code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCamelCase : Any = logging.get_logger(__name__)
__lowerCamelCase : Union[str, A... | 216 | """simple docstring"""
def lowercase_ ( _lowerCamelCase: float , _lowerCamelCase: float ) -> float:
'''simple docstring'''
return price * (1 + tax_rate)
if __name__ == "__main__":
print(F"""{price_plus_tax(100, 0.25) = }""")
print(F"""{price_plus_tax(1_25.50, 0.05) =... | 646 | 0 |
'''simple docstring'''
class UpperCAmelCase :
'''simple docstring'''
def __init__( self , __lowerCAmelCase ) -> Optional[int]:
# we need a list not a string, so do something to change the type
lowercase__ : Optional[Any] = arr.split(... | 152 | """simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_ima... | 646 | 0 |
"""simple docstring"""
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def SCREAMING_SNAKE_CASE__ ( ) -> Union[str, Any]:
lowercase__: List[str] = HfArgumentParser(_lowerCamelCase )
lowercase__: Tuple = parser.parse_args_into_dataclasses()... | 586 | """simple docstring"""
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap import floats_list
@require... | 646 | 0 |
'''simple docstring'''
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import ... | 430 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''naver-clova-ix/donut-base''': '''https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json''',
# See all Donut models at https://h... | 646 | 0 |
def UpperCAmelCase_ ( UpperCAmelCase__ = 1_0_0 ):
lowercase_ = 0
lowercase_ = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_ints**2 - sum_of_squares
if __name__ == "__main__":
print(F'''{solutio... | 412 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__A = logging.get_logger(__name__)
__A = {
'''SenseTime/deformable-detr''': '''https://huggingface.co/sensetime/deformable-detr/resolve/main/config.j... | 646 | 0 |
'''simple docstring'''
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from pathlib ... | 566 | """simple docstring"""
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def lowercase_ ( _lowerCamelCase: Any , _lowerCamelCase: int , _lowerCamelCase: Union[str, Any] ) ... | 646 | 0 |
import argparse
import os
import re
import zipfile
import torch
from transformers import AutoTokenizer, GPTaConfig
def lowerCamelCase__ ( _lowercase , _lowercase , _lowercase=0 ):
'''simple docstring'''
if name is None:
UpperCAmelCase_ : Dict = None
e... | 30 | """simple docstring"""
import math
from collections.abc import Iterator
from itertools import takewhile
def lowercase_ ( _lowerCamelCase: int ) -> bool:
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or n... | 646 | 0 |
"""simple docstring"""
import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, Ty... | 19 | """simple docstring"""
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
__A = [
'''Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone video of t... | 646 | 0 |
import math
from collections.abc import Iterator
from itertools import takewhile
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all mu... | 590 | """simple docstring"""
from manim import *
class _snake_case ( a__ ):
def lowerCamelCase__ ( self : str ):
__lowerCamelCase : Tuple = Rectangle(height=0.5 , width=0.5 )
__lowerCamelCase : Dict = Rectangle(height=... | 646 | 0 |
A_ = {str(digit): digit**5 for digit in range(10)}
def __UpperCAmelCase ( UpperCAmelCase )-> int:
"""simple docstring"""
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(_lowerCamelCase ) )
def __UpperCAmel... | 604 | """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/LICENSE-2.0... | 646 | 0 |
def lowerCamelCase( a__ ,a__):
return price * (1 + tax_rate)
if __name__ == "__main__":
print(f"""{price_plus_tax(1_00, 0.25) = }""")
print(f"""{price_plus_tax(1_25.50, 0.05) = }""") | 691 | """simple docstring"""
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
__A = 0b101100111110110010010000011110111011000110011110
# bin(x)... | 646 | 0 |
import random
from .binary_exp_mod import bin_exp_mod
def _snake_case ( lowerCAmelCase : Tuple , lowerCAmelCase : str=1_0_0_0 ):
"""simple docstring"""
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means n is odd
SCREAMING_SNAKE_CASE_ : Optio... | 216 | """simple docstring"""
# Imports
import numpy as np
class _snake_case :
def __init__( self : Union[str, Any] , UpperCAmelCase : Dict=None , UpperCAmelCase : Any=None , UpperCAmelCase : Optional[int]=None , UpperCAmelCase : ... | 646 | 0 |
'''simple docstring'''
from decimal import Decimal, getcontext
