter章节的修改即可拉起训练。
 
 ## loss对比
 
diff --git a/docs/msadapter/docs/source_zh_cn/note/pytorch_api_supporting_nn_functional.md b/docs/msadapter/docs/source_zh_cn/note/pytorch_api_supporting_nn_functional.md
index 3f2d6ae0e71ba428c77b68a29e1a487f78cf8793..9d32cee54981468bc1b2ea1b18bd9a1531999143 100644
--- a/docs/msadapter/docs/source_zh_cn/note/pytorch_api_supporting_nn_functional.md
+++ b/docs/msadapter/docs/source_zh_cn/note/pytorch_api_supporting_nn_functional.md
@@ -8,7 +8,7 @@
 |-------|-------|---------|
 |[conv1d](https://pytorch.org/docs/2.1/generated/torch.nn.functional.conv1d.html)|Beta|支持数据类型：fp16、fp32|
 |[conv2d](https://pytorch.org/docs/2.1/generated/torch.nn.functional.conv2d.html)|Beta|支持数据类型：bf16、fp16、fp32|
-|[conv3d](https://pytorch.org/docs/2.1/generated/torch.nn.functional.conv3d.html)|Not Support|N/A|
+|[conv3d](https://pytorch.org/docs/2.1/generated/torch.nn.functional.conv3d.html)|Stable|N/A|
 |[conv_transpose1d](https://pytorch.org/docs/2.1/generated/torch.nn.functional.conv_transpose1d.html)|Not Support|N/A|
 |[conv_transpose2d](https://pytorch.org/docs/2.1/generated/torch.nn.functional.conv_transpose2d.html)|Demo|不支持CPU平台|
 |[conv_transpose3d](https://pytorch.org/docs/2.1/generated/torch.nn.functional.conv_transpose3d.html)|Not Support|N/A|
@@ -24,7 +24,7 @@
 |[avg_pool3d](https://pytorch.org/docs/2.1/generated/torch.nn.functional.avg_pool3d.html)|Not Support|N/A|
 |[max_pool1d](https://pytorch.org/docs/2.1/generated/torch.nn.functional.max_pool1d.html)|Beta|N/A|
 |[max_pool2d](https://pytorch.org/docs/2.1/generated/torch.nn.functional.max_pool2d.html)|Stable|N/A|
-|[max_pool3d](https://pytorch.org/docs/2.1/generated/torch.nn.functional.max_pool3d.html)|Not Support|N/A|
+|[max_pool3d](https://pytorch.org/docs/2.1/generated/torch.nn.functional.max_pool3d.html)|Stable|N/A|
 |[max_unpool1d](https://pytorch.org/docs/2.1/generated/torch.nn.functional.max_unpool1d.html)|Not Support|N/A|
 |[max_unpool2d](https://pytorch.org/docs/2.1/generated/torch.nn.functional.max_unpool2d.html)|Not Support|N/A|
 |[max_unpool3d](https://pytorch.org/docs/2.1/generated/torch.nn.functional.max_unpool3d.html)|Not Support|N/A|
@@ -44,7 +44,7 @@
 
 |API名称|API状态|限制与说明|
 |-------|-------|---------|
-|[scaled_dot_product_attention](https://pytorch.org/docs/2.1/generated/torch.nn.functional.scaled_dot_product_attention.html)|Not Support|N/A|
+|[scaled_dot_product_attention](https://pytorch.org/docs/2.1/generated/torch.nn.functional.scaled_dot_product_attention.html)|Beta|N/A|
 
 ## Non-linear activation functions
 
@@ -89,7 +89,7 @@
 |[instance_norm](https://pytorch.org/docs/2.1/generated/torch.nn.functional.instance_norm.html)|Not Support|N/A|
 |[layer_norm](https://pytorch.org/docs/2.1/generated/torch.nn.functional.layer_norm.html)|Stable|支持数据类型：bf16、fp16、fp32|
 |[local_response_norm](https://pytorch.org/docs/2.1/generated/torch.nn.functional.local_response_norm.html)|Not Support|N/A|
-|[rms_norm](https://pytorch.org/docs/2.1/generated/torch.nn.functional.rms_norm.html)|Not Support|N/A|
+|[rms_norm](https://pytorch.org/docs/2.1/generated/torch.nn.functional.rms_norm.html)|Beta|N/A|
 |[normalize](https://pytorch.org/docs/2.1/generated/torch.nn.functional.normalize.html)|Beta|不支持out出参；支持数据类型：bf16、fp16、fp32|
 
 ## Linear functions
diff --git a/docs/msadapter/docs/source_zh_cn/note/pytorch_api_supporting_tensor.md b/docs/msadapter/docs/source_zh_cn/note/pytorch_api_supporting_tensor.md
index 44c473b9d6039e7d9f6def6b64396b5e5d2e4ccd..bbcc6e55bfeee5baf366714dacfcdb3ce2324e38 100644
