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 |
|---|---|---|---|---|
from heapq import heappop, heappush
import numpy as np
def __magic_name__ ( __lowerCAmelCase : np.ndarray , __lowerCAmelCase : tuple[int, int] , __lowerCAmelCase : tuple[int, int] , __lowerCAmelCase : bool , ) -> tuple[float | int, list[tuple[int, int]]]:
__lowerCamelCase ... | 270 |
from __future__ import annotations
from statistics import mean
def __magic_name__ ( __lowerCAmelCase : list[int] , __lowerCAmelCase : list[int] , __lowerCAmelCase : int ) -> list[int]:
__lowerCamelCase = [0] * no_of_processes
__lowerCamelCase = [0] * no_of_p... | 270 | 1 |
from string import ascii_uppercase
SCREAMING_SNAKE_CASE__ : Union[str, Any] = {str(ord(c) - 55): c for c in ascii_uppercase}
def __magic_name__ ( __lowerCAmelCase : int , __lowerCAmelCase : int ) -> str:
if isinstance(__lowerCAmelCase , __lowerCAmelCase ):
... | 270 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class lowerCAmelCase__ ( __lowercase ):
@staticmethod
@abstractmethod
def __A ( SCREAMING_SNAKE_CASE__ : ArgumentParser ) -> str:
raise NotImplementedError()
@abstractmethod
def __A... | 270 | 1 |
# Algorithm for the pigeonhole sorting
def __magic_name__ ( __lowerCAmelCase : Union[str, Any] ) -> Tuple:
__lowerCamelCase = min(__lowerCAmelCase ) # min() finds the minimum value
__lowerCamelCase = max(__lowerCAmelCase ) # max() finds the maximum value
... | 270 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingface ... | 270 | 1 |
import numpy as np
def __magic_name__ ( __lowerCAmelCase : np.array ) -> np.array:
return 1 / (1 + np.exp(-vector ))
def __magic_name__ ( __lowerCAmelCase : np.array ) -> np.array:
return vector * sigmoid(1.702 * vector )
if __name__ == "__main__":
... | 270 |
from __future__ import annotations
from fractions import Fraction
def __magic_name__ ( __lowerCAmelCase : int , __lowerCAmelCase : int ) -> bool:
return (
num != den and num % 10 == den // 10 and (num // 10) / (den % 10) == num / den
)
def __magic_name__ ( __lowerCA... | 270 | 1 |
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
SCREAMING_SNAKE_CASE__ : Dict = get_logger(__name__)
SCREAMING_SNAKE_CASE__ : List[str] = r"\n Args:\n input_ids (`... | 270 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
SCREAMING_SNAKE_CASE__ : List[str] = {
"configuration_blip": [
"BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
... | 270 | 1 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import PatchingSpec
from ...tokenizati... | 270 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE__ : Optional[Any] = {"configuration_wavlm": ["WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "WavLMConfig"]}
try:
if not is_torch_available():
raise Opt... | 270 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ : List[Any] = {
"configuration_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConf... | 270 |
import pprint
import requests
SCREAMING_SNAKE_CASE__ : str = "https://zenquotes.io/api"
def __magic_name__ ( ) -> list:
return requests.get(API_ENDPOINT_URL + '''/today''' ).json()
def __magic_name__ ( ) -> list:
return requests.get(API_ENDPOINT_URL + '''/random'... | 270 | 1 |
import os
import time
import numpy as np
import onnxruntime as ort
SCREAMING_SNAKE_CASE__ : Optional[Any] = "1"
SCREAMING_SNAKE_CASE__ : Union[str, Any] = "0"
SCREAMING_SNAKE_CASE__ : int = "1"
SCREAMING_SNAKE_CASE__ : Dict = ort.SessionOption... | 270 |
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def __magic_name__ ( __lowerCAmelCase : int ) -> int:
__lowerCamelCase = prime_factors(__lowerCAmelCase )
if is_square_free(__lowerCAmelCase ):
return -1 if len(__lowe... | 270 | 1 |
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
SCREAMING_SNAKE_CASE__ : Optional[Any] = logging.get_logger(__name__)
class lowerCAmelCase__ ( __lowercase ):
... | 270 |
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
SCREAMING_SNAKE_CASE__ : Union[str, Any] = re.compile(r"\b(a|an|the)\b", re.UNICODE)
SCREAMING_SNAKE_CASE__ : int = None
def __magic_name__ ( ) -> str:
_... | 270 | 1 |
def __magic_name__ ( __lowerCAmelCase : list[list[int | float]] ) -> int:
__lowerCamelCase = len(__lowerCAmelCase )
__lowerCamelCase = len(matrix[0] )
__lowerCamelCase = min(__lowerCAmelCase , __lowerCAmelCase )
for row in range(__lowerCAme... | 270 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subprocess_async,
get_g... | 270 | 1 |
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class lowerCAmelCase__ :
def __init__( self : Any , SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ) -> Dict:
... | 270 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE__ : Dict = {
"facebook/mask2former-swin-small-coco-instance": (