from math import ceil, factorial
def __UpperCamelCase ( UpperCAmelCase ):
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
raise TypeError('''Undefined for non-integers''' )
elif precision < 1:
raise ValueError('''Undefined for no... | 152 | """simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...te... | 646 | 0 |
"""simple docstring"""
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'''files''' , [
['''full:README.md''', '''dataset_infos.json'''],
['''empty:README.md... | 586 | """simple docstring"""
import inspect
import unittest
from transformers import ConvNextConfig
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_backbone_common import Backbo... | 646 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_lowerCamelCase : int = {
"configuration_nezha": ["NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP", "NezhaConfig"],
}
... | 430 | """simple docstring"""
import math
def lowercase_ ( _lowerCamelCase: int ) -> list[int]:
'''simple docstring'''
__lowerCamelCase : Optional[int] = []
__lowerCamelCase : Tuple = 2
__lowerCamelCase : str = int(math.sqrt(_lowerCamelCase ) ... | 646 | 0 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class UpperCamelCase__ ( unittest.TestCase ):
def UpperCAmelCase__ ( self : Dict ):
'''simple docstring'''
... | 412 | """simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers i... | 646 | 0 |
'''simple docstring'''
import copy
import tempfile
import unittest
from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError
from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_stagin... | 566 | """simple docstring"""
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
__A = log... | 646 | 0 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
__a = {'tokenization_tapex': ['TapexTokenizer']}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
__a = _LazyModule(__name__, globals()['__file__'], _import_struc... | 30 | """simple docstring"""
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
__A = logging.get_logger(__name__)
class _snake_case ( a__ ):
def __init__( self : Optional[Any] , *UpperCAmelCase : int , **... | 646 | 0 |
"""simple docstring"""
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
_a = TypeVar("""KT""")
_a = TypeVar("""VT""")
class _UpperCAmelCase( Generic[KT, VT] ):
def __init__( self ... | 19 | """simple docstring"""
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp... | 646 | 0 |
from math import ceil, sqrt
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE = 1_000_000 ):
A_ : Dict = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
A_ : Tuple = max(ceil(sqrt(outer_width**2 - limit ) ) , ... | 590 | """simple docstring"""
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize("repo_id" , ["canonical_dataset_name", "org-name/dataset-name"] )
@pytest.mark.parametrize("path" , ["filename.csv", "filename with blanks.csv"] )
@pytest.mark.parame... | 646 | 0 |
import io
import json
import fsspec
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def __UpperCAm... | 604 | """simple docstring"""
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class _snake_case ( ctypes.Structure ):
# _fields is a specific attr expected by ctypes
snake_case__ = [("... | 646 | 0 |
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
snake_case_ : List[Any] = [
'''Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone v... | 691 | """simple docstring"""
import unittest
from typing import Dict, List, Optional, Union
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 ImageProcessingSavingTe... | 646 | 0 |
def _snake_case ( lowerCAmelCase : int ):
"""simple docstring"""
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
raise ValueError("multiplicative_persistence() only accepts integral values" )
if num < 0:
raise ValueError("multiplicative_persistence() does not a... | 216 | """simple docstring"""
def lowercase_ ( _lowerCamelCase: float , _lowerCamelCase: float ) -> float:
'''simple docstring'''
return price * (1 + tax_rate)
if __name__ == "__main__":
print(F"""{price_plus_tax(100, 0.25) = }""")
print(F"""{price_plus_tax(1_25.50, 0.05) =... | 646 | 0 |
'''simple docstring'''
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class UpperCAmelCase ( a__ ):
'''simple... | 152 | """simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_ima... | 646 | 0 |
"""simple docstring"""
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
__A = logging.getLogger(__na... | 586 | """simple docstring"""
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap import floats_list
