code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
a__ : Optional[int] = re.compile(R'\b(a|an|the)\b', re.UNICODE)
a__ : int = None
def _UpperCamelCase ( ) -> Dict... | 80 |
'''simple docstring'''
from __future__ import annotations
def _UpperCamelCase ( __A ) -> float:
'''simple docstring'''
UpperCamelCase__ = 0.00
UpperCamelCase__ = 0
for resistor in resistors:
if resistor <= 0:
... | 80 | 1 |
'''simple docstring'''
def _UpperCamelCase ( __A ) -> int:
'''simple docstring'''
if not isinstance(__A , __A ) or number < 0:
raise ValueError("Input must be a non-negative integer" )
UpperCamelCase__ = 0
while number:
... | 80 |
'''simple docstring'''
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class lowercase_ ( ... | 80 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a__ : Union[str, Any] = {'... | 80 |
'''simple docstring'''
from ....utils import logging
a__ : Optional[Any] = logging.get_logger(__name__)
class lowercase_ ( a__ ):
def __init__( self , a , a=None , a=20_48 ):
UpperCamelCase__ = config.__dict__
UpperC... | 80 | 1 |
'''simple docstring'''
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def _UpperCamelCase ( __A ) -> Optional[Any]:
'''simple docstring'''
... | 80 |
'''simple docstring'''
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
a__ : Tuple = {'UserAgent': UserAgent().random}
def _UpperCamelCase ( __A ) -> dict:
'''simple docstr... | 80 | 1 |
'''simple docstring'''
import os
import sys
a__ : Tuple = os.path.join(os.path.dirname(__file__), 'src')
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,
AutoModelF... | 80 |
'''simple docstring'''
from __future__ import annotations
def _UpperCamelCase ( __A , __A , __A ) -> dict[str, float]:
'''simple docstring'''
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError("One and only one argument m... | 80 | 1 |
'''simple docstring'''
from math import pi, sqrt
def _UpperCamelCase ( __A ) -> float:
'''simple docstring'''
if num <= 0:
raise ValueError("math domain error" )
if num > 171.5:
raise OverflowError("math range error" )
elif ... | 80 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a__ : Union[str, Any] = {'... | 80 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_mode... | 80 |
'''simple docstring'''
from __future__ import annotations
import math
def _UpperCamelCase ( __A , __A ) -> list:
'''simple docstring'''
if len(__A ) != 2 or len(a[0] ) != 2 or len(__A ) != 2 or len(b[0] ) != 2:
raise Exception("Matric... | 80 | 1 |
'''simple docstring'''
from __future__ import annotations
import sys
from collections import deque
from typing import Generic, TypeVar
a__ : List[str] = TypeVar('T')
class lowercase_ ( Generic[T] ):
__UpperCAmelCase = 42 # Cache store of keys
__UpperCAmelCase ... | 80 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
... | 80 | 1 |
'''simple docstring'''
# Copyright 2021 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... | 80 |
'''simple docstring'''
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import Toke... | 80 | 1 |
'''simple docstring'''
def _UpperCamelCase ( __A , __A ) -> int:
'''simple docstring'''
return x if y == 0 else greatest_common_divisor(__A , x % y )
def _UpperCamelCase ( __A , __A ) -> int:
'''simple docstring'''... | 80 |
'''simple docstring'''
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
a__ : Optional[int] = re.compile(R'\b(a|an|the)\b', re.UNICODE)
a__ : int = None
def _UpperCamelCase ( ) -> Dict... | 80 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModel... | 80 |
'''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager im... | 80 | 1 |
'''simple docstring'''
import math
import sys
def _UpperCamelCase ( __A ) -> str:
'''simple docstring'''
UpperCamelCase__ = ""
try:
with open(__A , "rb" ) as binary_file:
UpperCamelCase__ = binary... | 80 |
'''simple docstring'''
from __future__ import annotations
import math
def _UpperCamelCase ( __A , __A , __A , __A , __A ) -> int:
'''simple docstring'''
if depth < 0:
raise ValueError("Depth cannot be less than 0" )
... | 80 | 1 |
'''simple docstring'''
a__ : List[Any] = {
'Pillow': 'Pillow<10.0.0',
'accelerate': 'accelerate>=0.20.3',
'av': 'av==9.2.0',
'beautifulsoup4': 'beautifulsoup4',
'black': 'black~=23.1',
'codecarbon': 'codecarbon==1.2.0',
'cookiecutter': 'cookiecutter==1.7.3',
'... | 80 |
'''simple docstring'''
def _UpperCamelCase ( __A ) -> int:
'''simple docstring'''
UpperCamelCase__ = 0
while num > 0:
digit_sum += num % 10
num //= 10
return digit_sum
def _UpperCamelCase ( __A = 100 ) ... | 80 | 1 |
