code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
class lowercase_ :
def __init__( self , lowercase_ , lowercase_) -> str:
a__ =name
a__ =val
def __str__( self) -> Tuple:
return F"""{self.__class__.__name__}({self.name}, {self.val})"""
def __lt__( self , ... | 20 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__: Dict = logging.get_logger(__name__)
A__: Optional[int] = {
'''microsoft/markuplm-base''': '''https://huggingface.co/microsoft/markuplm-base/re... | 694 | 0 |
import cmath
import math
def lowerCAmelCase_ ( lowerCamelCase , lowerCamelCase , lowerCamelCase , lowerCamelCase ):
__magic_name__ : List[str] =math.radians(lowerCamelCase )
__magic_name__ : Union[str, Any] =math.radians(lowerC... | 21 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
A__: Union[str, Any] = logging.get_logger('''transformers.models.speecht5''')
def SCR... | 694 | 0 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
... | 22 |
'''simple docstring'''
class A__ :
def __init__( self :List[Any] , SCREAMING_SNAKE_CASE :Dict , SCREAMING_SNAKE_CASE :Any , SCREAMING_SNAKE_CASE :List[str] ) -> List[str]:
'''simple docstring'''
_a : ... | 694 | 0 |
def _snake_case (__lowercase):
UpperCamelCase_ = 1
for i in range(1 , num + 1):
fact *= i
return fact
def _snake_case (__lowercase):
UpperCamelCase_ = 0
while number > 0:
UpperCamelCase_ = number % 10
sum_of_di... | 23 |
'''simple docstring'''
A__: Optional[int] = '''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transf... | 694 | 0 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
Wav... | 24 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : float ,_UpperCAmelCase : float ) -> float:
return price * (1 + tax_rate)
if __name__ == "__main__":
print(F"{price_plus_tax(100, 0.25) = }")
print(F"{price_plus_t... | 694 | 0 |
import contextlib
from multiprocessing import Pool, RLock
from tqdm.auto import tqdm
from ..utils import experimental, logging
a_ = logging.get_logger(__name__)
class _UpperCamelCase :
'''simple docstring'''
lowerCamelCase__ =None
@experimental
def lowerCamelCase__ ... | 25 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attent... | 694 | 0 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from .... | 26 |
'''simple docstring'''
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
A__: Tuple = logging.get_logger(__name__)
def SCREAMING_SNAKE_CASE_ ( ... | 694 | 0 |
def __lowerCAmelCase( _SCREAMING_SNAKE_CASE ) -> None:
"""simple docstring"""
_A = generate_pascal_triangle(_SCREAMING_SNAKE_CASE )
for row_idx in range(_SCREAMING_SNAKE_CASE ):
# Print left spaces
for _ in range(num_rows - ... | 27 |
'''simple docstring'''
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
... | 694 | 0 |
'''simple docstring'''
import warnings
from functools import wraps
from typing import Callable
def lowercase__( __UpperCamelCase: Callable ):
"""simple docstring"""
@wraps(__UpperCamelCase )
def _inner_fn(*__UpperCamelCase: List[Any] ... | 28 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int ,_UpperCAmelCase : int ) -> int:
return number | (1 << position)
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int ,_UpperCAmelCase : ... | 694 | 0 |
"""simple docstring"""
import random
from typing import Any
def lowercase ( lowerCAmelCase__ ):
for _ in range(len(lowerCAmelCase__ ) ):
lowerCamelCase_ = random.randint(0 ,len(lowerCAmelCase__ ) - 1 )
lowerCamelCase_ = random.randint(0 ,len(lowerCAmelCas... | 29 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : list ,_UpperCAmelCase : list ) -> float:
_validate_point(_UpperCAmelCase )
_validate_point(_UpperCAmelCase )
if len(_UpperCAmelCase ) != len(_UpperCAm... | 694 | 0 |
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/musicgen-small/resolve/main/compression... | 30 |
'''simple docstring'''
from __future__ import annotations
class A__ :
def __init__( self :str , SCREAMING_SNAKE_CASE :int ) -> None:
'''simple docstring'''
_a : int =order
# a_... | 694 | 0 |
def UpperCAmelCase_ ( __UpperCAmelCase : str , __UpperCAmelCase : int ) -> str:
SCREAMING_SNAKE_CASE_ = [[] for _ in range(__UpperCAmelCase )]
SCREAMING_SNAKE_CASE_ = key - 1
if key <= 0:
raise ValueError('Height of grid can... | 31 |
'''simple docstring'''
from queue import PriorityQueue
from typing import Any
import numpy as np
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : dict ,_UpperCAmelCase : str ,_UpperCAmelCase : set ,_UpperCAmelCase : set ... | 694 | 0 |
