code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class UpperCAmelCase_ ( unittest.TestCase ):
"""simple docstring"""
def lowerCamelCase ( self ... | 35 |
"""simple docstring"""
from math import sqrt
def _UpperCAmelCase ( __lowerCamelCase : int = 1_00_00_00 ) -> int:
_snake_case = 0
_snake_case = 0
_snake_case = 42
while num_cuboids <= limit:
max_cuboid_size += 1
for... | 288 | 0 |
from math import loga
def __UpperCamelCase ( _A ):
if a < 0:
raise ValueError('''Input value must be a positive integer''' )
elif isinstance(_snake_case , _snake_case ):
raise TypeError('''Input value must be a \'int\' type''' )
return 0 if (a == 0) e... | 352 |
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class A ( unittest.TestCase ):
@property
def S... | 167 | 0 |
import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format='''%(message)s''')
def lowerCamelCase_ ( _a ):
"""simple docstring"""
return input_array.reshape((input_array.size, 1) ... | 131 |
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import Callable, Dict, List, Tuple
import timm
import torch
import torch.nn as nn
from classy_vision.models.regnet import RegNet, RegNetParams, RegNetYaagf, RegNetYaag... | 131 | 1 |
'''simple docstring'''
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import C... | 368 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
_a : Union[str, Any] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailabl... | 46 | 0 |
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DPMSolverMultistepScheduler,
TextToVideoSDPipeline,
UNetaDConditionModel,
)
from diffusers.utils import is_xforme... | 180 | import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE = {
'BridgeTower/bridgetower-base': 'https://huggingface.co/BridgeTowe... | 180 | 1 |
from ...configuration_utils import PretrainedConfig
_snake_case : int = {
"google/tapas-base-finetuned-sqa": (
"https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json"
),
"google/tapas-base-finetuned-wtq": (
"https://huggingface.co/google/tapas-base... | 134 |
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transformers.utils import logging... | 134 | 1 |
'''simple docstring'''
from __future__ import annotations
def UpperCAmelCase_ ( __lowerCamelCase : list[float] ,__lowerCamelCase : Optional[int] ):
print(F'Vertex\tShortest Distance from vertex {src}' )
for i, d in enumerate(__lowerCamelCase ):
print(F'{i}\t... | 223 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .toke... | 223 | 1 |
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_tokeniz... | 369 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase_ : Optional[int] = logging.get_logger(__name__)
lowerCamelCase_ : Optional[int] = {"""ctrl""": """https://huggingface.co/ctrl/resolve/main/config.json"""}
class _UpperCamelCase ( _A ):
... | 223 | 0 |
"""simple docstring"""
from __future__ import annotations
import time
import numpy as np
lowerCamelCase__ = [8, 5, 9, 7]
lowerCamelCase__ = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
lowerCamelCase__ = [
[3, 2, 1, 4],
[0, 2, 5... | 86 |
"""simple docstring"""
def lowerCamelCase__ ( __snake_case = 10_00 ) -> int:
"""simple docstring"""
_UpperCamelCase = 2**power
_UpperCamelCase = str(__snake_case )
_UpperCamelCase = list(__snake_case )
_UpperCamelCase ... | 194 | 0 |
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class _UpperCAmelCase :
_lowerCAmelCase : int = 4_2
_lowerCAmelCase : Dict... | 351 |
"""simple docstring"""
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 155 | 0 |
'''simple docstring'''
_SCREAMING_SNAKE_CASE = {
"A": ".-", "B": "-...", "C": "-.-.", "D": "-..", "E": ".", "F": "..-.", "G": "--.",
"H": "....", "I": "..", "J": ".---", "K": "-.-", "L": ".-..", "M": "--", "N": "-.",
"O": "---", "P": ".--.", "Q": "--.-", "R": ".-.", "S": "...", "T": "-... | 158 |
'''simple docstring'''