'''simple docstring'''
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class lowercase_ ( nn.Module ):
__UpperCAmelCase = 42
__UpperCAmelCase = 42
... | 80 |
'''simple docstring'''
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def _UpperCamelCase ... | 80 | 1 |
'''simple docstring'''
# Copyright 2021 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... | 80 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : Any = logging.get_logger(__name__)
a__ : str = {
'SCUT-DLVCLab/lilt-roberta-en-base': (
'https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/res... | 80 | 1 |
'''simple docstring'''
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
Au... | 80 |
'''simple docstring'''
a__ : Union[str, Any] = [sum(int(c, 1_0) ** 2 for c in i.__str__()) for i in range(1_0_0_0_0_0)]
def _UpperCamelCase ( __A ) -> int:
'''simple docstring'''
UpperCamelCase__ = 0
while number:
# In... | 80 | 1 |
'''simple docstring'''
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis_float32 (there's also the fix_lavis branch)
# also note: to convert Vicuna checkpoints... | 80 |
'''simple docstring'''
import fire
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save
def _UpperCamelCase ( __A , __A , __A=1024 , __A=1024 , __A=False , **__A ... | 80 | 1 |
'''simple docstring'''
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def _UpperCamelCase ( __A , __A , __A = 1 / sqrt(2 ) ) -> IIRFilter:
'''simple docstring'''
UpperCamelCase__ = tau * frequency / ... | 80 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer import R... | 80 | 1 |
'''simple docstring'''
from __future__ import annotations
def _UpperCamelCase ( __A , __A = None , __A = None ) -> None:
'''simple docstring'''
if start is None:
UpperCamelCase__ = 0
if end is None:
UpperCamel... | 80 |
'''simple docstring'''
import os
from typing import List, Optional, Union
from ...tokenization_utils import PreTrainedTokenizer
from ...tokenization_utils_base import AddedToken
from ...utils import logging
a__ : List[str] = logging.get_logger(__name__)
a__ : Optional[int] = ... | 80 | 1 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class lowercase_ ( unittest.TestCase ):
... | 80 |
'''simple docstring'''
from math import factorial, pi
def _UpperCamelCase ( __A , __A = 30 ) -> float:
'''simple docstring'''
if not isinstance(__A , (int, float) ):
raise ValueError("maclaurin_sin() requires either an int or float for t... | 80 | 1 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
UpperCAmelCase__ = logging.get_logger("transformers.models.speecht5")
def _a ( a :Any , a :List[str] , a :Tup... | 0 |
'''simple docstring'''
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
... | 80 | 0 |
'''simple docstring'''
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class __A ( unittest.TestCase , UpperCamelCase__ ):
def _lowercase (self : Any ):
UpperCAmelCase_ = load_tool("text-classification"... | 1 |
'''simple docstring'''
# Copyright 2021 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... | 80 | 0 |
'''simple docstring'''
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create simlink
# import classes
... | 2 |
'''simple docstring'''
from __future__ import annotations
def _UpperCamelCase ( __A ) -> float:
'''simple docstring'''
UpperCamelCase__ = 0.00
UpperCamelCase__ = 0
for resistor in resistors:
if resistor <= 0:
... | 80 | 0 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case__ ):
'''simple docstring'''
if length <= 0 or not isinstance(snake_case__ , snake_case__ ):
raise ValueError('''Length must be a positive integer.''' )
return [n * (2 * n - 1) for n in rang... | 3 |
'''simple docstring'''
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class lowercase_ ( ... | 80 | 0 |
'''simple docstring'''
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils ... | 4 |
'''simple docstring'''
from ....utils import logging
a__ : Optional[Any] = logging.get_logger(__name__)
class lowercase_ ( a__ ):
def __init__( self , a , a=None , a=20_48 ):
UpperCamelCase__ = config.__dict__
UpperC... | 80 | 0 |
import math
def UpperCAmelCase_ ( __snake_case , __snake_case ) -> float:
"""simple docstring"""
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''' )
# handling of negative values of initial intensity
if angle < 0 or angle... | 5 |
'''simple docstring'''
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
a__ : Tuple = {'UserAgent': UserAgent().random}
def _UpperCamelCase ( __A ) -> dict:
'''simple docstr... | 80 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A : Tuple = logging.get_logger(__name__)
A : Dict = {
'Salesforce/blip-vqa-base': 'https://huggingface.co/Salesforce/blip-vqa-base/resolve/main/config.json',
'Salesf... | 6 |
'''simple docstring'''
from __future__ import annotations
def _UpperCamelCase ( __A , __A , __A ) -> dict[str, float]:
'''simple docstring'''
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError("One and only one argument m... | 80 | 0 |
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructureLi... | 7 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a__ : Union[str, Any] = {'... | 80 | 0 |
import json
import os
import torch
from diffusers import UNetaDModel
os.makedirs('''hub/hopper-medium-v2/unet/hor32''', exist_ok=True)
os.makedirs('''hub/hopper-medium-v2/unet/hor128''', exist_ok=True)
os.makedirs('''hub/hopper-medium-v2/value_function''', exist_ok=True)
def __SCREAMING_SNAKE... | 8 |
'''simple docstring'''
from __future__ import annotations
import math
def _UpperCamelCase ( __A , __A ) -> list:
'''simple docstring'''
if len(__A ) != 2 or len(a[0] ) != 2 or len(__A ) != 2 or len(b[0] ) != 2:
raise Exception("Matric... | 80 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCAmelCase : int =logging.get_logger(__name__)
__lowerCAmelCase : List[str] ={
'YituTech/conv-bert-base': 'https://hug... | 9 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
... | 80 | 0 |
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
from transformers.configura... | 10 |
'''simple docstring'''
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import Toke... | 80 | 0 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...... | 11 |
'''simple docstring'''
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
a__ : Optional[int] = re.compile(R'\b(a|an|the)\b', re.UNICODE)
a__ : int = None
def _UpperCamelCase ( ) -> Dict... | 80 | 0 |
from __future__ import annotations
from math import pi, sqrt
def lowerCamelCase__ ( A__ : float , A__ : float ):
'''simple docstring'''
if inductance <= 0:
raise ValueError("""Inductance cannot be 0 or negative""" )
elif capaci... | 12 |
'''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager im... | 80 | 0 |
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class __lowercase ( nn.Module ):
"""simple docstring"""
_UpperCAmelCase : int
_UpperCAmelCase : i... | 13 |
'''simple docstring'''
from __future__ import annotations
import math
def _UpperCamelCase ( __A , __A , __A , __A , __A ) -> int:
'''simple docstring'''
if depth < 0:
raise ValueError("Depth cannot be less than 0" )
... | 80 | 0 |
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
_lowerCamelCase : Tu... | 14 |
'''simple docstring'''
def _UpperCamelCase ( __A ) -> int:
'''simple docstring'''
UpperCamelCase__ = 0
while num > 0:
digit_sum += num % 10
num //= 10
return digit_sum
def _UpperCamelCase ( __A = 100 ) ... | 80 | 0 |
from typing import List
import numpy as np
def UpperCAmelCase ( a_ ) -> int:
"""simple docstring"""
__A = {key: len(a_ ) for key, value in gen_kwargs.items() if isinstance(a_ , a_ )}
if len(set(lists_lengths.values() ) ) > 1:
raise RuntimeError... | 15 |
'''simple docstring'''
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def _UpperCamelCase ... | 80 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
lowerCAmelCase_ = TypeVar('T')
lowerCAmelCase_ = TypeVar('U')
class __A ( Generic[T, U] ):
'''simple doc... | 16 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : Any = logging.get_logger(__name__)
a__ : str = {
'SCUT-DLVCLab/lilt-roberta-en-base': (
'https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/res... | 80 | 0 |
"""simple docstring"""
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
_a = 50_00_00
_a , _a = os.path.split(__file__)
_a = os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILEN... | 17 |
'''simple docstring'''
a__ : Union[str, Any] = [sum(int(c, 1_0) ** 2 for c in i.__str__()) for i in range(1_0_0_0_0_0)]
def _UpperCamelCase ( __A ) -> int:
'''simple docstring'''
UpperCamelCase__ = 0
while number:
# In... | 80 | 0 |
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
__lowerCamelCase : Union[str, Any] = TypeVar('''T''')
def _snake_case ( lowerCAmelCase : int ):
"""simple docstring"""
return (position - 1) // 2
def _snake_case ( lower... | 18 |
'''simple docstring'''
import fire
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save
def _UpperCamelCase ( __A , __A , __A=1024 , __A=1024 , __A=False , **__A ... | 80 | 0 |
