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 collections.abc import Generator
from math import sin
def UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
if len(lowerCAmelCase__ ) != 32:
raise ValueError('''Input must be of length 32''' )
lowercase = B''''''
for i in [3, 2, 1, 0]:
... | 101 | """simple docstring"""
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUES,
ENV_VARS... | 77 | 0 |
"""simple docstring"""
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECOR... | 102 | """simple docstring"""
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils impor... | 77 | 0 |
from math import factorial
A__ : str = {str(d): factorial(d) for d in range(10)}
def UpperCamelCase( __UpperCamelCase : int ):
return sum(DIGIT_FACTORIAL[d] for d in str(__UpperCamelCase ) )
def UpperCamelCase( ):
lowerCAmelCase_ : str = 7 * factorial(9 ) + 1
ret... | 103 | """simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling... | 77 | 0 |
'''simple docstring'''
import argparse
import json
import logging
import os
import sys
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, get_gpu_count, slow
lowerCAmelCase__ = [
os.path.join(os.path.dirname(__file__), dirname)
for dirname in [
'''t... | 104 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase : Tuple = logging.get_logger(__name__)
_UpperCamelCase : Union[str, Any] = {
"alibaba-damo/mgp-str-base": "https://huggingface.co/alibaba-damo/mgp-str-base/re... | 77 | 0 |
"""simple docstring"""
from collections.abc import Callable
class __UpperCamelCase :
def __init__( self , lowerCAmelCase__ = None ) -> None:
# Stores actual heap items.
a : list = []
# Stores indexes of each item... | 105 | """simple docstring"""
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def a_ ( _lowerCAmelCase : Tuple , _lowerCAmelCase : Optional[int] , _lo... | 77 | 0 |
"""simple docstring"""
def __SCREAMING_SNAKE_CASE ( A_ , A_ ):
while second != 0:
lowerCAmelCase__ : Tuple = first & second
first ^= second
lowerCAmelCase__ : Union[str, Any] = c << 1
return first
if __name__ == "__main__":
import doctest
doctest.test... | 106 | """simple docstring"""
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
... | 77 | 0 |
from __future__ import annotations
import unittest
from transformers import DebertaVaConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
... | 107 | """simple docstring"""
import math
import flax.linen as nn
import jax.numpy as jnp
def a_ ( _lowerCAmelCase : jnp.ndarray , _lowerCAmelCase : int , _lowerCAmelCase : float = 1 , _lowerCAmelCase : float = 1 , _lowerCAmelCase : float = 1.0E4 , _lowerCAmelCase : bool = False , _lo... | 77 | 0 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def a__ ( SCREAMING_SNAKE_CASE : Tuple ):
'''si... | 108 | """simple docstring"""
from __future__ import annotations
import math
from collections.abc import Callable
def a_ ( _lowerCAmelCase : Callable[[int | float], int | float] , _lowerCAmelCase : int | float , _lowerCAmelCase : int | float , _lowerCAmelCase : int = 100 , ):
''... | 77 | 0 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
A: str = logging.get_logger(__name__)
A: Tuple = {
"CarlCochet/trajectory-transformer-halfcheetah-medium-v2": (
"https://huggingface.co/CarlCochet/trajectory-transformer-halfc... | 109 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCamelCase : Tuple = {
"configuration_whisper": ["WHISPER... | 77 | 0 |
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 _a ( UpperCamelCase__ , UpperCame... | 110 | """simple docstring"""
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def a_ ( _lowerCAmelCase : str ):
'''simple docstring'''
lowercase__ : int = args.pruning_method
... | 77 | 0 |
"""simple docstring"""
import os
import pytest
from attr import dataclass
__UpperCamelCase : Any = "us-east-1" # defaults region
@dataclass
class SCREAMING_SNAKE_CASE :
"""simple docstring"""
lowercase__ = 42
lowercase__ = "arn:aws... | 106 | """simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import (
BaseOutput,
OptionalDependencyNotAvailable,
is_flax_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_... | 77 | 0 |
from __future__ import annotations
from scipy.special import comb # type: ignore
class SCREAMING_SNAKE_CASE__ :
"""simple docstring"""
def __init__( self , SCREAMING_SNAKE_CASE_ )-> Any:
'''simple docstring'''
__UpperCamelCase =... | 328 | """simple docstring"""
import pickle
import numpy as np
from matplotlib import pyplot as plt
class UpperCAmelCase_ :
