code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
def UpperCAmelCase__( __UpperCAmelCase : float , __UpperCAmelCase : float , __UpperCAmelCase : float , __UpperCAmelCase : float , __UpperCAmelCase : float , ):
__snake_case : Dict = [redshift, radiation_density, matter_density, dark_en... | 679 | import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
__magic_name__ = logging.get_logger(__name__)
__magic_name__ ... | 679 | 1 |
from __future__ import annotations
__magic_name__ = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def UpperCAmelCase__( __UpperCAmelCase : list[list[int]] , __UpperCAmelCase : list[int] , __UpperCAmelCase : list[int] ... | 679 | import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
__magic_name__ = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( UpperCamelCase):
"""simple docstring"""
def __init__( self , *_UpperCAmelCase , **_Upp... | 679 | 1 |
def UpperCAmelCase__( __UpperCAmelCase : Optional[Any] ):
__snake_case : Optional[int] = 0
__snake_case : List[Any] = len(__UpperCAmelCase )
for i in range(n - 1 ):
for j in range(i + 1 , __UpperCAmelCase ):
if arr[i] > arr[j]:
... | 679 | import math
import os
import sys
def UpperCAmelCase__( __UpperCAmelCase : str ):
__snake_case : Union[str, Any] = ''
try:
with open(__UpperCAmelCase , 'rb' ) as binary_file:
__snake_case : Optional[Any] = binary_file.read()
for dat i... | 679 | 1 |
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {
'''snap-research/efficientformer-l1-300''': (
'''https://huggingface.co/snap-research/efficientfor... | 679 | from itertools import permutations
def UpperCAmelCase__( __UpperCAmelCase : tuple ):
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
__snake_case : Any = [7, 11, 13, 17]
for i, t... | 679 | 1 |
def UpperCAmelCase__( __UpperCAmelCase : list ):
__snake_case : List[Any] = len(__UpperCAmelCase )
for _ in range(__UpperCAmelCase ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
if arr[i + 1] < arr[i]:
__snake_case , __snake_... | 679 | # Function to print upper half of diamond (pyramid)
def UpperCAmelCase__( __UpperCAmelCase : List[str] ):
for i in range(0 , __UpperCAmelCase ):
for _ in range(0 , n - i - 1 ): # printing spaces
print(' ' , end='' )
for _ in range(0 ... | 679 | 1 |
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
__magic_name__ = argparse.ArgumentParser(
description=(
'''Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Transfer Learned'''
''' Distillation'''
... | 679 | from timeit import timeit
def UpperCAmelCase__( __UpperCAmelCase : int ):
if number < 0:
raise ValueError('the value of input must not be negative' )
__snake_case : Dict = 0
while number:
number &= number - 1
result += 1
return result
def ... | 679 | 1 |
from __future__ import annotations
def UpperCAmelCase__( __UpperCAmelCase : list[float] ):
if len(__UpperCAmelCase ) < 2:
raise ValueError('Monogons and Digons are not polygons in the Euclidean space' )
if any(i <= 0 for i in nums ):
raise ValueError('All values must... | 679 | import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import patch
import pyarrow as pa
imp... | 679 | 1 |
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import Conf... | 679 | from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
__magic_name__ = TypeVar('''T''')
class __SCREAMING_SNAKE_CASE ( Generic[T]):
"""simple docstring"""
def __init__( self , _UpperCAmelCase ):
... | 679 | 1 |
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArguments
@require_tf
class _... | 679 | import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, slow
f... | 679 | 1 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__magic_name__ = {
'''configuration_autoformer''': [
'''AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''AutoformerConfig''',... | 679 | import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def UpperCAmelCase__( __UpperCAmelCase : int , __UpperCAmelCase : int , __UpperCAmelCase : Any ):
... | 679 | 1 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | 679 | import logging
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertEncoder,
... | 679 | 1 |
import pytest
from datasets.parallel import ParallelBackendConfig, parallel_backend
from datasets.utils.py_utils import map_nested
from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows
def UpperCAmelCase__( __UpperCAmelCase : Dict ): # picklable for multiprocessing... | 679 | def UpperCAmelCase__( __UpperCAmelCase : str ):
if not all(x.isalpha() for x in string ):
raise ValueError('String must only contain alphabetic characters.' )
__snake_case : str = sorted(string.lower() )
return len(__UpperCAmelCase ) == len(set(__UpperCAmelCa... | 679 | 1 |