--- a/docs/msadapter/docs/source_zh_cn/note/pytorch_api_supporting_tensor.md
+++ b/docs/msadapter/docs/source_zh_cn/note/pytorch_api_supporting_tensor.md
@@ -9,20 +9,20 @@
 |[Tensor.new_tensor](https://pytorch.org/docs/2.1/generated/torch.Tensor.new_tensor.html)|Not Support|N/A|
 |[Tensor.new_full](https://pytorch.org/docs/2.1/generated/torch.Tensor.new_full.html)|Not Support|N/A|
 |[Tensor.new_empty](https://pytorch.org/docs/2.1/generated/torch.Tensor.new_empty.html)|Not Support|N/A|
-|[Tensor.new_ones](https://pytorch.org/docs/2.1/generated/torch.Tensor.new_ones.html)|Not Support|N/A|
-|[Tensor.new_zeros](https://pytorch.org/docs/2.1/generated/torch.Tensor.new_zeros.html)|Not Support|N/A|
+|[Tensor.new_ones](https://pytorch.org/docs/2.1/generated/torch.Tensor.new_ones.html)|Beta|N/A|
+|[Tensor.new_zeros](https://pytorch.org/docs/2.1/generated/torch.Tensor.new_zeros.html)|Beta|N/A|
 |[Tensor.is_cuda](https://pytorch.org/docs/2.1/generated/torch.Tensor.is_cuda.html)|Not Support|N/A|
 |[Tensor.is_quantized](https://pytorch.org/docs/2.1/generated/torch.Tensor.is_quantized.html)|Not Support|N/A|
 |[Tensor.is_meta](https://pytorch.org/docs/2.1/generated/torch.Tensor.is_meta.html)|Not Support|N/A|
 |[Tensor.device](https://pytorch.org/docs/2.1/generated/torch.Tensor.device.html)|Not Support|N/A|
-|[Tensor.grad](https://pytorch.org/docs/2.1/generated/torch.Tensor.grad.html)|Not Support|N/A|
+|[Tensor.grad](https://pytorch.org/docs/2.1/generated/torch.Tensor.grad.html)|Beta|N/A|
 |[Tensor.ndim](https://pytorch.org/docs/2.1/generated/torch.Tensor.ndim.html)|Not Support|N/A|
-|[Tensor.real](https://pytorch.org/docs/2.1/generated/torch.Tensor.real.html)|Not Support|N/A|
-|[Tensor.imag](https://pytorch.org/docs/2.1/generated/torch.Tensor.imag.html)|Not Support|N/A|
+|[Tensor.real](https://pytorch.org/docs/2.1/generated/torch.Tensor.real.html)|Beta|N/A|
+|[Tensor.imag](https://pytorch.org/docs/2.1/generated/torch.Tensor.imag.html)|Beta|N/A|
 |[Tensor.nbytes](https://pytorch.org/docs/2.1/generated/torch.Tensor.nbytes.html)|Not Support|N/A|
 |[Tensor.itemsize](https://pytorch.org/docs/2.1/generated/torch.Tensor.itemsize.html)|Not Support|N/A|
 |[Tensor.abs](https://pytorch.org/docs/2.1/generated/torch.Tensor.abs.html)|Stable|支持数据类型：bf16、fp16、fp32、fp64、uint8、int8、int16、int32、int64、bool|
-|[Tensor.abs_](https://pytorch.org/docs/2.1/generated/torch.Tensor.abs_.html)|Not Support|N/A|
+|[Tensor.abs_](https://pytorch.org/docs/2.1/generated/torch.Tensor.abs_.html)|Beta|N/A|
 |[Tensor.absolute](https://pytorch.org/docs/2.1/generated/torch.Tensor.absolute.html)|Stable|支持数据类型：bf16、fp16、fp32、uint8、int8、int16、int32、int64|
 |[Tensor.absolute_](https://pytorch.org/docs/2.1/generated/torch.Tensor.absolute_.html)|Not Support|N/A|
 |[Tensor.acos](https://pytorch.org/docs/2.1/generated/torch.Tensor.acos.html)|Not Support|N/A|
@@ -34,9 +34,9 @@
 |[Tensor.addbmm](https://pytorch.org/docs/2.1/generated/torch.Tensor.addbmm.html)|Not Support|N/A|
 |[Tensor.addbmm_](https://pytorch.org/docs/2.1/generated/torch.Tensor.addbmm_.html)|Not Support|N/A|
 |[Tensor.addcdiv](https://pytorch.org/docs/2.1/generated/torch.Tensor.addcdiv.html)|Not Support|N/A|
-|[Tensor.addcdiv_](https://pytorch.org/docs/2.1/generated/torch.Tensor.addcdiv_.html)|Not Support|N/A|
+|[Tensor.addcdiv_](https://pytorch.org/docs/2.1/generated/torch.Tensor.addcdiv_.html)|Beta|N/A|
 |[Tensor.addcmul](https://pytorch.org/docs/2.1/generated/torch.Tensor.addcmul.html)|Not Support|N/A|