def __init__( self , a , a , a , a , a , a=0.2 , a=0.2 ) -> Dict:
lowercase__ : Any = bp_numa
lowercase__ ... | 77 | 0 |
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data import Dataset
from transfo... | 118 | """simple docstring"""
from collections.abc import Generator
def a_ ( ):
'''simple docstring'''
lowercase__ , lowercase__ : List[str] = 0, 1
while True:
lowercase__ , lowercase__ : Optional[int] = b, a + b
yi... | 77 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"alibaba-damo/mgp-str-base": "https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json",
}
class __snake... | 290 | """simple docstring"""
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class UpperCAmelCase_ :
def __init__( self , a ) -> List[str]:
if isinstance(a ... | 77 | 0 |
from timeit import timeit
def SCREAMING_SNAKE_CASE__ ( _UpperCAmelCase ) -> Optional[int]:
'''simple docstring'''
if number < 0:
raise ValueError('the value of input must not be negative' )
lowerCAmelCase : Any = 0
while number:
number &= number - 1... | 138 | """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 Image
... | 77 | 0 |
import argparse
import gc
import json
import os
import shutil
import warnings
import torch
from transformers import LlamaConfig, LlamaForCausalLM, LlamaTokenizer
try:
from transformers import LlamaTokenizerFast
except ImportError as e:
warnings.warn(e)
warnings.warn(
'''The converted tokenizer will b... | 5 | """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 PaddingSt... | 77 | 0 |
from __future__ import annotations
def __lowerCAmelCase ( a__ , a__ , a__ , ) -> Optional[Any]:
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError('''You cannot supply more or less than 2 values''' )
elif electron_conc < 0:
... | 6 | """simple docstring"""
_UpperCamelCase : Union[str, Any] = 8.3_1_4_4_5_9_8
def a_ ( _lowerCAmelCase : float , _lowerCAmelCase : float ):
'''simple docstring'''
if temperature < 0:
raise Exception('Temperature cannot be less than 0 K' )
... | 77 | 0 |
"""simple docstring"""
import os
from collections.abc import Iterator
def lowercase (SCREAMING_SNAKE_CASE_ : str = "." ) -> Any:
for dir_path, dir_names, filenames in os.walk(_lowerCAmelCase ):
SCREAMING_SNAKE_CASE = [d for d in dir_names if ... | 113 | """simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=_a)
class UpperCAmelCase_ ( _a):
# `task` is not a ClassVar since we want it to be part ... | 77 | 0 |
'''simple docstring'''
from pathlib import Path
import fire
from tqdm import tqdm
def snake_case_ ( __SCREAMING_SNAKE_CASE : Any="ro" , __SCREAMING_SNAKE_CASE : int="en" , __SCREAMING_SNAKE_CASE : Any="wmt16" , __SCREAMING_SNAKE_CASE : Any=Non... | 93 | """simple docstring"""
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
_UpperCamelCase : Any = re.compile(r"\b(a|an|the)\b", re.UNICODE)
_UpperCamelCase : Union[str, Any] = None
def a_ ( ):
... | 77 | 0 |
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class __lowerCAmelCase ( _a ):
"""simple docstring"""
A__ : Optional[Any] = (DDPMScheduler,)
def snake_case_ ( self : Optio... | 156 | """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 | 0 |
import unittest
import numpy as np
from transformers import is_flax_available
from transformers.testing_utils import require_flax
from ..test_modeling_flax_common import ids_tensor
if is_flax_available():
import jax
import jax.numpy as jnp
from transformers.generation import (
... | 124 | """simple docstring"""
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy... | 77 | 0 |
"""simple docstring"""
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
... | 106 | """simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=_a)
class UpperCAmelCase_ ( _a):
lowerCamelCase__ : str = field(default="language-modeling" , metad... | 77 | 0 |
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transformers.utils import logging
lo... | 328 | """simple docstring"""
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUES,
ENV_VARS... | 77 | 0 |
import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format="%(message)s")
def a__ ( __UpperCamelCase ):
return input_array.reshape((input_array.size, 1) )
def a__ ( __UpperCamelCase , __UpperCamelCase , ... | 118 | """simple docstring"""
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils impor... | 77 | 0 |
"""simple docstring"""
from manim import *
class __snake_case ( _a ):
def lowerCamelCase_ ( self) -> str:
'''simple docstring'''
a__: int = Rectangle(height=0.5 , width=0.5)