"https://huggingface.co/facebook/m... | 270 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ : int = {
"configuration_roformer": ["ROFORMER_PRETRAINED_CONFI... | 270 |
import os
def __magic_name__ ( ) -> str:
__lowerCamelCase = os.path.join(os.path.dirname(__lowerCAmelCase ) , '''num.txt''' )
with open(__lowerCAmelCase ) as file_hand:
return str(sum(int(__lowerCAmelCase ) for line in file_hand ) )[:10]
if __n... | 270 | 1 |
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxMode... | 270 |
import logging
import os
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
from filelock import FileLock
from transformers import PreTrainedTokenizer, is_tf_available, is_torch_available
SCREAMING_SNAKE_CASE__ : Optional[int] = logging.getLogger(__na... | 270 | 1 |
SCREAMING_SNAKE_CASE__ : List[Any] = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"
def __magic_name__ ( __lowerCAmelCase : bytes ) -> bytes:
# Make sure the supplied data is a bytes-like object
if not isinstance(__lowerCAmelCase , __lowerCAmelCase ... | 270 |
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class lowerCAmelCase__ ( __lowercase ):
def __init__( self : Tuple , SCREA... | 270 | 1 |
import requests
def __magic_name__ ( __lowerCAmelCase : str , __lowerCAmelCase : str ) -> None:
__lowerCamelCase = {'''Content-Type''': '''application/json'''}
__lowerCamelCase = requests.post(__lowerCAmelCase , json={'''text''': message_body} , headers=__lowerC... | 270 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0")):
raise OptionalDependencyNotAvailable()
except... | 270 | 1 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SegformerConfig,
SegformerForImageClassification,
SegformerForSemanticSegmentation,
Segfor... | 270 |
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
SCREAMING_SNAKE_CASE__ : Union[str, Any] = "\\n@inproceedings{popovic-2015-chrf,\n title = \"chr{F}: character n-gram {F}-score for automatic {MT} evaluation\",\n author = \"Popovi{\'c}, Maja\",\... | 270 | 1 |
def __magic_name__ ( __lowerCAmelCase : str , __lowerCAmelCase : str ) -> str:
if not (isinstance(__lowerCAmelCase , __lowerCAmelCase ) and isinstance(__lowerCAmelCase , __lowerCAmelCase )):
raise ValueError('''longest_common_substring() takes two strings for input... | 270 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ : List[Any] = {
"configuration_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConf... | 270 | 1 |
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import Con... | 270 |
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
... | 270 | 1 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusionPanoramaPipeline,
UNet... | 270 |
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from transformers.testing_utils import r... | 270 | 1 |
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def _a ( *a :Optional[Any] , a :Optional[Union[Dict, Any]] = None , a :List[str]=True , a :List[str]=2 ) -> int:
from .. import __version__
a = ... | 0 |
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class lowerCAmelCase__ :
def __init__( self : Any , SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ) -> Dict:
... | 270 | 0 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
class __A ( UpperCamelCase__ ):
a__ : Dict = ["""image_processor""", """feature_extractor"""]
a__ : List[str] = """TvltImageProcessor"""
a__ : Tuple = """... | 1 |
from queue import PriorityQueue
from typing import Any
import numpy as np
def __magic_name__ ( __lowerCAmelCase : dict , __lowerCAmelCase : str , __lowerCAmelCase : set , __lowerCAmelCase : set , __lowerCAmelCase : dict , __lowerCAmelCase : dict , __lowerCAmelCase : ... | 270 | 0 |
'''simple docstring'''
def _SCREAMING_SNAKE_CASE (A = 1_000 ) -> int:
"""simple docstring"""
return sum(e for e in range(3 , A ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(f"""{solution() = }""")
| 2 |
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
SCREAMING_SNAKE_CASE__ : List[Any] = TypeVar("T")
def __magic_name__ ( __lowerCAmelCase : int ) -> int:
return (position - 1) // 2
def __magic_name__ ( __lowerCAmelCase : ... | 270 | 0 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase_ ( snake_case__ , snake_case__ ):
'''simple docstring'''
if len(snake_case__ ) < k or k < 0:
raise ValueError('''Invalid Input''' )
A : Any =... | 3 |
from __future__ import annotations
from statistics import mean
def __magic_name__ ( __lowerCAmelCase : list[int] , __lowerCAmelCase : list[int] , __lowerCAmelCase : int ) -> list[int]:
__lowerCamelCase = [0] * no_of_processes
__lowerCamelCase = [0] * no_of_p... | 270 | 0 |
'''simple docstring'''
def a_ ( lowerCamelCase : str ):
