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.

Add Repository

Private Repository