@require... | 646 | 0 |
'''simple docstring'''
from typing import Union
import fire
import torch
from tqdm import tqdm
def __lowerCamelCase ( A__ , A__ = "cpu" , A__ = None ) -> None:
"""simple docstring"""
UpperCamelCase = torch.load(... | 430 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''naver-clova-ix/donut-base''': '''https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json''',
# See all Donut models at https://h... | 646 | 0 |
from __future__ import annotations
def UpperCAmelCase_ ( UpperCAmelCase__ , UpperCAmelCase__ ):
if len(_lowerCamelCase ) < k or k < 0:
raise ValueError("""Invalid Input""" )
lowercase_ = sum(array[:k] )
for i in range(len(_lowerCamelCase ) - k ):
lower... | 412 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__A = logging.get_logger(__name__)
__A = {
'''SenseTime/deformable-detr''': '''https://huggingface.co/sensetime/deformable-detr/resolve/main/config.j... | 646 | 0 |
'''simple docstring'''
import json
import os
from datetime import date
from pathlib import Path
from tabulate import DataRow, TableFormat, tabulate
snake_case : List[str] = TableFormat(
lineabove=None,
linebelowheader=None,
linebetweenrows=None,
linebelow=None,
headerrow=DataRow('', ... | 566 | """simple docstring"""
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def lowercase_ ( _lowerCamelCase: Any , _lowerCamelCase: int , _lowerCamelCase: Union[str, Any] ) ... | 646 | 0 |
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...test_... | 30 | """simple docstring"""
import math
from collections.abc import Iterator
from itertools import takewhile
def lowercase_ ( _lowerCamelCase: int ) -> bool:
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or n... | 646 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a = logging.get_logger(__name__)
_a = {
"""EleutherAI/gpt-neox-20b""": """https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json""",
# See all... | 19 | """simple docstring"""
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
__A = [
'''Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone video of t... | 646 | 0 |
import inspect
import unittest
from transformers import ConvNextConfig
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_backbone_common import BackboneTesterMixin
from ...tes... | 590 | """simple docstring"""
from manim import *
class _snake_case ( a__ ):
def lowerCamelCase__ ( self : str ):
__lowerCamelCase : Tuple = Rectangle(height=0.5 , width=0.5 )
__lowerCamelCase : Dict = Rectangle(height=... | 646 | 0 |
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def __UpperCAmelCase ( UpperCAmelCase = "isbn/0140328726" )-> dict:
"""simple docstring"""
lowercase = olid.strip().strip('''/''' ... | 604 | """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/LICENSE-2.0... | 646 | 0 |
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def lowerCamelCase( a__ ,a__ ,a__):
_SCREAMING_SNAKE_CASE =AlbertConfig.from_json_file(_lowerCamelCase)
print(f"Bui... | 691 | """simple docstring"""
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
__A = 0b101100111110110010010000011110111011000110011110
# bin(x)... | 646 | 0 |
from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf_common import floats_tensor, ids_tensor, rando... | 216 | """simple docstring"""
# Imports
import numpy as np
class _snake_case :
def __init__( self : Union[str, Any] , UpperCAmelCase : Dict=None , UpperCAmelCase : Any=None , UpperCAmelCase : Optional[int]=None , UpperCAmelCase : ... | 646 | 0 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
from filelock import FileLock
from transformers import PreTrainedTokenizer, is_tf_available, is_torch_available
__a: Any = logging.getLogger(__name__)
@datacl... | 152 | """simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...te... | 646 | 0 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> bool:
lowercase__: int = int(number**0.5 )
return number == sq * sq
def SCREAMING_SNAKE_CASE__ ( __UpperCAm... | 586 | """simple docstring"""
import inspect
import unittest
from transformers import ConvNextConfig
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_backbone_common import Backbo... | 646 | 0 |
'''simple docstring'''
from ..models.whisper import WhisperForConditionalGeneration, WhisperProcessor
from .base import PipelineTool
class SCREAMING_SNAKE_CASE ( a__ ):
"""simple docstring"""
_SCREAMING_SNAKE_CASE = """openai/whisper-base"""
... | 430 | """simple docstring"""
import math
def lowercase_ ( _lowerCamelCase: int ) -> list[int]:
'''simple docstring'''
__lowerCamelCase : Optional[int] = []
__lowerCamelCase : Tuple = 2
__lowerCamelCase : str = int(math.sqrt(_lowerCamelCase ) ... | 646 | 0 |
import argparse
import json
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Acc... | 412 | """simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers i... | 646 | 0 |
'''simple docstring'''
import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from cookiecutter.main import cookiecutter
snake_case : Tu... | 566 | """simple docstring"""
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
__A = log... | 646 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
'kssteven/ibert-roberta-base': 'https://huggingface.co/ksst... | 30 | """simple docstring"""
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
__A = logging.get_logger(__name__)
class _snake_case ( a__ ):
def __init__( self : Optional[Any] , *UpperCAmelCase : int , **... | 646 | 0 |
"""simple docstring"""
def lowerCamelCase__ ( __snake_case ) -> Tuple:
"""simple docstring"""
if not head:
return True
# split the list to two parts
_UpperCamelCase = head.next, head
while fast and fast.next:
... | 19 | """simple docstring"""
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp... | 646 | 0 |
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE ):
A_ : Tuple = prime_factors(_lowerCamelCase )
if is_square_free(_lowerCamelCase ):
return -1 if len(_lowerCamelCase ) % 2 else ... | 590 | """simple docstring"""
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize("repo_id" , ["canonical_dataset_name", "org-name/dataset-name"] )
@pytest.mark.parametrize("path" , ["filename.csv", "filename with blanks.csv"] )
@pytest.mark.parame... | 646 | 0 |
def __UpperCAmelCase ( UpperCAmelCase )-> bool:
"""simple docstring"""
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 604 | """simple docstring"""
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class _snake_case ( ctypes.Structure ):
# _fields is a specific attr expected by ctypes
snake_case__ = [("... | 646 | 0 |
snake_case_ : Any = {}
def lowerCamelCase( a__ ,a__ ,a__):
if late == 3 or absent == 2:
return 0
# if we have no days left, and have not failed any other rules,
# we have a prize string
if days == 0:
return 1
# No easy solution, so now we ... | 691 | """simple docstring"""
import unittest
from typing import Dict, List, Optional, Union
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 ImageProcessingSavingTe... | 646 | 0 |
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase : Union[str, Any] = logging.get_logger(__name__)
__lowerCamelCase : Optional[int] = {
'''huggingface/time-series-transformer-tourism-mont... | 216 | """simple docstring"""
def lowercase_ ( _lowerCamelCase: float , _lowerCamelCase: float ) -> float:
'''simple docstring'''
return price * (1 + tax_rate)
if __name__ == "__main__":
print(F"""{price_plus_tax(100, 0.25) = }""")
print(F"""{price_plus_tax(1_25.50, 0.05) =... | 646 | 0 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import (
Bit... | 152 | """simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_ima... | 646 | 0 |
"""simple docstring"""
import datasets
from .evaluate import evaluate
__A = "\\n@article{hendrycks2021cuad,\n title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},\n author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},\n journal={arXiv preprint arX... | 586 | """simple docstring"""
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap import floats_list
@require... | 646 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
def __lowerCamelCase ( A__ , A__ , A__ , A__ = 100 , ) -> float:
"""simple docstring"""
UpperCamelCase = x_sta... | 430 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''naver-clova-ix/donut-base''': '''https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json''',
# See all Donut models at https://h... | 646 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/config.json'}
class UpperCamelCase__ ( a__ ):
__SCREAMING_SNAKE_CASE : Optional[int] ... | 412 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__A = logging.get_logger(__name__)
__A = {
'''SenseTime/deformable-detr''': '''https://huggingface.co/sensetime/deformable-detr/resolve/main/config.j... | 646 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case : List[Any] = {
'configuration_git': ['GIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GitConfig', 'GitVisionConfig'],
'processing_git': ['GitProcessor'],
... | 566 | """simple docstring"""