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 4 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class lowerCAmelCase__ ( __lowercase ):
@staticmethod
@abstractmethod
def __A ( SCREAMING_SNAKE_CASE__ : ArgumentParser ) -> str:
raise NotImplementedError()
@abstractmethod
def __A... | 270 | 0 |
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class lowerCamelCase__ :
def __init__(self , UpperCAmelCase , UpperCAmelCase=sys.... | 5 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingface ... | 270 | 0 |
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class __A( nn.Module ):
def __init__( self , _snake_case = 16 , _snake_case = 88 , _snake_case = None , _snake_case = 1 , _snake_case = 0.0 , ... | 6 |
from __future__ import annotations
from fractions import Fraction
def __magic_name__ ( __lowerCAmelCase : int , __lowerCAmelCase : int ) -> bool:
return (
num != den and num % 10 == den // 10 and (num // 10) / (den % 10) == num / den
)
def __magic_name__ ( __lowerCA... | 270 | 0 |
def _snake_case( SCREAMING_SNAKE_CASE__ : str ) -> Dict:
'''simple docstring'''
A__ = []
A__ = []
A__ = {
'^': 3,
'*': 2,
'/': 2,
'%': 2,
'+': 1,
'-': 1,
}... | 7 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
SCREAMING_SNAKE_CASE__ : List[str] = {
"configuration_blip": [
"BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
... | 270 | 0 |
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class snake_case_ ( nn.Module ):
'''simple docstring'''
def __init__( self : Dict , _UpperCamelCase : int = 1_6 , _Uppe... | 8 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE__ : Optional[Any] = {"configuration_wavlm": ["WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "WavLMConfig"]}
try:
if not is_torch_available():
raise Opt... | 270 | 0 |
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
import sqlitea
im... | 9 |
import pprint
import requests
SCREAMING_SNAKE_CASE__ : str = "https://zenquotes.io/api"
def __magic_name__ ( ) -> list:
return requests.get(API_ENDPOINT_URL + '''/today''' ).json()
def __magic_name__ ( ) -> list:
return requests.get(API_ENDPOINT_URL + '''/random'... | 270 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"google/pix2struct-textcaps-base": (
"https://huggingface.co/google/pix2struct-textcaps-base/resolve/main... | 10 |
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def __magic_name__ ( __lowerCAmelCase : int ) -> int:
__lowerCamelCase = prime_factors(__lowerCAmelCase )
if is_square_free(__lowerCAmelCase ):
return -1 if len(__lowe... | 270 | 0 |
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_torch_available
from transformers.testing_utils import require_torch, torch_device
if is_torch_available():
from transformers import PyTorchBenchmark, PyTorchBenchmarkArguments
@require_torch
clas... | 11 |
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
SCREAMING_SNAKE_CASE__ : Union[str, Any] = re.compile(r"\b(a|an|the)\b", re.UNICODE)
SCREAMING_SNAKE_CASE__ : int = None
def __magic_name__ ( ) -> str:
_... | 270 | 0 |
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_images, to_numpy_array, vali... | 12 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subprocess_async,
get_g... | 270 | 0 |
import warnings
from functools import wraps
from typing import Callable
def A_ ( _UpperCAmelCase ):
@wraps(_UpperCAmelCase )
def _inner_fn(*_UpperCAmelCase , **_UpperCAmelCase ):
warnings.warn(
(f"'{fn.__name__}' is experimental and might be subje... | 13 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE__ : Dict = {
"facebook/mask2former-swin-small-coco-instance": (
"https://huggingface.co/facebook/m... | 270 | 0 |
from __future__ import annotations
from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class UpperCamelCase_ :
'''simple docstring'''
UpperCAmelCase__ = 42
UpperCAmelCase__ = No... | 14 |
import os
def __magic_name__ ( ) -> str:
__lowerCamelCase = os.path.join(os.path.dirname(__lowerCAmelCase ) , '''num.txt''' )
with open(__lowerCAmelCase ) as file_hand:
return str(sum(int(__lowerCAmelCase ) for line in file_hand ) )[:10]
if __n... | 270 | 0 |
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
SCREAMING_... | 15 |
import logging
import os
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
from filelock import FileLock
from transformers import PreTrainedTokenizer, is_tf_available, is_torch_available
SCREAMING_SNAKE_CASE__ : Optional[int] = logging.getLogger(__na... | 270 | 0 |
"""simple docstring"""
def __UpperCAmelCase ( __lowerCamelCase ) -> float:
lowercase__ : Optional[int] = 0
while len(__lowerCamelCase ) > 1:
lowercase__ : Optional[int] = 0
# Consider two files with minimum cost to be merged
for _ i... | 16 |
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class lowerCAmelCase__ ( __lowercase ):
