code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPP... | 319 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase=None , **__lowercase ) -> Any:
A: Any = [x.strip() for x in open(__lowercase ... | 319 | 1 |
'''simple docstring'''
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
UpperCamelCase... | 319 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase = 0 ) -> list:
A: Dict = length or len(__lowercase )
A: Dict = False
for i in range(length - 1 ):
if list_data[i] > list_data[i + 1]... | 319 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
UpperCamelCase = {'''configuration_speech_encoder_decoder''': ['''SpeechEncoderDecoderConfig''']}
try:
if not is_torch_... | 319 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasonin... | 319 | 1 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
... | 319 |
'''simple docstring'''
from itertools import permutations
def SCREAMING_SNAKE_CASE( __lowercase ) -> bool:
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
... | 319 | 1 |
'''simple docstring'''
from collections import Counter
from timeit import timeit
def SCREAMING_SNAKE_CASE( __lowercase = "" , ) -> bool:
return sum(c % 2 for c in Counter(input_str.replace(''' ''' , '''''' ).lower() ).values() ) < 2
def SCREAMIN... | 319 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
... | 319 | 1 |
'''simple docstring'''
from copy import deepcopy
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : Any , SCREAMING_SNAKE_CASE_ : list[int] | None = None , SCREAMING_SNAKE_CASE_ : int | None = None ) -... | 319 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> int:
if not isinstance(__lowercase , __lowercase ):
raise TypeError('''only integers accepted as input''' )
else:
A: str = str(abs(__lowercase ) ... | 319 | 1 |
'''simple docstring'''
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
@staticmethod
@abstractmethod
def _snake_case ( SCREAMING_SNAKE_CASE_ : A... | 319 |
'''simple docstring'''
from __future__ import annotations
import math
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> list:
if len(__lowercase ) != 2 or len(a[0] ) != 2 or len(__lowercase ) != 2 or len(b[0] ) != 2:
raise Excepti... | 319 | 1 |
'''simple docstring'''
import re
def SCREAMING_SNAKE_CASE( __lowercase ) -> str:
if len(re.findall('''[ATCG]''' , __lowercase ) ) != len(__lowercase ):
raise ValueError('''Invalid Strand''' )
return dna.translate(dna.maketrans('''... | 319 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
... | 319 | 1 |
'''simple docstring'''
import argparse
import logging
import os
import time
import timeit
import datasets
import numpy as np
import pycuda.autoinit # noqa: F401
import pycuda.driver as cuda
import tensorrt as trt
import torch
from absl import logging as absl_logging
from accelerate import ... | 319 |
'''simple docstring'''
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPP... | 319 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase , __lowercase ) -> Any:
# Return True if there is node that has not iterated.
A: int = [False] * len(__lowercase )
A: str... | 319 |
'''simple docstring'''
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme impor... | 319 | 1 |
'''simple docstring'''
import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command,... | 319 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
def __... | 319 | 1 |
'''simple docstring'''
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : Tuple ) -> Union[str, Any]:
... | 319 |
'''simple docstring'''
import os
import pytest
from transformers.dynamic_module_utils import get_imports
UpperCamelCase = '''
import os
'''
UpperCamelCase = '''
def foo():
import os
return False
'''
UpperCamelCase = '''
def foo():
def bar():
... | 319 | 1 |
'''simple docstring'''
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertCo... | 319 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTex... | 319 | 1 |
'''simple docstring'''
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import Bat... | 319 |
'''simple docstring'''
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing impor... | 319 | 1 |
'''simple docstring'''
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_s... | 319 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FocalNetCon... | 319 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase = {
'''configuration_x_clip''': [
'''XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''XCLIPConfig''',
'''X... | 319 |
'''simple docstring'''
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from ..image_utils import load_image
if... | 319 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> bool:
A: Union[str, Any] = n ** (1 / 3)
return (val * val * val) == n
if __name__ == "__main__":
print(perfect_cube(27))
print(perfect_cube(4))
