code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
SCREAMING_SNAKE_CASE = False
class UpperCAmelCase_ ( unittest.TestCase ):
... | 8 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (... | 8 | 1 |
'''simple docstring'''
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class UpperCAmelCase_ ( yaml.SafeLoader ):
"""simple docstring"""
def A__ ( self : int , UpperCAmelCase : Union[str, Any] ) ->... | 8 |
'''simple docstring'''
def lowercase_ ( __A : float , __A : int ) -> float:
"""simple docstring"""
if digit_amount > 0:
return round(number - int(__A ) , __A )
return number - int(__A )
if __name__ == "__main__":
print(decimal_i... | 8 | 1 |
'''simple docstring'''
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
@require_torch
def A__ ... | 8 |
'''simple docstring'''
from typing import Dict, Iterable, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import ... | 8 | 1 |
'''simple docstring'''
class UpperCAmelCase_ : # Public class to implement a graph
"""simple docstring"""
def __init__( self : List[Any] , UpperCAmelCase : int , UpperCAmelCase : int , UpperCAmelCase : list[list[bool]] ) -> None:
'''s... | 8 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, 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_t... | 8 | 1 |
'''simple docstring'''
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumen... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_rembert': ['REMBER... | 8 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE = {
'configuration_blip_2': [
'BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Blip2Config',
'Blip2QFormerConfig',
... | 8 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
SCREAMING_SNAKE_CASE = parse(importlib.metadata.version('torch'))
def lowercase_ ( __A : Union[str, Version] , ... | 8 | 1 |
'''simple docstring'''
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class UpperCAmelCase_ ( __A , __A ):
"""simple docstring"""
@register_to_config
def __init__( self : Dic... | 8 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
SCREAMING_SNAKE_CASE = 'https://www.indeed.co.in/jobs?q=mobile+app+development&l='
def lowercase_ ( __A : str = "mumbai" ) -> ... | 8 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {
'unc-nlp/lxmert-base-uncased': 'https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json',
}
... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE = {
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
... | 8 | 1 |
'''simple docstring'''
from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState
from acc... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_mega': ['MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegaConfig', 'MegaOnnxConfig'],
}
try:
if not ... | 8 | 1 |
'''simple docstring'''
def lowercase_ ( __A : int , __A : int ) -> str:
"""simple docstring"""
if number < 0 or shift_amount < 0:
raise ValueError('''both inputs must be positive integers''' )
lowercase : List[Any] =str(bin(__A ) )
... | 8 |
'''simple docstring'''
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {'vocab_file':... | 8 | 1 |
'''simple docstring'''
import argparse
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
CLIPTokenizer,
CLIPTokenizerFast,
VideoMAEImageProcessor,
XCLIPConfig,
XCLIPModel,
XCLIPProcessor,
XCLIPTextConfig,
XCLIP... | 8 |
'''simple docstring'''
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
@require_torch
def A__ ... | 8 | 1 |
'''simple docstring'''
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_available
from ...te... | 8 |
'''simple docstring'''
SCREAMING_SNAKE_CASE = 'Alexander Joslin'
import operator as op
from .stack import Stack
def lowercase_ ( __A : str ) -> int:
"""simple docstring"""
lowercase : int ={'''*''': op.mul, '''/''': op.truediv, '''+''': op.add, '''-... | 8 | 1 |
'''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,
Ad... | 8 |
'''simple docstring'''
import re
def lowercase_ ( __A : str ) -> bool:
"""simple docstring"""
lowercase : Any =re.compile(R'''^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$''' )
if match := re.search(__A , __A ):
return match.string == phone
return F... | 8 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
SCREAMING_SNAKE_CASE = {
'google/tapas-base-finetuned-sqa': (
'https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'
),
'google/tapas-base-finetuned-wtq': (
'https://hugging... | 8 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, 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_ten... | 8 | 1 |
'''simple docstring'''
from __future__ import annotations
SCREAMING_SNAKE_CASE = 8.988E9 # units = N * m^s * C^-2
def lowercase_ ( __A : float , __A : float , __A : float , __A : float ) -> dict[str, float]:
"""simple do... | 8 |
'''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 UpperCAmelCase_ ( ... | 8 | 1 |
'''simple docstring'''
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward... | 8 |
'''simple docstring'''
def lowercase_ ( __A : int = 6_0_0_8_5_1_4_7_5_1_4_3 ) -> int:
"""simple docstring"""
try:
lowercase : Any =int(__A )
except (TypeError, ValueError):
raise TypeError('''Parameter n must be int or castable to int.''' )
if n <=... | 8 | 1 |
'''simple docstring'''
from __future__ import annotations
import pandas as pd
def lowercase_ ( __A : list[int] , __A : list[int] , __A : int ) -> list[int]:
"""simple docstring"""
lowercase : Tuple =[0] * no_of_processes
low... | 8 |
'''simple docstring'''
from __future__ import annotations
import math
def lowercase_ ( __A : float , __A : int ) -> float:
"""simple docstring"""
lowercase : str =u
for i in range(1 , __A ):
lowercase : Any =temp * ... | 8 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE = {
'configuration_pegasus_x': ['PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PegasusXConfig'],
}
try:
if not is_torch_available():... | 8 |
'''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_ut... | 8 | 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
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE... | 8 |
'''simple docstring'''
from __future__ import annotations
SCREAMING_SNAKE_CASE = 8.988E9 # units = N * m^s * C^-2
def lowercase_ ( __A : float , __A : float , __A : float , __A : float ) -> dict[str, float]:
"""simple do... | 8 | 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 UpperCAmelCase_ ( ... | 8 |
'''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... | 8 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : List[str] , UpperCAmelCase : int ) -> None:
'''simple docstring'''
lowercase : int =size
# app... | 8 |
'''simple docstring'''
import mpmath # for roots of unity
import numpy as np
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : List[Any] , UpperCAmelCase : Dict=None , UpperCAmelCase : Optional[int]=None ) -> Optional[Any]:
'''s... | 8 | 1 |
'''simple docstring'''
def lowercase_ ( __A : int = 2_0_0 ) -> int:
"""simple docstring"""
lowercase : Dict =[1, 2, 5, 1_0, 2_0, 5_0, 1_0_0, 2_0_0]
lowercase : Any =[0] * (pence + 1)
lowercase : Optional[int] =1 # base case: 1 way to... | 8 |
'''simple docstring'''
def lowercase_ ( __A : int , __A : int ) -> str:
"""simple docstring"""
if number < 0 or shift_amount < 0:
raise ValueError('''both inputs must be positive integers''' )
lowercase : List[Any] =str(bin(__A ) )
... | 8 | 1 |
'''simple docstring'''
def lowercase_ ( __A : int = 1_0 ) -> str:
"""simple docstring"""
if not isinstance(__A , __A ) or n < 0:
raise ValueError('''Invalid input''' )
lowercase : str =1_0**n
lowercase : Optional[int] =2_8_4_3_3 *... | 8 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (... | 8 | 1 |
'''simple docstring'''
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational im... | 8 |
'''simple docstring'''
def lowercase_ ( __A : float , __A : int ) -> float:
"""simple docstring"""
if digit_amount > 0:
return round(number - int(__A ) , __A )
return number - int(__A )
if __name__ == "__main__":
print(decimal_i... | 8 | 1 |
'''simple docstring'''
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def lowercase_ ( ) -> Optional[Any]:
"""simple docstring"""
lowercase : List[str] =A... | 8 |
'''simple docstring'''
from typing import Dict, Iterable, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import ... | 8 | 1 |
'''simple docstring'''
import dataclasses
import re
import string
from typing import Any, Dict, Iterator, List, Mapping, Optional, Sequence, Tuple
import numpy as np
from . import residue_constants
SCREAMING_SNAKE_CASE = Mapping[str, np.ndarray]
SCREAMING_SNAKE_CASE = Mapping[str, Any] # Is a n... | 8 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, 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_t... | 8 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
SCREAMING_SNAKE_CASE = '2020.9.26'
SCREAMING_SNAKE_CASE = 'xcodz-dot, cclaus, dhruvmanila'
def lowercase_ ( __A : float , __A : float , __A : float , __A : float ... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_rembert': ['REMBER... | 8 | 1 |
'''simple docstring'''
import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class UpperCAmelCase_ ( unittest.TestCase ):
... | 8 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
SCREAMING_SNAKE_CASE = parse(importlib.metadata.version('torch'))
def lowercase_ ( __A : Union[str, Version] , ... | 8 | 1 |
'''simple docstring'''
SCREAMING_SNAKE_CASE = 0 # The first color of the flag.
SCREAMING_SNAKE_CASE = 1 # The second color of the flag.
SCREAMING_SNAKE_CASE = 2 # The third color of the flag.
SCREAMING_SNAKE_CASE = (red, white, blue)
def lowercase_ ( __A : list ) ... | 8 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
SCREAMING_SNAKE_CASE = 'https://www.indeed.co.in/jobs?q=mobile+app+development&l='
def lowercase_ ( __A : str = "mumbai" ) -> ... | 8 | 1 |
'''simple docstring'''
import os
SCREAMING_SNAKE_CASE = {'I': 1, 'V': 5, 'X': 10, 'L': 50, 'C': 100, 'D': 500, 'M': 1_000}
def lowercase_ ( __A : str ) -> int:
"""simple docstring"""
lowercase : str =0
lowercase : List[Any] =0
while ind... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE = {
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
... | 8 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCAmelCase_ ( metaclass=__A ):
"""simple docstring"""
UpperCamelCase_ = ['''torch''']
def __init__( self : int , *UpperCAmelCase : Union[str, Any] , **... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_mega': ['MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegaConfig', 'MegaOnnxConfig'],
}
try:
if not ... | 8 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {
'facebook/xmod-ba... | 8 |
'''simple docstring'''
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {'vocab_file':... | 8 | 1 |
'''simple docstring'''
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
def __init__( self : Dict , ... | 8 |
'''simple docstring'''
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
@require_torch
def A__ ... | 8 | 1 |
'''simple docstring'''
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
def lowercase_ ( __A : List[str]=None , ... | 8 |
'''simple docstring'''
SCREAMING_SNAKE_CASE = 'Alexander Joslin'
import operator as op
from .stack import Stack
def lowercase_ ( __A : str ) -> int:
"""simple docstring"""
lowercase : int ={'''*''': op.mul, '''/''': op.truediv, '''+''': op.add, '''-... | 8 | 1 |
'''simple docstring'''
from PIL import Image
def lowercase_ ( __A : Image , __A : float ) -> Image:
"""simple docstring"""
def brightness(__A : int ) -> float:
return 1_2_8 + level + (c - 1_2_8)
if not -255.0 <= level <= 255.0:
raise Valu... | 8 |
'''simple docstring'''
import re
def lowercase_ ( __A : str ) -> bool:
"""simple docstring"""
lowercase : Any =re.compile(R'''^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$''' )
if match := re.search(__A , __A ):
return match.string == phone
return F... | 8 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple
import torch
from torch import nn
from transformers import RobertaPreTrainedModel, XLMRobertaConfig, XLMRobertaModel
from transformers.utils import ModelOutput
@dataclass
class UpperCAmelCase_ ( __A ):
... | 8 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, 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_ten... | 8 | 1 |
'''simple docstring'''
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {
'google/umt5-small': 'https://huggingf... | 8 |
'''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 UpperCAmelCase_ ( ... | 8 | 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 lowercase_ ( __A : int ) -> Optio... | 8 |
'''simple docstring'''
def lowercase_ ( __A : int = 6_0_0_8_5_1_4_7_5_1_4_3 ) -> int:
"""simple docstring"""
try:
lowercase : Any =int(__A )
except (TypeError, ValueError):
raise TypeError('''Parameter n must be int or castable to int.''' )
if n <=... | 8 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_availabl... | 8 |
'''simple docstring'''
from __future__ import annotations
import math
def lowercase_ ( __A : float , __A : int ) -> float:
"""simple docstring"""
lowercase : str =u
for i in range(1 , __A ):
lowercase : Any =temp * ... | 8 | 1 |
'''simple docstring'''
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
SCREA... | 8 |
'''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_ut... | 8 | 1 |
'''simple docstring'''
import enum
import shutil
import sys
SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE = shutil.get_terminal_size()
SCREAMING_SNAKE_CASE = {'UP': 'A', 'DOWN': 'B', 'RIGHT': 'C', 'LEFT': 'D'}
class UpperCAmelCase_ ( enum.Enum ):
"""simple docstring"""
... | 8 |
'''simple docstring'''
from __future__ import annotations
SCREAMING_SNAKE_CASE = 8.988E9 # units = N * m^s * C^-2
def lowercase_ ( __A : float , __A : float , __A : float , __A : float ) -> dict[str, float]:
"""simple do... | 8 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def lowercase_ ( __A : List[str] , __A : int , __A : ... | 8 |
'''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... | 8 | 1 |
'''simple docstring'''
def lowercase_ ( __A : int = 6_0_0_8_5_1_4_7_5_1_4_3 ) -> int:
"""simple docstring"""
try:
lowercase : Any =int(__A )
except (TypeError, ValueError):
raise TypeError('''Parameter n must be int or castable to int.''' )
if n <=... | 8 |
'''simple docstring'''
import mpmath # for roots of unity
import numpy as np
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : List[Any] , UpperCAmelCase : Dict=None , UpperCAmelCase : Optional[int]=None ) -> Optional[Any]:
'''s... | 8 | 1 |
'''simple docstring'''
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, ... | 8 |
'''simple docstring'''
def lowercase_ ( __A : int , __A : int ) -> str:
"""simple docstring"""
if number < 0 or shift_amount < 0:
raise ValueError('''both inputs must be positive integers''' )
lowercase : List[Any] =str(bin(__A ) )
... | 8 | 1 |
'''simple docstring'''
from abc import ABC, abstractmethod
from typing import Optional, Union
from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike
class UpperCAmelCase_ ( __A ):
"""simp... | 8 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (... | 8 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE = {'configuration_vit_msn': ['VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ViTMSNConfig']}
try:
if not is_torch_available():
... | 8 |
'''simple docstring'''
def lowercase_ ( __A : float , __A : int ) -> float:
"""simple docstring"""
if digit_amount > 0:
return round(number - int(__A ) , __A )
return number - int(__A )
if __name__ == "__main__":
print(decimal_i... | 8 | 1 |
'''simple docstring'''
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {'vocab_file': 'vocab.json'}
SCREAMING_SNAKE_CASE = ... | 8 |
'''simple docstring'''
from typing import Dict, Iterable, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import ... | 8 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = [
['attention', 'a... | 8 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, 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_t... | 8 | 1 |
'''simple docstring'''
def lowercase_ ( __A : int ) -> int:
"""simple docstring"""
lowercase : str =[1]
lowercase , lowercase , lowercase : Dict =0, 0, 0
lowercase : List[Any] =ugly_nums[ia] * 2
lowercase : str =ugly_... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_rembert': ['REMBER... | 8 | 1 |
'''simple docstring'''
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_torc... | 8 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
SCREAMING_SNAKE_CASE = parse(importlib.metadata.version('torch'))
def lowercase_ ( __A : Union[str, Version] , ... | 8 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import YolosConfig
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_configuration_common import... | 8 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
SCREAMING_SNAKE_CASE = 'https://www.indeed.co.in/jobs?q=mobile+app+development&l='
def lowercase_ ( __A : str = "mumbai" ) -> ... | 8 | 1 |
'''simple docstring'''
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
SCREAMING_SNAKE_CASE ... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE = {
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
... | 8 | 1 |
'''simple docstring'''
from packaging import version
from .import_utils import is_accelerate_available
if is_accelerate_available():
import accelerate
def lowercase_ ( __A : Dict ) -> Tuple:
"""simple docstring"""
if not is_accelerate_available():
return m... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_mega': ['MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegaConfig', 'MegaOnnxConfig'],
}
try:
if not ... | 8 | 1 |
'''simple docstring'''
def lowercase_ ( __A : int , __A : int , __A : int ) -> float:
"""simple docstring"""
lowercase : Union[str, Any] =(num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for su... | 8 |
'''simple docstring'''
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {'vocab_file':... | 8 | 1 |
'''simple docstring'''
from __future__ import annotations
import queue
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : Optional[int] , UpperCAmelCase : List[str] ) -> Optional[int]:
'''simple docstring'''
lowercase : List[An... | 8 |
'''simple docstring'''
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
@require_torch
def A__ ... | 8 | 1 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {
'asapp/sew-d-tiny-100k': 'https://huggingface.co/asapp/sew-d-tiny-100k/resolve... | 8 |
'''simple docstring'''
SCREAMING_SNAKE_CASE = 'Alexander Joslin'
import operator as op
from .stack import Stack
def lowercase_ ( __A : str ) -> int:
"""simple docstring"""
lowercase : int ={'''*''': op.mul, '''/''': op.truediv, '''+''': op.add, '''-... | 8 | 1 |
'''simple docstring'''
SCREAMING_SNAKE_CASE = {
'a': 'AAAAA',
'b': 'AAAAB',
'c': 'AAABA',
'd': 'AAABB',
'e': 'AABAA',
'f': 'AABAB',
'g': 'AABBA',
'h': 'AABBB',
'i': 'ABAAA',
'j': 'BBBAA',
'k': 'ABAAB',
'l': 'ABABA',
'm': 'ABABB',
'n': 'ABBAA',
'... | 8 |
'''simple docstring'''
import re
def lowercase_ ( __A : str ) -> bool:
"""simple docstring"""
lowercase : Any =re.compile(R'''^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$''' )
if match := re.search(__A , __A ):
return match.string == phone
return F... | 8 | 1 |
'''simple docstring'''
def lowercase_ ( __A : str ) -> Tuple: # noqa: E741
"""simple docstring"""
lowercase : Optional[int] =len(__A )
lowercase : Optional[Any] =0
lowercase : Any =[0] * n
lowercase : List[Any] =[False]... | 8 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, 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_ten... | 8 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
SCREAMING_SNAKE_CASE = 'https://www.indeed.co.in/jobs?q=mobile+app+development&l='
def lowercase_ ( __A : str = "mumbai" ) -> ... | 8 |
'''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 UpperCAmelCase_ ( ... | 8 | 1 |
'''simple docstring'''
# Copyright (c) 2021-, NVIDIA CORPORATION. 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/LICENS... | 8 |
'''simple docstring'''
def lowercase_ ( __A : int = 6_0_0_8_5_1_4_7_5_1_4_3 ) -> int:
"""simple docstring"""
try:
lowercase : Any =int(__A )
except (TypeError, ValueError):
raise TypeError('''Parameter n must be int or castable to int.''' )
if n <=... | 8 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
... | 8 |
'''simple docstring'''
from __future__ import annotations
import math
def lowercase_ ( __A : float , __A : int ) -> float:
"""simple docstring"""
lowercase : str =u
for i in range(1 , __A ):
lowercase : Any =temp * ... | 8 | 1 |
'''simple docstring'''
from math import sqrt
def lowercase_ ( __A : int ) -> bool:
"""simple docstring"""
assert isinstance(__A , __A ) and (
number >= 0
), "'number' must been an int and positive"
lowercase : int =True
# 0 and 1 are n... | 8 |
'''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_ut... | 8 | 1 |
'''simple docstring'''
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlo... | 8 |
'''simple docstring'''
from __future__ import annotations
SCREAMING_SNAKE_CASE = 8.988E9 # units = N * m^s * C^-2
def lowercase_ ( __A : float , __A : float , __A : float , __A : float ) -> dict[str, float]:
"""simple do... | 8 | 1 |
'''simple docstring'''
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
SCREAMING_SNAKE_CASE = 3
def lowercase_ ( __A : int ) -> int:
"""simple docstring"""
print('''Generating primitive root of p''' ... | 8 |
'''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... | 8 | 1 |
'''simple docstring'''
import datasets
from .evaluate import evaluate
SCREAMING_SNAKE_CASE = '\\n@inproceedings{Rajpurkar2016SQuAD10,\n title={SQuAD: 100, 000+ Questions for Machine Comprehension of Text},\n author={Pranav Rajpurkar and Jian Zhang and Konstantin Lopyrev and Percy Liang},\n booktitl... | 8 |
'''simple docstring'''
import mpmath # for roots of unity
import numpy as np
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : List[Any] , UpperCAmelCase : Dict=None , UpperCAmelCase : Optional[int]=None ) -> Optional[Any]:
'''s... | 8 | 1 |
'''simple docstring'''
import os
from pathlib import Path
def lowercase_ ( ) -> str:
"""simple docstring"""
from torch.utils.cpp_extension import load
lowercase : Dict =Path(__A ).resolve().parent.parent.parent / '''kernels''' / '''deformable_detr'''
lowercas... | 8 |
'''simple docstring'''
def lowercase_ ( __A : int , __A : int ) -> str:
"""simple docstring"""
if number < 0 or shift_amount < 0:
raise ValueError('''both inputs must be positive integers''' )
lowercase : List[Any] =str(bin(__A ) )
... | 8 | 1 |
'''simple docstring'''
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class UpperCAmelCase_ ( unittest.TestCase )... | 8 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (... | 8 | 1 |
'''simple docstring'''
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import g... | 8 |
'''simple docstring'''
def lowercase_ ( __A : float , __A : int ) -> float:
"""simple docstring"""
if digit_amount > 0:
return round(number - int(__A ) , __A )
return number - int(__A )
if __name__ == "__main__":
print(decimal_i... | 8 | 1 |
'''simple docstring'''
def lowercase_ ( __A : float ) -> float:
"""simple docstring"""
if edge <= 0 or not isinstance(__A , __A ):
raise ValueError('''Length must be a positive.''' )
return 3 * ((2_5 + 1_0 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)
def... | 8 |
'''simple docstring'''
from typing import Dict, Iterable, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import ... | 8 | 1 |
'''simple docstring'''
import argparse
import datetime
import json
import time
import warnings
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import calculate_ble... | 8 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, 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_t... | 8 | 1 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS_CACHE,
WEIGHTS_NAME... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_rembert': ['REMBER... | 8 | 1 |
'''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/LICENS... | 8 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
SCREAMING_SNAKE_CASE = parse(importlib.metadata.version('torch'))
def lowercase_ ( __A : Union[str, Version] , ... | 8 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_resnet': ['RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ResNe... | 8 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
SCREAMING_SNAKE_CASE = 'https://www.indeed.co.in/jobs?q=mobile+app+development&l='
def lowercase_ ( __A : str = "mumbai" ) -> ... | 8 | 1 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vi... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE = {
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
... | 8 | 1 |
'''simple docstring'''
from __future__ import annotations
SCREAMING_SNAKE_CASE = []
def lowercase_ ( __A : list[list[int]] , __A : int , __A : int ) -> bool:
"""simple docstring"""
for i in range(len(__A ) ):
if board[row][i]... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_mega': ['MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegaConfig', 'MegaOnnxConfig'],
}
try:
if not ... | 8 | 1 |
'''simple docstring'''
import torch
from diffusers import DiffusionPipeline
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
def __init__( self : Any , UpperCAmelCase : Any , UpperCAmelCase : Optional[Any] ) -> str:
'''simple docstring... | 8 |
'''simple docstring'''
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {'vocab_file':... | 8 | 1 |
'''simple docstring'''
import torch
from torch import nn
class UpperCAmelCase_ ( nn.Module ):
"""simple docstring"""
def __init__( self : Union[str, Any] , UpperCAmelCase : Optional[int] , UpperCAmelCase : Tuple , UpperCAmelCase : Union[str,... | 8 |
'''simple docstring'''
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
@require_torch
def A__ ... | 8 | 1 |
'''simple docstring'''
import math
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : str , UpperCAmelCase : int=0 ) -> List[str]: # a graph with Node 0,1,...,N-1
'''simple docstring'''
lowercase : str =n
lowercase ... | 8 |
'''simple docstring'''
SCREAMING_SNAKE_CASE = 'Alexander Joslin'
import operator as op
from .stack import Stack
def lowercase_ ( __A : str ) -> int:
"""simple docstring"""
lowercase : int ={'''*''': op.mul, '''/''': op.truediv, '''+''': op.add, '''-... | 8 | 1 |
'''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 UpperCAmelCase_ :
"""simple docstring"""
def __init__( s... | 8 |
'''simple docstring'''
import re
def lowercase_ ( __A : str ) -> bool:
"""simple docstring"""
lowercase : Any =re.compile(R'''^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$''' )
if match := re.search(__A , __A ):
return match.string == phone
return F... | 8 | 1 |
'''simple docstring'''
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class UpperCAmelCase_ ( __A , ... | 8 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, 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_ten... | 8 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE = {
'configuration_squeezebert': [
'SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SqueezeBertCon... | 8 |
'''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 UpperCAmelCase_ ( ... | 8 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
SCREAMING_SNAKE_CASE = argparse.ArgumentParser(
description=(
'Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Transfer Le... | 8 |
'''simple docstring'''
def lowercase_ ( __A : int = 6_0_0_8_5_1_4_7_5_1_4_3 ) -> int:
"""simple docstring"""
try:
lowercase : Any =int(__A )
except (TypeError, ValueError):
raise TypeError('''Parameter n must be int or castable to int.''' )
if n <=... | 8 | 1 |
'''simple docstring'''
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def lowercase_ ( __A : int , __A : str , __A : str , __A : Union[str, Any] ) -> int:
"""simple docstring"""
lowercase : ... | 8 |
'''simple docstring'''
from __future__ import annotations
import math
def lowercase_ ( __A : float , __A : int ) -> float:
"""simple docstring"""
lowercase : str =u
for i in range(1 , __A ):
lowercase : Any =temp * ... | 8 | 1 |
'''simple docstring'''
import os
def lowercase_ ( __A : str = "matrix.txt" ) -> int:
"""simple docstring"""
with open(os.path.join(os.path.dirname(__A ) , __A ) ) as in_file:
lowercase : Union[str, Any] =in_file.read()
lowercase : ... | 8 |
'''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_ut... | 8 | 1 |
'''simple docstring'''
def lowercase_ ( __A : int , __A : int ) -> int:
"""simple docstring"""
while b:
lowercase , lowercase : Union[str, Any] =b, a % b
return a
def lowercase_ ( __A : int , __A : int ... | 8 |
'''simple docstring'''
from __future__ import annotations
SCREAMING_SNAKE_CASE = 8.988E9 # units = N * m^s * C^-2
def lowercase_ ( __A : float , __A : float , __A : float , __A : float ) -> dict[str, float]:
"""simple do... | 8 | 1 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_... | 8 |
'''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... | 8 | 1 |
'''simple docstring'''
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def lowercase_ ( __A : str , __A : str , **__A : Optional[Any] ) -> List[str]:
"""simple docstring"""
lowercase : int ... | 8 |
'''simple docstring'''
import mpmath # for roots of unity
import numpy as np