from collections.abc import Sequence
def __a(SCREAMING_SNAKE_CASE_ : Sequence[float] , SCREAMING_SNAKE_CASE_ : bool = False ):
'''simple docstring'''
if not arr:
return 0
_lowerCAmelCase = 0 if allow_empty_subarrays else float... | 158 | 1 |
import argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import logging as transformers_logging
sys.path.append(os.p... | 369 |
'''simple docstring'''
from __future__ import annotations
def A__ ( UpperCAmelCase_ ):
if not nums:
return 0
_UpperCamelCase : Any = nums[0]
_UpperCamelCase : Optional[int] = 0
for num in nums[1:]:
_UpperCamelCase , ... | 236 | 0 |
"""simple docstring"""
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class lowerCAmelCase__ :
'''simple docstring'''
de... | 91 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase_ = {"configuration_unispeech": ["UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MA... | 45 | 0 |
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
a__ : Any = datasets.uti... | 366 |
'''simple docstring'''
import csv
import tweepy
# Twitter API credentials
a__ : Dict = ''
a__ : List[str] = ''
a__ : Optional[Any] = ''
a__ : Any = ''
def _lowercase ( __A ):
'''simp... | 243 | 0 |
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
lowercase : List[str] = logging.get_logger(__name__)
class lowerCamelCase__ ( __lowercase):
'''simple docstring'''
def __init__( self :Dict... | 232 |
from __future__ import annotations
import sys
from collections import deque
from typing import Generic, TypeVar
lowercase : Optional[Any] = TypeVar('T')
class lowerCamelCase__ ( Generic[T]):
'''simple docstring'''
_A = 42 # Cache store ... | 232 | 1 |
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
__SCREAMING_SNAKE_... | 256 |
from queue import Queue
from typing import TYPE_CHECKING, Optional
if TYPE_CHECKING:
from ..models.auto import AutoTokenizer
class lowerCamelCase_ :
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( self : Any , __lowerCamelCase ... | 256 | 1 |
import os
import re
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
a__ = logging.get_logger(__name__)
a__ = {'''vocab_file''': '''spie... | 235 |
"""simple docstring"""
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {
"huggingface/informer-tourism-monthly": (
"https://huggingface.co/huggin... | 100 | 0 |
'''simple docstring'''
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
__lowerCAmelCase = '\\n@misc{wu2016googles,\n title={Google\'s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},\n ... | 270 |
'''simple docstring'''
from math import sqrt
def __SCREAMING_SNAKE_CASE ( _SCREAMING_SNAKE_CASE ):
_snake_case = 0
for i in range(1 , int(sqrt(_SCREAMING_SNAKE_CASE ) + 1 ) ):
if n % i == 0 and i != sqrt(_SCREAMING_SNAKE_CASE ):
to... | 270 | 1 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : str ) -> List[str]:
"""simple docstring"""
lowerCAmelCase_ : List[Any] = [False] * len(lowerCAmelCase__ )
lowerCAmelCase_ : str = [-1] * len(lowerCAmelCase... | 224 |
"""simple docstring"""
def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : int , SCREAMING_SNAKE_CASE : int ):
'''simple docstring'''
while b:
lowerCAmelCase , lowerCAmelCase = b, a % b
return a
def UpperCAmel... | 46 | 0 |
"""simple docstring"""
import string
from math import logaa
def __SCREAMING_SNAKE_CASE ( A_ , A_ ):
lowerCAmelCase__ : int = document.translate(
str.maketrans('''''' , '''''' , string.punctuation ) ).replace('''\n''' , '''''' )
lowerCAme... | 361 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from transformers import ViTConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_t... | 74 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
Upper... | 141 |
'''simple docstring'''
import datasets
UpperCAmelCase = '''\
@InProceedings{conneau2018xnli,
author = "Conneau, Alexis
and Rinott, Ruty
and Lample, Guillaume
and Williams, Adina
and Bowman, Samuel R.