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
UpperCAmelCase_ = logging.get_logger(__name__)... | 32 |
'''simple docstring'''
from math import factorial
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int = 100 ) -> int:
return sum(map(_UpperCAmelCase ,str(factorial(_UpperCAmelCase ) ) ) )
if __name__ == "__main__":
print(solution(... | 694 | 0 |
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __magic_name__ (snake_case_ ):
'''si... | 33 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : str ,_UpperCAmelCase : str ) -> list:
_a : Tuple =len(_UpperCAmelCase )
_a : str =[]
for i in range(len(_UpperCAmelCase ) - pat... | 694 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
'tiiuae/falcon-40b': 'https://huggingface.co/tiiuae/falcon-40b/resolve/main/config.json',
't... | 34 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...t... | 694 | 0 |
import argparse
from typing import List
import evaluate
import numpy as np
import torch
from datasets import DatasetDict, load_dataset
# New Code #
# We'll be using StratifiedKFold for this example
from sklearn.model_selection import StratifiedKFold
from torch.optim import AdamW
from torch.utils.data import DataLo... | 35 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : list[int] ,_UpperCAmelCase : int ) -> bool:
_a : Optional[int] =len(_UpperCAmelCase )
_a : Tuple =[[False] * (required_sum + 1) for _ in r... | 694 | 0 |
from __future__ import annotations
from math import gcd
def lowercase ( __A : int , __A : int = 2 , __A : int = 1 , __A : int = 3 , ) -> int | None:
'''simple docstring'''
if num < 2:
raise ValueError("""The input value cannot be less than 2"... | 36 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int = 4000000 ) -> int:
_a : Optional[Any] =[]
_a , _a : Union[str, Any] =0, 1
while b <= n:
if b % 2 == 0:
... | 694 | 0 |
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokenizer,
TFAutoModelForSequenceC... | 37 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int ) -> int:
if n == 1 or not isinstance(_UpperCAmelCase ,_UpperCAmelCase ):
return 0
elif n == 2:
return 1
else:
_a ... | 694 | 0 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase__ ( __magic_name__ : int , __magic_name__ : int ) -> list[list[int]]:
'''simple docstring'''
snake_case__ : list[list[int]] = []
create_all_state(1 , __magic_name__... | 38 |
'''simple docstring'''
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : Tuple ,_... | 694 | 0 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow having multi... | 39 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
A__: Optional[int] = logging.get... | 694 | 0 |
from random import randint, random
def UpperCamelCase ( snake_case__ : int , snake_case__ : int , snake_case__ : int , snake_case__ : bool = False , snake_case__ : bool = False , snake_case__ : int = 5 , ) -> list:
UpperCamelCase ... | 40 |
'''simple docstring'''
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import ... | 694 | 0 |
'''simple docstring'''
from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf_common import f... | 41 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : list[list] ) -> list[list]:
_a : Dict =current_set.copy()
for row_index, row in enumerate(_UpperCAmelCase ):
_a : Any =row[0]
... | 694 | 0 |
'''simple docstring'''
from __future__ import annotations
def _UpperCamelCase ( __UpperCamelCase ) -> bool:
lowerCamelCase_ = str(__UpperCamelCase )
return len(__UpperCamelCase ) == 9 and set(__UpperCamelCase ) == set('123456789' )
def _UpperCamelCase ( ) -> ... | 42 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__: Dict = logging.get_logger(__name__)
A__: Optional[int] = {
'''microsoft/markuplm-base''': '''https://huggingface.co/microsoft/markuplm-base/re... | 694 | 0 |
import unittest
from transformers import is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common import ANY
... | 43 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
A__: Union[str, Any] = logging.get_logger('''transformers.models.speecht5''')
def SCR... | 694 | 0 |
'''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 ... | 44 |
'''simple docstring'''
class A__ :
def __init__( self :List[Any] , SCREAMING_SNAKE_CASE :Dict , SCREAMING_SNAKE_CASE :Any , SCREAMING_SNAKE_CASE :List[str] ) -> List[str]:
'''simple docstring'''
_a : ... | 694 | 0 |
import json
import os