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def lowercase_ ( _lowerCamelCase: Any , _lowerCamelCase: int , _lowerCamelCase: Union[str, Any] ) ... | 646 | 0 |
import operator as op
__a = 'scaler.pt'
__a = 'pytorch_model'
__a = 'random_states'
__a = 'optimizer'
__a = 'scheduler'
__a = 'pytorch_model.bin'
__a = 'pytorch_model.bin.index.json'
__a = 'mod... | 30 | """simple docstring"""
import math
from collections.abc import Iterator
from itertools import takewhile
def lowercase_ ( _lowerCamelCase: int ) -> bool:
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or n... | 646 | 0 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a = logging.get_logger(__name__)
_a = {
"""microsoft/unispeech-sat-base-100h-libri-ft""": (
"""https://huggingface.co/... | 19 | """simple docstring"""
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
__A = [
'''Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone video of t... | 646 | 0 |
import unittest
from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipeline_mixin... | 590 | """simple docstring"""
from manim import *
class _snake_case ( a__ ):
def lowerCamelCase__ ( self : str ):
__lowerCamelCase : Tuple = Rectangle(height=0.5 , width=0.5 )
__lowerCamelCase : Dict = Rectangle(height=... | 646 | 0 |
from __future__ import annotations
import math
def __UpperCAmelCase ( UpperCAmelCase )-> bool:
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
... | 604 | """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/LICENSE-2.0... | 646 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case_ : Optional[int] = {
'''configuration_upernet''': ['''UperNetConfig'''],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvail... | 691 | """simple docstring"""
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
__A = 0b101100111110110010010000011110111011000110011110
# bin(x)... | 646 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCamelCase : str = logging.get_logger(__name__)
__lowerCamelCase : Dict = {
'''facebook/xmod-ba... | 216 | """simple docstring"""
# Imports
import numpy as np
class _snake_case :
def __init__( self : Union[str, Any] , UpperCAmelCase : Dict=None , UpperCAmelCase : Any=None , UpperCAmelCase : Optional[int]=None , UpperCAmelCase : ... | 646 | 0 |
'''simple docstring'''
import contextlib
import importlib
import io
import unittest
import transformers
# Try to import everything from transformers to ensure every object can be loaded.
from transformers import * # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, require_tf,... | 152 | """simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...te... | 646 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {"vocab_file... | 586 | """simple docstring"""
import inspect
import unittest
from transformers import ConvNextConfig
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_backbone_common import Backbo... | 646 | 0 |
'''simple docstring'''
from queue import PriorityQueue
from typing import Any
import numpy as np
def __lowerCamelCase ( A__ , A__ , A__ , A__ , A__ , A__ , A__ , A__ , A__ , ) -> float | int:
... | 430 | """simple docstring"""
import math
def lowercase_ ( _lowerCamelCase: int ) -> list[int]:
'''simple docstring'''
__lowerCamelCase : Optional[int] = []
__lowerCamelCase : Tuple = 2
__lowerCamelCase : str = int(math.sqrt(_lowerCamelCase ) ... | 646 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetImgaImgPipeline,
KandinskyVaaPriorEmbaEmbPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, l... | 412 | """simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers i... | 646 | 0 |
'''simple docstring'''
snake_case : int = {
'A': '.-', 'B': '-...', 'C': '-.-.', 'D': '-..', 'E': '.', 'F': '..-.', 'G': '--.',
'H': '....', 'I': '..', 'J': '.---', 'K': '-.-', 'L': '.-..', 'M': '--', 'N': '-.',
'O': '---', 'P': '.--.', 'Q': '--.-', 'R': '.-.', 'S': '...', 'T': '-', 'U': '..-',... | 566 | """simple docstring"""
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
__A = log... | 646 | 0 |
from typing import Any
class __a:
"""simple docstring"""
def __init__( self ,_SCREAMING_SNAKE_CASE ) -> Dict:
UpperCAmelCase_ : Tuple = data
UpperCAmelCase_ : List[Any] = None
def __repr__( self ) -> Any:
r... | 30 | """simple docstring"""
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
__A = logging.get_logger(__name__)
class _snake_case ( a__ ):
def __init__( self : Optional[Any] , *UpperCAmelCase : int , **... | 646 | 0 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a = logging.get_logger(__name__)