and Schwenk, Holge... | 141 | 1 |
'''simple docstring'''
import random
def __UpperCamelCase ( _UpperCAmelCase, _UpperCAmelCase, _UpperCAmelCase ):
__UpperCAmelCase : Any = a[left_index]
__UpperCAmelCase : Optional[Any] = left_index + 1
for j in range(left_index + 1, _UpperCAmelCase ... | 37 |
'''simple docstring'''
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import Toke... | 37 | 1 |
'''simple docstring'''
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config i... | 85 |
'''simple docstring'''
from __future__ import annotations
import requests
def UpperCamelCase_( snake_case : str ):
'''simple docstring'''
snake_case_ = f'https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty'
return requests.get(s... | 85 | 1 |
import os
from pathlib import Path
def _a ( UpperCAmelCase , UpperCAmelCase , UpperCAmelCase ) -> List[Any]:
"""simple docstring"""
lowerCamelCase__ : Optional[Any] = {
'''en''': '''Machine learning is great, isn\'t it?''',
'''ru'... | 359 |
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def _a ( *UpperCAmelCase , UpperCAmelCase = None , UpperCAmelCase=True , UpperCAmelCase=2 ) -> str:
"""simple docstring"""
from .. import __version__
... | 265 | 0 |
import functools
def __a ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> int:
'''simple docstring'''
# Validation
if not isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) or not all(isinstance(SCREAMING_SNAKE_CASE , SCREA... | 333 |
def __a ( ) -> list[list[int]]:
'''simple docstring'''
return [list(range(1_0_0_0 - i , -1_0_0_0 - i , -1 ) ) for i in range(1_0_0_0 )]
A_ : Union[str, Any] = generate_large_matrix()
A_ : Union[str, Any] = (
[[4,... | 333 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowerCAmelCase = logging.get_logger(__name__)
class A ( A_ , A_ ):
UpperCamelCase_ : List... | 304 |
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
lowerCAmelCase = (3, 9, -1_1, 0, 7, 5, 1, -1)
lowerCAmelCase = (4, 6, 2, 0, 8, 1_0, 3, -2)
@dataclass
class A :
UpperCamelCase_ : int
UpperCamelCase_ ... | 304 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_A = {'''configuration_swin''': ['''SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''SwinConfig''', '''SwinOnnxConfig''']}
try:
if not is_torch_available():
r... | 278 |
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
lowercase = logging.getLogger(__name__)
@dataclass
class UpperCamelCase_ ( snake_case_ ):
'''simple docstr... | 178 | 0 |
'''simple docstring'''
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import BaseOutput, is_torch_available, is_transformers_available
@dataclass
class _lowerCamelCase ( lowercas... | 357 |
'''simple docstring'''
def lowerCamelCase ( lowerCAmelCase : str , lowerCAmelCase : Any , lowerCAmelCase : Any=False ):
"""simple docstring"""
if isinstance(lowerCAmelCase , lowerCAmelCase ) and isinstance(lowerCAmelCase , lowerCAmelCase ):
__magic_name__ : ... | 275 | 0 |
'''simple docstring'''
import argparse
import csv
import logging
import os
import random
import numpy as np
import torch
from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
from tqdm import tqdm, trange
from transformers import (
CONFIG_NAME,
WEIGHTS_NAME,
AdamW... | 166 |
'''simple docstring'''
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"""google/umt5-small""": """https://huggi... | 166 | 1 |
"""simple docstring"""
lowerCamelCase_ = tuple[float, float, float]
lowerCamelCase_ = tuple[float, float, float]
def __lowerCamelCase ( a_ : Pointad , a_ : Pointad ) -> Vectorad:
__SCREAMING_SNAKE_CASE :int = end_poin... | 239 |
"""simple docstring"""
import math
import unittest
def __lowerCamelCase ( a_ : int ) -> bool:
assert isinstance(a_ , a_ ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
... | 239 | 1 |
from math import sqrt
def __magic_name__ ( A : int ):
'''simple docstring'''
a = 0
for i in range(1, int(sqrt(A ) + 1 ) ):
if n % i == 0 and i != sqrt(A ):
total += i + n // i
elif i == sqrt(A ):
total += i
return total - n
... | 107 | '''simple docstring'''
import re
from filelock import FileLock
try:
import nltk
_A : int = True
except (ImportError, ModuleNotFoundError):
_A : Optional[Any] = False
if NLTK_AVAILABLE:
with FileLock('''.lock''') as lock:
nltk.download('''punkt''', quie... | 229 | 0 |
"""simple docstring"""
import os
def UpperCAmelCase ( a_ = "input.txt" ):
'''simple docstring'''
with open(os.path.join(os.path.dirname(a_ ), a_ ) ) as input_file:
lowerCamelCase : Optional[Any] = [
[int(a_ ) for element in lin... | 205 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _lowercase ( __UpperCAmelCase ):
lowercase_ = ['image_processor', 'tokenizer']
lowercase_ = 'ChineseCLIPImageProcessor'
lo... | 205 | 1 |
import hashlib
import unittest
from typing import Dict
import numpy as np
from transformers import (
MODEL_FOR_MASK_GENERATION_MAPPING,
TF_MODEL_FOR_MASK_GENERATION_MAPPING,
is_vision_available,
pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from transformers.testing_utils... | 52 |
import json
import os
import unittest
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class __magic_name__ ( __lowerCAmelCase , unittest.TestCase):
