Loading all file paths into memory at once with list(dir_data.glob("*.pt")) can be memory-intensive if dir_data contains many files. Also, the iteration order from dir_data.glob("*.pt") is not guaranteed, which affects last_physical_to_logical_map.

If a specific last_physical_to_logical_map is critical, sort the paths explicitly: file_paths = sorted(list(dir_data.glob("*.pt"))). If any last_physical_to_logical_map is acceptable, iterate directly over the generator dir_data.glob("*.pt") for better memory efficiency. Clarify the intended behavior for last_physical_to_logical_map with a comment.

# Option 1: If a specific order is needed:
# file_paths_to_process = sorted(list(dir_data.glob("*.pt")))
# Option 2: If order doesn't matter and memory efficiency is prioritized:
file_paths_to_process = dir_data.glob("*.pt")
for path in tqdm(file_paths_to_process):

The code doesn't handle the case where dir_data.glob("*.pt") yields no files. last_physical_to_logical_map (line 23) would not be assigned, potentially leading to a NameError on line 49. items (line 37) would remain empty, and torch.stack(items) (line 44) would raise an error.

Initialize last_physical_to_logical_map to a default value (e.g., None) before the loop and check if items is empty before calling torch.stack. If no files are processed, return default/empty structures or raise a FileNotFoundError.

This print statement is for debugging. Remove or replace it with a proper logging mechanism before merging.

# Consider using logging:
# import logging
# logger = logging.getLogger(__name__)
# logger.debug(f"Make {forward_pass_ids=} into array")

This print statement is also for debugging. Remove it or convert it to a log message.

# Consider using logging:
# logger.debug(f"{gpc_of_forward_pass.shape=}")