text
stringlengths 0
15.3k
|
|---|
return re.sub('\\W', '_', task_name) |
def get_latest_filename(filenames: List[str]) -> str: |
return max(filenames, key=lambda f: get_file_datetime(f)) |
def get_results_filenames(filenames: List[str]) -> List[str]: |
return [f for f in filenames if '/results_' in f and '.json' in f] |
def get_sample_results_filenames(filenames: List[str]) -> List[str]: |
return [f for f in filenames if '/samples_' in f and '.json' in f] |
def get_rolling_token_windows(token_list, prefix_token, max_seq_len, context_len): |
assert 1 <= context_len <= max_seq_len |
if not token_list: |
return |
pred_len = max_seq_len - context_len + 1 |
predicted = 0 |
first_seq_len = min(max_seq_len, len(token_list)) |
yield ([prefix_token] + token_list[:first_seq_len - 1], token_list[:first_seq_len]) |
predicted += first_seq_len |
while predicted < len(token_list): |
window_pred_len = min(len(token_list) - predicted, pred_len) |
window_end = predicted + window_pred_len |
yield (token_list[window_end - max_seq_len - 1:window_end - 1], token_list[window_end - window_pred_len:window_end]) |
predicted += window_pred_len |
def make_disjoint_window(pair): |
(a, b) = pair |
return (a[:len(a) - (len(b) - 1)], b) |
class EnhancedJSONEncoder(json.JSONEncoder): |
def default(self, o): |
if is_dataclass(o): |
return asdict(o) |
return super().default(o) |
class Reorderer: |
def __init__(self, arr: List[Any], fn: Callable) -> None: |
self.size = len(arr) |
arr = list(enumerate(arr)) |
arr = group(arr, lambda x: fn(x[1])) |
arr = [([y[0]], x[0][1]) for x in arr for y in x] |
arr.sort(key=lambda x: fn(x[1])) |
self.arr = arr |
def get_reordered(self): |
return [x[1] for x in self.arr] |
def get_original(self, newarr): |
res = [None] * self.size |
cov = [False] * self.size |
for ((inds, _), v) in zip(self.arr, newarr): |
for ind in inds: |
res[ind] = v |
cov[ind] = True |
assert all(cov) |
return res |
def make_table(result_dict, column: str='results', sort_results: bool=False): |
from pytablewriter import LatexTableWriter, MarkdownTableWriter |
if column == 'results': |
column_name = 'Tasks' |
elif column == 'groups': |
column_name = 'Groups' |
all_headers = [column_name, 'Version', 'Filter', 'n-shot', 'Metric', '', 'Value', '', 'Stderr'] |
md_writer = MarkdownTableWriter() |
latex_writer = LatexTableWriter() |
md_writer.headers = all_headers |
latex_writer.headers = all_headers |
values = [] |
keys = result_dict[column].keys() |
if sort_results: |
keys = sorted(keys) |
for k in keys: |
dic = result_dict[column][k] |
version = result_dict['versions'].get(k, ' N/A') |
n = str(result_dict.get('n-shot', ' ').get(k, ' ')) |
higher_is_better = result_dict.get('higher_is_better', {}).get(k, {}) |
if 'alias' in dic: |
k = dic.pop('alias') |
metric_items = dic.items() |
metric_items = sorted(metric_items) |
for (mf, v) in metric_items: |
(m, _, f) = mf.partition(',') |
if m.endswith('_stderr'): |
continue |
hib = HIGHER_IS_BETTER_SYMBOLS.get(higher_is_better.get(m), '') |
v = '%.4f' % v if isinstance(v, float) else v |
if m + '_stderr' + ',' + f in dic: |
se = dic[m + '_stderr' + ',' + f] |
se = ' N/A' if se == 'N/A' else '%.4f' % se |
values.append([k, version, f, n, m, hib, v, '±', se]) |
else: |
values.append([k, version, f, n, m, hib, v, '', '']) |
k = '' |
version = '' |
md_writer.value_matrix = values |
latex_writer.value_matrix = values |
Subsets and Splits