a__: List[Any] = Rectangle(height=0.46 ... | 290 | """simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling... | 77 | 0 |
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=logging.INFO
)
__A ... | 138 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase : Tuple = logging.get_logger(__name__)
_UpperCamelCase : Union[str, Any] = {
"alibaba-damo/mgp-str-base": "https://huggingface.co/alibaba-damo/mgp-str-base/re... | 77 | 0 |
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
UpperCAmelCase__ = TypeVar('''KT''')
UpperCAmelCase__ = TypeVar('''VT''')
class lowerCamelCase__ ( Generic[KT, VT]):
def __init__(self , UpperCAmelCase = "root" , ... | 5 | """simple docstring"""
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def a_ ( _lowerCAmelCase : Tuple , _lowerCAmelCase : Optional[int] , _lo... | 77 | 0 |
def __lowerCAmelCase ( a__ ) -> List[Any]:
__a = len(_lowerCAmelCase )
__a = len(matrix[0] )
__a = min(_lowerCAmelCase , _lowerCAmelCase )
for row in range(_lowerCAmelCase ):
# Check if diagonal element is not zero
if matr... | 6 | """simple docstring"""
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
... | 77 | 0 |
"""simple docstring"""
import requests
__UpperCamelCase = "https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="
def lowercase (SCREAMING_SNAKE_CASE_ : str ) -> Union[str, Any]:
SCREAMING_SNAKE_CASE = requests.get(_NEWS_API + bbc_ne... | 113 | """simple docstring"""
import math
import flax.linen as nn
import jax.numpy as jnp
def a_ ( _lowerCAmelCase : jnp.ndarray , _lowerCAmelCase : int , _lowerCAmelCase : float = 1 , _lowerCAmelCase : float = 1 , _lowerCAmelCase : float = 1.0E4 , _lowerCAmelCase : bool = False , _lo... | 77 | 0 |
'''simple docstring'''
from collections.abc import Callable
class lowerCAmelCase__ :
def __init__( self , __SCREAMING_SNAKE_CASE = None ):
"""simple docstring"""
lowercase_ : list = []
... | 93 | """simple docstring"""
from __future__ import annotations
import math
from collections.abc import Callable
def a_ ( _lowerCAmelCase : Callable[[int | float], int | float] , _lowerCAmelCase : int | float , _lowerCAmelCase : int | float , _lowerCAmelCase : int = 100 , ):
''... | 77 | 0 |
from __future__ import annotations
from collections import namedtuple
def UpperCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ) -> Dict:
__lowercase : Union[str, Any] = namedtuple('''result''' , '''name value''' )
if (voltage, current, po... | 156 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCamelCase : Tuple = {
"configuration_whisper": ["WHISPER... | 77 | 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
lowerCamelCase : List[Any] = logging.get_logger(__name__)
lowerCamelCase : ... | 124 | """simple docstring"""
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def a_ ( _lowerCAmelCase : str ):
'''simple docstring'''
lowercase__ : int = args.pruning_method
... | 77 | 0 |
"""simple docstring"""
from __future__ import annotations
from random import choice
def __SCREAMING_SNAKE_CASE ( A_ ):
return choice(_lowerCAmelCase )
def __SCREAMING_SNAKE_CASE ( A_ , A_ ):
lowerCAmelCase__ : Optional[Any] = random_pivot(_lowerCAmelCase )
# partition ba... | 106 | """simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import (
BaseOutput,
OptionalDependencyNotAvailable,
is_flax_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_... | 77 | 0 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ : Tuple = {
"configuration_trajectory_transformer": [
"TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"TrajectoryTransformerConfig",
... | 328 | """simple docstring"""
import pickle
import numpy as np
from matplotlib import pyplot as plt
class UpperCAmelCase_ :
def __init__( self , a , a , a , a , a , a=0.2 , a=0.2 ) -> Dict:
lowercase__ : Any = bp_numa
lowercase__ ... | 77 | 0 |
from __future__ import annotations
def a__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase ):
if len(_lowerCAmelCase ) == 0:
raise ValueError("find_max() arg is an empty sequence" )
if (
left >= len(_lowerCAmelCase )
or left < -len(_lower... | 118 | """simple docstring"""
from collections.abc import Generator
def a_ ( ):
'''simple docstring'''
lowercase__ , lowercase__ : List[str] = 0, 1
while True:
lowercase__ , lowercase__ : Optional[int] = b, a + b
yi... | 77 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
lowercase__ = logging.get_logger(__name__)
class __snake_case ( _a ):
def __init__( self , *lowercase , **lowercase) -> None:
... | 290 | """simple docstring"""