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
from ...generation.test_utils import GenerationTester... | 679 | from ....configuration_utils import PretrainedConfig
from ....utils import logging
__magic_name__ = logging.get_logger(__name__)
# TODO: upload to AWS
__magic_name__ = {
'''yjernite/retribert-base-uncased''': (
'''https://huggingface.co/yjernite/retribert-base-uncased/... | 679 | 1 |
def UpperCAmelCase__( __UpperCAmelCase : int , __UpperCAmelCase : int , __UpperCAmelCase : list[list[int]] ):
def update_area_of_max_square(__UpperCAmelCase : int , __UpperCAmelCase : int ) -> int:
# BASE CASE
if row >= rows or col >= cols:
... | 679 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ = {
'''configuration_biogpt''': ['''BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BioGptConfig'''],
'''tokenization_biogpt''': ['''BioG... | 679 | 1 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_download, hf_hub_url
from PIL import Image
from transformers import DetaConfig, DetaForObjectDetection, DetaImageProcessor, SwinConfig
from transformers.utils import logging
logging.... | 679 | import inspect
import unittest
from transformers import MobileViTConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_mo... | 679 | 1 |
def UpperCAmelCase__( __UpperCAmelCase : int = 10_00 ):
__snake_case : int = 2**power
__snake_case : Any = str(__UpperCAmelCase )
__snake_case : Optional[Any] = list(__UpperCAmelCase )
__snake_case : List[Any] = 0
for i in list_num... | 679 | def UpperCAmelCase__( __UpperCAmelCase : int | float | str ):
try:
__snake_case : int = float(__UpperCAmelCase )
except ValueError:
raise ValueError('Please enter a valid number' )
__snake_case : Any = decimal - int(__UpperCAmelCase )
if fract... | 679 | 1 |
import argparse
import hashlib
import os
import urllib
import warnings
import torch
from torch import nn
from tqdm import tqdm
from transformers import WhisperConfig, WhisperForConditionalGeneration
__magic_name__ = {
'''tiny.en''': '''https://openaipublic.azureedge.net/main/whisper/models/d3d... | 679 | import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
... | 679 | 1 |
import argparse
import json
import os
import tensorstore as ts
import torch
from flax import serialization
from flax.traverse_util import flatten_dict, unflatten_dict
from tensorflow.io import gfile
from transformers.modeling_utils import dtype_byte_size
from transformers.models.switch_transformers.convert_switch_tra... | 679 | import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name_... | 679 | 1 |
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_INDEX_NAME, shard_checkpoint
__magic_name__ ... | 679 | def UpperCAmelCase__( __UpperCAmelCase : list ):
__snake_case : List[Any] = len(__UpperCAmelCase )
for _ in range(__UpperCAmelCase ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
if arr[i + 1] < arr[i]:
__snake_case , __snake_... | 679 | 1 |
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def UpperCAmelCase__( __UpperCAmelCase : int , __UpperCAmelCase : List[Any]=False ):
__snake_case : List[Any] = OmegaConf.load(__UpperCAmelCase )
if... | 679 | import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin... | 679 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mobilebert import MobileBertTokenizer
__magic_name__ = logging.get_logger(__name__)
__magic_name__... | 679 | from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
__UpperCAmelCase = 42
... | 679 | 1 |
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class __SCREAMING_SNAKE_CASE ( UpperCamelCase):
... | 679 | from __future__ import annotations
__magic_name__ = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def UpperCAmelCase__( __UpperCAmelCase : list[list[int]] , __UpperCAmelCase : list[int] , __UpperCAmelCase : list[int] ... | 679 | 1 |
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class __SCREAMING_SNAKE_CASE ( UpperCamelCase):
"""simple docstring"""
__UpperCAmelCase = "EncodecFeatureExtractor"
__UpperCAmelCase = ... | 679 | import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
__magic_name__ = logging.get_logger(__name__)
__magic_name__ ... | 679 | 1 |
from importlib import import_module
from .logging import get_logger
__magic_name__ = get_logger(__name__)
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
def __init__( self , _UpperCAmelCase , _UpperCAmelCase=None ):
__snake_case : Tuple ... | 679 | import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
__magic_name__ = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( UpperCamelCase):
"""simple docstring"""