import argparse
import os
import re
__A ='''src/diffusers'''
# Pattern that looks at the indentation in a line.
__A =re.compile(R'''^(\s*)\S''')
# Pattern that matches `"key":" and puts `key` in group 0.
__A =re.compile(R'''^\s*"([^"]+)":''')
# Pattern that matches `_import_structure["key"]` and puts `key`... | 19 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer import R... | 80 | 0 |
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils import require_token... | 20 |
'''simple docstring'''
import os
from typing import List, Optional, Union
from ...tokenization_utils import PreTrainedTokenizer
from ...tokenization_utils_base import AddedToken
from ...utils import logging
a__ : List[str] = logging.get_logger(__name__)
a__ : Optional[int] = ... | 80 | 0 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
SCREAMING_SNAKE_CASE : str = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : List[Any] = {
"CarlCochet/trajectory-transformer-halfcheetah-medium-v2": (
"https://huggingfac... | 21 |
'''simple docstring'''
from math import factorial, pi
def _UpperCamelCase ( __A , __A = 30 ) -> float:
'''simple docstring'''
if not isinstance(__A , (int, float) ):
raise ValueError("maclaurin_sin() requires either an int or float for t... | 80 | 0 |
'''simple docstring'''
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
__SCREAMING_SNAKE_CASE :Any = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE ... | 22 |
'''simple docstring'''
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
... | 80 | 0 |
'''simple docstring'''
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def snake_case_ ( _lowerCAmelCase : int ) -> int:
UpperCAmelCase : Union[str, Any] = prime_factors(_lowerCAmelCase )
if is... | 23 |
'''simple docstring'''
# Copyright 2021 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... | 80 | 0 |
from __future__ import annotations
def lowerCamelCase__ ( snake_case_ : list[int] , snake_case_ : int ) -> list[list[int]]:
__snake_case = []
__snake_case = []
__snake_case = 0
__snake_case ... | 24 |
'''simple docstring'''
from __future__ import annotations
def _UpperCamelCase ( __A ) -> float:
'''simple docstring'''
UpperCamelCase__ = 0.00
UpperCamelCase__ = 0
for resistor in resistors:
if resistor <= 0:
... | 80 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase__ : Lis... | 25 |
'''simple docstring'''
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class lowercase_ ( ... | 80 | 0 |
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
import sqlitea
import s... | 26 |
'''simple docstring'''
from ....utils import logging
a__ : Optional[Any] = logging.get_logger(__name__)
class lowercase_ ( a__ ):
def __init__( self , a , a=None , a=20_48 ):
UpperCamelCase__ = config.__dict__
UpperC... | 80 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowercase : Dict = {
'configuration_luke': ['LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LukeConfig'],
'tokenization_luke': ['LukeTokenizer'],
}
try:
if ... | 27 |
'''simple docstring'''
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
a__ : Tuple = {'UserAgent': UserAgent().random}
def _UpperCamelCase ( __A ) -> dict:
'''simple docstr... | 80 | 0 |
'''simple docstring'''
import torch
from torch import nn
class SCREAMING_SNAKE_CASE ( nn.Module ):
"""simple docstring"""
def __init__( self : List[Any] , UpperCamelCase__ : Dict , UpperCamelCase__ : List[Any] , UpperCamel... | 28 |
'''simple docstring'''
from __future__ import annotations
def _UpperCamelCase ( __A , __A , __A ) -> dict[str, float]:
'''simple docstring'''
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError("One and only one argument m... | 80 | 0 |
import math
import sys
def lowercase__ ( __snake_case : str ):
'''simple docstring'''
UpperCAmelCase_ : List[str] = ''
try:
with open(__snake_case , 'rb' ) as binary_file:
UpperCAmelCa... | 29 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a__ : Union[str, Any] = {'... | 80 | 0 |
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
'huggingface/time-series-transformer-tourism-monthly': (
'https://huggingface.co/huggingface/time-series-transf... | 30 |
'''simple docstring'''
from __future__ import annotations
import math
def _UpperCamelCase ( __A , __A ) -> list:
'''simple docstring'''
if len(__A ) != 2 or len(a[0] ) != 2 or len(__A ) != 2 or len(b[0] ) != 2:
raise Exception("Matric... | 80 | 0 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase_ ( _UpperCAmelCase : Dict , _UpperCAmelCase : Dict , _UpperCAmelCase : str , _UpperCAmelCase : Optional[int] ) -> Any: # noqa: E741
"""simple docstring"""
while r -... | 31 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
... | 80 | 0 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
)
from diffusers.utils import load_nump... | 32 |
'''simple docstring'''
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import Toke... | 80 | 0 |
"""simple docstring"""
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_torch_available
from transformers.testing_utils import require_torch, torch_device
if is_torch_available():
from transformers import PyTorchBenchmark,... | 33 |
'''simple docstring'''
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
a__ : Optional[int] = re.compile(R'\b(a|an|the)\b', re.UNICODE)
a__ : int = None
def _UpperCamelCase ( ) -> Dict... | 80 | 0 |
'''simple docstring'''
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _conc... | 34 |
'''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager im... | 80 | 0 |
'''simple docstring'''
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class UpperCAmelCase_ ( _a ):
"""simple docstring"""
lowercase = CustomTokenizer
pass
| 35 |
'''simple docstring'''
from __future__ import annotations
import math
def _UpperCamelCase ( __A , __A , __A , __A , __A ) -> int:
'''simple docstring'''
if depth < 0:
raise ValueError("Depth cannot be less than 0" )
... | 80 | 0 |
import argparse
import json
import subprocess
def A ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : Any = []
_lowerCAmelCase : Optional[int] = (
F"curl -H \"Accept: application/vnd.github+j... | 36 |
'''simple docstring'''
def _UpperCamelCase ( __A ) -> int:
'''simple docstring'''
UpperCamelCase__ = 0
while num > 0:
digit_sum += num % 10
num //= 10
return digit_sum
def _UpperCamelCase ( __A = 100 ) ... | 80 | 0 |
'''simple docstring'''
import argparse
import requests
import torch
from PIL import Image
from transformers import ViTMAEConfig, ViTMAEForPreTraining, ViTMAEImageProcessor
def _SCREAMING_SNAKE_CASE ( UpperCamelCase ):
"""simple docstring"""
if "cls_token" in name:
lowerCAm... | 37 |
'''simple docstring'''
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def _UpperCamelCase ... | 80 | 0 |
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase_ : List[Any] = logging.get_logger(__name__)
UpperCAmelCase_ : Any = {'''vocab_file''': '''vocab.json'''}
UpperCAmelCase_ : ... | 38 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : Any = logging.get_logger(__name__)
a__ : str = {
'SCUT-DLVCLab/lilt-roberta-en-base': (
'https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/res... | 80 | 0 |
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from .... | 39 |
'''simple docstring'''
a__ : Union[str, Any] = [sum(int(c, 1_0) ** 2 for c in i.__str__()) for i in range(1_0_0_0_0_0)]
def _UpperCamelCase ( __A ) -> int:
'''simple docstring'''
UpperCamelCase__ = 0
while number:
# In... | 80 | 0 |
"""simple docstring"""
import pytest
from datasets import inspect_metric, list_metrics, load_metric
@pytest.fixture
def lowercase ( A_ )-> List[Any]:
'''simple docstring'''
monkeypatch.setattr("datasets.utils.deprecation_utils._emitted_deprecation_w... | 40 |
'''simple docstring'''
import fire
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save
def _UpperCamelCase ( __A , __A , __A=1024 , __A=1024 , __A=False , **__A ... | 80 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_A : Dict ... | 41 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer import R... | 80 | 0 |
'''simple docstring'''
import math
class __UpperCAmelCase :
def lowerCamelCase ( self , lowerCAmelCase_ , lowerCAmelCase_ ):
"""simple docstring"""
_snake_case = 0.0
_snake_case = 0.0
for i in range(len(lower... | 42 |
'''simple docstring'''
import os
from typing import List, Optional, Union
from ...tokenization_utils import PreTrainedTokenizer
from ...tokenization_utils_base import AddedToken
from ...utils import logging
a__ : List[str] = logging.get_logger(__name__)
a__ : Optional[int] = ... | 80 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
Stable... | 43 |
'''simple docstring'''
from math import factorial, pi
def _UpperCamelCase ( __A , __A = 30 ) -> float:
'''simple docstring'''
if not isinstance(__A , (int, float) ):
raise ValueError("maclaurin_sin() requires either an int or float for t... | 80 | 0 |
"""simple docstring"""
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_flax_... | 44 |
'''simple docstring'''
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
... | 80 | 0 |
"""simple docstring"""
import importlib
import math
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Tuple, Union
import flax
import jax.numpy as jnp
from ..utils import BaseOutput
lowercase_ = "scheduler_config.json"
clas... | 45 |
'''simple docstring'''
# Copyright 2021 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... | 80 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import GPTaLMHeadModel, RobertaForMaskedLM
if __name__ == "__main__":
SCREAMING_SNAKE_CASE__ = argparse.ArgumentParser(
description=(
"Extraction some layers of the full RobertaForMaskedLM or GPT2... | 46 |
'''simple docstring'''
from __future__ import annotations
def _UpperCamelCase ( __A ) -> float:
'''simple docstring'''
UpperCamelCase__ = 0.00
UpperCamelCase__ = 0
for resistor in resistors:
if resistor <= 0:
... | 80 | 0 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbosity... | 47 |
'''simple docstring'''
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class lowercase_ ( ... | 80 | 0 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCamelCase__ (lowerCAmelCase__ ):
'''simple docstring'''
lowerCamelCase_ : Optional[int] = ["""image_processor""", """tokenizer"""]
... | 48 |
'''simple docstring'''
from ....utils import logging
a__ : Optional[Any] = logging.get_logger(__name__)
class lowercase_ ( a__ ):
def __init__( self , a , a=None , a=20_48 ):
UpperCamelCase__ = config.__dict__
UpperC... | 80 | 0 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
__snake_case :Any = {'''tokenization_tapex''': ['''TapexTokenizer''']}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
__snake_case :str = _LazyModule(__name__, globals()['... | 49 |
'''simple docstring'''
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
a__ : Tuple = {'UserAgent': UserAgent().random}
def _UpperCamelCase ( __A ) -> dict:
'''simple docstr... | 80 | 0 |
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
_UpperCAmelCase : Optional[int] = 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_copies # noqa: E402
... | 50 |
'''simple docstring'''
from __future__ import annotations
def _UpperCamelCase ( __A , __A , __A ) -> dict[str, float]:
'''simple docstring'''
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError("One and only one argument m... | 80 | 0 |
from copy import deepcopy
class __snake_case :
def __init__( self : List[str] , _snake_case : list[int] | None = None , _snake_case : int | None = None):
"""simple docstring"""
if arr is None and size is not No... | 51 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a__ : Union[str, Any] = {'... | 80 | 0 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
__lowerCamelCase : int = logging.get_logger(__name__)
def A_ ( _lowerCAmelCase , _lowerCAmelCase ... | 52 |
'''simple docstring'''
from __future__ import annotations
import math
def _UpperCamelCase ( __A , __A ) -> list:
'''simple docstring'''
if len(__A ) != 2 or len(a[0] ) != 2 or len(__A ) != 2 or len(b[0] ) != 2:
raise Exception("Matric... | 80 | 0 |
'''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class snake_case ( __lowerCamelCase , __lowerCamelCase ):
"""simple docst... | 53 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
... | 80 | 0 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENS... | 54 |
'''simple docstring'''
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import Toke... | 80 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import YosoConfig, YosoForMaskedLM
def __snake_case ( UpperCAmelCase_ : Tuple ):
if "model" in orig_key:
lowerCamelCase_ = orig_key.replace("model." , "" )
if "norm1" in orig_key:
... | 55 |
'''simple docstring'''
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
a__ : Optional[int] = re.compile(R'\b(a|an|the)\b', re.UNICODE)
a__ : int = None
def _UpperCamelCase ( ) -> Dict... | 80 | 0 |
'''simple docstring'''
from maths.prime_check import is_prime
