peacock-data-public-datasets-idc-cronscript
/
venv
/lib
/python3.10
/site-packages
/sacrebleu
/utils.py
import json | |
import os | |
import re | |
import sys | |
import gzip | |
import math | |
import hashlib | |
import logging | |
import portalocker | |
from collections import defaultdict | |
from typing import List, Optional, Sequence, Dict | |
from argparse import Namespace | |
from tabulate import tabulate | |
import colorama | |
# Where to store downloaded test sets. | |
# Define the environment variable $SACREBLEU, or use the default of ~/.sacrebleu. | |
# | |
# Querying for a HOME environment variable can result in None (e.g., on Windows) | |
# in which case the os.path.join() throws a TypeError. Using expanduser() is | |
# a safe way to get the user's home folder. | |
USERHOME = os.path.expanduser("~") | |
SACREBLEU_DIR = os.environ.get('SACREBLEU', os.path.join(USERHOME, '.sacrebleu')) | |
sacrelogger = logging.getLogger('sacrebleu') | |
class Color: | |
ENABLE_COLORS = True | |
def format(msg: str, color: str) -> str: | |
"""Returns a colored version of the given message string. | |
:param msg: The string to Color.format. | |
:param color: The color specifier i.e. 'red', 'blue', 'green', etc. | |
:return: A colored version of the string if the output is a terminal. | |
""" | |
if not Color.ENABLE_COLORS: | |
return msg | |
_ansi_str = getattr(colorama.Fore, color.upper(), None) | |
if _ansi_str: | |
return f'{_ansi_str}{msg}{colorama.Style.RESET_ALL}' | |
return msg | |
def _format_score_lines(scores: dict, | |
width: int = 2, | |
multiline: bool = True) -> Dict[str, List[str]]: | |
"""Formats the scores prior to tabulating them.""" | |
new_scores = {'System': scores.pop('System')} | |
p_val_break_char = '\n' if multiline else ' ' | |
is_bootstrap = False | |
def _color_p_value(p: float): | |
msg = f'(p = {p:.4f})' | |
if p > 0.05: | |
return Color.format(msg, 'red') | |
return msg + '*' | |
for metric, vals in scores.items(): | |
new_vals = [] | |
for result in vals: | |
if not isinstance(result, str): | |
# Format result instances | |
_str = f'{result.score:.{width}f}' | |
if result.mean is not None: | |
is_bootstrap = True | |
_str += f' ({result.mean:.{width}f} ± {result.ci:.{width}f})' | |
if result.p_value is not None: | |
_str += p_val_break_char + _color_p_value(result.p_value) | |
else: | |
# Already formatted in non paired-test mode | |
_str = result | |
new_vals.append(_str) | |
if is_bootstrap: | |
# Change titles | |
metric += ' (μ ± 95% CI)' | |
new_scores[metric] = new_vals | |
return new_scores | |
def print_results_table(results: dict, signatures: dict, args: Namespace): | |
"""Prints out a nicely formatted table for multi-system evaluation mode.""" | |
if args.format == 'json': | |
proper_json = [] | |
dict_keys = list(results.keys()) | |
for i in range(len(results['System'])): | |
value = {} | |
value['system'] = results['System'][i] | |
# parse metrics | |
for j in range(1, len(dict_keys)): | |
if isinstance(results[dict_keys[j]][i], str): | |
value[dict_keys[j]] = results[dict_keys[j]][i] | |
else: | |
# Values inside object as dict | |
value[dict_keys[j]] = results[dict_keys[j]][i].__dict__ | |
proper_json.append(value) | |
print(json.dumps(proper_json, indent=4)) | |
return | |
tablefmt = args.format | |
if tablefmt in ('text'): | |
tablefmt = 'fancy_grid' | |
elif tablefmt == 'latex': | |
# Use booktabs | |
tablefmt = 'latex_booktabs' | |
# If paired testing has been given, this'll format the score lines | |
results = _format_score_lines( | |
results, args.width, multiline=tablefmt == 'fancy_grid') | |
new_dict = {} | |
# Color the column names and the baseline system name and scores | |
has_baseline = False | |
baseline_name = '' | |
for name in results.keys(): | |
val = results[name] | |
if val[0].startswith('Baseline:') or has_baseline: | |
if val[0].startswith('Baseline:'): | |
baseline_name = val[0] | |
has_baseline = True | |
val[0] = Color.format(val[0], 'yellow') | |
new_dict[Color.format(name, 'cyan')] = results[name] | |
# Finally tabulate | |
table = tabulate( | |
new_dict, headers='keys', tablefmt=tablefmt, | |
