@numba_njit<EOL>def _get_context(center_idx, sentence_boundaries, window_size,<EOL>random_window_size, seed):
random.seed(seed + center_idx)<EOL>sentence_index = np.searchsorted(sentence_boundaries, center_idx)<EOL>sentence_start, sentence_end = _get_sentence_start_end(<EOL>sentence_boundaries, sentence_index)<EOL>if random_window_size:<EOL><INDENT>window_size = random.randint(<NUM_LIT:1>, window_size)<EOL><DEDENT>start_idx = max(sentence_start, center_idx - window_size)<EOL>end_idx = min(sentence_end, center_idx + window_size + <NUM_LIT:1>)<EOL>if start_idx != center_idx and center_idx + <NUM_LIT:1> != end_idx:<EOL><INDENT>context = np.concatenate((np.arange(start_idx, center_idx),<EOL>np.arange(center_idx + <NUM_LIT:1>, end_idx)))<EOL><DEDENT>elif start_idx != center_idx:<EOL><INDENT>context = np.arange(start_idx, center_idx)<EOL><DEDENT>elif center_idx + <NUM_LIT:1> != end_idx:<EOL><INDENT>context = np.arange(center_idx + <NUM_LIT:1>, end_idx)<EOL><DEDENT>else:<EOL><INDENT>context = None<EOL><DEDENT>return context<EOL>
Compute the context with respect to a center word in a sentence.

    Takes an numpy array of sentences boundaries.