A: ... | 146 | 0 |
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transforme... | 366 |
_SCREAMING_SNAKE_CASE = {
"""Pillow""": """Pillow""",
"""accelerate""": """accelerate>=0.11.0""",
"""compel""": """compel==0.1.8""",
"""black""": """black~=23.1""",
"""datasets""": """datasets""",
"""filelock""": """filelock""",
"""flax""": """flax>=0.4.1""",
"... | 88 | 0 |
from __future__ import annotations
import math
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int ) -> int:
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negat... | 68 |
"""simple docstring"""
# Lint as: python3
import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union
_lowercase = re.compile(r'''^(?P<major>\d+)''' r'''\.(?P<minor>\d+)''' r'''\.(?P<patch>\d+)$''')
@total_ordering
@datac... | 74 | 0 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowerCAmelCase : str = logging.get_logger(__name__)
lowerCAmelCase : int = {
'ut/deta': 'https://huggingface.co/ut/deta/resolve/m... | 370 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('>=', '4.25.0')):
raise O... | 251 | 0 |
'''simple docstring'''
import functools
def _SCREAMING_SNAKE_CASE ( UpperCamelCase , UpperCamelCase ):
"""simple docstring"""
if not isinstance(UpperCamelCase , UpperCamelCase ) or not all(isinstance(UpperCamelCase , UpperCamelCase ) for day in days ... | 37 |
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( UpperCamelCase = "The quick brown fox jumps over the lazy dog" , ):
"""simple docstring"""
lowerCAmelCase__ : str = set()
# Replace all the whitespace in our sentence
lowerCAmelCase__ : Tuple ... | 37 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
snake_case__ = argparse.ArgumentParser(
description=(
'''Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Transfer Learned'''
... | 370 |
"""simple docstring"""
import argparse
import json
import os
import torch
from torch import nn
from transformers import NllbMoeConfig, NllbMoeModel
from transformers.modeling_utils import dtype_byte_size
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
def _snake_case ( _snake_case ... | 314 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase__ = {
'configuration_electra': ['ELECTRA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Electr... | 11 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_a = logging.get_logger(__name__)
_a = {
"camembert-base": "https://huggingface.co/camembert-base/resolve/mai... | 209 | 0 |
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
__A = logging.get_logger(__name__)
class _SCREAMING_SNAKE_CASE ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__(self : Tuple , *UpperCAmelCase_ :... | 273 |
from __future__ import annotations
from typing import Any
class _SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__(self : Tuple , UpperCAmelCase_ : int , UpperCAmelCase_ : int , UpperCAmelCase_ : float = 0) ->None:
'''simple docstr... | 273 | 1 |
'''simple docstring'''
def __UpperCAmelCase ( A : list[int] , A : int ) -> bool:
UpperCAmelCase_ : Optional[int] = len(A )
UpperCAmelCase_ : Tuple = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr value, a sum ... | 304 |
'''simple docstring'''
from __future__ import annotations
def __UpperCAmelCase ( A : list , A : int , A : int , A : int ) -> list:
UpperCAmelCase_ : Any = []
UpperCAmelCase_ , UpperCAmelCase_ : Tuple = input_list[low:mid... | 304 | 1 |
'''simple docstring'''
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def _lowerCAmelCase ( _UpperCamelCase : Optional[Any] , _UpperCamelCase : List[str]=None ) -> int:
"""... | 355 |
'''simple docstring'''
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
lowerCamelCase : List[str] = {"UserAgent": UserAgent().random}
def _lowerCAmelCase ( _UpperCamelCase : str ) -> dict:
... | 114 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__a :str = {
'configuration_chinese_clip': [
'CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
'ChineseCLIPConfig',
'ChineseC... | 312 | """simple docstring"""
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import Padd... | 150 | 0 |
def __SCREAMING_SNAKE_CASE ( lowerCAmelCase: int , lowerCAmelCase: int ) -> bool:
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 189 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import (
BitConfig,
ViTHybridC... | 189 | 1 |
"""simple docstring"""
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
SCREAMING_SNAKE_CASE_ : Dict = '\\n@inproceedings{popovic-2015-chrf,\n title = "chr{F}: character n-gram {F}-score for automatic {MT} evaluation",\n author =... | 335 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses... | 335 | 1 |
"""simple docstring"""
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig... | 291 |
"""simple docstring"""
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_availab... | 291 | 1 |
'''simple docstring'''
def UpperCamelCase__ ( lowerCAmelCase ):
"""simple docstring"""
_lowerCAmelCase = len(lowerCAmelCase )
for i in range(length - 1 ):
_lowerCAmelCase = i
for k in rang... | 70 |