colalign=('right', ), | |
stralign='center', | |
numalign='center', | |
floatfmt=f'.{args.width}f') | |
print(table) | |
print() | |
is_paired = args.paired_bs or args.paired_ar | |
if is_paired: | |
test_type = 'bootstrap resampling' if args.paired_bs else 'approximate randomization' | |
n_samples_or_trials = args.paired_bs_n if args.paired_bs else args.paired_ar_n | |
test_sample_type = 'resampling trials' if args.paired_bs else 'trials' | |
msg = f'Paired {test_type} test with {n_samples_or_trials} {test_sample_type}' | |
bline = Color.format('baseline', 'yellow') | |
bline_name = Color.format(baseline_name, 'yellow') | |
null_hyp = Color.format('Null hypothesis', 'green') | |
pval_color = Color.format('highlighted in red', 'red') | |
# Print fancy header | |
print('-' * len(msg) + '\n' + msg + '\n' + '-' * len(msg)) | |
print(f' - Each system is pairwise compared to {bline_name}.') | |
if args.paired_bs: | |
print(' Actual system score / bootstrap estimated true mean / 95% CI are provided for each metric.') | |
else: | |
print(' Actual system score is provided for each metric.') | |
print() | |
print(f' - {null_hyp}: the system and the {bline} translations are essentially') | |
print(f' generated by the same underlying process. For a given system and the {bline},') | |
print(' the p-value is roughly the probability of the absolute score difference (delta)') | |
print(f' or higher occurring due to chance, under the assumption that the {null_hyp.lower()} is correct.') | |
print() | |
print(f' - Assuming a significance threshold of 0.05, the {null_hyp.lower()} can be rejected') | |
print(' for p-values < 0.05 (marked with "*"). This means that the delta is unlikely to be attributed') | |
print(f' to chance, hence the system is significantly "different" than the {bline}.') | |
print(f' Otherwise, the p-values are {pval_color}.') | |
print() | |
print(f' - NOTE: Significance does not tell whether a system is "better" than the {bline} but rather') | |
print(' emphasizes the "difference" of the systems in terms of the replicability of the delta.') | |
print() | |
print('-----------------') | |
print('Metric signatures') | |
print('-----------------') | |
for name, sig in signatures.items(): | |
print(f' - {name:<10} {sig}') | |
def print_single_results(results: List[str], args: Namespace): | |
"""Re-process metric strings to align them nicely.""" | |
if args.format == 'json': | |
if len(results) > 1: | |
proper_json = '[\n' + ',\n'.join(results) + '\n]' | |
print(proper_json) | |
else: | |
print(results[0]) | |
return | |
# Color confidence strings for emphasis | |
if 'μ' in results[0]: | |
color_re = re.compile(r'(\(μ = [0-9\.]+ ± [0-9\.]+\))') | |
for idx in range(len(results)): | |
results[idx] = color_re.sub( | |
lambda m: Color.format(m.group(), 'cyan'), results[idx]) | |
if len(results) == 1: | |
# Just one system, nothing to align. | |
print(results[0]) | |
return | |
# Align by '=' character | |
lens = [] | |
for line in results: | |
# If not score_only, split lines from '=' for re-alignment | |
try: | |
lens.append(line.index('=') - 1) | |
except ValueError: | |
print(line) | |
if len(lens) > 0: | |
w = max(lens) | |
for (_len, line) in zip(lens, results): | |
left, right = line[:_len], line[_len:] | |
print(f'{left:>{w}}{right}') | |
def sanity_check_lengths(system: Sequence[str], | |
refs: Sequence[Sequence[str]], | |
test_set: Optional[str] = None): | |
n_hyps = len(system) | |
if any(len(ref_stream) != n_hyps for ref_stream in refs): | |
sacrelogger.error("System and reference streams have different lengths.") | |
if test_set: | |
sacrelogger.error("This could be an issue with your system output " | |
"or with sacreBLEU's reference database if -t is given.") | |
sacrelogger.error("For the latter, try cleaning out the cache by typing:\n") | |
sacrelogger.error(f" rm -r {SACREBLEU_DIR}/{test_set}\n") | |
sacrelogger.error("The test sets will be re-downloaded the next time you run sacreBLEU.") | |
sys.exit(1) | |
def smart_open(file, mode='rt', encoding='utf-8'): | |
"""Convenience function for reading compressed or plain text files. | |