from typing import Dict, List, Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
"vocab_file": "vocab.json",
"merges_file": ... | 45 |
'''simple docstring'''
A__: Optional[int] = '''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transf... | 694 | 0 |
"""simple docstring"""
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase ) -> int:
'''simple docstring'''
_lowerCamelCase : List[str] = ""
for i in table:
res += inp[i - 1]
return res
def lowerCamelCase_( _lowerCamelCase ) ... | 46 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : float ,_UpperCAmelCase : float ) -> float:
return price * (1 + tax_rate)
if __name__ == "__main__":
print(F"{price_plus_tax(100, 0.25) = }")
print(F"{price_plus_t... | 694 | 0 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def UpperCAmelCase__ ( lowerCamelCase_ ... | 47 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attent... | 694 | 0 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ : int = logging.get_logger(__name__)
UpperCAmelCase__ : Tuple = {
"microsoft/wavlm-base": "https://huggingface.co/microsoft/wavlm-... | 48 |
'''simple docstring'''
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
A__: Tuple = logging.get_logger(__name__)
def SCREAMING_SNAKE_CASE_ ( ... | 694 | 0 |
"""simple docstring"""
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class _Uppe... | 49 |
'''simple docstring'''
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
... | 694 | 0 |
'''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... | 50 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int ,_UpperCAmelCase : int ) -> int:
return number | (1 << position)
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int ,_UpperCAmelCase : ... | 694 | 0 |
'''simple docstring'''
import unittest
import torch
from torch import nn
from accelerate.test_utils import require_cuda
from accelerate.utils.memory import find_executable_batch_size, release_memory
def __snake_case ( ) -> int:
"""simple docstring"""
raise RuntimeError('''CUD... | 51 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : list ,_UpperCAmelCase : list ) -> float:
_validate_point(_UpperCAmelCase )
_validate_point(_UpperCAmelCase )
if len(_UpperCAmelCase ) != len(_UpperCAm... | 694 | 0 |
"""simple docstring"""
import itertools
import string
from collections.abc import Generator, Iterable
def __A ( a_ :Iterable[str] , a_ :int) -> Generator[tuple[str, ...], None, None]:
__a : List[str] = iter(a_)
while True:
__a ... | 52 |
'''simple docstring'''
from __future__ import annotations
class A__ :
def __init__( self :str , SCREAMING_SNAKE_CASE :int ) -> None:
'''simple docstring'''
_a : int =order
# a_... | 694 | 0 |
def a_ ( lowerCAmelCase_ : int ):
if not isinstance(lowerCAmelCase_, lowerCAmelCase_ ) or number < 0:
raise ValueError('Input must be a non-negative integer' )
__lowerCAmelCase = 0
while number:
# This way we arrive at next set bit (next 1)... | 53 |
'''simple docstring'''
from queue import PriorityQueue
from typing import Any
import numpy as np
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : dict ,_UpperCAmelCase : str ,_UpperCAmelCase : set ,_UpperCAmelCase : set ... | 694 | 0 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
class A ( ... | 54 |
'''simple docstring'''
from math import factorial
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int = 100 ) -> int:
return sum(map(_UpperCAmelCase ,str(factorial(_UpperCAmelCase ) ) ) )
if __name__ == "__main__":
print(solution(... | 694 | 0 |
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
SCREAMING_SNAKE_CASE :Optional[Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE :Uni... | 55 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : str ,_UpperCAmelCase : str ) -> list:
_a : Tuple =len(_UpperCAmelCase )
_a : str =[]
for i in range(len(_UpperCAmelCase ) - pat... | 694 | 0 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_chan... | 56 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...t... | 694 | 0 |
import tensorflow as tf
from ...tf_utils import shape_list
class _lowerCAmelCase( tf.keras.layers.Layer ):
"""simple docstring"""
def __init__( self , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCa... | 57 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : list[int] ,_UpperCAmelCase : int ) -> bool:
_a : Optional[int] =len(_UpperCAmelCase )
_a : Tuple =[[False] * (required_sum + 1) for _ in r... | 694 | 0 |
"""simple docstring"""