-|[Tensor.addcmul_](https://pytorch.org/docs/2.1/generated/torch.Tensor.addcmul_.html)|Not Support|N/A|
+|[Tensor.addcmul_](https://pytorch.org/docs/2.1/generated/torch.Tensor.addcmul_.html)|Beta|N/A|
 |[Tensor.addmm](https://pytorch.org/docs/2.1/generated/torch.Tensor.addmm.html)|Not Support|N/A|
 |[Tensor.addmm_](https://pytorch.org/docs/2.1/generated/torch.Tensor.addmm_.html)|Not Support|N/A|
 |[Tensor.sspaddmm](https://pytorch.org/docs/2.1/generated/torch.Tensor.sspaddmm.html)|Not Support|N/A|
@@ -70,14 +70,14 @@
 |[Tensor.arctan2_](https://pytorch.org/docs/2.1/generated/torch.Tensor.arctan2_.html)|Not Support|N/A|
 |[Tensor.all](https://pytorch.org/docs/2.1/generated/torch.Tensor.all.html)|Not Support|N/A|
 |[Tensor.any](https://pytorch.org/docs/2.1/generated/torch.Tensor.any.html)|Not Support|N/A|
-|[Tensor.backward](https://pytorch.org/docs/2.1/generated/torch.Tensor.backward.html)|Not Support|N/A|
+|[Tensor.backward](https://pytorch.org/docs/2.1/generated/torch.Tensor.backward.html)|Demo|N/A|
 |[Tensor.baddbmm](https://pytorch.org/docs/2.1/generated/torch.Tensor.baddbmm.html)|Not Support|N/A|
 |[Tensor.baddbmm_](https://pytorch.org/docs/2.1/generated/torch.Tensor.baddbmm_.html)|Not Support|N/A|
 |[Tensor.bernoulli](https://pytorch.org/docs/2.1/generated/torch.Tensor.bernoulli.html)|Not Support|N/A|
 |[Tensor.bernoulli_](https://pytorch.org/docs/2.1/generated/torch.Tensor.bernoulli_.html)|Not Support|N/A|
 |[Tensor.bfloat16](https://pytorch.org/docs/2.1/generated/torch.Tensor.bfloat16.html)|Not Support|N/A|
 |[Tensor.bincount](https://pytorch.org/docs/2.1/generated/torch.Tensor.bincount.html)|Not Support|N/A|
-|[Tensor.bitwise_not](https://pytorch.org/docs/2.1/generated/torch.Tensor.bitwise_not.html)|Not Support|N/A|
+|[Tensor.bitwise_not](https://pytorch.org/docs/2.1/generated/torch.Tensor.bitwise_not.html)|Demo|N/A|
 |[Tensor.bitwise_not_](https://pytorch.org/docs/2.1/generated/torch.Tensor.bitwise_not_.html)|Not Support|N/A|
 |[Tensor.bitwise_and](https://pytorch.org/docs/2.1/generated/torch.Tensor.bitwise_and.html)|Not Support|N/A|
 |[Tensor.bitwise_and_](https://pytorch.org/docs/2.1/generated/torch.Tensor.bitwise_and_.html)|Not Support|N/A|
@@ -157,7 +157,7 @@
 |[Tensor.diff](https://pytorch.org/docs/2.1/generated/torch.Tensor.diff.html)|Not Support|N/A|
 |[Tensor.digamma](https://pytorch.org/docs/2.1/generated/torch.Tensor.digamma.html)|Not Support|N/A|
 |[Tensor.digamma_](https://pytorch.org/docs/2.1/generated/torch.Tensor.digamma_.html)|Not Support|N/A|
-|[Tensor.dim](https://pytorch.org/docs/2.1/generated/torch.Tensor.dim.html)|Not Support|N/A|
+|[Tensor.dim](https://pytorch.org/docs/2.1/generated/torch.Tensor.dim.html)|Stable|N/A|
 |[Tensor.dim_order](https://pytorch.org/docs/2.1/generated/torch.Tensor.dim_order.html)|Not Support|N/A|
 |[Tensor.dist](https://pytorch.org/docs/2.1/generated/torch.Tensor.dist.html)|Not Support|N/A|
 |[Tensor.div](https://pytorch.org/docs/2.1/generated/torch.Tensor.div.html)|Not Support|N/A|
@@ -167,7 +167,7 @@
 |[Tensor.dot](https://pytorch.org/docs/2.1/generated/torch.Tensor.dot.html)|Not Support|N/A|
 |[Tensor.double](https://pytorch.org/docs/2.1/generated/torch.Tensor.double.html)|Not Support|N/A|
 |[Tensor.dsplit](https://pytorch.org/docs/2.1/generated/torch.Tensor.dsplit.html)|Not Support|N/A|
-|[Tensor.element_size](https://pytorch.org/docs/2.1/generated/torch.Tensor.element_size.html)|Not Support|N/A|
+|[Tensor.element_size](https://pytorch.org/docs/2.1/generated/torch.Tensor.element_size.html)|Beta|N/A|