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class UpperCAmelCase_ :
def __init__( self , a ) -> List[str]:
if isinstance(a ... | 77 | 0 |
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available():... | 138 | """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 Image
... | 77 | 0 |
def UpperCAmelCase_ ( __snake_case , __snake_case ) -> Optional[Any]:
"""simple docstring"""
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(_lowerCAmelCase , int(b / 2 ) ) * actual_power(_lowerCAmelCase , int(b / 2 ) )
... | 5 | """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 PaddingSt... | 77 | 0 |
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 PaddingStrategy, logging
A : L... | 6 | """simple docstring"""
_UpperCamelCase : Union[str, Any] = 8.3_1_4_4_5_9_8
def a_ ( _lowerCAmelCase : float , _lowerCAmelCase : float ):
'''simple docstring'''
if temperature < 0:
raise Exception('Temperature cannot be less than 0 K' )
... | 77 | 0 |
"""simple docstring"""
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from... | 113 | """simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=_a)
class UpperCAmelCase_ ( _a):
# `task` is not a ClassVar since we want it to be part ... | 77 | 0 |
'''simple docstring'''
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import numpy as np
import pandas as pd
from datasets import load_dataset
import transformers
from transformers import (
AutoC... | 93 | """simple docstring"""
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
_UpperCamelCase : Any = re.compile(r"\b(a|an|the)\b", re.UNICODE)
_UpperCamelCase : Union[str, Any] = None
def a_ ( ):
... | 77 | 0 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
__lowerCAmelCase : Optional[int] = "\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot a... | 156 | """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 | 0 |
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def SCREAMING_SNAKE_CASE__ ( lowercase ) -> Any:
snake_case : int = args.pruning_method
snake_case : Tuple = args.... | 124 | """simple docstring"""
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy... | 77 | 0 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accele... | 106 | """simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=_a)
class UpperCAmelCase_ ( _a):
lowerCamelCase__ : str = field(default="language-modeling" , metad... | 77 | 0 |
import os
from pathlib import Path
def A_ ( ) -> Optional[Any]:
'''simple docstring'''
from torch.utils.cpp_extension import load
__UpperCamelCase = Path(_lowerCAmelCase ).resolve().parent.parent.parent / 'kernels' / 'deformable_detr'
__UpperCamelCase ... | 328 | """simple docstring"""
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUES,
ENV_VARS... | 77 | 0 |
def a__ ( __UpperCamelCase = 1_0_0_0 ):
SCREAMING_SNAKE_CASE_ = 2**power
SCREAMING_SNAKE_CASE_ = 0
while n:
SCREAMING_SNAKE_CASE_ = r + n % 1_0, n // 1_0
return r
if __name__ == "__main__":
print(solution(int(str(input()).strip())))
| 118 | """simple docstring"""
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils impor... | 77 | 0 |
"""simple docstring"""
from collections import Counter
from timeit import timeit
def __a ( _SCREAMING_SNAKE_CASE = "" , ) ->Union[str, Any]:
return sum(c % 2 for c in Counter(input_str.replace(' ' , '' ).lower() ).values() ) < 2
def __a ( _SCREAMING_SNAKE_CASE = "" ) ->... | 290 | """simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling... | 77 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__A : List[Any] = logging.get_logger(__name__)
__A : Dict = {
"microsoft/focalnet-tiny": "https://... | 138 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase : Tuple = logging.get_logger(__name__)
_UpperCamelCase : Union[str, Any] = {
"alibaba-damo/mgp-str-base": "https://huggingface.co/alibaba-damo/mgp-str-base/re... | 77 | 0 |
import unittest
from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
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 TokenizerTe... | 5 | """simple docstring"""
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def a_ ( _lowerCAmelCase : Tuple , _lowerCAmelCase : Optional[int] , _lo... | 77 | 0 |
from ..models.whisper import WhisperForConditionalGeneration, WhisperProcessor
from .base import PipelineTool
class __A( _a ):
snake_case_ = "openai/whisper-base"
snake_case_ = (
"This is a tool that transcribes an audio into text. It takes an input named `audio` and r... | 6 | """simple docstring"""
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
