Question

我正在尝试通过创建一个非常简单的项目并记录它来学习使用mlflow。

我尝试按照mlflow的示例进行操作，并且在将main.py作为常规bash命令运行时，我的代码可以正常运行。

我无法使用项目和简单文件通过mlflow CLI运行它。我收到以下错误。

(rlearning) yair@pc2016:~/reinforced_learning101$ mlflow run src/main.py 
2019/05/11 10:21:41 ERROR mlflow.cli: === Could not find main among entry points [] or interpret main as a runnable script. Supported script file extensions: ['.py', '.sh'] ===
(rlearning) yair@pc2016:~/reinforced_learning101$ mlflow run .
2019/05/11 10:40:25 INFO mlflow.projects: === Created directory /tmp/tmpe26oernf for downloading remote URIs passed to arguments of type 'path' ===
2019/05/11 10:40:25 INFO mlflow.projects: === Running command 'source activate mlflow-21497056aed7961402b515847613ed9f950fa9fc && python src/main.py 1.0' in run with ID 'ed51446de4c44903ab891d09cfe10e49' === 
bash: activate: No such file or directory
2019/05/11 10:40:25 ERROR mlflow.cli: === Run (ID 'ed51446de4c44903ab891d09cfe10e49') failed ===

不用说我的主后缀为.py。

是否有任何错误导致此问题？

我的main.py是：

import sys

import gym
import mlflow


if __name__ == '__main__':
    env = gym.make("CartPole-v0")
    right_percent = float(sys.argv[1]) if len(sys.argv) > 1 else 1.0
    with mlflow.start_run():
        obs = env.reset()
        print(env.action_space)
        action = 1  # accelerate right
        print(obs)
        mlflow.log_param("right percent", right_percent)
        mlflow.log_metric("mean score", 1)
        mlflow.log_metric("std score", 0)

conda_env.yaml

name: rlearning
channels:
  - defaults
dependencies:
  - python=3.7
  - numpy
  - pandas
  - tensorflow-gpu
  - pip:
      - mlflow
      - gym

MLproject

name: reinforced learning

conda_env: files/config/conda_environment.yaml

entry_points:
  main:
    parameters:
      right_percent: {type: float, default: 1.0}
    command: "python src/main.py {right_percent}"

Answer 1

似乎您对conda初始化有问题。仅出于测试目的，我建议您尝试--no-conda（在确保您之前pip安装了所有库之后）。

因此，请尝试以下操作：mlflow run . --no-conda

mlflow找不到.py文件

1 个答案: