id int64 0 190k | prompt stringlengths 21 13.4M | docstring stringlengths 1 12k ⌀ |
|---|---|---|
163,107 | import json
from copy import deepcopy
from matplotlib.pylab import *
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import os
from .utils import generate_perm_inv
from .utils import json_default_type_checker
from sqlova.args import device
def get_cnt_lx_list(cnt_... | null |
163,108 | import json
from copy import deepcopy
from matplotlib.pylab import *
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import os
from .utils import generate_perm_inv
from .utils import json_default_type_checker
from sqlova.args import device
def get_cnt_x_list(engin... | null |
163,109 | import json
from copy import deepcopy
from matplotlib.pylab import *
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import os
from .utils import generate_perm_inv
from .utils import json_default_type_checker
from sqlova.args import device
The provided code snippe... | Get list of mean, std of grad of each parameters Code based on web searched result.. |
163,110 | import json
from copy import deepcopy
from matplotlib.pylab import *
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import os
from .utils import generate_perm_inv
from .utils import json_default_type_checker
from sqlova.args import device
def generate_sql_i(pr_sc... | null |
163,111 | import json
from copy import deepcopy
from matplotlib.pylab import *
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import os
from .utils import generate_perm_inv
from .utils import json_default_type_checker
from sqlova.args import device
def json_default_type_ch... | null |
163,112 | import json
from copy import deepcopy
from matplotlib.pylab import *
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import os
from .utils import generate_perm_inv
from .utils import json_default_type_checker
from sqlova.args import device
def json_default_type_ch... | null |
163,113 | import json
from copy import deepcopy
from matplotlib.pylab import *
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import os
from .utils import generate_perm_inv
from .utils import json_default_type_checker
from sqlova.args import device
The provided code snippe... | Check whether pr_sc, pr_sa are allowed pairs or not. agg_ops = ['', 'MAX', 'MIN', 'COUNT', 'SUM', 'AVG'] |
163,114 | import json
from copy import deepcopy
from matplotlib.pylab import *
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import os
from .utils import generate_perm_inv
from .utils import json_default_type_checker
from sqlova.args import device
def remap_sc_idx(idxs, p... | null |
163,115 | import json
from copy import deepcopy
from matplotlib.pylab import *
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import os
from .utils import generate_perm_inv
from .utils import json_default_type_checker
from sqlova.args import device
def sort_and_generate_pr... | null |
163,116 | import json
from copy import deepcopy
from matplotlib.pylab import *
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import os
from .utils import generate_perm_inv
from .utils import json_default_type_checker
from sqlova.args import device
def generate_sql_q1(sql_i... | null |
163,117 | import json
from copy import deepcopy
from matplotlib.pylab import *
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import os
from .utils import generate_perm_inv
from .utils import json_default_type_checker
from sqlova.args import device
def get_pnt_idx1(col_pool... | sql_vocab = ( 0.. "sql none", "sql max", "sql min", "sql count", "sql sum", "sql average", ..5 6.. "sql select", "sql where", "sql and", .. 8 9.. "sql equal", "sql greater than", "sql less than", .. 11 12.. "sql start", "sql end" .. 13 ) |
163,118 | import json
from copy import deepcopy
from matplotlib.pylab import *
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import os
from .utils import generate_perm_inv
from .utils import json_default_type_checker
from sqlova.args import device
def pred_pnt_idxs(score,... | null |
163,119 | import json
from copy import deepcopy
from matplotlib.pylab import *
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import os
from .utils import generate_perm_inv
from .utils import json_default_type_checker
from sqlova.args import device
def generate_sql_q1_s2s(p... | null |
163,120 | import json
from copy import deepcopy
from matplotlib.pylab import *
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import os
from .utils import generate_perm_inv
from .utils import json_default_type_checker
from sqlova.args import device
def gen_pnt_i_from_pnt(pn... | null |
163,121 | import json
from copy import deepcopy
from matplotlib.pylab import *
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import os
from .utils import generate_perm_inv
from .utils import json_default_type_checker
from sqlova.args import device
def merge_wv_t1_eng(where... | ( "none", "max", "min", "count", "sum", "average", "select", "where", "and", "equal", "greater than", "less than", "start", "end" ), |
163,122 | import json
from copy import deepcopy
from matplotlib.pylab import *
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import os
from .utils import generate_perm_inv
from .utils import json_default_type_checker
from sqlova.args import device
def get_cnt_lx_list_s2s(... | null |
163,123 | import json
from copy import deepcopy
from matplotlib.pylab import *
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import os
from .utils import generate_perm_inv
from .utils import json_default_type_checker
from sqlova.args import device
device = torch.device("c... | As if [ [table-1-col-1-tok1, t1-c1-t2, ...], [t1-c2-t1, t1-c2-t2, ...]. ... [t2-c1-t1, ...,] ] # i_hds = [ [ Batch 1 ] [ Batch 2 ] ] # [Batch 1] = [ (col1_st_idx, col1_ed_idx), (col2_st_idx, col2_ed_idx), ...] # i_hds = [[(11, 14), (15, 19), (20, 21), (22, 24), (25, 27), (28, 29)], # [(16, 19), (20, 24), (25, 26), (27,... |
163,124 | import json
from copy import deepcopy
from matplotlib.pylab import *
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import os
from .utils import generate_perm_inv
from .utils import json_default_type_checker
from sqlova.args import device
def cal_prob_tot(p_select... | :param s_sc: [B, l_h] :param s_sa: [B, l_a] # 16 :param s_wn: [B, 5] :param s_wc: [B, l_h] :param s_wo: [B, 4, l_o] # :param s_wv: [B, 4, 22] :return: |
163,125 | import json
from copy import deepcopy
from matplotlib.pylab import *
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import os
from .utils import generate_perm_inv
from .utils import json_default_type_checker
from sqlova.args import device
The provided code snippe... | Input: list pr_wc = [B, n_conds] g_wc = [B, n_conds] Return: list pr_wc_sorted = [B, n_conds] |
163,126 | class QAInput:
def qg_input_abstrativeqa(cls, context, question,hint, options=None):
question = question
source_text = f'[TASK] [ABSTRACTIVE] [QUESTION] {question}. [CONTEXT] {context} the answer is: {hint}'
return source_text
def qg_input_boolqa(cls, context, question, hint,options=None... | null |
163,127 | class QAInput:
def qg_input_abstrativeqa(cls, context, question,hint, options=None):
question = question
source_text = f'[TASK] [ABSTRACTIVE] [QUESTION] {question}. [CONTEXT] {context} the answer is: {hint}'
return source_text
def qg_input_boolqa(cls, context, question, hint,options=None... | null |
163,128 | class QAInput:
def qg_input_abstrativeqa(cls, context, question,hint, options=None):
def qg_input_boolqa(cls, context, question, hint,options=None):
def qg_input_extractive_qa(cls, context, question, hint,options=None):
def qg_input_multirc(cls, context, question,hint, options=None):
def preprocess... | null |
163,129 | from transformers import Seq2SeqTrainer, is_torch_tpu_available, EvalPrediction
from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Tuple, Union
import nltk
import datasets
import re
import os
import numpy as np
import torch
import random
from pathlib import Path
import time
from transformers.trainer... | null |
163,139 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,140 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,141 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,142 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,143 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,144 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,145 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,146 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,147 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,148 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,149 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,150 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,151 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,152 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,153 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,154 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,155 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,156 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,157 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,158 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,159 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,160 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,161 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,162 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,163 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,164 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,165 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,166 | import collections
import csv
import json
import logging
import pickle
from typing import Dict
import jsonlines
import torch
from omegaconf import DictConfig
from dpr.utils.data_utils import App
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
from dpr.data.biencoder_... | null |
163,167 | import collections
import logging
import string
import unicodedata
from multiprocessing import Pool as ProcessPool
import regex as re
from functools import partial
from typing import Tuple, List, Dict
from dpr.data.retriever_data import TableChunk
from dpr.utils.tokenizers import SimpleTokenizer
logger = logging.getLog... | Evaluates answers presence in the set of documents. This function is supposed to be used with a large collection of documents and results. It internally forks multiple sub-processes for evaluation and then merges results :param all_docs: dictionary of the entire documents database. doc_id -> (doc_text, title) :param an... |
163,168 | import collections
import logging
import string
import unicodedata
from multiprocessing import Pool as ProcessPool
import regex as re
from functools import partial
from typing import Tuple, List, Dict
from dpr.data.retriever_data import TableChunk
from dpr.utils.tokenizers import SimpleTokenizer
def _normalize_answer(s... | null |
163,169 | import collections
import logging
import string
import unicodedata
from multiprocessing import Pool as ProcessPool
import regex as re
from functools import partial
from typing import Tuple, List, Dict
from dpr.data.retriever_data import TableChunk
from dpr.utils.tokenizers import SimpleTokenizer
logger = logging.getLog... | null |
163,170 | import collections
import csv
import glob
import logging
import os
import random
from typing import Dict, List, Tuple
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
import jsonlines
import numpy as np
import torch
from omegaconf import DictConfig
from torch import T... | null |
163,171 | import collections
import csv
import glob
import logging
import os
import random
from typing import Dict, List, Tuple
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
import jsonlines
import numpy as np
import torch
from omegaconf import DictConfig
from torch import T... | null |
163,172 | import collections
import csv
import glob
import logging
import os
import random
from typing import Dict, List, Tuple
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
import jsonlines
import numpy as np
import torch
from omegaconf import DictConfig
from torch import T... | null |
163,173 | import collections
import csv
import glob
import logging
import os
import random
from typing import Dict, List, Tuple
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
import jsonlines
import numpy as np
import torch
from omegaconf import DictConfig
from torch import T... | null |
163,174 | import collections
import csv
import glob
import logging
import os
import random
from typing import Dict, List, Tuple
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
import jsonlines
import numpy as np
import torch
from omegaconf import DictConfig
from torch import T... | null |
163,175 | import collections
import csv
import glob
import logging
import os
import random
from typing import Dict, List, Tuple
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
import jsonlines
import numpy as np
import torch
from omegaconf import DictConfig
from torch import T... | null |
163,176 | import collections
import csv
import glob
import logging
import os
import random
from typing import Dict, List, Tuple
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
import jsonlines
import numpy as np
import torch
from omegaconf import DictConfig
from torch import T... | null |
163,177 | import collections
import csv
import glob
import logging
import os
import random
from typing import Dict, List, Tuple
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
import jsonlines
import numpy as np
import torch
from omegaconf import DictConfig
from torch import T... | null |
163,178 | import collections
import csv
import glob
import logging
import os
import random
from typing import Dict, List, Tuple
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
import jsonlines
import numpy as np
import torch
from omegaconf import DictConfig
from torch import T... | null |
163,179 | import collections
import csv
import glob
import logging
import os
import random
from typing import Dict, List, Tuple
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
import jsonlines
import numpy as np
import torch
from omegaconf import DictConfig
from torch import T... | null |
163,180 | import collections
import csv
import glob
import logging
import os
import random
from typing import Dict, List, Tuple
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
import jsonlines
import numpy as np
import torch
from omegaconf import DictConfig
from torch import T... | null |
163,181 | import collections
import csv
import glob
import logging
import os
import random
from typing import Dict, List, Tuple
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
import jsonlines
import numpy as np
import torch
from omegaconf import DictConfig
from torch import T... | null |
163,182 | import collections
import csv
import glob
import logging
import os
import random
from typing import Dict, List, Tuple
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
import jsonlines
import numpy as np
import torch
from omegaconf import DictConfig
from torch import T... | null |
163,183 | import collections
import csv
import glob
import logging
import os
import random
from typing import Dict, List, Tuple
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
import jsonlines
import numpy as np
import torch
from omegaconf import DictConfig
from torch import T... | null |
163,184 | import collections
import csv
import glob
import logging
import os
import random
from typing import Dict, List, Tuple
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
import jsonlines
import numpy as np
import torch
from omegaconf import DictConfig
from torch import T... | null |
163,185 | import collections
import csv
import glob
import logging
import os
import random
from typing import Dict, List, Tuple
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
import jsonlines
import numpy as np
import torch
from omegaconf import DictConfig
from torch import T... | null |
163,186 | import collections
import csv
import glob
import logging
import os
import random
from typing import Dict, List, Tuple
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
import jsonlines
import numpy as np
import torch
from omegaconf import DictConfig
from torch import T... | null |
163,187 | import collections
import csv
import glob
import logging
import os
import random
from typing import Dict, List, Tuple
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
import jsonlines
import numpy as np
import torch
from omegaconf import DictConfig
from torch import T... | null |
163,188 | import collections
import csv
import glob
import logging
import os
import random
from typing import Dict, List, Tuple
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
import jsonlines
import numpy as np
import torch
from omegaconf import DictConfig
from torch import T... | null |
163,189 | import collections
import csv
import glob
import logging
import os
import random
from typing import Dict, List, Tuple
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
import jsonlines
import numpy as np
import torch
from omegaconf import DictConfig
from torch import T... | null |
163,190 | import collections
import csv
import glob
import logging
import os
import random
from typing import Dict, List, Tuple
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
import jsonlines
import numpy as np
import torch
from omegaconf import DictConfig
from torch import T... | null |
163,191 | import collections
import csv
import glob
import logging
import os
import random
from typing import Dict, List, Tuple
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
import jsonlines
import numpy as np
import torch
from omegaconf import DictConfig
from torch import T... | null |
163,192 | import collections
import csv
import glob
import logging
import os
import random
from typing import Dict, List, Tuple
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
import jsonlines
import numpy as np
import torch
from omegaconf import DictConfig
from torch import T... | null |
163,193 | import collections
import csv
import glob
import logging
import os
import random
from typing import Dict, List, Tuple
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
import jsonlines
import numpy as np
import torch
from omegaconf import DictConfig
from torch import T... | null |
163,194 | import collections
import csv
import glob
import logging
import os
import random
from typing import Dict, List, Tuple
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
import jsonlines
import numpy as np
import torch
from omegaconf import DictConfig
from torch import T... | null |
163,195 | import collections
import csv
import glob
import logging
import os
import random
from typing import Dict, List, Tuple
from datasets import load_dataset,load_from_disk
from dpr.utils.data_utils import load_train_dataset
import jsonlines
import numpy as np
import torch
from omegaconf import DictConfig
from torch import T... | null |
163,201 | import logging
from typing import Tuple
import torch
from torch import Tensor as T
from torch import nn
from transformers.models.bert import BertConfig, BertModel
from transformers.optimization import AdamW
from transformers.models.bert import BertTokenizer
from transformers.models.roberta import RobertaTokenizer
from ... | null |
163,202 | import logging
from typing import Tuple
import torch
from torch import Tensor as T
from torch import nn
from transformers.models.bert import BertConfig, BertModel
from transformers.optimization import AdamW
from transformers.models.bert import BertTokenizer
from transformers.models.roberta import RobertaTokenizer
from ... | null |
163,203 | import logging
from typing import Tuple
import torch
from pytext.models.representations.transformer_sentence_encoder import TransformerSentenceEncoder
from pytext.optimizer.optimizers import AdamW
from torch import Tensor as T
from torch import nn
from .biencoder import BiEncoder
def get_optimizer(model: nn.Module, lea... | null |
163,207 | import collections
import logging
import random
from typing import Tuple, List
import numpy as np
import torch
import torch.nn.functional as F
from torch import Tensor as T
from torch import nn
from dpr.data.biencoder_data import BiEncoderSample
from dpr.utils.data_utils import Tensorizer
from dpr.utils.model_utils imp... | null |
163,208 | import logging
from typing import Tuple
from fairseq.models.roberta.hub_interface import RobertaHubInterface
from fairseq.models.roberta.model import RobertaModel as FaiseqRobertaModel
from fairseq.optim.adam import FairseqAdam
from torch import Tensor as T
from torch import nn
from dpr.models.hf_models import get_robe... | null |
163,211 | import json
import logging
import pickle
import random
import itertools
import math
import torch
from torch import Tensor as T
from typing import List, Iterator, Callable, Tuple
import random
import random
random.seed(33)
def load_train_dataset(dataset,size=None,listify=True):
if size is not None:
p = si... | null |
163,212 | import json
import logging
import pickle
import random
import itertools
import math
import torch
from torch import Tensor as T
from typing import List, Iterator, Callable, Tuple
logger = logging.getLogger()
import random
def read_serialized_data_from_files(paths: List[str]) -> List:
results = []
for i, path in... | null |
163,213 | import json
import logging
import pickle
import random
import itertools
import math
import torch
from torch import Tensor as T
from typing import List, Iterator, Callable, Tuple
logger = logging.getLogger()
import random
def read_data_from_json_files(paths: List[str]) -> List:
results = []
for i, path in enume... | null |
163,214 | import pickle
import torch
import torch.distributed as dist
def get_rank():
return dist.get_rank()
def get_world_size():
return dist.get_world_size()
def all_reduce(tensor, group=None):
if group is None:
group = get_default_group()
return dist.all_reduce(tensor, group=group)
The provided code s... | Gathers arbitrary data from all nodes into a list. Similar to :func:`~torch.distributed.all_gather` but for arbitrary Python data. Note that *data* must be picklable. Args: data (Any): data from the local worker to be gathered on other workers group (optional): group of the collective |
163,217 | import collections
import glob
import logging
import os
from typing import List
import torch
from torch import nn
from torch.optim.lr_scheduler import LambdaLR
from torch.serialization import default_restore_location
def move_to_device(sample, device):
if len(sample) == 0:
return {}
def _move_to_devic... | null |
163,223 | import os
import time
import torch
import copy,random
import sys
import gc
import json
import torch.nn as nn
import numpy as np
import torch.nn.functional as F
from torch.utils.data.distributed import DistributedSampler
from torch.utils.data import DataLoader
from dataclasses import dataclass, field
from typing import ... | null |
163,224 | import os
import time
import torch
import copy,random
import sys
import gc
import json
import torch.nn as nn
import numpy as np
import torch.nn.functional as F
from torch.utils.data.distributed import DistributedSampler
from torch.utils.data import DataLoader
from dataclasses import dataclass, field
from typing import ... | null |
163,225 | import sys
from typing import List, Optional, Tuple
def preprocess_all(
examples,
question_column: str,
answer_column: str,
)-> Tuple[List[str], List[str]]:
questions = examples[question_column]
answers = examples[answer_column]
inputs = questions
targets = answers
return in... | null |
163,226 | import sys
from typing import List, Optional, Tuple
def preprocess_sqaud_batch(
examples,
question_column: str,
context_column: str,
answer_column: str,
) -> Tuple[List[str], List[str]]:
questions = examples[question_column]
contexts = examples[context_column]
answers = exam... | null |
163,227 | import sys
from typing import List, Optional, Tuple
def preprocess_sqaud_abstractive_batch(
examples,
question_column: str,
context_column: str,
answer_column: str,
) -> Tuple[List[str], List[str]]:
questions = examples[question_column]
contexts = examples[context_column]
an... | null |
163,228 | import sys
from typing import List, Optional, Tuple
def preprocess_boolq_batch(
examples,
question_column: str,
context_column: str,
answer_column: str,
) -> Tuple[List[str], List[str]]:
question_column, context_column, answer_column = 'question', 'passage', 'answer'
questions =... | null |
163,229 | import sys
from typing import List, Optional, Tuple
def preprocess_boolq_batch_pretrain(
examples,
question_column: str,
context_column: str,
answer_column: str,
) -> Tuple[List[str], List[str]]:
questions = examples[question_column]
contexts = examples[context_column]
answe... | null |
163,230 | import sys
from typing import List, Optional, Tuple
def preprocess_narrativeqa_batch(
examples,
question_column: str,
context_column: str,
answer_column: str,
) -> Tuple[List[str], List[str]]:
contexts = [exp['summary']['text'] for exp in examples['document']]
questions = [exp['... | null |
163,231 | import sys
from typing import List, Optional, Tuple
def preprocess_narrativeqa_batch_pretrain(
examples,
question_column: str,
context_column: str,
answer_column: str,
) -> Tuple[List[str], List[str]]:
questions = examples[question_column]
contexts = examples[context_column]
... | null |
163,232 | import sys
from typing import List, Optional, Tuple
def preprocess_drop_batch(
examples,
question_column: str,
context_column: str,
answer_column: str,
) -> Tuple[List[str], List[str]]:
contexts = examples['passage']
questions = examples['question']
answers = examples['answe... | null |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.