 |[Tensor.eq](https://pytorch.org/docs/2.1/generated/torch.Tensor.eq.html)|Not Support|N/A|
 |[Tensor.eq_](https://pytorch.org/docs/2.1/generated/torch.Tensor.eq_.html)|Not Support|N/A|
 |[Tensor.equal](https://pytorch.org/docs/2.1/generated/torch.Tensor.equal.html)|Not Support|N/A|
@@ -181,7 +181,7 @@
 |[Tensor.exp_](https://pytorch.org/docs/2.1/generated/torch.Tensor.exp_.html)|Not Support|N/A|
 |[Tensor.expm1](https://pytorch.org/docs/2.1/generated/torch.Tensor.expm1.html)|Not Support|N/A|
 |[Tensor.expm1_](https://pytorch.org/docs/2.1/generated/torch.Tensor.expm1_.html)|Not Support|N/A|
-|[Tensor.expand](https://pytorch.org/docs/2.1/generated/torch.Tensor.expand.html)|Not Support|N/A|
+|[Tensor.expand](https://pytorch.org/docs/2.1/generated/torch.Tensor.expand.html)|Stable|N/A|
 |[Tensor.expand_as](https://pytorch.org/docs/2.1/generated/torch.Tensor.expand_as.html)|Not Support|N/A|
 |[Tensor.exponential_](https://pytorch.org/docs/2.1/generated/torch.Tensor.exponential_.html)|Not Support|N/A|
 |[Tensor.fix](https://pytorch.org/docs/2.1/generated/torch.Tensor.fix.html)|Not Support|N/A|
@@ -191,7 +191,7 @@
 |[Tensor.flip](https://pytorch.org/docs/2.1/generated/torch.Tensor.flip.html)|Not Support|N/A|
 |[Tensor.fliplr](https://pytorch.org/docs/2.1/generated/torch.Tensor.fliplr.html)|Not Support|N/A|
 |[Tensor.flipud](https://pytorch.org/docs/2.1/generated/torch.Tensor.flipud.html)|Not Support|N/A|
-|[Tensor.float](https://pytorch.org/docs/2.1/generated/torch.Tensor.float.html)|Not Support|N/A|
+|[Tensor.float](https://pytorch.org/docs/2.1/generated/torch.Tensor.float.html)|Stable|N/A|
 |[Tensor.float_power](https://pytorch.org/docs/2.1/generated/torch.Tensor.float_power.html)|Not Support|N/A|
 |[Tensor.float_power_](https://pytorch.org/docs/2.1/generated/torch.Tensor.float_power_.html)|Not Support|N/A|
 |[Tensor.floor](https://pytorch.org/docs/2.1/generated/torch.Tensor.floor.html)|Stable|支持数据类型：fp16、fp32|
@@ -257,9 +257,9 @@
 |[Tensor.is_contiguous](https://pytorch.org/docs/2.1/generated/torch.Tensor.is_contiguous.html)|Not Support|N/A|
 |[Tensor.is_complex](https://pytorch.org/docs/2.1/generated/torch.Tensor.is_complex.html)|Not Support|N/A|
 |[Tensor.is_conj](https://pytorch.org/docs/2.1/generated/torch.Tensor.is_conj.html)|Not Support|N/A|
-|[Tensor.is_floating_point](https://pytorch.org/docs/2.1/generated/torch.Tensor.is_floating_point.html)|Not Support|N/A|
+|[Tensor.is_floating_point](https://pytorch.org/docs/2.1/generated/torch.Tensor.is_floating_point.html)|Beta|N/A|
 |[Tensor.is_inference](https://pytorch.org/docs/2.1/generated/torch.Tensor.is_inference.html)|Not Support|N/A|
-|[Tensor.is_leaf](https://pytorch.org/docs/2.1/generated/torch.Tensor.is_leaf.html)|Not Support|N/A|
+|[Tensor.is_leaf](https://pytorch.org/docs/2.1/generated/torch.Tensor.is_leaf.html)|Beta|N/A|
 |[Tensor.is_pinned](https://pytorch.org/docs/2.1/generated/torch.Tensor.is_pinned.html)|Not Support|N/A|
 |[Tensor.is_set_to](https://pytorch.org/docs/2.1/generated/torch.Tensor.is_set_to.html)|Not Support|N/A|
 |[Tensor.is_shared](https://pytorch.org/docs/2.1/generated/torch.Tensor.is_shared.html)|Not Support|N/A|
@@ -278,7 +278,7 @@
 |[Tensor.less_equal](https://pytorch.org/docs/2.1/generated/torch.Tensor.less_equal.html)|Not Support|N/A|
 |[Tensor.less_equal_](https://pytorch.org/docs/2.1/generated/torch.Tensor.less_equal_.html)|Not Support|N/A|
 |[Tensor.lerp](https://pytorch.org/docs/2.1/generated/torch.Tensor.lerp.html)|Not Support|N/A|