__lowerCAmelCase : Tuple = '''
# Installazione di Transformers
! pip install transformers datasets
# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e
# rimuovi la modalità commento al comando seguente.
# ... | 58 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int = 4000000 ) -> int:
_a : Optional[Any] =[]
_a , _a : Union[str, Any] =0, 1
while b <= n:
if b % 2 == 0:
... | 694 | 0 |
def lowerCAmelCase_ ( ) -> str:
"""simple docstring"""
lowerCamelCase__: str =[31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]
lowerCamelCase__: List[str] =6
lowerCamelCase__: int =1
lowerCamelCase__: int =1901
lowerCamelCase__: List[str] ... | 59 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int ) -> int:
if n == 1 or not isinstance(_UpperCAmelCase ,_UpperCAmelCase ):
return 0
elif n == 2:
return 1
else:
_a ... | 694 | 0 |
import os
import sys
import unittest
lowerCAmelCase_ = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_b... | 60 |
'''simple docstring'''
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : Tuple ,_... | 694 | 0 |
from collections.abc import Callable
def _A ( lowerCAmelCase_ : Callable[[float], float] , lowerCAmelCase_ : float , lowerCAmelCase_ : float ):
"""simple docstring"""
lowerCAmelCase__ = a
lowerCAmelCase__ = b
if funct... | 61 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
A__: Optional[int] = logging.get... | 694 | 0 |
import math
import flax.linen as nn
import jax.numpy as jnp
def lowerCamelCase__ ( lowercase , lowercase , lowercase = 1 , lowercase = 1 , lowercase = 1.0E4 , lowercase = False , lowercase = 1.0 , ):
"""simple docstring"""
assert timesteps.ndim == 1, "Timesteps sh... | 62 |
'''simple docstring'''
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import ... | 694 | 0 |
from __future__ import annotations
import queue
class a :
"""simple docstring"""
def __init__( self : Union[str, Any] , __lowercase : Optional[int] ) -> Union[str, Any]:
__UpperCAmelCase : Optional[int] = data
__U... | 63 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : list[list] ) -> list[list]:
_a : Dict =current_set.copy()
for row_index, row in enumerate(_UpperCAmelCase ):
_a : Any =row[0]
... | 694 | 0 |
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class _lowerCamelCase ( unittest.TestCase ):
def UpperCamelCase_ ... | 64 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__: Dict = logging.get_logger(__name__)
A__: Optional[int] = {
'''microsoft/markuplm-base''': '''https://huggingface.co/microsoft/markuplm-base/re... | 694 | 0 |
"""simple docstring"""
import argparse
import os
from . import (
ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
BART_PRETRAINED_MODEL_ARCHIVE_LIST,
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP,
DISTILBERT_PRETRAINED... | 65 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
A__: Union[str, Any] = logging.get_logger('''transformers.models.speecht5''')
def SCR... | 694 | 0 |
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn # noqa: F401 # Here t... | 66 |
'''simple docstring'''
class A__ :
def __init__( self :List[Any] , SCREAMING_SNAKE_CASE :Dict , SCREAMING_SNAKE_CASE :Any , SCREAMING_SNAKE_CASE :List[str] ) -> List[str]:
'''simple docstring'''
_a : ... | 694 | 0 |
def SCREAMING_SNAKE_CASE__ ( snake_case__ :str ) -> list:
_lowercase = [0] * len(snake_case__ )
for i in range(1 , len(snake_case__ ) ):
# use last results for better performance - dynamic programming
_lowercase = prefix_result[i - 1]
w... | 67 |
'''simple docstring'''
A__: Optional[int] = '''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transf... | 694 | 0 |
import json
import os
from typing import Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"vocab_file": "vocab.json",
"merges_file": "merges.txt",
}
__A = {
"vocab_file": ... | 68 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : float ,_UpperCAmelCase : float ) -> float:
return price * (1 + tax_rate)
if __name__ == "__main__":
print(F"{price_plus_tax(100, 0.25) = }")
print(F"{price_plus_t... | 694 | 0 |
'''simple docstring'''
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def _... | 69 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attent... | 694 | 0 |
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
lowerCamelCase : List[Any] = 0b101100111110110010010000011... | 70 |
'''simple docstring'''
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
