[Bug Report] Sagemaker debugger issue - CreateXgboostReport processing job fails when training XGBoost image version >= 1.3-1

**Link to the notebook**
[Add the link to the notebook.](https://github.com/aws/amazon-sagemaker-examples/blob/15c4d2433ca1839fc014e01dfeaece5cc87e13b0/sagemaker-debugger/xgboost_training_report/higgs_boson_detection.ipynb)

**Describe the bug**
If you run [Amazon SageMaker Debugger XGBoost training report for Higgs Boson Detection Challenge](https://github.com/aws/amazon-sagemaker-examples/blob/15c4d2433ca1839fc014e01dfeaece5cc87e13b0/sagemaker-debugger/xgboost_training_report/higgs_boson_detection.ipynb) notebook (latest version to date) from the `sagemaker-examples` repo with newer xgboost container versions `1.3-1` or `1.5-1`, then, as a result, you get `CreateXgboostReport` processing job failed.

**To reproduce**
Replace
```python
xgboost_container = image_uris.retrieve("xgboost", region, "1.2-1")
```
line of code with the newer container versions - `1.3-1` or `1.5-1`
```python
xgboost_container = image_uris.retrieve("xgboost", region, "1.3-1") # or 1.5-1
```
and run the whole notebook.

**Logs**
```
[2022-11-07 13:29:11.235 <...> INFO utils.py:27] RULE_JOB_STOP_SIGNAL_FILENAME: None
[2022-11-07 13:29:13.678 <...> INFO local_trial.py:35] Loading trial base_trial at path /opt/ml/processing/input/tensors
Exception during rule evaluation: Customer Error: No debugging data was saved by the training job. Check that the debugger hook was configured correctly before starting the training job. Exception: Training job has ended. All the collection files could not be loaded
Traceback (most recent call last):
File "evaluate.py", line 119, in _create_trials
range_steps=(self.start_step, self.end_step))
File "/usr/local/lib/python3.7/site-packages/smdebug/trials/utils.py", line 25, in create_trial
return LocalTrial(name=name, dirname=path, **kwargs)
File "/usr/local/lib/python3.7/site-packages/smdebug/trials/local_trial.py", line 36, in __init__
self._load_collections()
File "/usr/local/lib/python3.7/site-packages/smdebug/trials/trial.py", line 168, in _load_collections
_wait_for_collection_files(1) # wait for the first collection file
File "/usr/local/lib/python3.7/site-packages/smdebug/trials/trial.py", line 165, in _wait_for_collection_files
raise MissingCollectionFiles
smdebug.exceptions.MissingCollectionFiles: Training job has ended. All the collection files could not be loaded
```

I see several possible issue sources, however, I am not sure which one is the *one*:
- XGBoost container images:
- from `1.2-1` up to the latest version to date `1.5-1` code pieces that contain [`smdebug` library](https://github.com/awslabs/sagemaker-debugger) related code have not been changed.
- `smdebug` library:
- although the version of the library listed in [`requirements.txt`](https://github.com/aws/sagemaker-xgboost-container/blob/master/requirements.txt) had changed from `smdebug==1.0.7` in [`1.2-1`](https://github.com/aws/sagemaker-xgboost-container/blob/v1.2-1/requirements.txt#L20) to `smdebug==1.0.10` in [`1.2-2`](https://github.com/aws/sagemaker-xgboost-container/blob/v1.2-2/requirements.txt#L20) [and](https://github.com/aws/sagemaker-xgboost-container/blob/v1.3-1/requirements.txt#L22) [later](https://github.com/aws/sagemaker-xgboost-container/blob/v1.5-1/requirements.txt#L22), running the example notebook with xgboost container version `1.2-2` worked totally fine.
- `972752614525.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-debugger-rules:latest` image:
- in all cases, this image version has been used. I doubt that the image had been updated while I was running my "experiments".
- `sagemaker==2.112.2`.

Run the linked higgs_boson_detection.ipynb with XGBoost container versions 1.3-1 and 1.5-1, comparing against 1.2-1 and 1.2-2. Start with the CreateXgboostReport processing job and the reported MissingCollectionFiles traceback, then inspect the referenced smdebug requirements versions and container-related code. Done means the notebook completes successfully with the newer container versions and produces the training report.

Written by the indexing model from the issue text.