def __init__( self , *_UpperCAmelCase , **_Upp... | 679 | 1 |
from __future__ import annotations
__magic_name__ = 1.6_021e-19 # units = C
def UpperCAmelCase__( __UpperCAmelCase : float , __UpperCAmelCase : float , __UpperCAmelCase : float , ):
if (conductivity, electron_conc, mobility).count(0 ) != 1:
... | 679 | import math
import os
import sys
def UpperCAmelCase__( __UpperCAmelCase : str ):
__snake_case : Union[str, Any] = ''
try:
with open(__UpperCAmelCase , 'rb' ) as binary_file:
__snake_case : Optional[Any] = binary_file.read()
for dat i... | 679 | 1 |
import os
from distutils.util import strtobool
def UpperCAmelCase__( __UpperCAmelCase : Tuple , __UpperCAmelCase : List[Any] ):
for e in env_keys:
__snake_case : Optional[int] = int(os.environ.get(__UpperCAmelCase , -1 ) )
if val >= 0:
... | 679 | from itertools import permutations
def UpperCAmelCase__( __UpperCAmelCase : tuple ):
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
__snake_case : Any = [7, 11, 13, 17]
for i, t... | 679 | 1 |
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def UpperCAmelCase__( __UpperCAmelCase : int ):
__snake_case : Optional[int] = prime_factors(__UpperCAmelCase )
if is_square_free(__UpperCAmelCase ):
return -1 if len(__Up... | 679 | # Function to print upper half of diamond (pyramid)
def UpperCAmelCase__( __UpperCAmelCase : List[str] ):
for i in range(0 , __UpperCAmelCase ):
for _ in range(0 , n - i - 1 ): # printing spaces
print(' ' , end='' )
for _ in range(0 ... | 679 | 1 |
import inspect
import unittest
import numpy as np
from transformers import ViTConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor
if is_flax_available()... | 679 | from timeit import timeit
def UpperCAmelCase__( __UpperCAmelCase : int ):
if number < 0:
raise ValueError('the value of input must not be negative' )
__snake_case : Dict = 0
while number:
number &= number - 1
result += 1
return result
def ... | 679 | 1 |
__magic_name__ = '''
# Transformers 설치 방법
! pip install transformers datasets
# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.
# ! pip install git+https://github.com/huggingface/transformers.git
'''
__magic_name__ = [{'''type''': '''code''', '''content''': INSTALL_CONTENT}]
__m... | 679 | import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import patch
import pyarrow as pa
imp... | 679 | 1 |
import warnings
warnings.warn(
'''memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: '''
'''`from accelerate import find_executable_batch_size` to avoid this warning.''',
FutureWarning,
)
| 679 | from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
__magic_name__ = TypeVar('''T''')
class __SCREAMING_SNAKE_CASE ( Generic[T]):
"""simple docstring"""
def __init__( self , _UpperCAmelCase ):
... | 679 | 1 |
def UpperCAmelCase__( __UpperCAmelCase : list ):
def merge(__UpperCAmelCase : list , __UpperCAmelCase : list ) -> list:
def _merge():
while left and right:
yield (left if left[0] <= right[0] else right).pop(0 )
yield from left
yie... | 679 | import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, slow
f... | 679 | 1 |
import doctest
from collections import deque
import numpy as np
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
def __init__( self ):
__snake_case : List[Any] = [2, 1, 2, -1]
__snake_case : List[Any] = [1, 2, 3, 4]
def... | 679 | import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def UpperCAmelCase__( __UpperCAmelCase : int , __UpperCAmelCase : int , __UpperCAmelCase : Any ):
... | 679 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mvp import MvpTokenizer
__magic_name_... | 679 | import logging
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertEncoder,
... | 679 | 1 |
import enum
import shutil
import sys
__magic_name__ , __magic_name__ = shutil.get_terminal_size()
__magic_name__ = {'''UP''': '''A''', '''DOWN''': '''B''', '''RIGHT''': '''C''', '''LEFT''': '''D'''}
class __SCREAMING_SNAKE_CASE ( enum.Enum):
"""s... | 679 | def UpperCAmelCase__( __UpperCAmelCase : str ):
if not all(x.isalpha() for x in string ):
raise ValueError('String must only contain alphabetic characters.' )
__snake_case : str = sorted(string.lower() )
return len(__UpperCAmelCase ) == len(set(__UpperCAmelCa... | 679 | 1 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __SCREAMING_SNAKE_CASE ( ... | 679 | from ....configuration_utils import PretrainedConfig
from ....utils import logging
__magic_name__ = logging.get_logger(__name__)
# TODO: upload to AWS
__magic_name__ = {
'''yjernite/retribert-base-uncased''': (
'''https://huggingface.co/yjernite/retribert-base-uncased/... | 679 | 1 |
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from flax.training.common_utils import shard