-|[Tensor.lerp_](https://pytorch.org/docs/2.1/generated/torch.Tensor.lerp_.html)|Not Support|N/A|
+|[Tensor.lerp_](https://pytorch.org/docs/2.1/generated/torch.Tensor.lerp_.html)|Beta|N/A|
 |[Tensor.lgamma](https://pytorch.org/docs/2.1/generated/torch.Tensor.lgamma.html)|Not Support|N/A|
 |[Tensor.lgamma_](https://pytorch.org/docs/2.1/generated/torch.Tensor.lgamma_.html)|Not Support|N/A|
 |[Tensor.log](https://pytorch.org/docs/2.1/generated/torch.Tensor.log.html)|Stable|支持数据类型：bf16、fp16、fp32、fp64、uint8、int8、int16、int32、int64、bool|
@@ -313,15 +313,15 @@
 |[Tensor.lu_solve](https://pytorch.org/docs/2.1/generated/torch.Tensor.lu_solve.html)|Not Support|N/A|
 |[Tensor.as_subclass](https://pytorch.org/docs/2.1/generated/torch.Tensor.as_subclass.html)|Not Support|N/A|
 |[Tensor.map_](https://pytorch.org/docs/2.1/generated/torch.Tensor.map_.html)|Not Support|N/A|
-|[Tensor.masked_scatter_](https://pytorch.org/docs/2.1/generated/torch.Tensor.masked_scatter_.html)|Not Support|N/A|
+|[Tensor.masked_scatter_](https://pytorch.org/docs/2.1/generated/torch.Tensor.masked_scatter_.html)|Beta|N/A|
 |[Tensor.masked_scatter](https://pytorch.org/docs/2.1/generated/torch.Tensor.masked_scatter.html)|Not Support|N/A|
 |[Tensor.masked_fill_](https://pytorch.org/docs/2.1/generated/torch.Tensor.masked_fill_.html)|Not Support|N/A|
-|[Tensor.masked_fill](https://pytorch.org/docs/2.1/generated/torch.Tensor.masked_fill.html)|Not Support|N/A|
+|[Tensor.masked_fill](https://pytorch.org/docs/2.1/generated/torch.Tensor.masked_fill.html)|Stable|N/A|
 |[Tensor.masked_select](https://pytorch.org/docs/2.1/generated/torch.Tensor.masked_select.html)|Not Support|N/A|
 |[Tensor.matmul](https://pytorch.org/docs/2.1/generated/torch.Tensor.matmul.html)|Stable|支持数据类型：fp16、fp32|
 |[Tensor.matrix_power](https://pytorch.org/docs/2.1/generated/torch.Tensor.matrix_power.html)|Not Support|N/A|
 |[Tensor.matrix_exp](https://pytorch.org/docs/2.1/generated/torch.Tensor.matrix_exp.html)|Not Support|N/A|
-|[Tensor.max](https://pytorch.org/docs/2.1/generated/torch.Tensor.max.html)|Not Support|N/A|
+|[Tensor.max](https://pytorch.org/docs/2.1/generated/torch.Tensor.max.html)|Stable|N/A|
 |[Tensor.maximum](https://pytorch.org/docs/2.1/generated/torch.Tensor.maximum.html)|Not Support|N/A|
 |[Tensor.mean](https://pytorch.org/docs/2.1/generated/torch.Tensor.mean.html)|Not Support|N/A|
 |[Tensor.module_load](https://pytorch.org/docs/2.1/generated/torch.Tensor.module_load.html)|Not Support|N/A|
@@ -345,11 +345,11 @@
 |[Tensor.mvlgamma](https://pytorch.org/docs/2.1/generated/torch.Tensor.mvlgamma.html)|Not Support|N/A|
 |[Tensor.mvlgamma_](https://pytorch.org/docs/2.1/generated/torch.Tensor.mvlgamma_.html)|Not Support|N/A|
 |[Tensor.nansum](https://pytorch.org/docs/2.1/generated/torch.Tensor.nansum.html)|Not Support|N/A|
-|[Tensor.narrow](https://pytorch.org/docs/2.1/generated/torch.Tensor.narrow.html)|Not Support|N/A|
+|[Tensor.narrow](https://pytorch.org/docs/2.1/generated/torch.Tensor.narrow.html)|Stable|N/A|
 |[Tensor.narrow_copy](https://pytorch.org/docs/2.1/generated/torch.Tensor.narrow_copy.html)|Not Support|N/A|
 |[Tensor.ndimension](https://pytorch.org/docs/2.1/generated/torch.Tensor.ndimension.html)|Not Support|N/A|
 |[Tensor.nan_to_num](https://pytorch.org/docs/2.1/generated/torch.Tensor.nan_to_num.html)|Not Support|N/A|
-|[Tensor.nan_to_num_](https://pytorch.org/docs/2.1/generated/torch.Tensor.nan_to_num_.html)|Not Support|N/A|