:param file: The file to read. | |
:param mode: The file mode (read, write). | |
:param encoding: The file encoding. | |
""" | |
if file.endswith('.gz'): | |
return gzip.open(file, mode=mode, encoding=encoding, newline="\n") | |
return open(file, mode=mode, encoding=encoding, newline="\n") | |
def my_log(num: float) -> float: | |
""" | |
Floors the log function | |
:param num: the number | |
:return: log(num) floored to a very low number | |
""" | |
if num == 0.0: | |
return -9999999999 | |
return math.log(num) | |
def sum_of_lists(lists): | |
"""Aggregates list of numeric lists by summing.""" | |
if len(lists) == 1: | |
return lists[0] | |
# Preserve datatype | |
size = len(lists[0]) | |
init_val = type(lists[0][0])(0.0) | |
total = [init_val] * size | |
for ll in lists: | |
for i in range(size): | |
total[i] += ll[i] | |
return total | |
def args_to_dict(args, prefix: str, strip_prefix: bool = False): | |
"""Filters argparse's `Namespace` into dictionary with arguments | |
beginning with the given prefix.""" | |
prefix += '_' | |
d = {} | |
for k, v in args.__dict__.items(): | |
if k.startswith(prefix): | |
k = k.replace(prefix, '') if strip_prefix else k | |
d[k] = v | |
return d | |
def print_test_set(test_set, langpair, requested_fields, origlang=None, subset=None): | |
"""Prints to STDOUT the specified side of the specified test set. | |
:param test_set: the test set to print | |
:param langpair: the language pair | |
:param requested_fields: the fields to print | |
:param origlang: print only sentences with a given original language (2-char ISO639-1 code), "non-" prefix means negation | |
:param subset: print only sentences whose document annotation matches a given regex | |
""" | |
if test_set not in DATASETS: | |
raise Exception(f"No such test set {test_set}") | |
fieldnames = DATASETS[test_set].fieldnames(langpair) | |
all_files = DATASETS[test_set].get_files(langpair) | |
if "all" in requested_fields and len(requested_fields) != 1: | |
sacrelogger.error("Cannot use --echo all with other fields") | |
sys.exit(1) | |
elif "all" in requested_fields: | |
requested_fields = fieldnames | |
# backwards compatibility: allow "ref" even if not present (choose first) | |
if "ref" in requested_fields and "ref" not in fieldnames: | |
replacement_ref = min([f for f in fieldnames if f.startswith("ref")]) | |
requested_fields = [f if f != "ref" else replacement_ref for f in requested_fields] | |
files = [] | |
for field in requested_fields: | |
if field not in fieldnames: | |
sacrelogger.error(f"No such field {field} in test set {test_set} for language pair {langpair}.") | |
sacrelogger.error(f"available fields for {test_set}/{langpair}: {', '.join(fieldnames)}") | |
if "ref" not in fieldnames: | |
subref = min([f for f in fieldnames if f.startswith("ref")]) | |
sacrelogger.error(f"'ref' also allowed for backwards compatibility (will return {subref})") | |
sys.exit(1) | |
index = fieldnames.index(field) | |
files.append(all_files[index]) | |
streams = [smart_open(file) for file in files] | |
streams = filter_subset(streams, test_set, langpair, origlang, subset) | |
for lines in zip(*streams): | |
print('\t'.join(map(lambda x: x.rstrip(), lines))) | |
def get_source_file(test_set: str, langpair: str) -> str: | |
""" | |
Returns the source file for a given testset/langpair. | |
Downloads it first if it is not already local. | |
:param test_set: The test set (e.g., "wmt19") | |
:param langpair: The language pair (e.g., "de-en") | |
:return: the path to the requested source file | |
""" | |
if test_set not in DATASETS: | |
raise Exception(f"No such test set {test_set}") | |
return DATASETS[test_set].get_source_file(langpair) | |
def get_reference_files(test_set: str, langpair: str) -> List[str]: | |
""" | |
Returns a list of one or more reference file paths for the given testset/langpair. | |
Downloads the references first if they are not already local. | |
:param test_set: The test set (e.g., "wmt19") | |
:param langpair: The language pair (e.g., "de-en") | |
:return: a list of one or more reference file paths | |
""" | |
if test_set not in DATASETS: | |