def __init__( self : Tuple , SCREA... | 270 | 0 |
"""simple docstring"""
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class _lowerCAmelCase ( lowercase ):
"""simple docstring"""
__UpperCAmelCase : str = (EulerDiscreteSched... | 17 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0")):
raise OptionalDependencyNotAvailable()
except... | 270 | 0 |
def _snake_case ( lowerCAmelCase : Tuple ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Dict = 1
SCREAMING_SNAKE_CASE_ : Optional[Any] = 2
while i * i <= n:
SCREAMING_SNAKE_CASE_ : Optional[Any] = 0
while n % i == 0:
n //= i
... | 18 |
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
SCREAMING_SNAKE_CASE__ : Union[str, Any] = "\\n@inproceedings{popovic-2015-chrf,\n title = \"chr{F}: character n-gram {F}-score for automatic {MT} evaluation\",\n author = \"Popovi{\'c}, Maja\",\... | 270 | 0 |
import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse('''9.1.0'''):
__A ={
'''linear''': PIL.Image.Resampling.BILINEAR,
'''bilinear''': PIL.Image.Resampling.BILINEAR,
'''bicubi... | 19 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ : List[Any] = {
"configuration_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConf... | 270 | 0 |
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class __snake_case :
_a : int
_a : TreeNode | None= None
_a : TreeNode | None= None
lowercase : Dict = namedtuple("""CoinsDistribResult""",... | 20 |
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
... | 270 | 0 |
from __future__ import annotations
import time
import numpy as np
SCREAMING_SNAKE_CASE : Optional[Any] = [8, 5, 9, 7]
SCREAMING_SNAKE_CASE : int = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
SCREAMING_SNAKE_CASE : ... | 21 |
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from transformers.testing_utils import r... | 270 | 0 |
'''simple docstring'''
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s''',
datefmt='''%m/%d/%Y %H:%M:%S''',
level=logging.INFO,
)
__SCREAMING_SNA... | 22 |
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class lowerCAmelCase__ :
def __init__( self : Any , SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ) -> Dict:
... | 270 | 0 |
'''simple docstring'''
import datasets
UpperCamelCase__: Tuple = "\\n@InProceedings{conneau2018xnli,\n author = \"Conneau, Alexis\n and Rinott, Ruty\n and Lample, Guillaume\n and Williams, Adina\n and Bowman, Samuel R.... | 23 |
from queue import PriorityQueue
from typing import Any
import numpy as np
def __magic_name__ ( __lowerCAmelCase : dict , __lowerCAmelCase : str , __lowerCAmelCase : set , __lowerCAmelCase : set , __lowerCAmelCase : dict , __lowerCAmelCase : dict , __lowerCAmelCase : ... | 270 | 0 |
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.numpy as jnp
from jax imp... | 24 |
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
SCREAMING_SNAKE_CASE__ : List[Any] = TypeVar("T")
def __magic_name__ ( __lowerCAmelCase : int ) -> int:
return (position - 1) // 2
def __magic_name__ ( __lowerCAmelCase : ... | 270 | 0 |
"""simple docstring"""
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import DiffusionPipeline
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pip... | 25 |
from __future__ import annotations
from statistics import mean
def __magic_name__ ( __lowerCAmelCase : list[int] , __lowerCAmelCase : list[int] , __lowerCAmelCase : int ) -> list[int]:
__lowerCamelCase = [0] * no_of_processes
__lowerCamelCase = [0] * no_of_p... | 270 | 0 |
import random
def lowerCAmelCase_ ( snake_case_ ):
_A : Optional[Any] = num - 1
_A : Optional[int] = 0
while s % 2 == 0:
_A : str = s // 2
t += 1
for _ in range(5 ):
_A : ... | 26 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class lowerCAmelCase__ ( __lowercase ):
@staticmethod
@abstractmethod
def __A ( SCREAMING_SNAKE_CASE__ : ArgumentParser ) -> str:
raise NotImplementedError()
@abstractmethod
def __A... | 270 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase : int = logging.get_logger(__name__)
__lowercase : Optional[Any] = {
'microsoft/trocr-base-handwritten': (
'https://huggingface.co/microsoft/trocr-base-handwritt... | 27 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingface ... | 270 | 0 |
'''simple docstring'''
import math
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 SchedulerMix... | 28 |
from __future__ import annotations
from fractions import Fraction
def __magic_name__ ( __lowerCAmelCase : int , __lowerCAmelCase : int ) -> bool:
return (
num != den and num % 10 == den // 10 and (num // 10) / (den % 10) == num / den
)
def __magic_name__ ( __lowerCA... | 270 | 0 |
def lowercase__ ( __snake_case : int = 4_000_000 ):
'''simple docstring'''