A__: Tuple = logging.get_logger(__name__)
def SCREAMING_SNAKE_CASE_ ( ... | 694 | 0 |
'''simple docstring'''
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
... | 71 |
'''simple docstring'''
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
... | 694 | 0 |
'''simple docstring'''
_UpperCAmelCase : int = '''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
'''
_UpperCAmelCa... | 72 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int ,_UpperCAmelCase : int ) -> int:
return number | (1 << position)
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int ,_UpperCAmelCase : ... | 694 | 0 |
import math
def lowerCamelCase__ (_UpperCAmelCase):
SCREAMING_SNAKE_CASE = 0
SCREAMING_SNAKE_CASE = 0
while num > 0:
SCREAMING_SNAKE_CASE = num % 8
SCREAMING_SNAKE_CASE = octal + (remainder * math.floor(math.pow(10 , _UpperCAmelCase)))
... | 73 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : list ,_UpperCAmelCase : list ) -> float:
_validate_point(_UpperCAmelCase )
_validate_point(_UpperCAmelCase )
if len(_UpperCAmelCase ) != len(_UpperCAm... | 694 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase_ = {"""configuration_encoder_decoder""": ["""EncoderDecoderConfig"""]}
try:
if not is_torch_available():
raise ... | 74 |
'''simple docstring'''
from __future__ import annotations
class A__ :
def __init__( self :str , SCREAMING_SNAKE_CASE :int ) -> None:
'''simple docstring'''
_a : int =order
# a_... | 694 | 0 |
'''simple docstring'''
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...te... | 75 |
'''simple docstring'''
from queue import PriorityQueue
from typing import Any
import numpy as np
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : dict ,_UpperCAmelCase : str ,_UpperCAmelCase : set ,_UpperCAmelCase : set ... | 694 | 0 |
"""simple docstring"""
import math
import flax.linen as nn
import jax.numpy as jnp
def __UpperCAmelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase = 1 , __UpperCamelCase = 1 , __UpperCamelCase = 1.0e4 , __UpperCamelCase = False , __UpperCame... | 76 |
'''simple docstring'''
from math import factorial
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int = 100 ) -> int:
return sum(map(_UpperCAmelCase ,str(factorial(_UpperCAmelCase ) ) ) )
if __name__ == "__main__":
print(solution(... | 694 | 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/LICENSE-2.0... | 77 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : str ,_UpperCAmelCase : str ) -> list:
_a : Tuple =len(_UpperCAmelCase )
_a : str =[]
for i in range(len(_UpperCAmelCase ) - pat... | 694 | 0 |
'''simple docstring'''
from math import asin, atan, cos, radians, sin, sqrt, tan
SCREAMING_SNAKE_CASE_: int =6378137.0
SCREAMING_SNAKE_CASE_: List[Any] =6356752.314245
SCREAMING_SNAKE_CASE_: Dict =6_37_81_37
def lowerCAmelCase_ ( snake_case_ : float , snake_case_ : ... | 78 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...t... | 694 | 0 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
SCREAMING_SNAKE_CASE__ : Optional[int] = """"""
SCREAMING_SNAKE_CASE__ : Union[str, Any] = """"""
SCREAMING_SNAKE_CASE__ : Any = """"""
SCREAMING_SNAKE_CASE__ : ... | 79 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : list[int] ,_UpperCAmelCase : int ) -> bool:
_a : Optional[int] =len(_UpperCAmelCase )
_a : Tuple =[[False] * (required_sum + 1) for _ in r... | 694 | 0 |
def snake_case ( lowerCamelCase ):
'''simple docstring'''
for i in range(len(lowerCamelCase ) - 1 , 0 , -1 ):
__lowercase = False
for j in range(lowerCamelCase , 0 , -1 ):
if unsorted[j] < unsorted[j - 1]:
__lowercase , __lo... | 80 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int = 4000000 ) -> int:
_a : Optional[Any] =[]
_a , _a : Union[str, Any] =0, 1
while b <= n:
if b % 2 == 0:
... | 694 | 0 |
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class a (_lowerCAmelCase ):
"""simple docstring"""
def __init__( self : int , lowerCamelCase : List[Any] , lowerCamelCase : str ) -> ... | 81 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int ) -> int:
if n == 1 or not isinstance(_UpperCAmelCase ,_UpperCAmelCase ):
return 0
elif n == 2:
return 1
else:
_a ... | 694 | 0 |
"""simple docstring"""
import fire
from utils import calculate_rouge, save_json
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__=None , **lowerCAmelCase__ ):
UpperCAmelCase_ = [x.strip() for x in open(lowerCAmelCase__ ).readline... | 82 |