... | 77 | 0 |
"""simple docstring"""
from math import sqrt
def lowercase (SCREAMING_SNAKE_CASE_ : int ) -> Union[str, Any]:
assert isinstance(_lowerCAmelCase , _lowerCAmelCase ) and (
number >= 0
), "'number' must been an int and positive"
SCREAMING_SNAKE_CAS... | 113 | """simple docstring"""
import math
import flax.linen as nn
import jax.numpy as jnp
def a_ ( _lowerCAmelCase : jnp.ndarray , _lowerCAmelCase : int , _lowerCAmelCase : float = 1 , _lowerCAmelCase : float = 1 , _lowerCAmelCase : float = 1.0E4 , _lowerCAmelCase : bool = False , _lo... | 77 | 0 |
'''simple docstring'''
def snake_case_ ( __SCREAMING_SNAKE_CASE : int ):
"""simple docstring"""
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
lowercase_ : Dict = 1
lowercase_ : Dict = ... | 93 | """simple docstring"""
from __future__ import annotations
import math
from collections.abc import Callable
def a_ ( _lowerCAmelCase : Callable[[int | float], int | float] , _lowerCAmelCase : int | float , _lowerCAmelCase : int | float , _lowerCAmelCase : int = 100 , ):
''... | 77 | 0 |
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version(">=", FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch.distributed.checkpoint.defa... | 156 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCamelCase : Tuple = {
"configuration_whisper": ["WHISPER... | 77 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowerCamelCase : str = logging.get_logger(__name__)
class __lowercase (_a , _a ):
... | 124 | """simple docstring"""
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def a_ ( _lowerCAmelCase : str ):
'''simple docstring'''
lowercase__ : int = args.pruning_method
... | 77 | 0 |
"""simple docstring"""
import inspect
import unittest
class SCREAMING_SNAKE_CASE ( unittest.TestCase ):
"""simple docstring"""
def __lowerCAmelCase ( self : str ):
try:
import diffusers # noqa: F401
except ImportError:
assert ... | 106 | """simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import (
BaseOutput,
OptionalDependencyNotAvailable,
is_flax_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_... | 77 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ : Union[str, Any] = logging.get_logger(__name__)
lowercase__ : str = {
"came... | 328 | """simple docstring"""
import pickle
import numpy as np
from matplotlib import pyplot as plt
class UpperCAmelCase_ :
def __init__( self , a , a , a , a , a , a=0.2 , a=0.2 ) -> Dict:
lowercase__ : Any = bp_numa
lowercase__ ... | 77 | 0 |
import logging
import os
from .state import PartialState
class lowerCamelCase (logging.LoggerAdapter ):
"""simple docstring"""
@staticmethod
def __A ( __magic_name__ : Any ) -> Dict:
SCREAMING_SNAKE_CASE_ = PartialState()
return not ma... | 118 | """simple docstring"""
from collections.abc import Generator
def a_ ( ):
'''simple docstring'''
lowercase__ , lowercase__ : List[str] = 0, 1
while True:
lowercase__ , lowercase__ : Optional[int] = b, a + b
yi... | 77 | 0 |
"""simple docstring"""
def __a ( _SCREAMING_SNAKE_CASE ) ->List[Any]:
a__: Dict = [int(_lowerCAmelCase ) for i in ip_va_address.split('.' ) if i.isdigit()]
return len(_lowerCAmelCase ) == 4 and all(0 <= int(_lowerCAmelCase ) <= 254 for octet in octets )
if __name__ == "__main__":
... | 290 | """simple docstring"""
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class UpperCAmelCase_ :
def __init__( self , a ) -> List[str]:
if isinstance(a ... | 77 | 0 |
from math import pi
def SCREAMING_SNAKE_CASE__ ( _UpperCAmelCase, _UpperCAmelCase ) -> Any:
'''simple docstring'''
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10))
| 138 | """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 Image
... | 77 | 0 |
import math
import tensorflow as tf
from packaging import version
def UpperCAmelCase_ ( __snake_case ) -> Optional[Any]:
"""simple docstring"""
_lowercase =tf.convert_to_tensor(_lowerCAmelCase )
_lowercase =0.5 * (1.0 + tf.math.erf(x / tf.cast(tf.sqr... | 5 | """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 PaddingSt... | 77 | 0 |
import math
import flax.linen as nn
import jax.numpy as jnp
def __lowerCAmelCase ( a__ , a__ , a__ = 1 , a__ = 1 , a__ = 1.0e4 , a__ = False , a__ = 1.0 , ) -> Optional[int]:
assert timesteps.ndim == 1, "Timesteps should be a 1d-array"
a... | 6 | """simple docstring"""
_UpperCamelCase : Union[str, Any] = 8.3_1_4_4_5_9_8
def a_ ( _lowerCAmelCase : float , _lowerCAmelCase : float ):
'''simple docstring'''
if temperature < 0:
raise Exception('Temperature cannot be less than 0 K' )