UpperCAmelCase_ : int = [0, 1]
UpperCAmelCase_ : List[str] = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
... | 29 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
SCREAMING_SNAKE_CASE__ : List[str] = {
"configuration_blip": [
"BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
... | 270 | 0 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('>=', '4.25.0')):
raise OptionalDependencyNotAvai... | 30 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE__ : Optional[Any] = {"configuration_wavlm": ["WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "WavLMConfig"]}
try:
if not is_torch_available():
raise Opt... | 270 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : int = {}
try:
if not is_sentencepiece_available():
... | 31 |
import pprint
import requests
SCREAMING_SNAKE_CASE__ : str = "https://zenquotes.io/api"
def __magic_name__ ( ) -> list:
return requests.get(API_ENDPOINT_URL + '''/today''' ).json()
def __magic_name__ ( ) -> list:
return requests.get(API_ENDPOINT_URL + '''/random'... | 270 | 0 |
from __future__ import annotations
import math
def SCREAMING_SNAKE_CASE_ ( __A : int ) -> list[int]:
"""simple docstring"""
if num <= 0:
a_ : str = F"""{num}: Invalid input, please enter a positive integer."""
rais... | 32 |
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def __magic_name__ ( __lowerCAmelCase : int ) -> int:
__lowerCamelCase = prime_factors(__lowerCAmelCase )
if is_square_free(__lowerCAmelCase ):
return -1 if len(__lowe... | 270 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
__A : Dict = logging.get_logger(__name__)
class _UpperCAmelCase ( _A ):
def __init__( self : ... | 33 |
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
SCREAMING_SNAKE_CASE__ : Union[str, Any] = re.compile(r"\b(a|an|the)\b", re.UNICODE)
SCREAMING_SNAKE_CASE__ : int = None
def __magic_name__ ( ) -> str:
_... | 270 | 0 |
'''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... | 34 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subprocess_async,
get_g... | 270 | 0 |
'''simple docstring'''
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be che... | 35 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE__ : Dict = {
"facebook/mask2former-swin-small-coco-instance": (
"https://huggingface.co/facebook/m... | 270 | 0 |
_snake_case = [
(1000, "M"),
(900, "CM"),
(500, "D"),
(400, "CD"),
(100, "C"),
(90, "XC"),
(50, "L"),
(40, "XL"),
(10, "X"),
(9, "IX"),
(5, "V"),
(4, "IV"),
(1, "I"),
]
def A ( _lowerCamelCase ):
'''simple docstring'''
_l... | 36 |
import os
def __magic_name__ ( ) -> str:
__lowerCamelCase = os.path.join(os.path.dirname(__lowerCAmelCase ) , '''num.txt''' )
with open(__lowerCAmelCase ) as file_hand:
return str(sum(int(__lowerCAmelCase ) for line in file_hand ) )[:10]
if __n... | 270 | 0 |
'''simple docstring'''
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
'''vocab_file''': '... | 37 |
import logging
import os
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
from filelock import FileLock
from transformers import PreTrainedTokenizer, is_tf_available, is_torch_available
SCREAMING_SNAKE_CASE__ : Optional[int] = logging.getLogger(__na... | 270 | 0 |
from math import isqrt
def SCREAMING_SNAKE_CASE_ ( __magic_name__ : int ) -> bool:
"""simple docstring"""
return all(number % divisor != 0 for divisor in range(2 , isqrt(__magic_name__ ) + 1 ) )
def SCREAMING_SNAKE_CASE_ ( __magic_name__ : ... | 38 |
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class lowerCAmelCase__ ( __lowercase ):
def __init__( self : Tuple , SCREA... | 270 | 0 |
import random
from typing import Any
def __A ( __lowerCAmelCase )-> list[Any]:
"""simple docstring"""
for _ in range(len(__lowerCAmelCase ) ):
_UpperCAmelCase = random.randint(0 , len(__lowerCAmelCase ) - 1 )
_UpperCAmelCase... | 39 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0")):
raise OptionalDependencyNotAvailable()
except... | 270 | 0 |
"""simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import... | 40 |
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
SCREAMING_SNAKE_CASE__ : Union[str, Any] = "\\n@inproceedings{popovic-2015-chrf,\n title = \"chr{F}: character n-gram {F}-score for automatic {MT} evaluation\",\n author = \"Popovi{\'c}, Maja\",\... | 270 | 0 |
'''simple docstring'''
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def SCREAMING_SNAKE_CASE_ (UpperCamelCase ) -> Tuple:
lowerCamelCase... | 41 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ : List[Any] = {
"configuration_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConf... | 270 | 0 |
'''simple docstring'''
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
lowercase : Optional[Any] = False