'''simple docstring'''
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : Tuple ,_... | 694 | 0 |
"""simple docstring"""
from torch import nn
def snake_case_ ( A_ : int ):
'''simple docstring'''
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif act_fn == "gelu":
retu... | 83 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
A__: Optional[int] = logging.get... | 694 | 0 |
import math
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE ):
lowercase = [True] * n
lowercase = False
lowercase = False
lowercase = True
for i in range(3 , int(n**0.5 + 1 ) , 2 ):
lowercase = i * 2
while index < n:
l... | 84 |
'''simple docstring'''
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import ... | 694 | 0 |
import io
import math
from typing import Dict, Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import convert_to_rgb, normalize, to_channel_dimension_format, to_pil_image
from ...image_utils ... | 85 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : list[list] ) -> list[list]:
_a : Dict =current_set.copy()
for row_index, row in enumerate(_UpperCAmelCase ):
_a : Any =row[0]
... | 694 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__a :Any = {
'configuration_blip': [
'BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
'BlipConfig',... | 86 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__: Dict = logging.get_logger(__name__)
A__: Optional[int] = {
'''microsoft/markuplm-base''': '''https://huggingface.co/microsoft/markuplm-base/re... | 694 | 0 |
import html
from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from ...utils import is_bsa_available, logging, requires_backends
if is_bsa_available():
import bsa
from bsa import BeautifulSoup
_lowerCamelCase : Optional[int] = logging.get_logger(__name__)
class... | 87 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
A__: Union[str, Any] = logging.get_logger('''transformers.models.speecht5''')
def SCR... | 694 | 0 |
"""simple docstring"""
import torch
from transformers import AutoModel
class lowercase__ ( torch.nn.Module ):
def __init__( self , SCREAMING_SNAKE_CASE="sayef/fsner-bert-base-uncased") -> str:
super(SCREAMING_SNAKE_CASE , self).__init__()
... | 88 |
'''simple docstring'''
class A__ :
def __init__( self :List[Any] , SCREAMING_SNAKE_CASE :Dict , SCREAMING_SNAKE_CASE :Any , SCREAMING_SNAKE_CASE :List[str] ) -> List[str]:
'''simple docstring'''
_a : ... | 694 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : List[str] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Optional[int] = {
"facebook/dpr-ctx_encoder-single-nq-base": (
"https://huggingface.co/facebook/dpr-ctx_encode... | 89 |
'''simple docstring'''
A__: Optional[int] = '''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transf... | 694 | 0 |
'''simple docstring'''
import math
import sys
def _snake_case ( A ) -> str:
lowerCAmelCase__ = ''''''
try:
with open(A , '''rb''' ) as binary_file:
lowerCAmelCase__ = binary_file.read()
... | 90 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : float ,_UpperCAmelCase : float ) -> float:
return price * (1 + tax_rate)
if __name__ == "__main__":
print(F"{price_plus_tax(100, 0.25) = }")
print(F"{price_plus_t... | 694 | 0 |
"""simple docstring"""
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import Ite... | 91 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attent... | 694 | 0 |
'''simple docstring'''
from abc import ABC, abstractmethod
from typing import List, Optional
class __SCREAMING_SNAKE_CASE ( lowercase__ ):
def __init__( self : str ):
'''simple docstring'''
# test for the above condition
self.test()
... | 92 |
'''simple docstring'''
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
A__: Tuple = logging.get_logger(__name__)
def SCREAMING_SNAKE_CASE_ ( ... | 694 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import... | 93 |
'''simple docstring'''
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
... | 694 | 0 |
'''simple docstring'''
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def lowercase_ (... | 94 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int ,_UpperCAmelCase : int ) -> int:
return number | (1 << position)
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int ,_UpperCAmelCase : ... | 694 | 0 |
"""simple docstring"""
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
