update doc

baidubce · Jan 11, 2024 · e5cc562 · e5cc562
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diff --git a/docs/cli.md b/docs/cli.md
@@ -242,4 +242,59 @@ $ qianfan dataset view [OPTIONS] DATASET
 * `--row TEXT`：待预览的数据集行。用 `,` 分隔数个行，用 `-` 表示一个范围 (e.g. 1,3-5,12)。默认情况下仅打印前 5 行，可以通过 `--row all` 来打印所有数据。
 * `--column TEXT`：待预览的数据集的列。用 `,` 分隔每个列名称。 (e.g. prompt,response)
 * `--raw`：展示原始数据。
-* `--help`：展示帮助文档。
+* `--help`：展示帮助文档。
+
+## trainer 训练
+
+**用法**:
+
+```console
+$ qianfan trainer [OPTIONS] COMMAND [ARGS]...
+```
+
+**Options 选项**:
+
+* `--help`：展示帮助文档
+
+**Commands 命令**:
+
+* `run`：运行 trainer 任务
+
+### run 
+
+运行 trainer 任务
+
+**用法**:
+
+```console
+$ qianfan trainer run [OPTIONS]
+```
+
+**Options 选项**:
+
+* `--train-type TEXT`：训练类型  [required]
+* `--dataset-id INTEGER`：数据集 id  [required]
+* `--help`：展示帮助文档
+
+训练相关配置，参数含义与 [训练 API 文档](https://cloud.baidu.com/doc/WENXINWORKSHOP/s/mlmrgo4yx#body%E5%8F%82%E6%95%B0) 中对应参数含义一致：
+
+* `--train-epoch INTEGER`：训练轮数
+* `--train-batch-size INTEGER`：训练每轮 batch 的大小
+* `--train-learning-rate FLOAT`：学习率
+* `--train-max-seq-len INTEGER`：最大训练长度
+* `--train-peft-type [all|p_tuning|lo_ra]`：Parameter efficient finetuning 方式
+* `--trainset-rate INTEGER`：数据拆分比例  [default：20]
+* `--train-logging-steps INTEGER`：日志记录间隔
+* `--train-warmup-ratio FLOAT`：预热比例
+* `--train-weight-decay FLOAT`：正则化系数
+* `--train-lora-rank INTEGER`：LoRA 策略中的秩
+* `--train-lora-all-linear TEXT`：LoRA 是否所有均为线性层
+
+部署相关配置，参数含义与 [创建服务 API 文档](https://cloud.baidu.com/doc/WENXINWORKSHOP/s/Plnlmxdgy#body%E5%8F%82%E6%95%B0) 中对应参数含义一致：
+
+* `--deploy-name TEXT`：部署服务名称。设置该值后会开始部署 action。
+* `--deploy-endpoint-prefix TEXT`：部署服务的 endpoint 前缀
+* `--deploy-description TEXT`：服务描述
+* `--deploy-replicas INTEGER`：副本数  [default：1]
+* `--deploy-pool-type [public_resource|private_resource]`：资源池类型  [default：private_resource]
+* `--deploy-service-type [chat|completion|embedding|text2_image]`：服务类型  [default：chat]
diff --git a/src/qianfan/common/client/trainer.py b/src/qianfan/common/client/trainer.py
@@ -156,7 +156,6 @@ def handle_evaluate(self, event: Event) -> None:
                 self.progress.update(self.current_task, total=100, completed=100)
 
     def dispatch(self, event: Event) -> None:
-        # self.progress.log(str(event))
         if event.action_state == ActionState.Stopped:
             print_error_msg(f"{event.action_class.__name__} {event.action_id} stopped.")
             return
@@ -187,7 +186,7 @@ def dispatch(self, event: Event) -> None:
 
 @trainer_app.command()
 def run(
-    dataset_id: int = typer.Option(..., help="Dataset name"),
+    dataset_id: int = typer.Option(..., help="Dataset id"),
     train_type: str = typer.Option(..., help="Train type"),
     train_epoch: Optional[int] = typer.Option(
         None, help="Train epoch", rich_help_panel=TRAIN_CONFIG_PANEL
@@ -199,7 +198,7 @@ def run(
         None, help="Train learning rate", rich_help_panel=TRAIN_CONFIG_PANEL
     ),
     train_max_seq_len: Optional[int] = typer.Option(
-        None, help="Train max seq len", rich_help_panel=TRAIN_CONFIG_PANEL
+        None, help="Max sequence length", rich_help_panel=TRAIN_CONFIG_PANEL
     ),
     train_peft_type: Optional[PeftType] = typer.Option(
         None,
@@ -208,25 +207,29 @@ def run(
         rich_help_panel=TRAIN_CONFIG_PANEL,
     ),
     trainset_rate: int = typer.Option(
-        20, help="Trainset rate", rich_help_panel=TRAIN_CONFIG_PANEL
+        20, help="Trainset ratio", rich_help_panel=TRAIN_CONFIG_PANEL
     ),
     train_logging_steps: Optional[int] = typer.Option(
-        None, help="Train logging steps", rich_help_panel=TRAIN_CONFIG_PANEL
+        None, help="Logging steps", rich_help_panel=TRAIN_CONFIG_PANEL
     ),
     train_warmup_ratio: Optional[float] = typer.Option(
-        None, help="Train warmup ratio", rich_help_panel=TRAIN_CONFIG_PANEL
+        None, help="Warmup ratio", rich_help_panel=TRAIN_CONFIG_PANEL
     ),
     train_weight_decay: Optional[float] = typer.Option(
-        None, help="Train weight decay", rich_help_panel=TRAIN_CONFIG_PANEL
+        None, help="Weight decay", rich_help_panel=TRAIN_CONFIG_PANEL
     ),
     train_lora_rank: Optional[int] = typer.Option(
-        None, help="Train lora rank", rich_help_panel=TRAIN_CONFIG_PANEL
+        None, help="Lora rank", rich_help_panel=TRAIN_CONFIG_PANEL
     ),
     train_lora_all_linear: Optional[str] = typer.Option(
-        None, help="Train lora all linear", rich_help_panel=TRAIN_CONFIG_PANEL
+        None,
+        help="Whether lora is all linear layer",
+        rich_help_panel=TRAIN_CONFIG_PANEL,
     ),
     deploy_name: Optional[str] = typer.Option(
-        None, help="Deploy name", rich_help_panel=DEPLOY_CONFIG_PANEL
+        None,
+        help="Deploy name. Set this value to enable deploy action.",
+        rich_help_panel=DEPLOY_CONFIG_PANEL,
     ),
     deploy_endpoint_prefix: Optional[str] = typer.Option(
         None, help="Deploy endpoint prefix", rich_help_panel=DEPLOY_CONFIG_PANEL
@@ -253,7 +256,6 @@ def run(
     """
     Run a trainer job.
     """
-    # qianfan.enable_log("INFO")
     console = replace_logger_handler()
     callback = MyEventHandler(console=console)
     ds = Dataset.load(qianfan_dataset_id=dataset_id)