class __... | 42 |
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
... | 270 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__lowercase = {'''configuration_xglm''': ['''XGLM_PRETRAINED_CONFI... | 43 |
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from transformers.testing_utils import r... | 270 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, i... | 44 |
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class lowerCAmelCase__ :
def __init__( self : Any , SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ) -> Dict:
... | 270 | 0 |
"""simple docstring"""
import argparse
import json
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_... | 45 |
from queue import PriorityQueue
from typing import Any
import numpy as np
def __magic_name__ ( __lowerCAmelCase : dict , __lowerCAmelCase : str , __lowerCAmelCase : set , __lowerCAmelCase : set , __lowerCAmelCase : dict , __lowerCAmelCase : dict , __lowerCAmelCase : ... | 270 | 0 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_visio... | 46 |
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
SCREAMING_SNAKE_CASE__ : List[Any] = TypeVar("T")
def __magic_name__ ( __lowerCAmelCase : int ) -> int:
return (position - 1) // 2
def __magic_name__ ( __lowerCAmelCase : ... | 270 | 0 |
'''simple docstring'''
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
lowerCamelCase : List[Any] = "\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained ... | 47 |
from __future__ import annotations
from statistics import mean
def __magic_name__ ( __lowerCAmelCase : list[int] , __lowerCAmelCase : list[int] , __lowerCAmelCase : int ) -> list[int]:
__lowerCamelCase = [0] * no_of_processes
__lowerCamelCase = [0] * no_of_p... | 270 | 0 |
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
fr... | 48 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class lowerCAmelCase__ ( __lowercase ):
@staticmethod
@abstractmethod
def __A ( SCREAMING_SNAKE_CASE__ : ArgumentParser ) -> str:
raise NotImplementedError()
@abstractmethod
def __A... | 270 | 0 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__snake_case :int = logging.get_logger(__name__)
__snake_case :List[Any] = ... | 49 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingface ... | 270 | 0 |
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F401
from ..controlnet.pipeline_controlnet i... | 50 |
from __future__ import annotations
from fractions import Fraction
def __magic_name__ ( __lowerCAmelCase : int , __lowerCAmelCase : int ) -> bool:
return (
num != den and num % 10 == den // 10 and (num // 10) / (den % 10) == num / den
)
def __magic_name__ ( __lowerCA... | 270 | 0 |
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
@require_... | 51 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
SCREAMING_SNAKE_CASE__ : List[str] = {
"configuration_blip": [
"BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
... | 270 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowerCamelCase : Union[str, Any] = {
"""configuration_tapas""": ["""TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TapasConfig"""],
"""tokenization_tapas"... | 52 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE__ : Optional[Any] = {"configuration_wavlm": ["WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "WavLMConfig"]}
try:
if not is_torch_available():
raise Opt... | 270 | 0 |
'''simple docstring'''
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
a__ : str =[
'''Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell ph... | 53 |
import pprint
import requests
SCREAMING_SNAKE_CASE__ : str = "https://zenquotes.io/api"
def __magic_name__ ( ) -> list:
return requests.get(API_ENDPOINT_URL + '''/today''' ).json()
def __magic_name__ ( ) -> list:
return requests.get(API_ENDPOINT_URL + '''/random'... | 270 | 0 |
"""simple docstring"""
from __future__ import annotations
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ = None , lowerCAmelCase_ = None ):
'''simple docstring'''
if start is None:
__SCREAMING_SNAKE_CASE = 0
if end is None:
... | 54 |
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def __magic_name__ ( __lowerCAmelCase : int ) -> int:
__lowerCamelCase = prime_factors(__lowerCAmelCase )
if is_square_free(__lowerCAmelCase ):
return -1 if len(__lowe... | 270 | 0 |
'''simple docstring'''
from abc import ABC, abstractmethod
from typing import List, Optional
class snake_case ( lowercase ):
"""simple docstring"""
def __init__( self ):
"""simple docstring"""
# test for the above condition
self.... | 55 |
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
SCREAMING_SNAKE_CASE__ : Union[str, Any] = re.compile(r"\b(a|an|the)\b", re.UNICODE)
SCREAMING_SNAKE_CASE__ : int = None