raise Exception(f"No such test set {test_set}") | |
return DATASETS[test_set].get_reference_files(langpair) | |
def get_files(test_set, langpair) -> List[str]: | |
""" | |
Returns the path of the source file and all reference files for | |
the provided test set / language pair. | |
Downloads the references first if they are not already local. | |
:param test_set: The test set (e.g., "wmt19") | |
:param langpair: The language pair (e.g., "de-en") | |
:return: a list of the source file and all reference files | |
""" | |
if test_set not in DATASETS: | |
raise Exception(f"No such test set {test_set}") | |
return DATASETS[test_set].get_files(langpair) | |
def extract_tarball(filepath, destdir): | |
sacrelogger.info(f'Extracting {filepath} to {destdir}') | |
if filepath.endswith('.tar.gz') or filepath.endswith('.tgz'): | |
import tarfile | |
with tarfile.open(filepath) as tar: | |
tar.extractall(path=destdir) | |
elif filepath.endswith('.zip'): | |
import zipfile | |
with zipfile.ZipFile(filepath, 'r') as zipfile: | |
zipfile.extractall(path=destdir) | |
def get_md5sum(dest_path): | |
# Check md5sum | |
md5 = hashlib.md5() | |
with open(dest_path, 'rb') as infile: | |
for line in infile: | |
md5.update(line) | |
return md5.hexdigest() | |
def download_file(source_path, dest_path, extract_to=None, expected_md5=None): | |
"""Downloading utility. | |
Downloads the specified test to the system location specified by the SACREBLEU environment variable. | |
:param source_path: the remote uri to download | |
:param dest_path: where to save the file | |
:param extract_to: for tarballs, where to extract to | |
:param expected_md5: the MD5 sum | |
:return: the set of processed file names | |
""" | |
import urllib.request | |
import ssl | |
outdir = os.path.dirname(dest_path) | |
os.makedirs(outdir, exist_ok=True) | |
# Make sure to open in mode "a" | |
lockfile = f"{dest_path}.lock" | |
with portalocker.Lock(lockfile, timeout=60): | |
if not os.path.exists(dest_path) or os.path.getsize(dest_path) == 0: | |
sacrelogger.info(f"Downloading {source_path} to {dest_path}") | |
try: | |
with urllib.request.urlopen(source_path) as f, open(dest_path, 'wb') as out: | |
out.write(f.read()) | |
except ssl.SSLError: | |
sacrelogger.error('An SSL error was encountered in downloading the files. If you\'re on a Mac, ' | |
'you may need to run the "Install Certificates.command" file located in the ' | |
'"Python 3" folder, often found under /Applications') | |
sys.exit(1) | |
if expected_md5 is not None: | |
cur_md5 = get_md5sum(dest_path) | |
if cur_md5 != expected_md5: | |
sacrelogger.error(f'Fatal: MD5 sum of downloaded file was incorrect (got {cur_md5}, expected {expected_md5}).') | |
sacrelogger.error(f'Please manually delete {dest_path!r} and rerun the command.') | |
sacrelogger.error('If the problem persists, the tarball may have changed, in which case, please contact the SacreBLEU maintainer.') | |
sys.exit(1) | |
# Extract the tarball | |
if extract_to is not None: | |
extract_tarball(dest_path, extract_to) | |
def download_test_set(test_set, langpair=None): | |
"""Downloads the specified test to the system location specified by the SACREBLEU environment variable. | |
:param test_set: the test set to download | |
:param langpair: the language pair (needed for some datasets) | |
:return: the set of processed file names | |
""" | |
if test_set not in DATASETS: | |
raise Exception(f"No such test set {test_set}") | |
dataset = DATASETS[test_set] | |
file_paths = dataset.get_files(langpair) | |
return file_paths | |
def get_langpairs_for_testset(testset: str) -> List[str]: | |
"""Return a list of language pairs for a given test set.""" | |
if testset not in DATASETS: | |
return [] | |
return list(DATASETS[testset].langpairs.keys()) | |
def get_available_testsets() -> List[str]: | |
"""Return a list of available test sets.""" | |
return sorted(DATASETS.keys(), reverse=True) | |
def get_available_testsets_for_langpair(langpair: str) -> List[str]: | |
"""Return a list of available test sets for a given language pair""" | |
parts = langpair.split('-') | |
srclang = parts[0] | |
trglang = parts[1] | |