_a = {
"""microsoft/git-base""": """https://huggingface.co/microsoft/git-base/r... | 19 | """simple docstring"""
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp... | 646 | 0 |
from typing import Dict, Optional
import numpy as np
import datasets
UpperCamelCase = """
IoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union
between the predicted segmentation and the ground truth. For binary (two classes) or multi-cl... | 590 | """simple docstring"""
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize("repo_id" , ["canonical_dataset_name", "org-name/dataset-name"] )
@pytest.mark.parametrize("path" , ["filename.csv", "filename with blanks.csv"] )
@pytest.mark.parame... | 646 | 0 |
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from utils_ner import Spl... | 604 | """simple docstring"""
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class _snake_case ( ctypes.Structure ):
# _fields is a specific attr expected by ctypes
snake_case__ = [("... | 646 | 0 |
class A__ :
def __init__( self : int , _a : list[int] ) -> Any:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =len(_a )
_SCREAMING_SNAKE_CASE =[0] * len_array
if len_array > 0:
_SCREAMING_SNAKE... | 691 | """simple docstring"""
import unittest
from typing import Dict, List, Optional, Union
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 ImageProcessingSavingTe... | 646 | 0 |
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
renew_vae_attention_paths,
renew_v... | 216 | """simple docstring"""
def lowercase_ ( _lowerCamelCase: float , _lowerCamelCase: float ) -> float:
'''simple docstring'''
return price * (1 + tax_rate)
if __name__ == "__main__":
print(F"""{price_plus_tax(100, 0.25) = }""")
print(F"""{price_plus_tax(1_25.50, 0.05) =... | 646 | 0 |
'''simple docstring'''
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize('''repo_id''' , ['''canonical_dataset_name''', '''org-name/dataset-name'''] )
@pytest.mark.parametrize('''path''' , ['''filename.csv''', '''filename with blanks.csv'''] )
@... | 152 | """simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_ima... | 646 | 0 |
"""simple docstring"""
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class UpperCAmelCase :
"""simple docstring"""
_UpperCAmelCase :str = None
_UpperCAmelCase :List[Any] = False... | 586 | """simple docstring"""
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap import floats_list
@require... | 646 | 0 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def __lowerCamelCase ( A__ , A__ ) -> str:
"""simple docstring"""
UpperCamelCase = BeautifulSoup(requests.get(_lowerCamelCase , params=_lowerCamel... | 430 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''naver-clova-ix/donut-base''': '''https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json''',
# See all Donut models at https://h... | 646 | 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
a = logging.get_logger(__name__)
def UpperCAmelCase_ ( UpperCAmelCase__ , UpperCAmelCase__ ):
lowercase_ ... | 412 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__A = logging.get_logger(__name__)
__A = {
'''SenseTime/deformable-detr''': '''https://huggingface.co/sensetime/deformable-detr/resolve/main/config.j... | 646 | 0 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
snake_case : str = logging.get_logger('transformers.models.speecht5')
def lowercase__ ( __UpperCamelCase : ... | 566 | """simple docstring"""
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def lowercase_ ( _lowerCamelCase: Any , _lowerCamelCase: int , _lowerCamelCase: Union[str, Any] ) ... | 646 | 0 |
import unittest
from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
if is_flax_available():
import jax.numpy as jnp
from transformers import FlaxXLMRobertaModel
@require_sentencepiece
@require_... | 30 | """simple docstring"""
import math
from collections.abc import Iterator
from itertools import takewhile
def lowercase_ ( _lowerCamelCase: int ) -> bool:
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or n... | 646 | 0 |
"""simple docstring"""
import numpy as np
class _UpperCAmelCase:
def __init__( self , __a=None , __a=None , __a=None , __a=None , __a=None) -> List[str]:
'''simple docstring'''
self.set_mat... | 19 | """simple docstring"""
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
__A = [
'''Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone video of t... | 646 | 0 |
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE ):
if not grid or not grid[0]:
raise TypeError('''The grid does not contain the appropriate information''' )
for cell_n in range(1 , len(grid[0] ) ):
grid[0][cell_n] += grid[0][cell_n - 1]
A_ : Optional[Any] = ... | 590 | """simple docstring"""
from manim import *
class _snake_case ( a__ ):
def lowerCamelCase__ ( self : str ):
__lowerCamelCase : Tuple = Rectangle(height=0.5 , width=0.5 )
__lowerCamelCase : Dict = Rectangle(height=... | 646 | 0 |
from math import factorial
def __UpperCAmelCase ( UpperCAmelCase = 20 )-> int:
"""simple docstring"""
lowercase = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
lowercase = n // 2
... | 604 | """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/LICENSE-2.0... | 646 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_image, load_numpy, slow, tor... | 691 | """simple docstring"""
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
__A = 0b101100111110110010010000011110111011000110011110
# bin(x)... | 646 | 0 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class a__ ( a__ ):
def __init__( self : Union[str, Any],_A : Callable,_A : Optional[Features] = None,_A : str = Non... | 216 | """simple docstring"""
# Imports
import numpy as np
class _snake_case :
def __init__( self : Union[str, Any] , UpperCAmelCase : Dict=None , UpperCAmelCase : Any=None , UpperCAmelCase : Optional[int]=None , UpperCAmelCase : ... | 646 | 0 |
'''simple docstring'''
from __future__ import annotations
def __UpperCamelCase ( UpperCAmelCase , UpperCAmelCase ):
lowercase__ : list[list[int]] = []
lowercase__ : list[int] = []
lowercase__ : str = 0
lowercase__ : Optio... | 152 | """simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...te... | 646 | 0 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .... | 586 | """simple docstring"""
import inspect
import unittest
from transformers import ConvNextConfig
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_backbone_common import Backbo... | 646 | 0 |
import argparse
from copy import deepcopy
import numpy as np
from datasets import ClassLabel, DatasetDict, load_dataset
from evaluate import load
from transformers import (
AutoModelForSequenceClassification,
AutoTokenizer,
DataCollatorWithPadding,
Trainer,
TrainerCallback,
TrainingArgumen... | 647 |
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import DDIMScheduler, KandinskyVaaPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.utils import floats_tensor, load_numpy, slow, torch_device
from diffusers.utils.testing_utils import enable_ful... | 647 | 1 |
def lowerCAmelCase__ ( lowerCamelCase_ : str = "The quick brown fox jumps over the lazy dog" ,):
'''simple docstring'''
lowerCAmelCase__ : Any = set()
# Replace all the whitespace in our sentence
lowerCAmelCase__ : Tuple = input_str.replace(''' '... | 647 |
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.rob... | 647 | 1 |
from __future__ import annotations
class lowerCamelCase__ :
'''simple docstring'''
def __init__(self ,__lowerCamelCase ,__lowerCamelCase ) -> Any:
"""simple docstring"""
lowerCAmelCase__ , lowerCAmelCase__ : int = text, pattern
lowerCAme... | 647 |
__snake_case : str ='\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
__snake_case : ... | 647 | 1 |
from scipy.stats import pearsonr
import datasets
__snake_case : List[str] ='\nPearson correlation coefficient and p-value for testing non-correlation.\nThe Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies on the assumptio... | 647 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_grad_enabled(False)
de... | 647 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : List[str] =logging.get_logger(__name__)
__snake_case : List[Any] ={
'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json',
}
cl... | 647 |
import requests
__snake_case : Optional[int] ='YOUR API KEY'
def lowerCAmelCase__ ( lowerCamelCase_ : str ,lowerCamelCase_ : str = giphy_api_key):
'''simple docstring'''
lowerCAmelCase__ : Tuple = '''+'''.join(query.split())
lo... | 647 | 1 |
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_available
from ...test_backbone_common import Bac... | 647 |
from collections.abc import Callable
class lowerCamelCase__ :
'''simple docstring'''
def __init__(self ,__lowerCamelCase = None ) -> None:
"""simple docstring"""
lowerCAmelCase__ : list = []
# Stores indexes of each item for supporting updates and ... | 647 | 1 |
def lowerCAmelCase__ ( ):
'''simple docstring'''
return 1
def lowerCAmelCase__ ( lowerCamelCase_ : int):
'''simple docstring'''
return 0 if x < 0 else two_pence(x - 2) + one_pence()