def __magic_name__ ( ) -> str:
_... | 270 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase ) -> int:
'''simple docstring'''
if depth < 0:
raise ValueError('''Depth cannot... | 56 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subprocess_async,
get_g... | 270 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
A : int = logging.get_logger(__name__)
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
def __init__( self , *__a , ... | 57 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE__ : Dict = {
"facebook/mask2former-swin-small-coco-instance": (
"https://huggingface.co/facebook/m... | 270 | 0 |
'''simple docstring'''
def lowerCamelCase ( __lowerCamelCase : int = 400_0000 ) ->int:
_SCREAMING_SNAKE_CASE = [0, 1]
_SCREAMING_SNAKE_CASE = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if fib[i + 2] > n:
break
i... | 58 |
import os
def __magic_name__ ( ) -> str:
__lowerCamelCase = os.path.join(os.path.dirname(__lowerCAmelCase ) , '''num.txt''' )
with open(__lowerCAmelCase ) as file_hand:
return str(sum(int(__lowerCAmelCase ) for line in file_hand ) )[:10]
if __n... | 270 | 0 |
import argparse
from collections import defaultdict
import yaml
__lowerCamelCase = """docs/source/en/_toctree.yml"""
def UpperCamelCase ( __lowerCamelCase : Optional[Any] ):
snake_case : Any = defaultdict(__lowerCamelCase )
snake_case ... | 59 |
import logging
import os
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
from filelock import FileLock
from transformers import PreTrainedTokenizer, is_tf_available, is_torch_available
SCREAMING_SNAKE_CASE__ : Optional[int] = logging.getLogger(__na... | 270 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...... | 60 |
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class lowerCAmelCase__ ( __lowercase ):
def __init__( self : Tuple , SCREA... | 270 | 0 |
"""simple docstring"""
def __a ( __lowerCamelCase, __lowerCamelCase ):
return price * (1 + tax_rate)
if __name__ == "__main__":
print(f"""{price_plus_tax(100, 0.25) = }""")
print(f"""{price_plus_tax(125.50, 0.05) = }""")
| 61 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0")):
raise OptionalDependencyNotAvailable()
except... | 270 | 0 |
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
_A = collections.namedtuple('_Datasets', ['train', 'validation', 'test'... | 62 |
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
SCREAMING_SNAKE_CASE__ : Union[str, Any] = "\\n@inproceedings{popovic-2015-chrf,\n title = \"chr{F}: character n-gram {F}-score for automatic {MT} evaluation\",\n author = \"Popovi{\'c}, Maja\",\... | 270 | 0 |
'''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 __SCREAMING_SNAKE_CASE (lowerCam... | 63 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ : List[Any] = {
"configuration_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConf... | 270 | 0 |
"""simple docstring"""
# Copyright 2023 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/... | 64 |
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
... | 270 | 0 |
import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
UpperCamelCase__ = np.linspace(start=0, stop=7_5, num=7_5, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any membership function
... | 65 |
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from transformers.testing_utils import r... | 270 | 0 |
"""simple docstring"""
from __future__ import annotations
import copy
import inspect
import json
import math
import os
import tempfile
import unittest
from importlib import import_module
import numpy as np
from transformers import ViTMAEConfig
from transformers.file_utils import cached_property, is_tf_available,... | 66 |
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class lowerCAmelCase__ :
def __init__( self : Any , SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ) -> Dict:
... | 270 | 0 |
'''simple docstring'''
import os
__UpperCAmelCase ={"I": 1, "V": 5, "X": 1_0, "L": 5_0, "C": 1_0_0, "D": 5_0_0, "M": 1_0_0_0}
def __lowerCAmelCase ( UpperCamelCase__ ) -> int:
__lowerCamelCase = 0
__lowerCamelCase = 0
while index < len(UpperCamelCase__ ) - 1:
... | 67 |
from queue import PriorityQueue
from typing import Any
import numpy as np
def __magic_name__ ( __lowerCAmelCase : dict , __lowerCAmelCase : str , __lowerCAmelCase : set , __lowerCAmelCase : set , __lowerCAmelCase : dict , __lowerCAmelCase : dict , __lowerCAmelCase : ... | 270 | 0 |
import json
import os
import shutil
import tempfile
import unittest
from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils import cached_property
from ...test_toke... | 68 |
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
SCREAMING_SNAKE_CASE__ : List[Any] = TypeVar("T")