... | 77 | 0 |
"""simple docstring"""
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def lowercase (SCREAMING_SNAKE_CASE_ : Union[str, Any] ) -> int:
SCREAMING_SNAKE_CASE = [
... | 113 | """simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=_a)
class UpperCAmelCase_ ( _a):
# `task` is not a ClassVar since we want it to be part ... | 77 | 0 |
'''simple docstring'''
_lowercase : int = [
"VerificationMode",
"Version",
"disable_progress_bar",
"enable_progress_bar",
"is_progress_bar_enabled",
"experimental",
]
from .info_utils import VerificationMode
from .logging import disable_progress_bar, ... | 93 | """simple docstring"""
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
_UpperCamelCase : Any = re.compile(r"\b(a|an|the)\b", re.UNICODE)
_UpperCamelCase : Union[str, Any] = None
def a_ ( ):
... | 77 | 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
__lowerCAmelCase : Any = logging.get_logger(__name__)
__lowerCAmelCase : Tuple ... | 156 | """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 | 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,
UnCLIPIm... | 124 | """simple docstring"""
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy... | 77 | 0 |
"""simple docstring"""
def __SCREAMING_SNAKE_CASE ( A_ , A_ , A_ , A_ ):
lowerCAmelCase__ : Tuple = len(_lowerCAmelCase ), len(grid[0] )
if (
min(_lowerCAmelCase , _lowerCAmelCase ) < 0
or row == row_length
or col == col_length
or (row, ... | 106 | """simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=_a)
class UpperCAmelCase_ ( _a):
lowerCamelCase__ : str = field(default="language-modeling" , metad... | 77 | 0 |
import doctest
from collections import deque
import numpy as np
class SCREAMING_SNAKE_CASE__ :
"""simple docstring"""
def __init__( self )-> None:
'''simple docstring'''
__UpperCamelCase = [2, 1, 2, -1]
__UpperCamelCase... | 328 | """simple docstring"""
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUES,
ENV_VARS... | 77 | 0 |
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 Image
from ..image_utils impor... | 118 | """simple docstring"""
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils impor... | 77 | 0 |
"""simple docstring"""
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def __a ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE=1024 ) ->Optional[Any]:
a__: Any ... | 290 | """simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling... | 77 | 0 |
from collections import defaultdict
from math import gcd
def SCREAMING_SNAKE_CASE__ ( _UpperCAmelCase = 1_500_000 ) -> str:
'''simple docstring'''
lowerCAmelCase : defaultdict = defaultdict(_lowerCAmelCase )
lowerCAmelCase : int = 2
while 2 * euclid_m * (euc... | 138 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase : Tuple = logging.get_logger(__name__)
_UpperCamelCase : Union[str, Any] = {
"alibaba-damo/mgp-str-base": "https://huggingface.co/alibaba-damo/mgp-str-base/re... | 77 | 0 |
import pytest
UpperCAmelCase__ = "__dummy_dataset1__"
UpperCAmelCase__ = "\nimport json\nimport os\n\nimport datasets\n\n\nREPO_URL = \"https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/\"\nURLS = {\"train\": REPO_URL + \"wikiann-bn-train.jsonl\", \"validation\": REPO_... | 5 | """simple docstring"""
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def a_ ( _lowerCAmelCase : Tuple , _lowerCAmelCase : Optional[int] , _lo... | 77 | 0 |
from math import loga
def __lowerCAmelCase ( a__ ) -> Tuple:
if a < 0:
raise ValueError('''Input value must be a positive integer''' )
elif isinstance(_lowerCAmelCase , _lowerCAmelCase ):
raise TypeError('''Input value must be a \'int\' type''' )
return 0 if (a... | 6 | """simple docstring"""
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
... | 77 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__UpperCamelCase = {
"configuration_whisper"... | 113 | """simple docstring"""
import math
import flax.linen as nn
import jax.numpy as jnp
def a_ ( _lowerCAmelCase : jnp.ndarray , _lowerCAmelCase : int , _lowerCAmelCase : float = 1 , _lowerCAmelCase : float = 1 , _lowerCAmelCase : float = 1.0E4 , _lowerCAmelCase : bool = False , _lo... | 77 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def snake_case_ ( __SCREAMING_SNAKE_CASE : Tuple , _... | 93 | """simple docstring"""
from __future__ import annotations
import math
from collections.abc import Callable
def a_ ( _lowerCAmelCase : Callable[[int | float], int | float] , _lowerCAmelCase : int | float , _lowerCAmelCase : int | float , _lowerCAmelCase : int = 100 , ):