def __magic_name__ ( __UpperCAmelCase ) -> int:
'''simple docstring'''
if not isinstance(__UpperCAmelCase, __UpperCAmelCase ):
snake_case_ = F"Input value of [number={number}] must be an integer"
... | 56 |
'''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager im... | 80 | 0 |
"""simple docstring"""
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
A : int = logging.get_logger(__name__)... | 57 |
'''simple docstring'''
from __future__ import annotations
import math
def _UpperCamelCase ( __A , __A , __A , __A , __A ) -> int:
'''simple docstring'''
if depth < 0:
raise ValueError("Depth cannot be less than 0" )
... | 80 | 0 |
'''simple docstring'''
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class a_ ( snake_case_ ):
'''simple docstring'''
def snake_case_( self ) -> Tuple:
return [
{"col_1": 3, "col_2": "... | 58 |
'''simple docstring'''
def _UpperCamelCase ( __A ) -> int:
'''simple docstring'''
UpperCamelCase__ = 0
while num > 0:
digit_sum += num % 10
num //= 10
return digit_sum
def _UpperCamelCase ( __A = 100 ) ... | 80 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase = {
"""configuration_pix2struct""": [
"""PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""Pix2StructConfig""",
... | 59 |
'''simple docstring'''
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def _UpperCamelCase ... | 80 | 0 |
"""simple docstring"""
from manim import *
class snake_case_( a__ ):
def lowerCamelCase__ ( self : Tuple ):
lowerCAmelCase : List[str] = Rectangle(height=0.5 , width=0.5 )
lowerCAmelCase : Union[str, Any] = Rectangle(height=0.4... | 60 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : Any = logging.get_logger(__name__)
a__ : str = {
'SCUT-DLVCLab/lilt-roberta-en-base': (
'https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/res... | 80 | 0 |
"""simple docstring"""
from manim import *
class A_ (lowercase__ ):
'''simple docstring'''
def UpperCamelCase__ ( self ):
"""simple docstring"""
UpperCAmelCase_ : str = Rectangle(height=0.5 , width=0.5 )
UpperCAmelCase_ : Optional[... | 61 |
'''simple docstring'''
a__ : Union[str, Any] = [sum(int(c, 1_0) ** 2 for c in i.__str__()) for i in range(1_0_0_0_0_0)]
def _UpperCamelCase ( __A ) -> int:
'''simple docstring'''
UpperCamelCase__ = 0
while number:
# In... | 80 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyImgaImgPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandinsky.text_encoder import ... | 62 |
'''simple docstring'''
import fire
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save
def _UpperCamelCase ( __A , __A , __A=1024 , __A=1024 , __A=False , **__A ... | 80 | 0 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : str ) -> str:
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 63 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer import R... | 80 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
A_ = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMConfig''', '''XLMOnnxConfig'''],
'''token... | 64 |
'''simple docstring'''
import os
from typing import List, Optional, Union
from ...tokenization_utils import PreTrainedTokenizer
from ...tokenization_utils_base import AddedToken
from ...utils import logging
a__ : List[str] = logging.get_logger(__name__)
a__ : Optional[int] = ... | 80 | 0 |
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from .sql import sql # no... | 65 |
'''simple docstring'''
from math import factorial, pi
def _UpperCamelCase ( __A , __A = 30 ) -> float:
'''simple docstring'''
if not isinstance(__A , (int, float) ):
raise ValueError("maclaurin_sin() requires either an int or float for t... | 80 | 0 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
VOCAB_FILES_NAMES,
BlenderbotSmallTokenizer,
)
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCamelCase ( _lowerCAmelCase , ... | 66 |
'''simple docstring'''
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
... | 80 | 0 |
'''simple docstring'''
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_tran... | 67 |
'''simple docstring'''
# Copyright 2021 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... | 80 | 0 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: str ) -> list:
'''simple docstring'''
A__ = [0] * len(SCREAMING_SNAKE_CASE_ )
for i in range(1 , len(SCREAMING_SNAKE_CASE_ ) ):
