# Download the Debugger XGBoost training report
<a name="debugger-training-xgboost-report-download"></a>

Download the Debugger XGBoost training report while your training job is running or after the job has finished using the [Amazon SageMaker Python SDK](https://sagemaker.readthedocs.io/en/stable) and AWS Command Line Interface (CLI).

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#### [ Download using the SageMaker Python SDK and AWS CLI ]

1. Check the current job's default S3 output base URI.

   ```
   estimator.output_path
   ```

1. Check the current job name.

   ```
   estimator.latest_training_job.job_name
   ```

1. The Debugger XGBoost report is stored under `<default-s3-output-base-uri>/<training-job-name>/rule-output`. Configure the rule output path as follows:

   ```
   rule_output_path = estimator.output_path + "/" + estimator.latest_training_job.job_name + "/rule-output"
   ```

1. To check if the report is generated, list directories and files recursively under the `rule_output_path` using `aws s3 ls` with the `--recursive` option.

   ```
   ! aws s3 ls {rule_output_path} --recursive
   ```

   This should return a complete list of files under autogenerated folders that are named `CreateXgboostReport` and `ProfilerReport-1234567890`. The XGBoost training report is stored in the `CreateXgboostReport`, and the profiling report is stored in the `ProfilerReport-1234567890` folder. To learn more about the profiling report generated by default with the XGBoost training job, see [SageMaker Debugger interactive report](debugger-profiling-report.md).  
![\[An example of rule output.\]](http://docs.aws.amazon.com/sagemaker/latest/dg/images/debugger/debugger-xgboost-report-ls.png)

   The `xgboost_report.html` is an autogenerated XGBoost training report by Debugger. The `xgboost_report.ipynb` is a Jupyter notebook that's used to aggregate training results into the report. You can download all of the files, browse the HTML report file, and modify the report using the notebook.

1. Download the files recursively using `aws s3 cp`. The following command saves all of the rule output files to the `ProfilerReport-1234567890` folder under the current working directory.

   ```
   ! aws s3 cp {rule_output_path} ./ --recursive
   ```
**Tip**  
If you are using a Jupyter notebook server, run `!pwd` to verify the current working directory.

1. Under the `/CreateXgboostReport` directory, open `xgboost_report.html`. If you are using JupyterLab, choose **Trust HTML** to see the autogenerated Debugger training report.  
![\[An example of rule output.\]](http://docs.aws.amazon.com/sagemaker/latest/dg/images/debugger/debugger-xgboost-report-open-trust.png)

1. Open the `xgboost_report.ipynb` file to explore how the report is generated. You can customize and extend the training report using the Jupyter notebook file.

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#### [ Download using the Amazon S3 console ]

1. Sign in to the AWS Management Console and open the Amazon S3 console at [https://console.aws.amazon.com/s3/](https://console.aws.amazon.com/s3/).

1. Search for the base S3 bucket. For example, if you haven't specified any base job name, the base S3 bucket name should be in the following format: `sagemaker-<region>-111122223333`. Look up the base S3 bucket through the **Find bucket by name** field.  
![\[The Find bucket by name field in the Amazon S3 console.\]](http://docs.aws.amazon.com/sagemaker/latest/dg/images/debugger/debugger-report-download-s3console-0.png)

1. In the base S3 bucket, look up the training job name by entering your job name prefix in **Find objects by prefix** and then choosing the training job name.  
![\[The Find objects by prefix field in the Amazon S3 console.\]](http://docs.aws.amazon.com/sagemaker/latest/dg/images/debugger/debugger-report-download-s3console-1.png)

1. In the training job's S3 bucket, choose **rule-output/** subfolder. There must be three subfolders for training data collected by Debugger: **debug-output/**, **profiler-output/**, and **rule-output/**.   
![\[An example to the rule output S3 bucket URI.\]](http://docs.aws.amazon.com/sagemaker/latest/dg/images/debugger/debugger-report-download-s3console-2.png)

1. In the **rule-output/** folder, choose the **CreateXgboostReport/** folder. The folder contains **xbgoost\$1report.html** (the autogenerated report in html) and **xbgoost\$1report.ipynb** (a Jupyter notebook with scripts that are used for generating the report).

1. Choose the **xbgoost\$1report.html** file, choose **Download actions**, and then choose **Download**.  
![\[An example to the rule output S3 bucket URI.\]](http://docs.aws.amazon.com/sagemaker/latest/dg/images/debugger/debugger-xgboost-report-s3-download.png)

1. Open the downloaded **xbgoost\$1report.html** file in a web browser.

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