lowerCamelCase_ = '''\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and Saurav K... | 95 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : list ,_UpperCAmelCase : list ) -> float:
_validate_point(_UpperCAmelCase )
_validate_point(_UpperCAmelCase )
if len(_UpperCAmelCase ) != len(_UpperCAm... | 694 | 0 |
"""simple docstring"""
from __future__ import annotations
import os
from collections.abc import Mapping
__lowerCamelCase = tuple[int, int]
class __A :
def __init__( self : Tuple , __snake_case : set[int] , __snake_case : Mapping[... | 96 |
'''simple docstring'''
from __future__ import annotations
class A__ :
def __init__( self :str , SCREAMING_SNAKE_CASE :int ) -> None:
'''simple docstring'''
_a : int =order
# a_... | 694 | 0 |
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def a ( snake_case__: Any ... | 97 |
'''simple docstring'''
from queue import PriorityQueue
from typing import Any
import numpy as np
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : dict ,_UpperCAmelCase : str ,_UpperCAmelCase : set ,_UpperCAmelCase : set ... | 694 | 0 |
'''simple docstring'''
from __future__ import annotations
import copy
import tempfile
import unittest
from transformers import CONFIG_MAPPING, AutoConfig, BertConfig, GPTaConfig, TaConfig, TapasConfig, is_tf_available
from transformers.testing_utils import (
DUMMY_UNKNOWN_IDENTIFIER,
SMALL_MODEL_IDENTI... | 98 |
'''simple docstring'''
from math import factorial
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int = 100 ) -> int:
return sum(map(_UpperCAmelCase ,str(factorial(_UpperCAmelCase ) ) ) )
if __name__ == "__main__":
print(solution(... | 694 | 0 |
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vision_available
... | 99 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : str ,_UpperCAmelCase : str ) -> list:
_a : Tuple =len(_UpperCAmelCase )
_a : str =[]
for i in range(len(_UpperCAmelCase ) - pat... | 694 | 0 |
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
_A : Dict = get_tests_dir("""fixtures/test_sentencepiece_bpe.... | 100 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...t... | 694 | 0 |
import unittest
from transformers import AutoTokenizer, FalconConfig, 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 i... | 101 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : list[int] ,_UpperCAmelCase : int ) -> bool:
_a : Optional[int] =len(_UpperCAmelCase )
_a : Tuple =[[False] * (required_sum + 1) for _ in r... | 694 | 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 Schedule... | 102 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int = 4000000 ) -> int:
_a : Optional[Any] =[]
_a , _a : Union[str, Any] =0, 1
while b <= n:
if b % 2 == 0:
... | 694 | 0 |
"""simple docstring"""
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
snake_case = '''\
@misc{chen2021evaluat... | 103 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int ) -> int:
if n == 1 or not isinstance(_UpperCAmelCase ,_UpperCAmelCase ):
return 0
elif n == 2:
return 1
else:
_a ... | 694 | 0 |
"""simple docstring"""
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_... | 104 |
'''simple docstring'''
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : Tuple ,_... | 694 | 0 |
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def __UpperCAmelCase ( lowerCamelCa... | 105 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
A__: Optional[int] = logging.get... | 694 | 0 |
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def lowerCamelCase_ ( lowerCAmelCase__ : NDArray[floataa] , lowerCAmelCase__ : NDArray[floataa] , lowerCAmelCase__ : list[int] , lowerCAmelCase__ : int , ) -> list[float]... | 106 |
'''simple docstring'''
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import ... | 694 | 0 |
'''simple docstring'''
from sklearn.metrics import fa_score
import datasets
_UpperCAmelCase : Dict = '''
The F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:
F1 = 2 * (precision * recall) / (precision + recall)
'''
_UpperCAmelCase : ... | 107 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : list[list] ) -> list[list]:
_a : Dict =current_set.copy()
for row_index, row in enumerate(_UpperCAmelCase ):
_a : Any =row[0]
... | 694 | 0 |
from collections import namedtuple
import requests
from lxml import html # type: ignore
__a: List[str] = namedtuple('''covid_data''', '''cases deaths recovered''')
def _SCREAMING_SNAKE_CASE ( __snake_case = "https://www.worldometers.info/coronavirus/" ) -> covid_data:
