code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
UpperCAmelCase_ : Dict = datasets.utils.logging.get_logger(__name__)
@dataclass
clas... | 44 |
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ : list[int] , SCREAMING_SNAKE_CASE_ : int ) -> bool:
_lowercase = len(SCREAMING_SNAKE_CASE_ )
_lowercase = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr value, a su... | 287 | 0 |
'''simple docstring'''
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
'snap-research/efficientformer-l1-300': (
'https://huggingface... | 411 |
'''simple docstring'''
from math import factorial
def _SCREAMING_SNAKE_CASE( snake_case_ : int , snake_case_ : int ) ->int:
'''simple docstring'''
# If either of the conditions are true, the function is being asked
... | 411 | 1 |
import json
import os
import unittest
from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@requi... | 100 | '''simple docstring'''
from numpy import exp, pi, sqrt
def __UpperCAmelCase ( a_: int, a_: float = 0.0, a_: float = 1.0 ):
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )
if __name__ == "__main__":
import doctest
doctest.testmod() | 494 | 0 |
from itertools import permutations
def lowercase ( a ):
'''simple docstring'''
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
SCREAMING_SNAKE_CASE_ :Dict = [7, 11, 13, 17]
for i, ... | 140 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import torch
... | 140 | 1 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_utils... | 688 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer
__SCREAMING_SNAKE_CASE = logging.get_lo... | 688 | 1 |
lowerCamelCase : Union[str, Any] = {
'meter': 'm',
'kilometer': 'km',
'megametre': 'Mm',
'gigametre': 'Gm',
'terametre': 'Tm',
'petametre': 'Pm',
'exametre': 'Em',
'zettametre': 'Zm',
'yottametre': 'Ym',
}
# Exponent of the factor(meter)
lowerC... | 702 |
import argparse
import os
import re
import numpy as np
import PIL
import torch
from timm import create_model
from torch.optim.lr_scheduler import OneCycleLR
from torch.utils.data import DataLoader, Dataset
from torchvision.transforms import Compose, RandomResizedCrop, Resize, ToTensor
from accelerate import Ac... | 290 | 0 |
from __future__ import annotations
from typing import TypedDict
class _a ( snake_case_ ):
"""simple docstring"""
_lowerCamelCase : str
_lowerCamelCase : int
def __snake_case ( __UpperCamelCase : str ):
"""simple docs... | 86 |
import torch
from diffusers import DDPMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class _a ( snake_case_ ):
"""simple docstring"""
_lowerCamelCase : Optional[Any] = (DDPMParallelScheduler,)
def __A ( self ... | 86 | 1 |
import argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import logging as transformers_logging
sys.path.append(os.pa... | 715 |
import argparse
import json
import os
import fairseq
import torch
from torch import nn
from transformers import (
SpeechaTextaConfig,
SpeechaTextaForCausalLM,
SpeechaTextaTokenizer,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
Wava... | 250 | 0 |
# Lint as: python3
import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union
_SCREAMING_SNAKE_CASE : List[str] = re.compile(R"^(?P<major>\d+)" R"\.(?P<minor>\d+)" R"\.(?P<patch>\d+)$")
@total_ordering
@da... | 550 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
from torch... | 550 | 1 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import numpy as np
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
import transformers
from tr... | 705 |
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def lowerCamelCase_ ( lowerCAmelCase__ : Optional[A... | 224 | 0 |
'''simple docstring'''
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def UpperCamelCase__ ( __magic_name__ : Optional[Any] , __magic_name__ : Dict , __... | 38 |
'''simple docstring'''
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNot... | 369 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__lowercase = {
'''configuration_mobilevit''': ['''MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP'''... | 605 | '''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase = logging.get_logger(__name__)
__lowercase = {
'''google/switch-base-8''': '''https://huggingface.co/google/switch-base-8/blob/main/config.json''',
}
class ... | 605 | 1 |
from ....utils import logging
SCREAMING_SNAKE_CASE__ : List[Any] = logging.get_logger(__name__)
class snake_case ( UpperCamelCase_ ):
def __init__( self : Tuple , a_ : str , a_ : str=None , a_ : int=2048 )-> Union[str, Any]:
... | 85 | """simple docstring"""
__A : Union[str, Any] = {str(digit): digit**5 for digit in range(10)}
def lowercase ( UpperCamelCase : int ):
"""simple docstring"""
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(UpperCamelCase ) )
def lowercase ( ):
... | 656 | 0 |
'''simple docstring'''
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokeniza... | 216 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class snake_case__ ( UpperCamelCase ... | 216 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
import random
from collections.abc import Collection
from typing import overload
class UpperCAmelCase :
def __init__( self : Union[str, Any] , __lowerCamelCase : Collection[fl... | 103 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | 171 | 0 |
"""simple docstring"""
import os
from argparse import ArgumentParser
from typing import List
import torch.utils.data
from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node
_snake_case : Optional[Any] = 4
_snake_case : Dict = 3
class _UpperC... | 524 |
"""simple docstring"""
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
_snake_case : str = 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
# Th... | 524 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
A_ = {
"configuration_wav2vec2": ["WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP", "Wav2Vec2Config"],