f... | 679 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ = {
'''configuration_biogpt''': ['''BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BioGptConfig'''],
'''tokenization_biogpt''': ['''BioG... | 679 | 1 |
from ..utils import DummyObject, requires_backends
class __SCREAMING_SNAKE_CASE ( metaclass=UpperCamelCase):
"""simple docstring"""
__UpperCAmelCase = ["torch", "transformers", "onnx"]
def __init__( self , *_UpperCAmelCase , **_UpperCAmelCase ):
... | 679 | import inspect
import unittest
from transformers import MobileViTConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_mo... | 679 | 1 |
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
__UpperCAmelCase = 42
... | 679 | def UpperCAmelCase__( __UpperCAmelCase : int | float | str ):
try:
__snake_case : int = float(__UpperCAmelCase )
except ValueError:
raise ValueError('Please enter a valid number' )
__snake_case : Any = decimal - int(__UpperCAmelCase )
if fract... | 679 | 1 |
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
def UpperCAmelCase__( ... | 679 | import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
... | 679 | 1 |
import random
import sys
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.colors import ListedColormap
__magic_name__ = '''Usage of script: script_name <size_of_canvas:int>'''
__magic_name__ = [0] * 100 + [1] * 10
random.shuffle(choice)
def Uppe... | 679 | import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name_... | 679 | 1 |
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
__magic_name__ = logging.get_logger(__name__)
def UpperCAmelCase__( __UpperCAme... | 679 | def UpperCAmelCase__( __UpperCAmelCase : list ):
__snake_case : List[Any] = len(__UpperCAmelCase )
for _ in range(__UpperCAmelCase ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
if arr[i + 1] < arr[i]:
__snake_case , __snake_... | 679 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
__magic_name__ = {
'''configuration_audio_spectrogram_transformer''': [
'''AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'... | 679 | import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin... | 679 | 1 |
def UpperCAmelCase__( __UpperCAmelCase : int = 1 , __UpperCAmelCase : int = 10_00 ):
__snake_case : List[Any] = 1
__snake_case : Any = 0
for divide_by_number in range(__UpperCAmelCase , digit + 1 ):
__snake_case : list[int] = ... | 679 | from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
__UpperCAmelCase = 42
... | 679 | 1 |
def UpperCAmelCase__( ):
__snake_case : int = []
__snake_case : str = 1
while len(__UpperCAmelCase ) < 1E6:
constant.append(str(__UpperCAmelCase ) )
i += 1
__snake_case : str = ''.join(__UpperCAmelCase )
return (
int(cons... | 679 | from __future__ import annotations
__magic_name__ = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def UpperCAmelCase__( __UpperCAmelCase : list[list[int]] , __UpperCAmelCase : list[int] , __UpperCAmelCase : list[int] ... | 679 | 1 |
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def UpperCAmelCase__( __UpperCAmelCase : List[str] , __UpperCAmelCase : Optional[Any] , __Up... | 679 | import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
__magic_name__ = logging.get_logger(__name__)
__magic_name__ ... | 679 | 1 |
import math
import os
import sys
def UpperCAmelCase__( __UpperCAmelCase : str ):
__snake_case : Union[str, Any] = ''
try:
with open(__UpperCAmelCase , 'rb' ) as binary_file:
__snake_case : Optional[Any] = binary_file.read()
for dat i... | 679 | import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
__magic_name__ = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( UpperCamelCase):
"""simple docstring"""
def __init__( self , *_UpperCAmelCase , **_Upp... | 679 | 1 |
import os
import unittest
from transformers import LayoutLMTokenizer, LayoutLMTokenizerFast
from transformers.models.layoutlm.tokenization_layoutlm import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class ... | 679 | import math
import os
import sys
def UpperCAmelCase__( __UpperCAmelCase : str ):
__snake_case : Union[str, Any] = ''
try:
with open(__UpperCAmelCase , 'rb' ) as binary_file:
__snake_case : Optional[Any] = binary_file.read()
for dat i... | 679 | 1 |
import numpy
# List of input, output pairs
__magic_name__ = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
__magic_name__ = (((515, 22, 13), 555), ((61, 35, 49), 150))
__magic_name__ = [2, 4, 1, 5]
... | 679 | from itertools import permutations
def UpperCAmelCase__( __UpperCAmelCase : tuple ):
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
__snake_case : Any = [7, 11, 13, 17]
for i, t... | 679 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {
'''naver-clova-ix/donut-base''': '''https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json''',
# See all Don... | 679 | # Function to print upper half of diamond (pyramid)
def UpperCAmelCase__( __UpperCAmelCase : List[str] ):
for i in range(0 , __UpperCAmelCase ):
for _ in range(0 , n - i - 1 ): # printing spaces
print(' ' , end='' )
for _ in range(0 ... | 679 | 1 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
__magic_name__ = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( UpperCamelCase):
"""simple docstring"""
def __init__( self , *_UpperCAmelCase... | 679 | from timeit import timeit
def UpperCAmelCase__( __UpperCAmelCase : int ):
if number < 0:
raise ValueError('the value of input must not be negative' )
__snake_case : Dict = 0
while number:
number &= number - 1
result += 1
return result
def ... | 679 | 1 |
from __future__ import annotations
import pandas as pd
def UpperCAmelCase__( __UpperCAmelCase : list[int] , __UpperCAmelCase : list[int] , __UpperCAmelCase : int ):
__snake_case : Dict = [0] * no_of_processes
__snake_case : Any = [0] * no_of_... | 679 | import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import patch
import pyarrow as pa
imp... | 679 | 1 |
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMi... | 679 | from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
__magic_name__ = TypeVar('''T''')
class __SCREAMING_SNAKE_CASE ( Generic[T]):
"""simple docstring"""
def __init__( self , _UpperCAmelCase ):
... | 679 | 1 |
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = '''T5Config'''
class __SCREAMING_SNAKE_CASE ( ... | 679 | import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, slow
f... | 679 | 1 |
import collections
import importlib.util
import os
import re
from pathlib import Path
__magic_name__ = '''src/transformers'''
# Matches is_xxx_available()
__magic_name__ = re.compile(r'''is\_([a-z_]*)_available()''')
# Catches a one-line _import_struct = {xxx}
__magic_name__ ... | 679 | import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def UpperCAmelCase__( __UpperCAmelCase : int , __UpperCAmelCase : int , __UpperCAmelCase : Any ):
... | 679 | 1 |
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE ( UpperCamelCase):
"""simple docstring"""
__UpperCAmelCase = (DDIMParallelScheduler,)
__UpperCAmelCase = (("eta", 0.0), ("num_inf... | 679 | import logging
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertEncoder,
... | 679 | 1 |
import os
import unittest
from huggingface_hub.utils import are_progress_bars_disabled
import transformers.models.bart.tokenization_bart
from transformers import logging
from transformers.testing_utils import CaptureLogger, mockenv, mockenv_context
from transformers.utils.logging import disable_progress_bar, enable_p... | 679 | def UpperCAmelCase__( __UpperCAmelCase : str ):
if not all(x.isalpha() for x in string ):
raise ValueError('String must only contain alphabetic characters.' )
__snake_case : str = sorted(string.lower() )
return len(__UpperCAmelCase ) == len(set(__UpperCAmelCa... | 679 | 1 |
from typing import List, Optional, Tuple, Union
import torch
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class __SCREAMING_SNAKE_CASE ( UpperCamelCase):
"""simple docstring"""
def __init_... | 679 | from ....configuration_utils import PretrainedConfig
from ....utils import logging
__magic_name__ = logging.get_logger(__name__)
# TODO: upload to AWS
__magic_name__ = {
'''yjernite/retribert-base-uncased''': (
'''https://huggingface.co/yjernite/retribert-base-uncased/... | 679 | 1 |
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
__magic_name__ = (3, 9, -11, 0, 7, 5, 1, -1)
__magic_name__ = (4, 6, 2, 0, 8, 10, 3, -2)
@dataclass
class __SCREAMING_SNAKE_CASE :
"""simple docs... | 679 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ = {
'''configuration_biogpt''': ['''BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BioGptConfig'''],
'''tokenization_biogpt''': ['''BioG... | 679 | 1 |
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
__magic_name__ = argparse.ArgumentParser('''Stable Diffusion script with intel optimization''', add_help=False)
parser.add_argument('''--dpm''', action... | 679 | import inspect
import unittest
from transformers import MobileViTConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_mo... | 679 | 1 |
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
__magic_name__ = logging.get_logger(__name__)
def UpperCAmelCase__( __UpperCAmelCase : Any ):
__snake_cas... | 679 | def UpperCAmelCase__( __UpperCAmelCase : int | float | str ):
try:
__snake_case : int = float(__UpperCAmelCase )
except ValueError:
raise ValueError('Please enter a valid number' )
__snake_case : Any = decimal - int(__UpperCAmelCase )
if fract... | 679 | 1 |
from __future__ import annotations
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
def __init__( self , _UpperCAmelCase ):
__snake_case : Union[str, Any] = order
# a_{0} ... a_{k}
__snake_case : Optional[Any] = [1.0] + [0... | 679 | import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
... | 679 | 1 |
import math
import time
from typing import Dict, List, Optional
from torch.utils.data import Dataset
from transformers import SeqaSeqTrainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_model ... | 679 | import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name_... | 679 | 1 |
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
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {
'''mi... | 679 | def UpperCAmelCase__( __UpperCAmelCase : list ):
__snake_case : List[Any] = len(__UpperCAmelCase )
for _ in range(__UpperCAmelCase ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
if arr[i + 1] < arr[i]:
__snake_case , __snake_... | 679 | 1 |
def UpperCAmelCase__( __UpperCAmelCase : int ):
if n == 1 or not isinstance(__UpperCAmelCase , __UpperCAmelCase ):
return 0
elif n == 2:
return 1
else:
__snake_case : List[Any] = [0, 1]
for i in range(2 , n + 1 ):
sequence.... | 679 | import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin... | 679 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {
'''roberta-base''': '''https://huggi... | 679 | from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
__UpperCAmelCase = 42
... | 679 | 1 |
def UpperCAmelCase__( __UpperCAmelCase : int , __UpperCAmelCase : float , __UpperCAmelCase : float ):
return round(float(moles / volume ) * nfactor )
def UpperCAmelCase__( __UpperCAmelCase : float , __UpperCAmelCase : float , __... | 679 | from __future__ import annotations
__magic_name__ = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def UpperCAmelCase__( __UpperCAmelCase : list[list[int]] , __UpperCAmelCase : list[int] , __UpperCAmelCase : list[int] ... | 679 | 1 |
def UpperCAmelCase__( __UpperCAmelCase : float , __UpperCAmelCase : float ):
if density <= 0:
raise ValueError('Impossible fluid density' )
if bulk_modulus <= 0:
raise ValueError('Impossible bulk modulus' )
return (bulk_modulus / density) ** 0.5
if __name__ ... | 679 | import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
__magic_name__ = logging.get_logger(__name__)
__magic_name__ ... | 679 | 1 |
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
__magic_name__ = argparse.ArgumentParser()
parser.add_argument('''--dump_path''', default=None, type=str, requ... | 679 | import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
__magic_name__ = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( UpperCamelCase):
"""simple docstring"""
def __init__( self , *_UpperCAmelCase , **_Upp... | 679 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__magic_name__ = {
'''configuration_lilt''': ['''LILT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LiltConfig'''],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAva... | 679 | import math
import os
import sys
def UpperCAmelCase__( __UpperCAmelCase : str ):
__snake_case : Union[str, Any] = ''
try:
with open(__UpperCAmelCase , 'rb' ) as binary_file:
__snake_case : Optional[Any] = binary_file.read()
for dat i... | 679 | 1 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimens... | 679 | from itertools import permutations
def UpperCAmelCase__( __UpperCAmelCase : tuple ):
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
__snake_case : Any = [7, 11, 13, 17]
for i, t... | 679 | 1 |
from __future__ import annotations
from typing import Generic, TypeVar
__magic_name__ = TypeVar('''T''')
class __SCREAMING_SNAKE_CASE ( Generic[T]):
"""simple docstring"""
def __init__( self , _UpperCAmelCase ):
__snake_case : int = dat... | 679 | # Function to print upper half of diamond (pyramid)
def UpperCAmelCase__( __UpperCAmelCase : List[str] ):
for i in range(0 , __UpperCAmelCase ):
for _ in range(0 , n - i - 1 ): # printing spaces
print(' ' , end='' )
for _ in range(0 ... | 679 | 1 |
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor
from .... | 679 | from timeit import timeit
def UpperCAmelCase__( __UpperCAmelCase : int ):
if number < 0:
raise ValueError('the value of input must not be negative' )
__snake_case : Dict = 0
while number:
number &= number - 1
result += 1
return result
def ... | 679 | 1 |
import logging
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertEncoder,