| 319 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''Yi... | 319 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase = {
'''configuration_blip''': [
'''BLIP_PRETRAINE... | 319 |
'''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE( __lowercase ) -> bool:
if len(__lowercase ) < 2:
raise ValueError('''Monogons and Digons are not polygons in the Euclidean space''' )
if any(i <= 0 for i in nums ):
... | 319 | 1 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer
UpperCamelCase = loggi... | 319 |
'''simple docstring'''
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTe... | 319 | 1 |
'''simple docstring'''
import pytest
from datasets.parallel import ParallelBackendConfig, parallel_backend
from datasets.utils.py_utils import map_nested
from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows
def SCREAMING_SNAKE_CASE( __lowercase ) -> ... | 319 |
'''simple docstring'''
import heapq
import sys
import numpy as np
UpperCamelCase = tuple[int, int]
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : List[Any] ) -> str:
'''simple ... | 319 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> str: # noqa: E741
A: str = len(__lowercase )
A: Optional[Any] = 0
A: Any = [0] * n
A: List[Any] = [False] * n
A: List[s... | 319 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase = 1 , __lowercase = 1_0_0_0 ) -> int:
A: Any = 1
A: Optional[Any] = 0
for divide_by_number in range(__lowercase , digit + 1 ):
A: li... | 319 | 1 |
'''simple docstring'''
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme impor... | 319 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {
'''configuration_vision_encoder_decoder''': ['''VisionEn... | 319 | 1 |
'''simple docstring'''
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 ... | 319 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase=None , **__lowercase ) -> Any:
A: Any = [x.strip() for x in open(__lowercase ... | 319 | 1 |
'''simple docstring'''
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 a... | 319 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase = 0 ) -> list:
A: Dict = length or len(__lowercase )
A: Dict = False
for i in range(length - 1 ):
if list_data[i] > list_data[i + 1]... | 319 | 1 |
'''simple docstring'''
from __future__ import annotations
UpperCamelCase = tuple[int, int, int]
UpperCamelCase = tuple[str, str, str]
# used alphabet --------------------------
# from string.ascii_uppercase
UpperCamelCase = '''ABCDEFGHIJKLMNOPQRSTUVWXYZ'''
# -----... | 319 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasonin... | 319 | 1 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gp... | 319 |
'''simple docstring'''
from itertools import permutations
def SCREAMING_SNAKE_CASE( __lowercase ) -> bool:
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
... | 319 | 1 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class ... | 319 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
... | 319 | 1 |
'''simple docstring'''
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
UpperCamelCase = '''\
@inproceedings{kakwani2020indicnlpsuite,
title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-train... | 319 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> int:
if not isinstance(__lowercase , __lowercase ):
raise TypeError('''only integers accepted as input''' )
else:
A: str = str(abs(__lowercase ) ... | 319 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase = 1_0_0_0_0_0_0 ) -> int:
A: Optional[Any] = limit + 1
A: List[Any] = [0] * limit
for first_term in range(1 , __lowercase ):
for n in range(__lowercas... | 319 |
'''simple docstring'''
from __future__ import annotations
import math
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> list:
if len(__lowercase ) != 2 or len(a[0] ) != 2 or len(__lowercase ) != 2 or len(b[0] ) != 2:
raise Excepti... | 319 | 1 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasonin... | 319 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
... | 319 | 1 |
'''simple docstring'''
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
'''The `inpainting.py` script is outdated. Please use directly `from diffusers import'''
''' StableDiffusionInpaintPipeline` instead.... | 319 |
'''simple docstring'''
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPP... | 319 | 1 |
'''simple docstring'''
import collections
import gzip
import os
import urllib
import numpy
from tensorflow.python.framework import dtypes, random_seed
from tensorflow.python.platform import gfile
from tensorflow.python.util.deprecation import deprecated
UpperCamelCase = collections.n... | 319 |
'''simple docstring'''
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme impor... | 319 | 1 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
clas... | 319 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
def __... | 319 | 1 |
'''simple docstring'''
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, RegNe... | 319 |
'''simple docstring'''
import os
import pytest
from transformers.dynamic_module_utils import get_imports
UpperCamelCase = '''
import os
'''
UpperCamelCase = '''
def foo():
import os
return False
'''
UpperCamelCase = '''
def foo():
def bar():
... | 319 | 1 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, lo... | 319 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTex... | 319 | 1 |
'''simple docstring'''
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
UpperCamelCase = False
... | 319 |
'''simple docstring'''
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing impor... | 319 | 1 |
'''simple docstring'''
UpperCamelCase = 8.31_44_62 # Unit - J mol-1 K-1
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase ) -> float:
if moles < 0 or kelvin < 0 or volume < 0:
raise ValueError('''Invalid inputs. Enter p... | 319 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FocalNetCon... | 319 | 1 |
'''simple docstring'''
from bisect import bisect
from itertools import accumulate
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase , __lowercase ) -> int:
A: Any = sorted(zip(__lowercase , __lowercase ... | 319 |
'''simple docstring'''
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from ..image_utils import load_image
if... | 319 | 1 |
'''simple docstring'''
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase , __lowercase , __lowercase , __lowercase ) ... | 319 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''Yi... | 319 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
... | 319 |
'''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE( __lowercase ) -> bool:
if len(__lowercase ) < 2:
raise ValueError('''Monogons and Digons are not polygons in the Euclidean space''' )
if any(i <= 0 for i in nums ):
... | 319 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> int:
return 1 if digit in (0, 1) else (digit * factorial(digit - 1 ))
def SCREAMING_SNAKE_CASE( __lowercase ) -> bool:
A: List[Any] = 0
A: Dict = ... | 319 |
'''simple docstring'''
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTe... | 319 | 1 |
'''simple docstring'''
# flake8: noqa
# Lint as: python3
from typing import Dict, List, Optional, Type
from .. import config
from ..utils import logging
from .formatting import (
ArrowFormatter,
CustomFormatter,
Formatter,
PandasFormatter,
PythonFormatter,
TensorFor... | 319 |
'''simple docstring'''
import heapq
import sys
import numpy as np
UpperCamelCase = tuple[int, int]
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : List[Any] ) -> str:
'''simple ... | 319 | 1 |
'''simple docstring'''
UpperCamelCase = [
(1000, '''M'''),
(900, '''CM'''),
(500, '''D'''),
(400, '''CD'''),
(100, '''C'''),
(90, '''XC'''),
(50, '''L'''),
(40, '''XL'''),
(10, '''X'''),
(9, '''IX'''),
(5, '''V'''),
(4, '''IV'''),
... | 319 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase = 1 , __lowercase = 1_0_0_0 ) -> int:
A: Any = 1
A: Optional[Any] = 0
for divide_by_number in range(__lowercase , digit + 1 ):
A: li... | 319 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> float:
return price * (1 + tax_rate)
if __name__ == "__main__":
print(f'{price_plus_tax(100, 0.25) = }')
print(f'{price_plus_tax(1_25.50, 0.05) = }')
| 319 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {
'''configuration_vision_encoder_decoder''': ['''VisionEn... | 319 | 1 |
'''simple docstring'''
import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_... | 319 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase=None , **__lowercase ) -> Any:
A: Any = [x.strip() for x in open(__lowercase ... | 319 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
def ... | 319 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase = 0 ) -> list:
A: Dict = length or len(__lowercase )
A: Dict = False
for i in range(length - 1 ):
if list_data[i] > list_data[i + 1]... | 319 | 1 |
'''simple docstring'''
import baseaa
def SCREAMING_SNAKE_CASE( __lowercase ) -> bytes:
return baseaa.baaencode(string.encode('''utf-8''' ) )
def SCREAMING_SNAKE_CASE( __lowercase ) -> str:
return baseaa.baadecode(__lowercase ).decode('''ut... | 319 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasonin... | 319 | 1 |
'''simple docstring'''
import numpy as np
from transformers import BatchFeature
from transformers.testing_utils import require_tf, require_torch
from .test_feature_extraction_common import FeatureExtractionSavingTestMixin
class lowerCAmelCase_ ( UpperCAmelCase_ ):
... | 319 |
'''simple docstring'''
from itertools import permutations
def SCREAMING_SNAKE_CASE( __lowercase ) -> bool:
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
... | 319 | 1 |
'''simple docstring'''
# Author: OMKAR PATHAK, Nwachukwu Chidiebere
# Use a Python dictionary to construct the graph.
from __future__ import annotations
from pprint import pformat
from typing import Generic, TypeVar
UpperCamelCase = TypeVar('''T''')
class lowerCAmelCase... | 319 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
... | 319 | 1 |
'''simple docstring'''
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transform... | 319 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> int:
if not isinstance(__lowercase , __lowercase ):
raise TypeError('''only integers accepted as input''' )
else:
A: str = str(abs(__lowercase ) ... | 319 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase = {
'''configuration_clap''': [
'''CLAP_PRETRAINED_MODEL_ARCHIVE_LIST''',
'''ClapAudioConfig''',
'''... | 319 |
'''simple docstring'''
from __future__ import annotations
import math
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> list:
if len(__lowercase ) != 2 or len(a[0] ) != 2 or len(__lowercase ) != 2 or len(b[0] ) != 2:
raise Excepti... | 319 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
from .timesteps import (
fastaa_timesteps,
smar... | 319 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
... | 319 | 1 |
'''simple docstring'''
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import is_speech_available, is_vision_available
from transformers.testing_utils import require_torch
if is_vision_available():
from transformers import TvltImagePro... | 319 |
'''simple docstring'''
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPP... | 319 | 1 |
'''simple docstring'''
import numpy as np
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase , __lowercase , __lowercase ) -> Dict:
A: List[Any] = int(np.ceil((x_end - xa) / h ) )
A: in... | 319 |
'''simple docstring'''
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme impor... | 319 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''... | 319 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
def __... | 319 | 1 |
'''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE( __lowercase ) -> list[int]:
A: Optional[int] = [True] * limit
A: List[Any] = False
A: Optional[Any] = False
A: str = ... | 319 |
'''simple docstring'''
import os
import pytest
from transformers.dynamic_module_utils import get_imports
UpperCamelCase = '''
import os
'''
UpperCamelCase = '''
def foo():
import os
return False
'''
UpperCamelCase = '''
def foo():
def bar():
... | 319 | 1 |
'''simple docstring'''
from __future__ import annotations
import csv
import requests
from bsa import BeautifulSoup
def SCREAMING_SNAKE_CASE( __lowercase = "" ) -> dict[str, float]:
A: Tuple = url or '''https://www.imdb.com/chart/top/?ref_=nv_mv_250'''
... | 319 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTex... | 319 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase = {
'''configuration_mobilenet_v2''': [
'''MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
... | 319 |
'''simple docstring'''
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing impor... | 319 | 1 |
'''simple docstring'''
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 lowerCAmelCase_ ... | 319 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FocalNetCon... | 319 | 1 |
'''simple docstring'''
from __future__ import annotations
import numpy as np
def SCREAMING_SNAKE_CASE( __lowercase ) -> Tuple:
return np.maximum(0 , __lowercase )
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0, 5]
... | 319 |
'''simple docstring'''
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from ..image_utils import load_image
if... | 319 | 1 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
Co... | 319 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''Yi... | 319 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase = {
'''configuration_roberta''... | 319 |
'''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE( __lowercase ) -> bool:
if len(__lowercase ) < 2:
raise ValueError('''Monogons and Digons are not polygons in the Euclidean space''' )
if any(i <= 0 for i in nums ):
... | 319 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> bool:
A: Union[str, Any] = len(__lowercase )
A: str = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr value, ... | 319 |
'''simple docstring'''
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTe... | 319 | 1 |
'''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... | 319 |
'''simple docstring'''
import heapq
import sys
import numpy as np
UpperCamelCase = tuple[int, int]
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : List[Any] ) -> str:
'''simple ... | 319 | 1 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : Dict , SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNAKE_CASE_ : int , SCREAMI... | 319 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase = 1 , __lowercase = 1_0_0_0 ) -> int:
A: Any = 1
A: Optional[Any] = 0
for divide_by_number in range(__lowercase , digit + 1 ):
A: li... | 319 | 1 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jn... | 319 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {
'''configuration_vision_encoder_decoder''': ['''VisionEn... | 319 | 1 |
'''simple docstring'''
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
UpperCamelCase = get_logger(__name__)
UpperCamelCase = R'''
Args:
input_ids (`jnp... | 319 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase=None , **__lowercase ) -> Any:
A: Any = [x.strip() for x in open(__lowercase ... | 319 | 1 |
'''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE( __lowercase ) -> bool:
if len(__lowercase ) < 2:
raise ValueError('''Monogons and Digons are not polygons in the Euclidean space''' )
if any(i <= 0 for i in nums ):
... | 319 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase = 0 ) -> list:
A: Dict = length or len(__lowercase )
A: Dict = False
for i in range(length - 1 ):
if list_data[i] > list_data[i + 1]... | 319 | 1 |
'''simple docstring'''
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from ..image_utils import load_image
if... | 319 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasonin... | 319 | 1 |
'''simple docstring'''
from functools import lru_cache
@lru_cache
def SCREAMING_SNAKE_CASE( __lowercase ) -> int:
if num < 0:
raise ValueError('''Number should not be negative.''' )
return 1 if num in (0, 1) else num * factorial(num - 1 )
if __n... | 319 |
'''simple docstring'''
from itertools import permutations
def SCREAMING_SNAKE_CASE( __lowercase ) -> bool:
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
... | 319 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> int:
if not isinstance(__lowercase , __lowercase ):
raise TypeError('''only integers accepted as input''' )
else:
A: str = str(abs(__lowercase ) ... | 319 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
... | 319 | 1 |
'''simple docstring'''
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTe... | 319 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> int:
if not isinstance(__lowercase , __lowercase ):
raise TypeError('''only integers accepted as input''' )
else:
A: str = str(abs(__lowercase ) ... | 319 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
UpperCamelCase_ : str... | 319 |
'''simple docstring'''
from __future__ import annotations
import math
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> list:
if len(__lowercase ) != 2 or len(a[0] ) != 2 or len(__lowercase ) != 2 or len(b[0] ) != 2:
raise Excepti... | 319 | 1 |
'''simple docstring'''
from collections.abc import Iterable
from typing import Generic, TypeVar
UpperCamelCase = TypeVar('''_T''')
class lowerCAmelCase_ ( Generic[_T] ):
'''simple docstring'''
def __init__( self : Dict , SCREAMIN... | 319 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
... | 319 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
UpperCamelCase = list[list[float | int]]
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> Matrix:
A: int = len(__lowercase )
... | 319 |
'''simple docstring'''
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPP... | 319 | 1 |
'''simple docstring'''
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_... | 319 |
'''simple docstring'''
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme impor... | 319 | 1 |
'''simple docstring'''
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_token... | 319 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
def __... | 319 | 1 |
'''simple docstring'''
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from huggingface_hub import HfFolder, Repository, create_repo, delete_repo
from requests.exceptions import HTTPError
import transformers
from transfor... | 319 |
'''simple docstring'''
import os
import pytest
from transformers.dynamic_module_utils import get_imports
UpperCamelCase = '''
import os
'''
UpperCamelCase = '''
def foo():
import os
return False
'''
UpperCamelCase = '''
def foo():
def bar():
... | 319 | 1 |
'''simple docstring'''
# Lint as: python3
import itertools
import os
import re
UpperCamelCase = re.compile(R'''([A-Z]+)([A-Z][a-z])''')
UpperCamelCase = re.compile(R'''([a-z\d])([A-Z])''')
UpperCamelCase = re.compile(R'''(?<!_)_(?!_)''')
UpperCamelCase = r... | 319 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTex... | 319 | 1 |
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class lowercase_ ( lowerca... | 0 |
'''simple docstring'''
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing impor... | 319 | 0 |
'''simple docstring'''
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL... | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FocalNetCon... | 319 | 0 |
'''simple docstring'''
import operator as op
lowerCamelCase : Dict = 'scaler.pt'
lowerCamelCase : Optional[Any] = 'pytorch_model'
lowerCamelCase : List[Any] = 'random_states'
lowerCamelCase : Union[str, Any] = 'optimizer'
lowerCamelCase : str ... | 2 |
'''simple docstring'''
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from ..image_utils import load_image
if... | 319 | 0 |
'''simple docstring'''
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import (
Bnb... | 3 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''Yi... | 319 | 0 |
'''simple docstring'''
import os
__snake_case ={"""I""": 1, """V""": 5, """X""": 10, """L""": 50, """C""": 100, """D""": 500, """M""": 1_000}
def a_ ( lowerCamelCase : str ):
lowerCAmelCase = 0
lowerCAmelCase = 0
while index < len(lowerCamelCas... | 4 |
'''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE( __lowercase ) -> bool:
if len(__lowercase ) < 2:
raise ValueError('''Monogons and Digons are not polygons in the Euclidean space''' )
if any(i <= 0 for i in nums ):
... | 319 | 0 |
from __future__ import annotations