"feature_ext... | 604 | from __future__ import annotations
import os
from collections.abc import Mapping
A_ = tuple[int, int]
class __lowercase :
def __init__( self : Dict , __lowerCamelCase : set[int] , __lowerCamelCase : Mapping[EdgeT, int] ) -> None:
... | 604 | 1 |
"""simple docstring"""
from datetime import datetime
import requests
def _a ( UpperCAmelCase__ ) -> bytes:
__SCREAMING_SNAKE_CASE = '''https://downloadgram.net/wp-json/wppress/video-downloader/video?url='''
__SCREAMING_SNAKE_CASE = requests.get(base_u... | 709 |
"""simple docstring"""
from sklearn.metrics import recall_score
import datasets
lowerCAmelCase__ ="\nRecall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation:\nRecall = TP / (TP + FN)\nWhere TP is the true positives ... | 690 | 0 |
"""simple docstring"""
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers import VQDiffusio... | 626 |
from math import factorial
def snake_case_ ( lowerCAmelCase_ : int = 100 ):
return sum(map(lowerCAmelCase_ , str(factorial(lowerCAmelCase_ ) ) ) )
if __name__ == "__main__":
print(solution(int(input('''Enter the Number: ''').strip()))) | 149 | 0 |
def SCREAMING_SNAKE_CASE ( lowercase_ = 50 ) -> int:
"""simple docstring"""
A__ = [1] * (length + 1)
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_length - tile_length ... | 177 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable
_lowerCamelCase : Union[str, Any] = {"""configuration_dpt""": ["""DPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DPT... | 177 | 1 |
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils import DUM... | 14 |
'''simple docstring'''
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# 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-... | 50 | 0 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVeca... | 711 |
'''simple docstring'''
import argparse
import shutil
import time
from json import JSONDecodeError
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoToken... | 540 | 0 |
import argparse
from .config import config_command_parser
from .config_args import default_config_file, load_config_from_file # noqa: F401
from .default import default_command_parser
from .update import update_command_parser
def _A ( lowerCamelCase=None ):
a__ : Optional[Any] = argpars... | 112 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : Optional[int] = logging.get_logger(__name__)
__snake_case : int = {
"transfo-xl-wt103": "https://huggingface.co/transfo-xl-wt103/resolve/main/config.json",... | 131 | 0 |
"""simple docstring"""
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def _a ( _SCREAMING_SNAKE_CASE = 3 ) -> qiskit.result.counts.Counts:
if isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_... | 714 |
"""simple docstring"""
from __future__ import annotations
def _a ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> list[int]:
snake_case_ = 0
snake_case_ = len(_SCREAMING_SNAKE_CASE ) - 1
while i < j:
if nums[i] + nums[j... | 2 | 0 |
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
... | 662 |
UpperCAmelCase_ = {
"A": ".-", "B": "-...", "C": "-.-.", "D": "-..", "E": ".", "F": "..-.", "G": "--.",
"H": "....", "I": "..", "J": ".---", "K": "-.-", "L": ".-..", "M": "--", "N": "-.",
"O": "---", "P": ".--.", "Q": "--.-", "R": ".-.", "S": "...", "T": "-", "U": "..-",
"V": "...-", "W"... | 32 | 0 |
'''simple docstring'''
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreT... | 720 |
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import Confi... | 198 | 0 |
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeacher, LevitImageProcessor
from transformers.u... | 272 |
lowercase = 8.314_4598
def __lowerCAmelCase ( UpperCAmelCase__ : float , UpperCAmelCase__ : float ) -> float:
if temperature < 0:
raise Exception("""Temperature cannot be less than 0 K""" )
if molar_mass <= 0:
raise Ex... | 272 | 1 |
import copy
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
from ..auto import CONFIG_MAPPING
__snake_case :List[str] = logging.get_logger(__name__)
... | 60 |
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING, Dict, Optional
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.logging import get_logger
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING... | 60 | 1 |
'''simple docstring'''
import json
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingSt... | 92 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
r... | 22 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
"facebook/convnextv2-tiny-1k-2... | 720 |
from __future__ import annotations
def A ( lowercase__ : list[int] ) -> int:
if not nums:
return 0
UpperCamelCase__ :Dict = nums[0]
UpperCamelCase__ :Dict = 0
for num in nums[1:]:
UpperCamelCase__ , UpperCamelCase__ :Optional[Any] = ... | 383 | 0 |
"""simple docstring"""
import importlib.util
import json
import os
import warnings
from dataclasses import dataclass, field
import torch
from ..training_args import TrainingArguments
from ..utils import cached_property, is_sagemaker_dp_enabled, logging
UpperCamelCase : Optional[Any] = logging... | 690 |
"""simple docstring"""
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import (
BnbQuantizationConfig,... | 690 | 1 |
"""simple docstring"""
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class _lowerCamelCase ( unittest.TestCase ):
def snake_case_ (self ) -> Any... | 544 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
StableDi... | 544 | 1 |
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
lowerCAmelCase = '\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Multilingual Language Models for ... | 43 |
"""simple docstring"""
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def _UpperCamelCase ( _A , _A=None ) -> Optional[int]:
"""simple docstring"""
_UpperCAmelCase = None