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import datasets
import datasets.config
from .utils import require_beam
class __a ( datasets.BeamBasedBuilder ):
def __lowercase ... | 189 | 0 |
"""simple docstring"""
def lowerCamelCase__ ( __snake_case = 2_00_00_00 ) -> int:
"""simple docstring"""
_UpperCamelCase = [0 for i in range(n + 1 )]
_UpperCamelCase = 1
_UpperCamelCase = 1
for i in range(2... | 100 |
"""simple docstring"""
import copy
from collections import OrderedDict
from typing import Dict, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_a ... | 100 | 1 |
from .imports import is_rich_available
if is_rich_available():
from rich.traceback import install
install(show_locals=False)
else:
raise ModuleNotFoundError('''To use the rich extension, install rich with `pip install rich`''')
| 157 | def _UpperCamelCase ( snake_case__ ) -> int:
__UpperCAmelCase : Union[str, Any] = abs(snake_case__ )
__UpperCAmelCase : Dict = 0
while n > 0:
res += n % 10
n //= 10
return res
def _UpperCamelCas... | 157 | 1 |
from io import BytesIO
from typing import List, Union
import requests
from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_decord_available():
import numpy as np
from decord import Vide... | 266 |
import argparse
import json
import os
import torch
from torch import nn
from transformers import NllbMoeConfig, NllbMoeModel
from transformers.modeling_utils import dtype_byte_size
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
def lowerCAmelCase_ ( _lowercase : ... | 266 | 1 |
"""simple docstring"""
# Function to print upper half of diamond (pyramid)
def _snake_case ( snake_case__ : Dict ):
for i in range(0 , snake_case__ ):
for _ in range(0 , n - i - 1 ): # printing spaces
print(' ' , end='' )
for _ in range(0 , i + 1 ): # pr... | 74 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {"openai-gpt": "https://huggingface.co/openai-gpt/resolve/main/config.json"}
class _... | 251 | 0 |
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import Confi... | 367 |
def __lowerCAmelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE )-> list[int]:
"""simple docstring"""
snake_case_ = int(SCREAMING_SNAKE_CASE )
# Initialize Result
snake_case_ = []
# Traverse through all denomination
for denomination in reversed(SCREAMING_SNAKE_C... | 267 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import BitConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import Backbo... | 229 | '''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A : int = logging.get_logger(__name__)
_A : Any = {'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''}
class _lowercase ... | 229 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
__UpperCamelCase : List[str] = logging.get_logger(__name__)
... | 258 | import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : str = logging.get_logger(__name__)
__UpperCamelCase : Dict = {
'facebook/encodec_24khz': 'https://huggingfac... | 258 | 1 |
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_pro... | 12 |
"""simple docstring"""
import argparse
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM
from transformers.utils import logging
logging.set_verbosity_info()
_lowercase = logging.get_logger(__name_... | 74 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase_ : int = {
'''configuration_cpmant''': ['''CPMANT_PRETRAI... | 356 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
... | 170 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
lowerCAmelCase_ = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
low... | 308 |
import warnings
from contextlib import contextmanager
from ....processing_utils import ProcessorMixin
class a ( lowercase__ ):
"""simple docstring"""
a : List[str] = 'MCTCTFeatureExtractor'
a : str = 'AutoTokenizer'
def __init... | 114 | 0 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, TensorType
UpperCamelCase = ... | 333 | import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=__A )
class snake_case_ ( __A ):
# `task` is not a ClassVar since we want it to be part of the `asdict` output f... | 333 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_UpperCAmelCase : Tuple = {
"configuration_mask2former": [
"MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"Mask2FormerConfig",
],
}
try:
if n... | 236 |
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate_available,
is_accel... | 236 | 1 |
"""simple docstring"""
import os
from collections.abc import Iterator
def UpperCAmelCase_ ( a_ = "." ):
'''simple docstring'''
for dir_path, dir_names, filenames in os.walk(a_ ):
lowerCamelCase : Any = [d for d in dir_names if d != 'scripts' and d[0] not ... | 354 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A = logging.get_logger(__name__)
_A = {
'asapp/sew-d-tiny-100k': 'https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/config.json',
# ... | 205 | 0 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_tor... | 122 |
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxMode... | 122 | 1 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unles... | 358 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