... | 679 | import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import patch
import pyarrow as pa
imp... | 679 | 1 |
from argparse import ArgumentParser
from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
__magic_name__ = logging.get_logger(__name__) # pylint: disable=invalid-name
def UpperCAmelCase_... | 679 | from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
__magic_name__ = TypeVar('''T''')
class __SCREAMING_SNAKE_CASE ( Generic[T]):
"""simple docstring"""
def __init__( self , _UpperCAmelCase ):
... | 679 | 1 |
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.default_plann... | 679 | import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, slow
f... | 679 | 1 |
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
__magic_name__ = loggi... | 679 | import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def UpperCAmelCase__( __UpperCAmelCase : int , __UpperCAmelCase : int , __UpperCAmelCase : Any ):
... | 679 | 1 |
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__magic_name__ = get_tests_dir('''fixtures/spiece.m... | 679 | import logging
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertEncoder,
... | 679 | 1 |
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
__UpperCAmelCase = field(
default="codeparrot/codeparrot" , metadata={"help": "Model name or path of model to be trained."})
__Uppe... | 679 | def UpperCAmelCase__( __UpperCAmelCase : str ):
if not all(x.isalpha() for x in string ):
raise ValueError('String must only contain alphabetic characters.' )
__snake_case : str = sorted(string.lower() )
return len(__UpperCAmelCase ) == len(set(__UpperCAmelCa... | 679 | 1 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_... | 679 | from ....configuration_utils import PretrainedConfig
from ....utils import logging
__magic_name__ = logging.get_logger(__name__)
# TODO: upload to AWS
__magic_name__ = {
'''yjernite/retribert-base-uncased''': (
'''https://huggingface.co/yjernite/retribert-base-uncased/... | 679 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__magic_name__ = {
'''configuration_rembert''': ['''REMBERT_PRETRAINED_CONFIG_... | 679 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ = {
'''configuration_biogpt''': ['''BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BioGptConfig'''],
'''tokenization_biogpt''': ['''BioG... | 679 | 1 |
from __future__ import annotations
from typing import Any
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
def __init__( self , _UpperCAmelCase ):
__snake_case : Union[str, Any] = num_of_nodes
__snake_case : list[list[int]] = []
... | 679 | import inspect
import unittest
from transformers import MobileViTConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_mo... | 679 | 1 |
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_common import FlaxModel... | 679 | def UpperCAmelCase__( __UpperCAmelCase : int | float | str ):
try:
__snake_case : int = float(__UpperCAmelCase )
except ValueError:
raise ValueError('Please enter a valid number' )
__snake_case : Any = decimal - int(__UpperCAmelCase )
if fract... | 679 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__magic_name__ = {
'''configuration_clip''': [
'''CLIP... | 679 | import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
... | 679 | 1 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | 679 | import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name_... | 679 | 1 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import F... | 679 | def UpperCAmelCase__( __UpperCAmelCase : list ):
__snake_case : List[Any] = len(__UpperCAmelCase )
for _ in range(__UpperCAmelCase ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
if arr[i + 1] < arr[i]:
__snake_case , __snake_... | 679 | 1 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, slow
f... | 679 | import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin... | 679 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ = {
'''configuration_biogpt''': ['''BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BioGptConfig'''],
'''tokenization_biogpt''': ['''BioG... | 679 | from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
__UpperCAmelCase = 42
... | 679 | 1 |
def UpperCAmelCase__( __UpperCAmelCase : str ):
if not all(x.isalpha() for x in string ):
raise ValueError('String must only contain alphabetic characters.' )
__snake_case : str = sorted(string.lower() )
return len(__UpperCAmelCase ) == len(set(__UpperCAmelCa... | 679 | from __future__ import annotations
__magic_name__ = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def UpperCAmelCase__( __UpperCAmelCase : list[list[int]] , __UpperCAmelCase : list[int] , __UpperCAmelCase : list[int] ... | 679 | 1 |
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {'''vocab_file''': '''vocab.json'''}