+|[Tensor.nan_to_num_](https://pytorch.org/docs/2.1/generated/torch.Tensor.nan_to_num_.html)|Beta|N/A|
 |[Tensor.ne](https://pytorch.org/docs/2.1/generated/torch.Tensor.ne.html)|Stable|支持数据类型：bf16、fp16、fp32、uint8、int8、int16、int32、int64、bool|
 |[Tensor.ne_](https://pytorch.org/docs/2.1/generated/torch.Tensor.ne_.html)|Not Support|N/A|
 |[Tensor.not_equal](https://pytorch.org/docs/2.1/generated/torch.Tensor.not_equal.html)|Not Support|N/A|
@@ -358,13 +358,13 @@
 |[Tensor.neg_](https://pytorch.org/docs/2.1/generated/torch.Tensor.neg_.html)|Not Support|N/A|
 |[Tensor.negative](https://pytorch.org/docs/2.1/generated/torch.Tensor.negative.html)|Not Support|N/A|
 |[Tensor.negative_](https://pytorch.org/docs/2.1/generated/torch.Tensor.negative_.html)|Not Support|N/A|
-|[Tensor.nelement](https://pytorch.org/docs/2.1/generated/torch.Tensor.nelement.html)|Not Support|N/A|
+|[Tensor.nelement](https://pytorch.org/docs/2.1/generated/torch.Tensor.nelement.html)|Stable|N/A|
 |[Tensor.nextafter](https://pytorch.org/docs/2.1/generated/torch.Tensor.nextafter.html)|Not Support|N/A|
 |[Tensor.nextafter_](https://pytorch.org/docs/2.1/generated/torch.Tensor.nextafter_.html)|Not Support|N/A|
 |[Tensor.nonzero](https://pytorch.org/docs/2.1/generated/torch.Tensor.nonzero.html)|Not Support|N/A|
 |[Tensor.norm](https://pytorch.org/docs/2.1/generated/torch.Tensor.norm.html)|Not Support|N/A|
 |[Tensor.normal_](https://pytorch.org/docs/2.1/generated/torch.Tensor.normal_.html)|Not Support|N/A|
-|[Tensor.numel](https://pytorch.org/docs/2.1/generated/torch.Tensor.numel.html)|Not Support|N/A|
+|[Tensor.numel](https://pytorch.org/docs/2.1/generated/torch.Tensor.numel.html)|Stable|N/A|
 |[Tensor.numpy](https://pytorch.org/docs/2.1/generated/torch.Tensor.numpy.html)|Not Support|N/A|
 |[Tensor.orgqr](https://pytorch.org/docs/2.1/generated/torch.Tensor.orgqr.html)|Not Support|N/A|
 |[Tensor.ormqr](https://pytorch.org/docs/2.1/generated/torch.Tensor.ormqr.html)|Not Support|N/A|
@@ -394,22 +394,22 @@
 |[Tensor.reciprocal](https://pytorch.org/docs/2.1/generated/torch.Tensor.reciprocal.html)|Not Support|N/A|
 |[Tensor.reciprocal_](https://pytorch.org/docs/2.1/generated/torch.Tensor.reciprocal_.html)|Not Support|N/A|
 |[Tensor.record_stream](https://pytorch.org/docs/2.1/generated/torch.Tensor.record_stream.html)|Not Support|N/A|
-|[Tensor.register_hook](https://pytorch.org/docs/2.1/generated/torch.Tensor.register_hook.html)|Not Support|N/A|
+|[Tensor.register_hook](https://pytorch.org/docs/2.1/generated/torch.Tensor.register_hook.html)|Beta|N/A|
 |[Tensor.register_post_accumulate_grad_hook](https://pytorch.org/docs/2.1/generated/torch.Tensor.register_post_accumulate_grad_hook.html)|Not Support|N/A|
 |[Tensor.remainder](https://pytorch.org/docs/2.1/generated/torch.Tensor.remainder.html)|Not Support|N/A|
 |[Tensor.remainder_](https://pytorch.org/docs/2.1/generated/torch.Tensor.remainder_.html)|Not Support|N/A|
 |[Tensor.renorm](https://pytorch.org/docs/2.1/generated/torch.Tensor.renorm.html)|Not Support|N/A|
 |[Tensor.renorm_](https://pytorch.org/docs/2.1/generated/torch.Tensor.renorm_.html)|Not Support|N/A|
-|[Tensor.repeat](https://pytorch.org/docs/2.1/generated/torch.Tensor.repeat.html)|Not Support|N/A|
+|[Tensor.repeat](https://pytorch.org/docs/2.1/generated/torch.Tensor.repeat.html)|Stable|N/A|
 |[Tensor.repeat_interleave](https://pytorch.org/docs/2.1/generated/torch.Tensor.repeat_interleave.html)|Not Support|N/A|
-|[Tensor.requires_grad](https://pytorch.org/docs/2.1/generated/torch.Tensor.requires_grad.html)|Not Support|N/A|
