Fix SubprocessDiedError

✅ Solution

SubprocessDiedError in NumPy often arises from running out of memory or encountering a fatal signal (like SIGSEGV) in a child process during parallel computations, especially with functions utilizing multiple cores. To mitigate this, try reducing the number of cores used by NumPy (e.g., `os.environ['NUMPY_NUM_THREADS'] = '1'`) or address the underlying memory issue by processing data in smaller chunks or optimizing memory usage within the problematic NumPy function. If the error persists, inspect the input data for corrupt or invalid values that could trigger a fatal error.