UpperCAmelCase__ = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def UpperCAmelCase_ ( __snake_case , __snake_case , __snake_case , __snake_case , __snake_case , ) -> t... | 5 |
'''simple docstring'''
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTe... | 319 | 0 |
from collections.abc import Callable
import numpy as np
def __lowerCAmelCase ( a__ , a__ , a__ , a__ , a__ ) -> np.array:
__a = int(np.ceil((x_end - xa) / step_size ) )
__a = np.zeros((n + 1,) )
__a = ya
__a ... | 6 |
'''simple docstring'''
import heapq
import sys
import numpy as np
UpperCamelCase = tuple[int, int]
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : List[Any] ) -> str:
'''simple ... | 319 | 0 |
from __future__ import annotations
from scipy.special import comb # type: ignore
class A :
"""simple docstring"""
def __init__( self : Tuple,lowercase_ : list[tuple[float, float]] )-> Tuple:
'''simple docstring'''
... | 7 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase = 1 , __lowercase = 1_0_0_0 ) -> int:
A: Any = 1
A: Optional[Any] = 0
for divide_by_number in range(__lowercase , digit + 1 ):
A: li... | 319 | 0 |
def __SCREAMING_SNAKE_CASE (SCREAMING_SNAKE_CASE__ ):
snake_case_ = n ** (1 / 3)
return (val * val * val) == n
if __name__ == "__main__":
print(perfect_cube(27))
print(perfect_cube(4)) | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {
'''configuration_vision_encoder_decoder''': ['''VisionEn... | 319 | 0 |
def _UpperCamelCase ( lowercase__ ):
if num <= 0:
raise ValueError('''Input must be a positive integer''' )
__SCREAMING_SNAKE_CASE : Tuple = [True] * (num + 1)
__SCREAMING_SNAKE_CASE : Dict = 2
while p * p <= num:
... | 9 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase=None , **__lowercase ) -> Any:
A: Any = [x.strip() for x in open(__lowercase ... | 319 | 0 |
from typing import Any
def lowerCAmelCase_ ( __a , __a , __a , __a , __a , ) -> list:
"""simple docstring"""
_validation(
__a , __a , __a , __a , __a , )
# Creates data structures and fill initial step
lowerCamelCase__: dict ={}... | 10 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase = 0 ) -> list:
A: Dict = length or len(__lowercase )
A: Dict = False
for i in range(length - 1 ):
if list_data[i] > list_data[i + 1]... | 319 | 0 |
import unittest
import torch
from diffusers import VQModel
from diffusers.utils import floats_tensor, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
enable_full_determinism()
class lowerCAmelCase__ ... | 11 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasonin... | 319 | 0 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(_... | 12 |
'''simple docstring'''
from itertools import permutations
def SCREAMING_SNAKE_CASE( __lowercase ) -> bool:
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
... | 319 | 0 |
import os
import re
import warnings
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_ta import TaTokenizer
else:
... | 13 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
... | 319 | 0 |
from __future__ import annotations
import typing
from collections.abc import Iterable
import numpy as np
_lowerCamelCase : str = typing.Union[Iterable[float], Iterable[int], np.ndarray] # noqa: UP007
_lowerCamelCase : Tuple = typing.Union[np.floataa, int, float] # noqa: UP007
... | 14 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> int:
if not isinstance(__lowercase , __lowercase ):
raise TypeError('''only integers accepted as input''' )
else:
A: str = str(abs(__lowercase ) ... | 319 | 0 |
import math
def UpperCAmelCase ( a_ , a_ ) -> float:
"""simple docstring"""
if (
not isinstance(a_ , (int, float) )
or power_factor < -1
or power_factor > 1
):
raise ValueError("power_factor must be a valid float value between -1 and 1." ... | 15 |
'''simple docstring'''
from __future__ import annotations
import math
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> list:
if len(__lowercase ) != 2 or len(a[0] ) != 2 or len(__lowercase ) != 2 or len(b[0] ) != 2:
raise Excepti... | 319 | 0 |
"""simple docstring"""
import argparse
import re
import requests
import torch
# git clone https://github.com/salesforce/BLIP.git
from models.blip import blip_decoder
from models.blip_itm import blip_itm
from models.blip_vqa import blip_vqa
from PIL import Image
from torchvision impor... | 16 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
... | 319 | 0 |
"""simple docstring"""
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_at... | 17 |
'''simple docstring'''
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPP... | 319 | 0 |
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, ra... | 18 |
'''simple docstring'''
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme impor... | 319 | 0 |
# 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/licenses/LICENSE-2.0
#
# Unless required by applicab... | 19 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
def __... | 319 | 0 |
def _snake_case( SCREAMING_SNAKE_CASE__ ) -> int:
lowercase : Any = hex_num.strip()
if not hex_num:
raise ValueError("""No value was passed to the function""" )
lowercase : int = hex_num[0] == """-"""
if is_negative:... | 20 |
'''simple docstring'''
import os
import pytest
from transformers.dynamic_module_utils import get_imports
UpperCamelCase = '''
import os
'''
UpperCamelCase = '''
def foo():
import os
return False
'''
UpperCamelCase = '''
def foo():
def bar():
... | 319 | 0 |
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