import numpy as np
# Parrameters
__UpperCamelCase : Union[str, Any] = (720, 1_280) # Height, Width
__UpperCamelCase : Any = (0.4, 0.6) # if height or width lower than this scale, drop it.
__Upp... | 347 | 0 |
"""simple docstring"""
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
from transformers import ... | 100 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.... | 100 | 1 |
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import DEFAULTS, task_specific_par... | 159 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
_lowerCamelCase : List[str] = logging.get_logger(__name__)
class __snake_case (_a ):
def __init__( self : Optional[Any] , *_UpperCAmelCase : str , **_UpperCAmelCase... | 159 | 1 |
from __future__ import annotations
import collections
import pprint
from pathlib import Path
def __lowerCamelCase ( UpperCamelCase__ ):
'''simple docstring'''
return "".join(sorted(UpperCamelCase__ ) )
def __lowerCamelCase ( UpperCamelCase__ ):
... | 285 |
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class lowercase ( lowercase_ , unittest.TestCase ):
__SCRE... | 285 | 1 |
'''simple docstring'''
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
a__ : Optional[Any] = logging.getLogger(__name__)
class UpperCAmelCase__ ... | 243 |
'''simple docstring'''
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
... | 243 | 1 |
import numpy as np
class _SCREAMING_SNAKE_CASE :
def __init__( self : int ):
UpperCamelCase :int = (0, 0)
UpperCamelCase :List[str] = None
UpperCamelCase :Union[str, Any] = 0
UpperCamelCase :Optional[Any] = 0
UpperCamelCase ... | 38 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
a_ = {
'configuration_convnext': ['CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MA... | 249 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( __A ) -> int:
if a < 0:
raise ValueError('Input value must be a positive integer' )
elif isinstance(__A , __A ):
raise TypeError('Input value must be a \'int\' type' )
return bin(__A ).count('1' )
if _... | 160 |
'''simple docstring'''
import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, L... | 160 | 1 |
"""simple docstring"""
import warnings
from typing import List
from unittest.mock import Mock
import torch
from torch.utils.data import DataLoader, IterableDataset, TensorDataset
from accelerate.accelerator import Accelerator
from accelerate.utils.dataclasses import DistributedType
class lower... | 91 |
"""simple docstring"""
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def a__ ( __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_... | 217 | 0 |
"""simple docstring"""
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/license... | 53 |
"""simple docstring"""
import unittest
from transformers import DonutProcessor
_UpperCamelCase: Any = 'naver-clova-ix/donut-base'
class a__ ( unittest.TestCase ):
def lowercase ( self : Optional[Any] ) -> Tuple:
... | 53 | 1 |
'''simple docstring'''
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def UpperCamelCase ( _lowerCamelCase : str , _lowerCamelCase : str , **_lowerCamelCase : Optional[Any] ):
A__ = AutoConfig... | 237 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
_lowercase : int ={}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
... | 170 | 0 |
'''simple docstring'''
UpperCAmelCase = {
'Pillow': 'Pillow',
'accelerate': 'accelerate>=0.11.0',
'compel': 'compel==0.1.8',
'black': 'black~=23.1',
'datasets': 'datasets',
'filelock': 'filelock',
'flax': 'flax>=0.4.1',
'hf-doc-builder': 'hf-doc-builder>=0.3.0'... | 187 |
'''simple docstring'''
import pytest
import datasets
# Import fixture modules as plugins
UpperCAmelCase = ['tests.fixtures.files', 'tests.fixtures.hub', 'tests.fixtures.fsspec']
def _snake_case ( _SCREAMING_SNAKE_CASE : str , _SCREAMING_SNAKE_CASE : i... | 187 | 1 |
'''simple docstring'''
from sklearn.metrics import matthews_corrcoef
import datasets
__lowercase = '''
Compute the Matthews correlation coefficient (MCC)
The Matthews correlation coefficient is used in machine learning as a
measure of the quality of binary and multiclass classifications. It takes
into... | 272 | '''simple docstring'''
from math import sqrt
def snake_case__ ( _A: int = 1000000 ) -> int:
'''simple docstring'''
lowerCAmelCase = 0
lowerCAmelCase = 0
lowerCAmelCase = 42
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides ... | 272 | 1 |
'''simple docstring'''
def UpperCAmelCase_ (__a : float , __a : int ):
"""simple docstring"""
if digit_amount > 0:
return round(number - int(__a ) , __a )
return number - int(__a )
if __name__ == "__main__":
print(decimal_isolate(1.53, 0))
print(decima... | 5 |
'''simple docstring'''
def UpperCAmelCase_ (__a : str ):
"""simple docstring"""
_a : List[Any] = 0
# if input_string is "aba" than new_input_string become "a|b|a"
_a : Optional[int] = ''
_a : List[str] = ''
# append each c... | 5 | 1 |
def snake_case_ ( snake_case ) -> str:
return "".join([hex(snake_case )[2:].zfill(2 ).upper() for byte in list(snake_case )] )
def snake_case_ ( snake_case ) -> bytes:
# Check data validity, following RFC3548
# https://www.ietf.org/r... | 196 |
import unittest
from knapsack import knapsack as k