-|[Tensor.requires_grad_](https://pytorch.org/docs/2.1/generated/torch.Tensor.requires_grad_.html)|Not Support|N/A|
-|[Tensor.reshape](https://pytorch.org/docs/2.1/generated/torch.Tensor.reshape.html)|Not Support|N/A|
+|[Tensor.requires_grad](https://pytorch.org/docs/2.1/generated/torch.Tensor.requires_grad.html)|Beta|N/A|
+|[Tensor.requires_grad_](https://pytorch.org/docs/2.1/generated/torch.Tensor.requires_grad_.html)|Beta|N/A|
+|[Tensor.reshape](https://pytorch.org/docs/2.1/generated/torch.Tensor.reshape.html)|Stable|N/A|
 |[Tensor.reshape_as](https://pytorch.org/docs/2.1/generated/torch.Tensor.reshape_as.html)|Not Support|N/A|
-|[Tensor.resize_](https://pytorch.org/docs/2.1/generated/torch.Tensor.resize_.html)|Not Support|N/A|
+|[Tensor.resize_](https://pytorch.org/docs/2.1/generated/torch.Tensor.resize_.html)|Beta|N/A|
 |[Tensor.resize_as_](https://pytorch.org/docs/2.1/generated/torch.Tensor.resize_as_.html)|Not Support|N/A|
-|[Tensor.retain_grad](https://pytorch.org/docs/2.1/generated/torch.Tensor.retain_grad.html)|Not Support|N/A|
-|[Tensor.retains_grad](https://pytorch.org/docs/2.1/generated/torch.Tensor.retains_grad.html)|Not Support|N/A|
+|[Tensor.retain_grad](https://pytorch.org/docs/2.1/generated/torch.Tensor.retain_grad.html)|Beta|N/A|
+|[Tensor.retains_grad](https://pytorch.org/docs/2.1/generated/torch.Tensor.retains_grad.html)|Beta|N/A|
 |[Tensor.roll](https://pytorch.org/docs/2.1/generated/torch.Tensor.roll.html)|Not Support|N/A|
 |[Tensor.rot90](https://pytorch.org/docs/2.1/generated/torch.Tensor.rot90.html)|Not Support|N/A|
 |[Tensor.round](https://pytorch.org/docs/2.1/generated/torch.Tensor.round.html)|Not Support|N/A|
@@ -445,12 +445,12 @@
 |[Tensor.arcsinh](https://pytorch.org/docs/2.1/generated/torch.Tensor.arcsinh.html)|Not Support|N/A|
 |[Tensor.arcsinh_](https://pytorch.org/docs/2.1/generated/torch.Tensor.arcsinh_.html)|Not Support|N/A|
 |[Tensor.shape](https://pytorch.org/docs/2.1/generated/torch.Tensor.shape.html)|Not Support|N/A|
-|[Tensor.size](https://pytorch.org/docs/2.1/generated/torch.Tensor.size.html)|Not Support|N/A|
+|[Tensor.size](https://pytorch.org/docs/2.1/generated/torch.Tensor.size.html)|Stable|N/A|
 |[Tensor.slogdet](https://pytorch.org/docs/2.1/generated/torch.Tensor.slogdet.html)|Not Support|N/A|
 |[Tensor.slice_scatter](https://pytorch.org/docs/2.1/generated/torch.Tensor.slice_scatter.html)|Not Support|N/A|
 |[Tensor.softmax](https://pytorch.org/docs/2.1/generated/torch.Tensor.softmax.html)|Not Support|N/A|
 |[Tensor.sort](https://pytorch.org/docs/2.1/generated/torch.Tensor.sort.html)|Not Support|N/A|
-|[Tensor.split](https://pytorch.org/docs/2.1/generated/torch.Tensor.split.html)|Not Support|N/A|
+|[Tensor.split](https://pytorch.org/docs/2.1/generated/torch.Tensor.split.html)|Stable|N/A|
 |[Tensor.sparse_mask](https://pytorch.org/docs/2.1/generated/torch.Tensor.sparse_mask.html)|Not Support|N/A|
 |[Tensor.sparse_dim](https://pytorch.org/docs/2.1/generated/torch.Tensor.sparse_dim.html)|Not Support|N/A|
 |[Tensor.sqrt](https://pytorch.org/docs/2.1/generated/torch.Tensor.sqrt.html)|Stable|支持数据类型：bf16、fp16、fp32、fp64、uint8、int8、int16、int32、int64、bool|
@@ -458,7 +458,7 @@
 |[Tensor.square](https://pytorch.org/docs/2.1/generated/torch.Tensor.square.html)|Stable|支持数据类型：fp16、fp32、fp64、uint8、int8、int16、int32、int64|
 |[Tensor.square_](https://pytorch.org/docs/2.1/generated/torch.Tensor.square_.html)|Not Support|N/A|
