Use consistent string formatting in logging statements throughout the codebase. Prefer % style placeholders over f-strings or .format() in logging calls as this is more efficient when logs are filtered by level (placeholders are only evaluated if the log is actually emitted).

For good logging practices:

1. Use placeholder style consistently: ```python

   Recommended

   logging.info(‘%s benchmark running.’, operation_type)

Avoid mixing styles in the same codebase

logging.error(‘No models found in S3 bucket: {}’.format(bucket_name)) logging.warning(f’Failed to process {item_name}’) # Avoid f-strings in logging

2. Reduce duplicate logging logic:
```python
# Instead of:
if opt.train:
    logging.info('%s training benchmark.', cell)
else:
    logging.info('%s inference benchmark.', cell)

# Prefer:
mode = 'training' if opt.train else 'inference'
logging.info('%s %s benchmark.', cell, mode)

1. Choose appropriate log levels based on severity:
   • Use logging.error() for failures that prevent normal operation
   • Use logging.warning() for potential issues that don’t stop execution
   • Use assertions only for developer-facing invariants that should never be violated
   • Consider warnings instead of assertions in user-facing code