def lowerCAmelCase__ ( lowerCamel... | 647 |
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers import AutoToke... | 647 | 1 |
def lowerCAmelCase__ ( lowerCamelCase_ : int = 10**9):
'''simple docstring'''
lowerCAmelCase__ : Tuple = 1
lowerCAmelCase__ : Tuple = 2
lowerCAmelCase__ : List[Any] = 0
lowerCAmelCase__ : List[str] = 0
lowerCAmelCase__ : ... | 647 |
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowerCamelCase__ ( lowerCamelCase__):
'''simple docstring'''
snake_case_ =(KDPMaDiscreteScheduler,)
snake_case_ =10
def... | 647 | 1 |
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
__snake_case : Dict =logging.get_logger(__name__)
class lowerCamelCase__ ( lowerCamelCase__):
'''simple docstring'''
def __init__(self ,*__lowerCamelCase ,**__l... | 647 |
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class lowerCamelCase__ ( unittest.TestCase):
'''simple docstring'''
def lowerCAmelCase__ (self ) -> str:
"""simple docstring"""
... | 647 | 1 |
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class lowerCamelCase__ ( unittest.TestCase):
'''simple docstring'''
def lowerCAmelCase__ (self ) -> str:
"""simple docstring"""
... | 647 |
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
__snake_case : List[Any] =get_tests_dir('fixtures/test_sent... | 647 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__snake_case : List[Any] =logging.get_logger(__name__)
__snake_case : str ={
'roberta-base': 'https:/... | 647 |
import math
import unittest
def lowerCAmelCase__ ( lowerCamelCase_ : int):
'''simple docstring'''
assert isinstance(lowerCamelCase_ ,lowerCamelCase_) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 a... | 647 | 1 |
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class lowerCamelCase__ ( unittest.TestCase):
'''simple docstrin... | 647 |
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock import FileLock
from .logging import get_logg... | 647 | 1 |
def lowerCAmelCase__ ( lowerCamelCase_ : list[list]):
'''simple docstring'''
lowerCAmelCase__ : Union[str, Any] = current_set.copy()
for row_index, row in enumerate(lowerCamelCase_):
lowerCAmelCase__ : List[Any] = row[0]
for column_index... | 647 |
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_video_inputs
if is_torch_available():
import ... | 647 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__snake_case : int ={
'configuration_mobilenet_v2': [
'MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP',
'MobileNetV2Config',
'MobileNe... | 647 |
def lowerCAmelCase__ ( lowerCamelCase_ : Dict):
'''simple docstring'''
lowerCAmelCase__ : Optional[Any] = len(lowerCamelCase_)
while cur > 1:
# Find the maximum number in arr
lowerCAmelCase__ : Tuple = arr.index(max(arr[0:cur]))
... | 647 | 1 |
from math import asin, atan, cos, radians, sin, sqrt, tan
__snake_case : str =6378137.0
__snake_case : Optional[int] =6356752.314245
__snake_case : List[str] =6_3_7_8_1_3_7
def lowerCAmelCase__ ( lowerCamelCase_ : float ,lowerCamelC... | 647 |
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from utils_ner import Split, To... | 647 | 1 |
# 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
#
# Unless required by appli... | 647 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__snake_case : int ={
'configuration_gpt_bigcode': ['GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTBigCodeConfig'],
}
try:
if not is_torch_available... | 647 | 1 |
import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pytorch_model
from transformers.... | 647 |
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class lowerCamelCase__ :
'''simple docstring'''
snake_case_ =None
snake_case_ =False
snake_case_ =False
snake_case_ =False
snake_case_ =Non... | 647 | 1 |
import inspect
import unittest
from transformers import SegformerConfig, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_comm... | 647 |
def lowerCAmelCase__ ( lowerCamelCase_ : Dict ,lowerCamelCase_ : Optional[int]):
'''simple docstring'''
lowerCAmelCase__ : int = (boundary[1] - boundary[0]) / steps
lowerCAmelCase__ : Optional[int] = boundary[0]
lowerCAmelCase__ : ... | 647 | 1 |
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from utils_ner import Split, To... | 647 |
from __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFMode... | 647 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaInpaintPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, slow,... | 647 |
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_con... | 647 | 1 |
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