''... | 77 | 0 |
def UpperCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase ) -> Optional[Any]:
return x if y == 0 else greatest_common_divisor(_lowerCAmelCase , x % y )
def UpperCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase ) -> Union[str, Any]:
return (x * y) // greatest... | 156 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCamelCase : Tuple = {
"configuration_whisper": ["WHISPER... | 77 | 0 |
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_vision
from transformers.utils... | 124 | """simple docstring"""
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def a_ ( _lowerCAmelCase : str ):
'''simple docstring'''
lowercase__ : int = args.pruning_method
... | 77 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__UpperCamelCase : Optional[int] = logging.get_logger(__name__)
_... | 106 | """simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import (
BaseOutput,
OptionalDependencyNotAvailable,
is_flax_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_... | 77 | 0 |
import torch
def A_ ( ) -> Optional[int]:
'''simple docstring'''
if torch.cuda.is_available():
__UpperCamelCase = torch.cuda.device_count()
else:
__UpperCamelCase = 0
print(f"Successfully ran on {num_gpus} GPUs" )
if __na... | 328 | """simple docstring"""
import pickle
import numpy as np
from matplotlib import pyplot as plt
class UpperCAmelCase_ :
def __init__( self , a , a , a , a , a , a=0.2 , a=0.2 ) -> Dict:
lowercase__ : Any = bp_numa
lowercase__ ... | 77 | 0 |
import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
A : Optional[Any] = np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any membership function
# (... | 118 | """simple docstring"""
from collections.abc import Generator
def a_ ( ):
'''simple docstring'''
lowercase__ , lowercase__ : List[str] = 0, 1
while True:
lowercase__ , lowercase__ : Optional[int] = b, a + b
yi... | 77 | 0 |
"""simple docstring"""
from collections.abc import Generator
def __a ( ) ->int:
a__: List[str] = 0, 1
while True:
a__: Optional[int] = b, a + b
yield b
def __a ( _SCREAMING_SNAKE_CASE = 1000 ) ->List[str]:
a__: List[Any] = 1
a__: ... | 290 | """simple docstring"""
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class UpperCAmelCase_ :
def __init__( self , a ) -> List[str]:
if isinstance(a ... | 77 | 0 |
__A : List[Any] = 256
# Modulus to hash a string
__A : List[Any] = 100_0003
def SCREAMING_SNAKE_CASE__ ( _UpperCAmelCase, _UpperCAmelCase ) -> Tuple:
'''simple docstring'''
lowerCAmelCase : List[Any] = len(_lowerCAmelCase )
lowerCAme... | 138 | """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 Image
... | 77 | 0 |
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
UpperCAmelCase__ = re.compile(R'''\b(a|an|the)\b''', re.UNICODE)
UpperCAmelCase__ = None
def UpperCAmelCase_ ( ) -> List[str]:
"""simple docstring"""
_lo... | 5 | """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 PaddingSt... | 77 | 0 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTe... | 6 | """simple docstring"""
_UpperCamelCase : Union[str, Any] = 8.3_1_4_4_5_9_8
def a_ ( _lowerCAmelCase : float , _lowerCAmelCase : float ):
'''simple docstring'''
if temperature < 0:
raise Exception('Temperature cannot be less than 0 K' )
... | 77 | 0 |
"""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
... | 113 | """simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=_a)
class UpperCAmelCase_ ( _a):
# `task` is not a ClassVar since we want it to be part ... | 77 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDConditionMode... | 93 | """simple docstring"""
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
_UpperCamelCase : Any = re.compile(r"\b(a|an|the)\b", re.UNICODE)
_UpperCamelCase : Union[str, Any] = None
def a_ ( ):
... | 77 | 0 |
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
__lowerCAmelCase : List[Any] = (
"4S 3H 2C 7S 5H",
"9D 8H 2C 6S 7H",
"2D 6D 9D TH 7D",
"TC 8C 2S JH 6C",
"JH 8S TH AH QH",
"TS KS 5S 9S AC",
... | 156 | """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 | 0 |
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
lowerCamelCase : Optional[int] = lo... | 124 | """simple docstring"""
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy... | 77 | 0 |
"""simple docstring"""
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
__UpperCamelCase : Union[str, Any] = 5_0_0_0_0_0
__UpperCamelCase : Optional[Any] = os.path.split(__file__)
__UpperC... | 106 | """simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=_a)
class UpperCAmelCase_ ( _a):