testsets = [] | |
for dataset in DATASETS.values(): | |
if f'{srclang}-{trglang}' in dataset.langpairs \ | |
or f'{trglang}-{srclang}' in dataset.langpairs: | |
testsets.append(dataset.name) | |
return testsets | |
def get_available_origlangs(test_sets, langpair) -> List[str]: | |
"""Return a list of origlang values in according to the raw SGM files.""" | |
if test_sets is None: | |
return [] | |
origlangs = set() | |
for test_set in test_sets.split(','): | |
dataset = DATASETS[test_set] | |
rawfile = os.path.join(SACREBLEU_DIR, test_set, 'raw', dataset.langpairs[langpair][0]) | |
if rawfile.endswith('.sgm'): | |
with smart_open(rawfile) as fin: | |
for line in fin: | |
if line.startswith('<doc '): | |
doc_origlang = re.sub(r'.* origlang="([^"]+)".*\n', '\\1', line) | |
origlangs.add(doc_origlang) | |
return sorted(list(origlangs)) | |
def filter_subset(systems, test_sets, langpair, origlang, subset=None): | |
"""Filter sentences with a given origlang (or subset) according to the raw SGM files.""" | |
if origlang is None and subset is None: | |
return systems | |
if test_sets is None or langpair is None: | |
raise ValueError('Filtering for --origlang or --subset needs a test (-t) and a language pair (-l).') | |
re_origlang = re.compile(r'.* origlang="([^"]+)".*\n') | |
re_id = re.compile(r'.* docid="([^"]+)".*\n') | |
indices_to_keep = [] | |
for test_set in test_sets.split(','): | |
dataset = DATASETS[test_set] | |
rawfile = os.path.join(SACREBLEU_DIR, test_set, 'raw', dataset.langpairs[langpair][0]) | |
if not rawfile.endswith('.sgm'): | |
raise Exception(f'--origlang and --subset supports only *.sgm files, not {rawfile!r}') | |
if subset is not None: | |
if test_set not in SUBSETS: | |
raise Exception('No subset annotation available for test set ' + test_set) | |
doc_to_tags = SUBSETS[test_set] | |
number_sentences_included = 0 | |
with smart_open(rawfile) as fin: | |
include_doc = False | |
for line in fin: | |
if line.startswith('<doc '): | |
if origlang is None: | |
include_doc = True | |
else: | |
doc_origlang = re_origlang.sub(r'\1', line) | |
if origlang.startswith('non-'): | |
include_doc = doc_origlang != origlang[4:] | |
else: | |
include_doc = doc_origlang == origlang | |
if subset is not None: | |
doc_id = re_id.sub(r'\1', line) | |
if not re.search(subset, doc_to_tags.get(doc_id, '')): | |
include_doc = False | |
if line.startswith('<seg '): | |
indices_to_keep.append(include_doc) | |
number_sentences_included += 1 if include_doc else 0 | |
return [[sentence for sentence, keep in zip(sys, indices_to_keep) if keep] for sys in systems] | |
def print_subset_results(metrics, full_system, full_refs, args): | |
w = args.width | |
origlangs = args.origlang if args.origlang else \ | |
get_available_origlangs(args.test_set, args.langpair) | |
if len(origlangs) == 0: | |
print('No subset information found. Consider using --origlang argument.') | |
return | |
results = defaultdict(list) | |
for origlang in origlangs: | |
subsets = [None] | |
if args.subset is not None: | |
subsets += [args.subset] | |
elif all(t in SUBSETS for t in args.test_set.split(',')): | |
subsets += COUNTRIES + DOMAINS | |
for subset in subsets: | |
system, *refs = filter_subset( | |
[full_system, *full_refs], args.test_set, args.langpair, origlang, subset) | |
if len(system) == 0: | |
continue | |
key = f'origlang={origlang}' | |
if subset in COUNTRIES: | |
key += f' country={subset}' | |
elif subset in DOMAINS: | |
key += f' domain={subset}' | |
for metric in metrics.values(): | |
score = metric.corpus_score(system, refs) | |
results[key].append((len(system), score)) | |
max_left_width = max([len(k) for k in results.keys()]) + 1 | |
max_metric_width = max([len(val[1].name) for val in list(results.values())[0]]) | |
for key, scores in results.items(): | |
key = Color.format(f'{key:<{max_left_width}}', 'yellow') | |
for n_system, score in scores: | |
print(f'{key}: sentences={n_system:<6} {score.name:<{max_metric_width}} = {score.score:.{w}f}') | |
# import at the end to avoid circular import | |
from .dataset import DATASETS, SUBSETS, DOMAINS, COUNTRIES # noqa: E402 | |