... | 108 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__: Dict = logging.get_logger(__name__)
A__: Optional[int] = {
'''microsoft/markuplm-base''': '''https://huggingface.co/microsoft/markuplm-base/re... | 694 | 0 |
'''simple docstring'''
import argparse
import struct
import unittest
class __a :
def __init__( self : str ,lowerCamelCase : bytes ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = data
# Initialize hash values
__SCREAMING_SN... | 109 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
A__: Union[str, Any] = logging.get_logger('''transformers.models.speecht5''')
def SCR... | 694 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : Dict = logging.get_logger(__name__)
lowercase__ : Optional[Any] = {
'''bigcode/gpt_bigcode-santacoder''': '''https://huggingface.co/bigcode/gpt_bigcode-santacoder... | 98 |
'''simple docstring'''
class A__ :
def __init__( self :List[Any] , SCREAMING_SNAKE_CASE :Dict , SCREAMING_SNAKE_CASE :Any , SCREAMING_SNAKE_CASE :List[str] ) -> List[str]:
'''simple docstring'''
_a : ... | 694 | 0 |
"""simple docstring"""
def _snake_case ( lowercase__ , lowercase__ ):
return number | (1 << position)
def _snake_case ( lowercase__ , lowercase__ ):
return number & ~(1 << position)
def _snake_case ( ... | 630 |
'''simple docstring'''
A__: Optional[int] = '''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transf... | 694 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configu... | 238 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : float ,_UpperCAmelCase : float ) -> float:
return price * (1 + tax_rate)
if __name__ == "__main__":
print(F"{price_plus_tax(100, 0.25) = }")
print(F"{price_plus_t... | 694 | 0 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
__lowercase : Optional[Any] = {'''tokenization_wav2vec2_phoneme''': ['''Wav2Vec2PhonemeCTCTokenizer''']}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
import sys
__low... | 36 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attent... | 694 | 0 |
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImageClassification
if is_vision_... | 458 |
'''simple docstring'''
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
A__: Tuple = logging.get_logger(__name__)
def SCREAMING_SNAKE_CASE_ ( ... | 694 | 0 |
"""simple docstring"""
class __lowerCAmelCase :
'''simple docstring'''
def __init__( self: List[Any] , UpperCamelCase_: Dict , UpperCamelCase_: Any , UpperCamelCase_: List[str] ):
UpperCamelCase_ =None
UpperCamelCase_ =None
... | 391 |
'''simple docstring'''
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
... | 694 | 0 |
"""simple docstring"""
def A ( snake_case__ = 10_00 ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = 1, 1
SCREAMING_SNAKE_CASE__ = 2
while True:
SCREAMING_SNAKE_CASE__ = 0
SCREAMING_SNAKE_CASE__ = fa + ... | 196 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int ,_UpperCAmelCase : int ) -> int:
return number | (1 << position)
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int ,_UpperCAmelCase : ... | 694 | 0 |
a_ :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, enable_progress_bar, is_progress_bar_en... | 35 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : list ,_UpperCAmelCase : list ) -> float:
_validate_point(_UpperCAmelCase )
_validate_point(_UpperCAmelCase )
if len(_UpperCAmelCase ) != len(_UpperCAm... | 694 | 0 |
import argparse
import os
import re
lowercase = '''src/diffusers'''
# Pattern that looks at the indentation in a line.
lowercase = re.compile(r'''^(\s*)\S''')
# Pattern that matches `"key":" and puts `key` in group 0.
lowercase = re.compile(r'''^\s*"([^"]+)":''')
# Pattern that matches `_import_st... | 272 |
'''simple docstring'''
from __future__ import annotations
class A__ :
def __init__( self :str , SCREAMING_SNAKE_CASE :int ) -> None:
'''simple docstring'''
_a : int =order
# a_... | 694 | 0 |
"""simple docstring"""
import unittest
from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
if is_flax_available():
import jax.numpy as jnp
from transformers import FlaxXLMRobertaModel
@re... | 586 |
'''simple docstring'''
from queue import PriorityQueue
from typing import Any
import numpy as np
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : dict ,_UpperCAmelCase : str ,_UpperCAmelCase : set ,_UpperCAmelCase : set ... | 694 | 0 |
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