lowerCamelCase__ : str = field(default="language-modeling" , metad... | 77 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_albert import Al... | 328 | """simple docstring"""
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUES,
ENV_VARS... | 77 | 0 |
A : Union[str, Any] = 8.3_14_45_98
def a__ ( __UpperCamelCase , __UpperCamelCase ):
if temperature < 0:
raise Exception("Temperature cannot be less than 0 K" )
if molar_mass <= 0:
raise Exception("Molar mass cannot be less than or equal to 0 kg/m... | 118 | """simple docstring"""
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils impor... | 77 | 0 |
"""simple docstring"""
import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.serialization import fr... | 290 | """simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling... | 77 | 0 |
import copy
import os
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Dict, Mapping, Optional, Union
if TYPE_CHECKING:
from ...processing_utils import ProcessorMixin
from ...utils import TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ... | 138 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase : Tuple = logging.get_logger(__name__)
_UpperCamelCase : Union[str, Any] = {
"alibaba-damo/mgp-str-base": "https://huggingface.co/alibaba-damo/mgp-str-base/re... | 77 | 0 |
from ...configuration_utils import PretrainedConfig
class lowerCamelCase__ ( _a):
SCREAMING_SNAKE_CASE__ = "bert-generation"
def __init__(self , UpperCAmelCase=5_0_3_5_8 , UpperCAmelCase=1_0_2_4 , UpperCAmelCase=2_4 , UpperCAmelCase=1_6 , UpperCA... | 5 | """simple docstring"""
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def a_ ( _lowerCAmelCase : Tuple , _lowerCAmelCase : Optional[int] , _lo... | 77 | 0 |
import random
def __lowerCAmelCase ( a__ , a__ ) -> Any:
__a = [], [], []
for element in data:
if element < pivot:
less.append(_lowerCAmelCase )
elif element > pivot:
greater.append(_lowerCAmelCase )
else:
equal... | 6 | """simple docstring"""
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
... | 77 | 0 |
"""simple docstring"""
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class lowerCAmelCase ( _a , _a ):
'''simple docstring'''
... | 113 | """simple docstring"""
import math
import flax.linen as nn
import jax.numpy as jnp
def a_ ( _lowerCAmelCase : jnp.ndarray , _lowerCAmelCase : int , _lowerCAmelCase : float = 1 , _lowerCAmelCase : float = 1 , _lowerCAmelCase : float = 1.0E4 , _lowerCAmelCase : bool = False , _lo... | 77 | 0 |
'''simple docstring'''
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, ... | 93 | """simple docstring"""
from __future__ import annotations
import math
from collections.abc import Callable
def a_ ( _lowerCAmelCase : Callable[[int | float], int | float] , _lowerCAmelCase : int | float , _lowerCAmelCase : int | float , _lowerCAmelCase : int = 100 , ):
''... | 77 | 0 |
from random import randint, random
def UpperCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase = False , __lowerCAmelCase = False , __lowerCAmelCase = 5 , ) -> Dict:
__lowercase : str = [[-1] * number_of_cells] # Create ... | 156 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCamelCase : Tuple = {
"configuration_whisper": ["WHISPER... | 77 | 0 |
def SCREAMING_SNAKE_CASE__ ( lowercase ) -> List[Any]:
snake_case : Union[str, Any] = abs(_lowerCAmelCase )
snake_case : Union[str, Any] = 0
while n > 0:
res += n % 10
n //= 10
return res
def SCREAMING_SNAKE_CASE__ ( ... | 124 | """simple docstring"""
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def a_ ( _lowerCAmelCase : str ):
'''simple docstring'''
lowercase__ : int = args.pruning_method
... | 77 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__UpperCamelCase : Optional[Any] = {"configuration_mra": ["MRA_PRETRAINED_CONFIG_ARCHIVE... | 106 | """simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import (
BaseOutput,
OptionalDependencyNotAvailable,
is_flax_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_... | 77 | 0 |
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def A_ ( ) -> int:
'''simple docstring'''
__UpperCamelCase = [randint(-1000 , 1000 ) for i in range(10 )]
__UpperCamelCa... | 328 | """simple docstring"""
import pickle
import numpy as np
from matplotlib import pyplot as plt
class UpperCAmelCase_ :
def __init__( self , a , a , a , a , a , a=0.2 , a=0.2 ) -> Dict:
lowercase__ : Any = bp_numa
lowercase__ ... | 77 | 0 |
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