class __a ( unittest.TestCase ):
def SCREAMING_SNAKE_CASE__ ( self ) -> Tuple:
'''simple docstring'''
lowercase__: List[Any] = 0
lowercase__: List[Any] = [0]
lowe... | 196 | 1 |
"""simple docstring"""
import pickle
import numpy as np
from matplotlib import pyplot as plt
class __snake_case :
def __init__( self : Dict , _UpperCAmelCase : Union[str, Any] , _UpperCAmelCase : Optional[int] , _UpperCAmelCase : List[Any] , _UpperCAm... | 358 |
import argparse
import json
import os
import fairseq
import torch
from torch import nn
from transformers import (
SpeechaTextaConfig,
SpeechaTextaForCausalLM,
SpeechaTextaTokenizer,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
Wa... | 159 | 0 |
'''simple docstring'''
import argparse
from collections import defaultdict
def lowercase__( __UpperCamelCase: List[Any] ,__UpperCamelCase: List[Any] ,__UpperCamelCase: Dict ,__UpperCamelCase: Optional[int] ,__UpperCamelCase: List[str] ):
"""simple docstring"""
... | 251 |
import itertools
from dataclasses import dataclass
from typing import Optional
import pandas as pd
import pyarrow as pa
import datasets
from datasets.table import table_cast
@dataclass
class snake_case__ (datasets.BuilderConfig ):
"""simple docstring"""
_... | 170 | 0 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BertTokenizer, Blip... | 15 |
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
a__ = '''\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},
author={Wang, Alex and Pruksachatku... | 15 | 1 |
import random
def UpperCamelCase_( _snake_case : int , _snake_case : float , _snake_case : bool = False ):
"""simple docstring"""
__a ={i: [] for i in range(_snake_case )}
# if probability is greater or equal than 1, the... | 218 |
from ... import PretrainedConfig
_lowerCAmelCase : Any = {
"sijunhe/nezha-cn-base": "https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json",
}
class __magic_name__ ( lowerCAmelCase_ ):
SCREAMING_SNAKE_CASE = NEZHA_PRETRAINED_CONFIG_AR... | 218 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
__A : Any = logging.get_logger(__name__... | 27 |
"""simple docstring"""
import torch
from transformers import AutoModel
class lowerCamelCase ( torch.nn.Module ):
def __init__( self , SCREAMING_SNAKE_CASE_="sayef/fsner-bert-base-uncased" ):
super(SCREAMING_SNAKE_CASE_ , self ).__init__()
UpperCamelCase ... | 27 | 1 |
'''simple docstring'''
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class _snake_case ( _... | 139 |
'''simple docstring'''
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
A_ = ... | 139 | 1 |
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGEX_COMMIT_HASH
from huggingfa... | 354 |
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class _SCREAMING_SNAKE_CASE ( __SCREAMIN... | 273 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowercase : Any = logging.get_logger(__name__)
_lowercase : Union... | 239 |
'''simple docstring'''
from __future__ import annotations
def _UpperCamelCase ( __A ) -> float:
'''simple docstring'''
UpperCamelCase__ = 0.00
UpperCamelCase__ = 0
for resistor in resistors:
if resistor <= 0:
... | 80 | 0 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import ... | 234 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_pegasus import PegasusToken... | 234 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowercase__ ( __lowercase : Any , __lowercase : str , __low... | 53 |
'''simple docstring'''
from __future__ import annotations
class snake_case :
"""simple docstring"""
def __init__( self : Optional[int] , __A : list[list[int]] ):
__UpperCamelCase = TypeError(
'Matrices must be formed from a list of ... | 53 | 1 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import torch
... | 66 |
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __lowerc... | 66 | 1 |
def lowerCamelCase__ ( _A ):
'''simple docstring'''
snake_case_ = len(_A )
for i in range(_A ):
for j in range(i + 1 , _A ):
if numbers[j] < numbers[i]:
snake_case_ , snake_case_ = numbers[j], numbers[i]
... | 187 |
def lowerCamelCase__ ( _A ):
'''simple docstring'''
if num <= 0:
raise ValueError("Input must be a positive integer" )
snake_case_ = [True] * (num + 1)
snake_case_ = 2
while p * p <= num:
if primes[p]:
for i in range(p * p... | 187 | 1 |
def UpperCamelCase ( __lowercase : float ,__lowercase : float ):
'''simple docstring'''
return price * (1 + tax_rate)
if __name__ == "__main__":
print(F"""{price_plus_tax(100, 0.25) = }""")
print(F"""{price_plus_tax(125.50, 0.05) = }""")
| 192 | import sys
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked befor... | 192 | 1 |
def UpperCAmelCase_ ( __snake_case , __snake_case ) -> float:
"""simple docstring"""
if digit_amount > 0:
return round(number - int(__snake_case ) , __snake_case )
return number - int(__snake_case )
if __name__ == "__main__":
print(decimal_i... | 5 |
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ = logging.get_logger(__name__)
# TODO Update this
UpperCAmelCase__ = {
'''facebook/esm-1b''': '''https://huggingface.co/fac... | 5 | 1 |
'''simple docstring'''
import math
def UpperCAmelCase ( lowerCamelCase_ :str , lowerCamelCase_ :Any ):
'''simple docstring'''
if 0 not in (x, y):
