repo stringlengths 2 99 | file stringlengths 13 225 | code stringlengths 0 18.3M | file_length int64 0 18.3M | avg_line_length float64 0 1.36M | max_line_length int64 0 4.26M | extension_type stringclasses 1
value |
|---|---|---|---|---|---|---|
ngmm_tools | ngmm_tools-master/Analyses/Code_Verification/preprocessing/CreateMergedCatalogNGAWest3CA.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Jun 29 13:58:20 2021
@author: glavrent
"""
# %% Required Packages
# ======================================
#load libraries
import os
import sys
import pathlib
import glob
import re #regular expression package
import warnings
#arithmetic librar... | 15,940 | 42.673973 | 165 | py |
ngmm_tools | ngmm_tools-master/Analyses/Code_Verification/preprocessing/CreateCatalogNewEvents2021Lite.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Jun 27 16:12:57 2021
@author: glavrent
"""
# Required Packages
# ======================================
#load libraries
import os
import sys
import pathlib
import glob
import re #regular expression package
#arithmetic libraries
import numpy as... | 12,697 | 41.610738 | 162 | py |
ngmm_tools | ngmm_tools-master/Examples/example1/regression_inla_postprocessing.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Mar 27 12:20:36 2022
@author: glavrent
"""
# Working directory and Packages
# ---------------------------
#load packages
import sys
import pathlib
import glob
import re #regular expression package
import pickle
from joblib import cpu_count
#a... | 3,583 | 27 | 130 | py |
ngmm_tools | ngmm_tools-master/Examples/example1/create_examp_data.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sat Mar 26 16:01:54 2022
@author: glavrent
"""
# Working directory and Packages
# ---------------------------
#load packages
import os
import sys
import pathlib
import numpy as np
import pandas as pd
from scipy import sparse
from scipy import linalg as scip... | 5,227 | 27.259459 | 120 | py |
ngmm_tools | ngmm_tools-master/Examples/example1/regression_stan.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Mar 27 12:20:36 2022
@author: glavrent
"""
# Working directory and Packages
# ---------------------------
#load packages
import os
import sys
import pathlib
import glob
import re #regular expression package
import pickle
from joblib import cp... | 9,279 | 31.561404 | 130 | py |
ngmm_tools | ngmm_tools-master/Examples/example2/comparison_posterior.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Aug 17 07:00:55 2022
@author: glavrent
"""
# Load Packages
# ---------------------------
#arithmetic libraries
import numpy as np
from scipy import stats
#statistics libraries
import pandas as pd
#plottign libraries
import matplotlib as mpl
from matplo... | 5,270 | 33.907285 | 111 | py |
ngmm_tools | ngmm_tools-master/Examples/example2/create_reg_dataset.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sat Mar 26 16:01:54 2022
@author: glavrent
"""
# Working directory and Packages
# ---------------------------
import os
import sys
import pathlib
#load packages
import numpy as np
import pandas as pd
#plottign libraries
import matplotlib as mpl
from matplot... | 1,674 | 19.180723 | 65 | py |
ngmm_tools | ngmm_tools-master/Examples/example2/regression_stan.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Mar 27 12:20:36 2022
@author: glavrent
"""
# Working directory and Packages
# ---------------------------
#load packages
import os
import sys
import pathlib
import glob
import re #regular expression package
import pickle
from joblib import cp... | 6,923 | 27.85 | 118 | py |
PT-M2 | PT-M2-main/errant_score.py | from copy import deepcopy
import math
from tqdm import tqdm
def get_ref(edits, src):
cnt = 0
src = src.split()
e_s = src
for edit in edits:
s_idx, e_idx, rep_tok = edit
s_idx = cnt + s_idx
e_idx = cnt + e_idx
e_s = e_s[:s_idx] + rep_tok.split() + e_s[e_idx:] if rep_tok e... | 22,995 | 39.062718 | 187 | py |
PT-M2 | PT-M2-main/evaluate.py | import argparse
import torch
import os
from utils import load_file, load_dir, write_to_csv
from metrics import PTM2
def main():
parser = argparse.ArgumentParser("PT-M2")
parser.add_argument("--source", type=str, default="source file path")
parser.add_argument("--reference", type=str, default="reference f... | 2,143 | 43.666667 | 124 | py |
PT-M2 | PT-M2-main/utils.py | import os
import sys
import csv
import random
import numpy as np
import torch
sys.path.append("m2scorer")
def load_file(src_file):