__magic_name__ = {
... | 679 | import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
__magic_name__ = logging.get_logger(__name__)
__magic_name__ ... | 679 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__magic_name__ = {
'''configuration_perceiver''': ['''PERCEIVER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Perce... | 679 | import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
__magic_name__ = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( UpperCamelCase):
"""simple docstring"""
def __init__( self , *_UpperCAmelCase , **_Upp... | 679 | 1 |
import argparse
import tensorflow as tf
import torch
from transformers import BertConfig, BertForMaskedLM
from transformers.models.bert.modeling_bert import (
BertIntermediate,
BertLayer,
BertOutput,
BertPooler,
BertSelfAttention,
BertSelfOutput,
)
from transformers.utils import logging
logg... | 679 | import math
import os
import sys
def UpperCAmelCase__( __UpperCAmelCase : str ):
__snake_case : Union[str, Any] = ''
try:
with open(__UpperCAmelCase , 'rb' ) as binary_file:
__snake_case : Optional[Any] = binary_file.read()
for dat i... | 679 | 1 |
from __future__ import annotations
def UpperCAmelCase__( __UpperCAmelCase : float , __UpperCAmelCase : float , __UpperCAmelCase : float ):
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError('One and only one argument must be 0' )
if resi... | 679 | from itertools import permutations
def UpperCAmelCase__( __UpperCAmelCase : tuple ):
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
__snake_case : Any = [7, 11, 13, 17]
for i, t... | 679 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__magic_name__ = {
'''configuration_mobilevit''': ['''MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MobileViTConf... | 679 | # Function to print upper half of diamond (pyramid)
def UpperCAmelCase__( __UpperCAmelCase : List[str] ):
for i in range(0 , __UpperCAmelCase ):
for _ in range(0 , n - i - 1 ): # printing spaces
print(' ' , end='' )
for _ in range(0 ... | 679 | 1 |
import math
def UpperCAmelCase__( __UpperCAmelCase : int ):
__snake_case : Dict = [True] * n
__snake_case : List[Any] = False
__snake_case : Tuple = False
__snake_case : List[str] = True
for i in range(3 , int(n**0.5 + 1 ... | 679 | from timeit import timeit
def UpperCAmelCase__( __UpperCAmelCase : int ):
if number < 0:
raise ValueError('the value of input must not be negative' )
__snake_case : Dict = 0
while number:
number &= number - 1
result += 1
return result
def ... | 679 | 1 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
__magic_name__ = pytest.mark.integration
@pytest.mark.parametrize('path' , ['paws'... | 679 | import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import patch
import pyarrow as pa
imp... | 679 | 1 |
import sacrebleu as scb
from packaging import version
from sacrebleu import TER
import datasets
__magic_name__ = '''\
@inproceedings{snover-etal-2006-study,
title = "A Study of Translation Edit Rate with Targeted Human Annotation",
author = "Snover, Matthew and
Dorr, Bonnie and
... | 679 | from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
__magic_name__ = TypeVar('''T''')
class __SCREAMING_SNAKE_CASE ( Generic[T]):
"""simple docstring"""
def __init__( self , _UpperCAmelCase ):
... | 679 | 1 |
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class __SCREAMING_SNAKE_CASE ( unittest.TestCase):
"""simple docstring"""
def lowercase_ ( self ):
__snake_case ... | 679 | import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, slow
f... | 679 | 1 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import torch
if ... | 679 | import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def UpperCAmelCase__( __UpperCAmelCase : int , __UpperCAmelCase : int , __UpperCAmelCase : Any ):
... | 679 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {
'''facebook/s2t-small-librispeech-asr''': (
'''https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/confi... | 679 | import logging
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertEncoder,
... | 679 | 1 |
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {
'''google/umt5-small''': '''https://huggingface.co/google... | 679 | def UpperCAmelCase__( __UpperCAmelCase : str ):
if not all(x.isalpha() for x in string ):
raise ValueError('String must only contain alphabetic characters.' )
__snake_case : str = sorted(string.lower() )
return len(__UpperCAmelCase ) == len(set(__UpperCAmelCa... | 679 | 1 |
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