def __magic_name__ ( __lowerCAmelCase : int ) -> int:
return (position - 1) // 2
def __magic_name__ ( __lowerCAmelCase : ... | 270 | 0 |
"""simple docstring"""
from __future__ import annotations
class UpperCamelCase :
def __init__( self, lowerCAmelCase__, lowerCAmelCase__) -> str:
snake_case_ , snake_case_ = text, pattern
snake_case_ , snake_case_ ... | 69 |
from __future__ import annotations
from statistics import mean
def __magic_name__ ( __lowerCAmelCase : list[int] , __lowerCAmelCase : list[int] , __lowerCAmelCase : int ) -> list[int]:
__lowerCamelCase = [0] * no_of_processes
__lowerCamelCase = [0] * no_of_p... | 270 | 0 |
'''simple docstring'''
# XXX: we want transformers master here - in the absense of conftest manipulating sys.path:
# hack it in for now:
import sys
from pathlib import Path
A__ : Dict =Path(__file__).resolve().parents[3] / '''src'''
sys.path.insert(1, str(git_repo_path))
i... | 70 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class lowerCAmelCase__ ( __lowercase ):
@staticmethod
@abstractmethod
def __A ( SCREAMING_SNAKE_CASE__ : ArgumentParser ) -> str:
raise NotImplementedError()
@abstractmethod
def __A... | 270 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import AutoencoderKL, DDIMSchedule... | 71 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingface ... | 270 | 0 |
"""simple docstring"""
import unittest
from transformers import XLMConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common... | 72 |
from __future__ import annotations
from fractions import Fraction
def __magic_name__ ( __lowerCAmelCase : int , __lowerCAmelCase : int ) -> bool:
return (
num != den and num % 10 == den // 10 and (num // 10) / (den % 10) == num / den
)
def __magic_name__ ( __lowerCA... | 270 | 0 |
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
a =datasets.utils.logging.get_logger(__name__)
@dataclass
class A_ ( datasets.Build... | 73 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
SCREAMING_SNAKE_CASE__ : List[str] = {
"configuration_blip": [
"BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
... | 270 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class lowerCAmelCase_ ( metaclass=_lowercase ):
'''simple docstring'''
_lowerCamelCase: int = ['''torch''']
def __init__( self : Union[str, Any] ,*A_ : Tuple ,**A_ : ... | 74 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE__ : Optional[Any] = {"configuration_wavlm": ["WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "WavLMConfig"]}
try:
if not is_torch_available():
raise Opt... | 270 | 0 |
'''simple docstring'''
import itertools
import math
def a_ ( __snake_case : int ) -> bool:
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 =... | 75 |
import pprint
import requests
SCREAMING_SNAKE_CASE__ : str = "https://zenquotes.io/api"
def __magic_name__ ( ) -> list:
return requests.get(API_ENDPOINT_URL + '''/today''' ).json()
def __magic_name__ ( ) -> list:
return requests.get(API_ENDPOINT_URL + '''/random'... | 270 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import (
DiffusionPipeline,
UnCLIPImage... | 76 |
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def __magic_name__ ( __lowerCAmelCase : int ) -> int:
__lowerCamelCase = prime_factors(__lowerCAmelCase )
if is_square_free(__lowerCAmelCase ):
return -1 if len(__lowe... | 270 | 0 |
"""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_utils i... | 77 |
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
SCREAMING_SNAKE_CASE__ : Union[str, Any] = re.compile(r"\b(a|an|the)\b", re.UNICODE)
SCREAMING_SNAKE_CASE__ : int = None
def __magic_name__ ( ) -> str:
_... | 270 | 0 |
"""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 TFModelTesterM... | 78 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subprocess_async,
get_g... | 270 | 0 |
'''simple docstring'''
from __future__ import annotations
def __lowercase ( __lowercase , __lowercase = None , __lowercase = None ) -> None:
'''simple docstring'''
if start is None:
_A = 0
if end is None:
_A = len... | 79 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE__ : Dict = {
"facebook/mask2former-swin-small-coco-instance": (
"https://huggingface.co/facebook/m... | 270 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
a__ : Dict = {
'google/tapas-base-finetuned-sqa': (
'https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'
),
'google/tapas-base-finetuned-wtq': (
'https://hugg... | 80 |
import os
def __magic_name__ ( ) -> str:
__lowerCamelCase = os.path.join(os.path.dirname(__lowerCAmelCase ) , '''num.txt''' )
with open(__lowerCAmelCase ) as file_hand:
return str(sum(int(__lowerCAmelCase ) for line in file_hand ) )[:10]
if __n... | 270 | 0 |
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