# use last results for better performance - dynamic programming
... | 68 |
'''simple docstring'''
from __future__ import annotations
def _UpperCamelCase ( __A ) -> float:
'''simple docstring'''
UpperCamelCase__ = 0.00
UpperCamelCase__ = 0
for resistor in resistors:
if resistor <= 0:
... | 80 | 0 |
"""simple docstring"""
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
__UpperCamelCase = loggi... | 69 |
'''simple docstring'''
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class lowercase_ ( ... | 80 | 0 |
'''simple docstring'''
from collections.abc import Sequence
def UpperCamelCase__ ( lowerCAmelCase = None ):
"""simple docstring"""
if nums is None or not nums:
raise ValueError("""Input sequence should not be empty""" )
_lowerCAmelCa... | 70 |
'''simple docstring'''
from ....utils import logging
a__ : Optional[Any] = logging.get_logger(__name__)
class lowercase_ ( a__ ):
def __init__( self , a , a=None , a=20_48 ):
UpperCamelCase__ = config.__dict__
UpperC... | 80 | 0 |
def A ( a_ ) -> List[str]:
__UpperCamelCase : List[Any] =len(a_ )
__UpperCamelCase : Optional[int] =sum(a_ )
__UpperCamelCase : Optional[int] =[[False for x in range(s + 1 )] for y in range(n +... | 71 |
'''simple docstring'''
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
a__ : Tuple = {'UserAgent': UserAgent().random}
def _UpperCamelCase ( __A ) -> dict:
'''simple docstr... | 80 | 0 |
"""simple docstring"""
import os
# Precomputes a list of the 100 first triangular numbers
lowerCAmelCase__ = [int(0.5 * n * (n + 1)) for n in range(1, 101)]
def snake_case_ ( ):
'''simple docstring'''
_lowerCamelCase : Tuple = os.path.dirname(os... | 72 |
'''simple docstring'''
from __future__ import annotations
def _UpperCamelCase ( __A , __A , __A ) -> dict[str, float]:
'''simple docstring'''
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError("One and only one argument m... | 80 | 0 |
from __future__ import annotations
def SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ) -> List[Any]: # noqa: E741
while r - l > 1:
__lowerCamelCase : int = (l + r) // 2
if v[m] >= key:
__lowerCamelCase ... | 73 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a__ : Union[str, Any] = {'... | 80 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
_lowercase = '''2020.9.26'''
_lowercase = '''xcodz-dot, cclaus, dhruvmanila'''
def _snake_case ( snake_case__ : float , snake_case__ : float , snake_case__ : float , sna... | 74 |
'''simple docstring'''
from __future__ import annotations
import math
def _UpperCamelCase ( __A , __A ) -> list:
'''simple docstring'''
if len(__A ) != 2 or len(a[0] ) != 2 or len(__A ) != 2 or len(b[0] ) != 2:
raise Exception("Matric... | 80 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class __UpperCamelCase (... | 75 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
... | 80 | 0 |
import json
import sys
def lowerCamelCase__ ( _a , _a):
with open(_a , encoding="utf-8") as f:
SCREAMING_SNAKE_CASE : Any = json.load(_a)
SCREAMING_SNAKE_CASE : Any = ["<details>", "<summary>Show updated benchmarks!</summary>", " "]
for benchmark_name ... | 76 |
'''simple docstring'''
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import Toke... | 80 | 0 |
"""simple docstring"""
from maths.prime_factors import prime_factors
def a_ ( _lowerCAmelCase : int ):
'''simple docstring'''
if not isinstance(_lowerCAmelCase , _lowerCAmelCase ):
lowercase__ : Union[str, Any] = f"""Input value of [number={nu... | 77 |
'''simple docstring'''
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
a__ : Optional[int] = re.compile(R'\b(a|an|the)\b', re.UNICODE)
a__ : int = None
def _UpperCamelCase ( ) -> Dict... | 80 | 0 |
"""simple docstring"""
from manim import *
class A_ ( SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
def UpperCAmelCase__ ( self :List[Any] ) -> Tuple:
UpperCAmelCase = Rectangle(height=0.5 , width=... | 78 |
'''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager im... | 80 | 0 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDepen... | 79 |
'''simple docstring'''
from __future__ import annotations
import math
def _UpperCamelCase ( __A , __A , __A , __A , __A ) -> int:
'''simple docstring'''
if depth < 0:
raise ValueError("Depth cannot be less than 0" )
... | 80 | 0 |
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