Use higher-level iterations

When working with multiple sequences that need to be combined, prefer higher-level iteration abstractions over nested loops. This improves code readability, reduces nesting depth, and helps prevent logical errors when managing multiple iterative dimensions.

For example, instead of writing nested loops:

dtypes = [torch.int, torch.long, torch.short]
for count_dtype in dtypes:
    for prob_dtype in dtypes:
        # process with count_dtype and prob_dtype

Use itertools.product for a cleaner approach:

dtypes = [torch.int, torch.long, torch.short]
for count_dtype, prob_dtype in itertools.product(dtypes, repeat=2):
    # process with count_dtype and prob_dtype

Similarly, other Python constructs can simplify iteration patterns:

• Use enumerate when you need both index and value
• Use zip to iterate through multiple sequences in parallel
• Use comprehensions instead of building collections with loops
• Consider reversed, sorted, or other builtin functions when applicable

These higher-level abstractions make algorithmic intent more evident and reduce opportunities for off-by-one errors or incorrect nested logic.