sources = []
with open(src_file, "r", encoding="utf8") as fr:
for line in fr:
sources.append(line.strip("\n"))
return sources
def load_dir(ref_dir):
... | 945 | 23.25641 | 59 | py |
PT-M2 | PT-M2-main/bart_score.py | # %%
import torch
import torch.nn as nn
import traceback
from transformers import BartTokenizer, BartForConditionalGeneration
from typing import List
import numpy as np
class BARTScorer:
def __init__(self, device='cuda:0', max_length=1024, checkpoint='facebook/bart-large-cnn'):
# Set up model
self... | 4,219 | 36.678571 | 97 | py |
PT-M2 | PT-M2-main/metrics.py | from tqdm import tqdm
import numpy as np
import sys
sys.path.append("m2score")
from m2score.m2scorer import load_annotation
from m2score.util import smart_open
from m2score.levenshtein import batch_multi_pre_rec_f1, batch_multi_pre_rec_f1_sent
from errant_score import batch_multi_pre_rec_f1_errant, batch_multi_pre_rec... | 4,065 | 44.177778 | 140 | py |
PT-M2 | PT-M2-main/bert_score/score.py | import os
import sys
import time
import pathlib
import torch
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable
import numpy as np
import pandas as pd
from collections import defaultdict
from transformers import AutoTokenizer
from .utils import (
get_model,
get_tokenizer,
... | 11,254 | 35.781046 | 112 | py |
PT-M2 | PT-M2-main/bert_score/scorer.py | import os
import sys
import time
import pathlib
import torch
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable
import numpy as np
import pandas as pd
import warnings
from collections import defaultdict
from transformers import AutoTokenizer
from .utils import (
get_model,
... | 11,730 | 35.095385 | 133 | py |
PT-M2 | PT-M2-main/bert_score/utils.py | import sys
import os
import torch
from math import log
from itertools import chain
from collections import defaultdict, Counter
from multiprocessing import Pool
from functools import partial
from tqdm.auto import tqdm
from torch.nn.utils.rnn import pad_sequence
from distutils.version import LooseVersion
from transform... | 28,789 | 44.553797 | 173 | py |
PT-M2 | PT-M2-main/bert_score/__init__.py | __version__ = "0.3.11"
from .score import *
from .scorer import *
| 66 | 15.75 | 22 | py |
PT-M2 | PT-M2-main/m2score/token_offsets.py |
import sys
import re
import os
from util import *
from Tokenizer import PTBTokenizer
assert len(sys.argv) == 1
# main
# loop over sentences cum annotation
tokenizer = PTBTokenizer()
sentence = ''
for line in sys.stdin:
line = line.decode("utf8").strip()
if line.startswith("S "):
sentence = line[2:... | 1,233 | 28.380952 | 96 | py |
PT-M2 | PT-M2-main/m2score/levenshtein.py | from optparse import OptionParser
from util import uniq
import re
import sys
import math
from copy import deepcopy
from tqdm import tqdm
from util import compute_weight_edits
# batch evaluation of a list of sentences
def batch_precision(candidates, sources, gold_edits, max_unchanged_words=2, beta=0.5, ignore_whites... | 38,568 | 38.761856 | 187 | py |
PT-M2 | PT-M2-main/m2score/combiner.py |
import sys
import levenshtein
from getopt import getopt
from util import paragraphs
from util import smart_open
def load_annotation(gold_file):
source_sentences = []
gold_edits = []
fgold = smart_open(gold_file, 'r')
puffer = fgold.read()
fgold.close()
puffer = puffer.decode('utf8')
for ... | 3,436 | 38.505747 | 154 | py |
PT-M2 | PT-M2-main/m2score/m2scorer.py |
import sys
import levenshtein
from getopt import getopt
from util import paragraphs
from util import smart_open
def load_annotation(gold_file):
source_sentences = []
gold_edits = []
fgold = smart_open(gold_file, 'r')
puffer = fgold.read()
fgold.close()
# puffer = puffer.decode('utf8')
f... | 4,440 | 37.95614 | 171 | py |
PT-M2 | PT-M2-main/m2score/util.py |
import operator
import random
import math
import re
def smart_open(fname, mode = 'r'):
if fname.endswith('.gz'):
import gzip
# Using max compression (9) by default seems to be slow.
# Let's try using the fastest. ... | 7,012 | 30.308036 | 127 | py |
PT-M2 | PT-M2-main/m2score/__init__.py | 0 | 0 | 0 | py | |
PT-M2 | PT-M2-main/m2score/Tokenizer.py |
import re
import sys
class DummyTokenizer(object):
def tokenize(self, text):
return text.split()
class PTBTokenizer(object):
def __init__(self, language="en"):
self.language = language
self.nonbreaking_prefixes = {}
self.nonbreaking_prefixes_numeric = {}
self.non... | 6,383 | 39.923077 | 98 | py |
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