# Access the profile data
<a name="debugger-analyze-data-profiling"></a>

The SMDebug `TrainingJob` class reads data from the S3 bucket where the system and framework metrics are saved. 

**To set up a `TrainingJob` object and retrieve profiling event files of a training job**

```
from smdebug.profiler.analysis.notebook_utils.training_job import TrainingJob
tj = TrainingJob(training_job_name, region)
```

**Tip**  
You need to specify the `training_job_name` and `region` parameters to log to a training job. There are two ways to specify the training job information:   
Use the SageMaker Python SDK while the estimator is still attached to the training job.  

  ```
  import sagemaker
  training_job_name=estimator.latest_training_job.job_name
  region=sagemaker.Session().boto_region_name
  ```
Pass strings directly.  

  ```
  training_job_name="your-training-job-name-YYYY-MM-DD-HH-MM-SS-SSS"
  region="us-west-2"
  ```

**Note**  
By default, SageMaker Debugger collects system metrics to monitor hardware resource utilization and system bottlenecks. Running the following functions, you might receive error messages regarding unavailability of framework metrics. To retrieve framework profiling data and gain insights into framework operations, you must enable framework profiling.  
If you use SageMaker Python SDK to manipulate your training job request, pass the `framework_profile_params` to the `profiler_config` argument of your estimator. To learn more, see [Configure SageMaker Debugger Framework Profiling](https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-configure-framework-profiling.html).
If you use Studio Classic, turn on profiling using the **Profiling** toggle button in the Debugger insights dashboard. To learn more, see [SageMaker Debugger Insights Dashboard Controller](https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-on-studio-insights-controllers.html).

**To retrieve a description of the training job description and the S3 bucket URI where the metric data are saved**

```
tj.describe_training_job()
tj.get_config_and_profiler_s3_output_path()
```

**To check if the system and framework metrics are available from the S3 URI**

```
tj.wait_for_sys_profiling_data_to_be_available()
tj.wait_for_framework_profiling_data_to_be_available()
```

**To create system and framework reader objects after the metric data become available**

```
system_metrics_reader = tj.get_systems_metrics_reader()
framework_metrics_reader = tj.get_framework_metrics_reader()
```

**To refresh and retrieve the latest training event files**

The reader objects have an extended method, `refresh_event_file_list()`, to retrieve the latest training event files.

```
system_metrics_reader.refresh_event_file_list()
framework_metrics_reader.refresh_event_file_list()
```