 |[Tensor.squeeze](https://pytorch.org/docs/2.1/generated/torch.Tensor.squeeze.html)|Not Support|N/A|
-|[Tensor.squeeze_](https://pytorch.org/docs/2.1/generated/torch.Tensor.squeeze_.html)|Not Support|N/A|
+|[Tensor.squeeze_](https://pytorch.org/docs/2.1/generated/torch.Tensor.squeeze_.html)|Stable|N/A|
 |[Tensor.std](https://pytorch.org/docs/2.1/generated/torch.Tensor.std.html)|Not Support|N/A|
 |[Tensor.stft](https://pytorch.org/docs/2.1/generated/torch.Tensor.stft.html)|Not Support|N/A|
 |[Tensor.storage](https://pytorch.org/docs/2.1/generated/torch.Tensor.storage.html)|Not Support|N/A|
@@ -478,7 +478,7 @@
 |[Tensor.t](https://pytorch.org/docs/2.1/generated/torch.Tensor.t.html)|Not Support|N/A|
 |[Tensor.t_](https://pytorch.org/docs/2.1/generated/torch.Tensor.t_.html)|Not Support|N/A|
 |[Tensor.tensor_split](https://pytorch.org/docs/2.1/generated/torch.Tensor.tensor_split.html)|Not Support|N/A|
-|[Tensor.tile](https://pytorch.org/docs/2.1/generated/torch.Tensor.tile.html)|Not Support|N/A|
+|[Tensor.tile](https://pytorch.org/docs/2.1/generated/torch.Tensor.tile.html)|Stable|N/A|
 |[Tensor.to](https://pytorch.org/docs/2.1/generated/torch.Tensor.to.html)|Not Support|N/A|
 |[Tensor.to_mkldnn](https://pytorch.org/docs/2.1/generated/torch.Tensor.to_mkldnn.html)|Not Support|N/A|
 |[Tensor.take](https://pytorch.org/docs/2.1/generated/torch.Tensor.take.html)|Not Support|N/A|
@@ -501,9 +501,9 @@
 |[Tensor.to_sparse_bsc](https://pytorch.org/docs/2.1/generated/torch.Tensor.to_sparse_bsc.html)|Not Support|N/A|
 |[Tensor.trace](https://pytorch.org/docs/2.1/generated/torch.Tensor.trace.html)|Not Support|N/A|
 |[Tensor.transpose](https://pytorch.org/docs/2.1/generated/torch.Tensor.transpose.html)|Not Support|N/A|
-|[Tensor.transpose_](https://pytorch.org/docs/2.1/generated/torch.Tensor.transpose_.html)|Not Support|N/A|
+|[Tensor.transpose_](https://pytorch.org/docs/2.1/generated/torch.Tensor.transpose_.html)|Beta|N/A|
 |[Tensor.triangular_solve](https://pytorch.org/docs/2.1/generated/torch.Tensor.triangular_solve.html)|Not Support|N/A|
-|[Tensor.tril](https://pytorch.org/docs/2.1/generated/torch.Tensor.tril.html)|Not Support|N/A|
+|[Tensor.tril](https://pytorch.org/docs/2.1/generated/torch.Tensor.tril.html)|Demo|N/A|
 |[Tensor.tril_](https://pytorch.org/docs/2.1/generated/torch.Tensor.tril_.html)|Not Support|N/A|
 |[Tensor.triu](https://pytorch.org/docs/2.1/generated/torch.Tensor.triu.html)|Not Support|N/A|
 |[Tensor.triu_](https://pytorch.org/docs/2.1/generated/torch.Tensor.triu_.html)|Demo|N/A|
@@ -524,8 +524,8 @@
 |[Tensor.values](https://pytorch.org/docs/2.1/generated/torch.Tensor.values.html)|Not Support|N/A|
 |[Tensor.var](https://pytorch.org/docs/2.1/generated/torch.Tensor.var.html)|Not Support|N/A|
 |[Tensor.vdot](https://pytorch.org/docs/2.1/generated/torch.Tensor.vdot.html)|Not Support|N/A|
-|[Tensor.view](https://pytorch.org/docs/2.1/generated/torch.Tensor.view.html)|Not Support|N/A|
-|[Tensor.view_as](https://pytorch.org/docs/2.1/generated/torch.Tensor.view_as.html)|Not Support|N/A|
+|[Tensor.view](https://pytorch.org/docs/2.1/generated/torch.Tensor.view.html)|Stable|N/A|
+|[Tensor.view_as](https://pytorch.org/docs/2.1/generated/torch.Tensor.view_as.html)|Stable|N/A|
 |[Tensor.vsplit](https://pytorch.org/docs/2.1/generated/torch.Tensor.vsplit.html)|Not Support|N/A|
 |[Tensor.where](https://pytorch.org/docs/2.1/generated/torch.Tensor.where.html)|Not Support|N/A|
 |[Tensor.xlogy](https://pytorch.org/docs/2.1/generated/torch.Tensor.xlogy.html)|Not Support|N/A|