plugin csvwriter

Author: Zeyi-Lin

en/plugin/writer-csv.md

@@ -1,3 +1,75 @@
-# CSV Writer
+# CSV Table Logger
 
-waiting for update...
+If you wish to record some configuration information and metrics locally in a CSV file during training (in a format consistent with the "Table View" on the SwanLab webpage), we highly recommend using the `CSV Logger` plugin.
+
+:::warning Improving the Plugin
+All SwanLab plugins are open-source. You can view the [Github source code](https://github.com/SwanHubX/SwanLab/blob/main/swanlab/plugin/writer.py). We welcome your suggestions and PRs!
+:::
+
+## Plugin Usage
+
+**1. Initialize the CSV Logger:**
+
+```python
+from swanlab.plugin.writer import CSVWriter
+
+csv_writer = CSVWriter(dir="logs")
+```
+
+The `dir` parameter specifies the save path for the CSV file. By default, it is saved in the current working directory.
+
+**2. Pass the Plugin:**
+
+```python
+swanlab.init(
+    ...
+    callbacks=[csv_writer]
+)
+```
+
+After executing the code, a `swanlab_run.csv` file will be generated in the `logs` directory, and data recording will begin. For each subsequent training session, a new row will be added to this CSV file.
+
+If you want to specify a different file name, you can pass the `filename` parameter:
+
+```python
+csv_writer = CSVWriter(dir="logs", filename="my_csv_file.csv")
+```
+
+## Example Code
+
+```python
+import swanlab
+from swanlab.plugin.writer import CSVWriter
+import random
+
+csv_writer = CSVWriter(dir="logs")
+
+# Create a SwanLab project
+swanlab.init(
+    # Set the project name
+    project="my-awesome-project",
+    
+    # Set hyperparameters
+    config={
+        "learning_rate": 0.02,
+        "architecture": "CNN",
+        "dataset": "CIFAR-100",
+        "epochs": 10,
+        "batch_size": 128
+    },
+    callbacks=[csv_writer]
+)
+
+# Simulate a training session
+epochs = 10
+offset = random.random() / 5
+for epoch in range(2, epochs):
+  acc = 1 - 2 ** -epoch - random.random() / epoch - offset
+  loss = 2 ** -epoch + random.random() / epoch + offset
+
+  # Log training metrics
+  swanlab.log({"acc": acc, "loss2": loss})
+
+# [Optional] Finish training, which is necessary in notebook environments
+swanlab.finish()
+```

zh/plugin/writer-csv.md

@@ -1,3 +1,77 @@
 # CSV表格记录器
 
-waiting for update...
+如果你希望在训练过程中，将一些配置信息、指标信息记录在本地的CSV文件中（格式和SwanLab网页中的“表格视图“一致），那么非常推荐你使用`CSV记录器`插件。
+
+:::warning 改进插件
+SwanLab插件均为开源代码，你可以在[Github源代码](https://github.com/SwanHubX/SwanLab/blob/main/swanlab/plugin/writer.py)中查看，欢迎提交你的建议和PR！
+:::
+
+## 插件用法
+
+**1. 初始化CSV记录器：**
+
+```python
+from swanlab.plugin.writer import CSVWriter
+
+csv_writer = CSVWriter(dir="logs")
+```
+
+`dir`参数指定了CSV文件的保存路径，默认保存到当前工作目录。
+
+**2. 传入插件：**
+
+```python
+swanlab.init(
+    ...
+    callbacks=[csv_writer]
+)
+```
+
+执行代码后，就会在`logs`目录下生成一个`swanlab_run.csv`文件，并开始记录数据。后续的每一次训练，都会在该csv文件中添加新的行。
+
+如果想要指定其他文件名，可以传入`filename`参数：
+
+```python
+csv_writer = CSVWriter(dir="logs", filename="my_csv_file.csv")
+```
+
+
+## 示例代码
+
+
+```python
+import swanlab
+from swanlab.plugin.writer import CSVWriter
+import random
+
+csv_writer = CSVWriter(dir="logs")
+
+# 创建一个SwanLab项目
+swanlab.init(
+    # 设置项目名
+    project="my-awesome-project",
+    
+    # 设置超参数
+    config={
+        "learning_rate": 0.02,
+        "architecture": "CNN",
+        "dataset": "CIFAR-100",
+        "epochs": 10,
+        "batch_size": 128
+    },
+    callbacks=[csv_writer]
+)
+
+# 模拟一次训练
+epochs = 10
+offset = random.random() / 5
+for epoch in range(2, epochs):
+  acc = 1 - 2 ** -epoch - random.random() / epoch - offset
+  loss = 2 ** -epoch + random.random() / epoch + offset
+
+  # 记录训练指标
+  swanlab.log({"acc": acc, "loss2": loss})
+
+# [可选] 完成训练，这在notebook环境中是必要的
+swanlab.finish()
+```