# We use the relation x^y = y*log10(x), where 10 is the base.
return y * math.logaa(lowerCamelCase_ )
else:
if x ... | 350 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_sentencepiece
@requi... | 8 | 0 |
'''simple docstring'''
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
A__ : Dict = pd.read_csv("""sample_data.csv""", header=None... | 185 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinvaConfig, SwinvaForImageClassification
def UpperCamelCase( __UpperCamelCase : List[str] ):
... | 103 | 0 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
return " ".join(
"".join(word[::-1] ) if len(lowerCAmelCase_ ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.te... | 195 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : int = logging.get_logger(__name__)
a__ : Tuple = {'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''}
class UpperCamelCase... | 195 | 1 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BertTokenizer, BlipImageProcesso... | 15 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
SCREAMING_SNAKE_CASE :List[Any] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 15 | 1 |
"""simple docstring"""
from __future__ import annotations
UpperCAmelCase__ = 1.6021E-19 # units = C
def __UpperCAmelCase ( lowercase ,lowercase ,lowercase ,):
"""simple docstring"""
if (conductivity, electron_conc, mobility).count(0 ) != 1:
raise ValueError(... | 352 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
UpperCAmelCase__ = {
"""configuration_trocr""": ["""TROCR_PRETRAINED_CONFIG_ARCHIVE_M... | 30 | 0 |
'''simple docstring'''
import warnings
from functools import wraps
from typing import Callable
def lowerCamelCase (_SCREAMING_SNAKE_CASE : Callable ):
@wraps(_SCREAMING_SNAKE_CASE )
def _inner_fn(*_SCREAMING_SNAKE_CASE : List[str] , **_SCREAMING_SNAKE_CASE ... | 27 |
'''simple docstring'''
import os
import sys
__lowercase : List[Any] = os.path.join(os.path.dirname(__file__), 'src')
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,
AutoModel... | 27 | 1 |
"""simple docstring"""
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class a ( unittest.TestCase ):
def lowerCAmelCase_ ( self : int ):
debug_launcher(test_script.main )
d... | 30 | """simple docstring"""
def __UpperCAmelCase ( lowercase = 10_00 ):
"""simple docstring"""
_UpperCAmelCase = 2**power
_UpperCAmelCase = 0
while n:
_UpperCAmelCase , _UpperCAmelCase = r + n % 10, n // 10
return r
if __name__ == "__main__":
print(solution(int(str(input... | 30 | 1 |
from string import ascii_lowercase, ascii_uppercase
def _a ( SCREAMING_SNAKE_CASE : str ):
"""simple docstring"""
if not sentence:
return ""
UpperCamelCase__ : Optional[Any] = dict(zip(snake_case_ , snake_case_ ) )
return lower_to_upper.get(sentence[0] , ... | 146 | '''simple docstring'''
import itertools
from dataclasses import dataclass
from typing import Optional
import pandas as pd
import pyarrow as pa
import datasets
from datasets.table import table_cast
@dataclass
class _lowercase ( datasets.BuilderConfig ):
'''simple docstring... | 229 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__UpperCAmelCase :List[str] = logging.get_logger... | 240 |
'''simple docstring'''
import unittest
from transformers import DebertaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common im... | 240 | 1 |
'''simple docstring'''
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
fro... | 234 |
'''simple docstring'''
def __lowerCAmelCase (__lowerCAmelCase , __lowerCAmelCase ):
if density <= 0:
raise ValueError("Impossible fluid density" )
if bulk_modulus <= 0:
raise ValueError("Impossible bulk modulus" )
return (bulk_modulus / density) **... | 234 | 1 |
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print("Googling.....")
_lowercase: Dict = "https://www.google.com/search?q=" + " ".join(sys.argv[1:])
_lowercase: Dict = requests.get(url, ... | 71 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase: Optional[Any] = logging.get_logger(__name__)
_lowercase: Any = {
"microsoft/git-base": "https://huggingface.co/microsoft/git-base/resolve/main/c... | 71 | 1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.