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : List[Any] , UpperCAmelCase : Dict=None , UpperCAmelCase : Optional[int]=None ) -> Optional[Any]:
'''s... | 8 | 1 |
'''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... | 8 |
'''simple docstring'''
def lowercase_ ( __A : int , __A : int ) -> str:
"""simple docstring"""
if number < 0 or shift_amount < 0:
raise ValueError('''both inputs must be positive integers''' )
lowercase : List[Any] =str(bin(__A ) )
... | 8 | 1 |
'''simple docstring'''
import argparse
import os
import re
SCREAMING_SNAKE_CASE = 'src/diffusers'
# Pattern that looks at the indentation in a line.
SCREAMING_SNAKE_CASE = re.compile(r'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
SCREAMING_SNAKE_CASE = re.compile(r'^... | 8 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (... | 8 | 1 |
'''simple docstring'''
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_to... | 8 |
'''simple docstring'''
def lowercase_ ( __A : float , __A : int ) -> float:
"""simple docstring"""
if digit_amount > 0:
return round(number - int(__A ) , __A )
return number - int(__A )
if __name__ == "__main__":
print(decimal_i... | 8 | 1 |
'''simple docstring'''
import json
import os
from typing import Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {
'vocab_file': 'vocab.json',
... | 8 |
'''simple docstring'''
from typing import Dict, Iterable, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import ... | 8 | 1 |
'''simple docstring'''
import collections
import inspect
import unittest
from transformers import SwinvaConfig
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_configu... | 8 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, 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_t... | 8 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
def lowercase_ ( __A : float , __A : int ) -> float:
"""simple docstring"""
lowercase : str =u
for i in range(1 , __A ):
lowercase : Any =temp * ... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_rembert': ['REMBER... | 8 | 1 |
'''simple docstring'''
# Copyright 2022 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... | 8 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
SCREAMING_SNAKE_CASE = parse(importlib.metadata.version('torch'))
def lowercase_ ( __A : Union[str, Version] , ... | 8 | 1 |
'''simple docstring'''
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_available():
from PIL import Imag... | 8 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
SCREAMING_SNAKE_CASE = 'https://www.indeed.co.in/jobs?q=mobile+app+development&l='
def lowercase_ ( __A : str = "mumbai" ) -> ... | 8 | 1 |
'''simple docstring'''
def lowercase_ ( __A : int , __A : list ) -> Union[str, Any]:
"""simple docstring"""
_enforce_args(__A , __A )
if n == 0:
return 0
lowercase : List[str] =float('''-inf''' )
for i in range(1 , n... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE = {
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
... | 8 | 1 |
'''simple docstring'''
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..tabl... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_mega': ['MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegaConfig', 'MegaOnnxConfig'],
}
try:
if not ... | 8 | 1 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCAmelCase_ ( __A , un... | 8 |
'''simple docstring'''
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {'vocab_file':... | 8 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDif... | 8 |
'''simple docstring'''
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
@require_torch
def A__ ... | 8 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImag... | 8 |
'''simple docstring'''
SCREAMING_SNAKE_CASE = 'Alexander Joslin'
import operator as op
from .stack import Stack
def lowercase_ ( __A : str ) -> int:
"""simple docstring"""
lowercase : int ={'''*''': op.mul, '''/''': op.truediv, '''+''': op.add, '''-... | 8 | 1 |
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