... | 555 | 0 |
import os
import unittest
from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class... | 416 |
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import datasets
import datasets.config
from .utils import require_beam
class lowerCAmelCase_ ( datasets.BeamBasedBuilder ):
def a_ ( self : Dict ... | 416 | 1 |
from ...configuration_utils import PretrainedConfig
class A__ ( UpperCamelCase__ ):
UpperCAmelCase = "bert-generation"
def __init__( self : Optional[Any] , _a : List[str]=5_0358 , _a : Optional[Any]=1024 , _a : str=24 ... | 691 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCAmelCase_ ( metaclass=A ):
'''simple docstring'''
lowercase_ : Optional[int] = ["torch", "transformers", "onnx"]
def __init__( self : Tuple , *snake_case__ : str ... | 199 | 0 |
from bisect import bisect
from itertools import accumulate
def a_ ( lowerCAmelCase_ : Optional[Any], lowerCAmelCase_ : Dict, lowerCAmelCase_ : Tuple, lowerCAmelCase_ : Optional[Any] ):
__lowerCAmelCase = sorted(zip(snake_case__, snake_case__ ), key=lam... | 700 |
_snake_case : List[Any] = [
999,
800,
799,
600,
599,
500,
400,
399,
377,
355,
333,
311,
288,
266,
244,
222,
200,
199,
177,
155,
133,
111,
88,
66,
44,
22,
0,
]
_snake_case : Lis... | 421 | 0 |
from scipy.stats import pearsonr
import datasets
__lowerCamelCase : Union[str, Any] = "\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 as... | 323 |
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
'''The `inpainting.py` script is outdated. Please use directly `from diffusers import'''
''' StableDiffusionInpaintPipeline` instead.'''
)
| 230 | 0 |
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class _lowerCAmelCase ( UpperCAmelCase_ )... | 669 |
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 .attention_processor imp... | 669 | 1 |
"""simple docstring"""
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeli... | 29 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowercase ( _lower... | 422 | 0 |
"""simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from transformers import CLIPImageProcessor, CLIPVisionModel
from ...models import PriorTransformer
from ...pipelines import DiffusionPipeline
from ...schedulers impor... | 625 |
"""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
_lowercase : List[st... | 625 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor... | 603 |
'''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_ = {'configuratio... | 603 | 1 |
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_common import SequenceFe... | 130 |
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 B... | 130 | 1 |
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
_A : List[Any] = """
@inproceedings{xu-etal-2016-optimizing,
title = {Optimizing Statistical Machine Translation for Text Simplification},
authors={Xu, W... | 100 | import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common... | 576 | 0 |
"""simple docstring"""
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.conf... | 85 |
"""simple docstring"""
def lowercase__(A ) ->list:
"""simple docstring"""
if n_term == "":
return []
lowercase__ : list= []
for temp in range(int(A ) ):
series.append(f'''1/{temp + 1}''' if series else "1... | 85 | 1 |
"""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 ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils... | 389 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeli... | 389 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
__a = logging.get_logger(__name__)
class A__ ( UpperCamelCase ):
"""simple docstring"""
def __init__( self : Dict , *lowerCA... | 257 | '''simple docstring'''
import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
import huggi... | 257 | 1 |
'''simple docstring'''
from collections import Counter
from timeit import timeit
def lowercase__ ( __UpperCamelCase = "" , )-> bool:
return sum(c % 2 for c in Counter(input_str.replace(""" """ , """""" ).lower() ).values() ) < 2
... | 301 |
'''simple docstring'''
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
SCREA... | 301 | 1 |
'''simple docstring'''
from math import factorial
def __lowerCAmelCase (__lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ):
if successes > trials:
raise ValueError("successes must be lower or equal to trials" )
if trials < 0 or successes < 0:
raise Valu... | 716 |
'''simple docstring'''
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -... | 40 | 0 |
def _a ( lowercase__ : list , lowercase__ : int = 0 ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : Union[str, Any] = length or len(lowercase__ )
SCREAMING_SNAKE_CASE__ : Optional[int] = False
for i in range(length - 1 ):
... | 85 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaP... | 527 | 0 |
'''simple docstring'''
import math
from typing import Callable, List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_dif... | 720 | '''simple docstring'''
def UpperCamelCase_ ( snake_case_ : list , snake_case_ : int , snake_case_ : int = 0 , snake_case_ : int = 0 ) -> int:
'''simple docstring'''
__lowerCAmelCase = right or len(snake_case_ ) - 1
if left > right:
return -1
elif list_data[... | 330 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
SCREAMING_SNAKE_CASE : List[Any] = {
'''configuration_layoutlmv2''': ['''LA... | 156 |
"""simple docstring"""
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import datasets
class _... | 156 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():... | 117 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from acceler... | 117 | 1 |
"""simple docstring"""
import argparse
import os
# New Code #
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_w... | 65 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image... | 65 | 1 |
'''simple docstring'''
import math
def _snake_case ( lowercase ) -> bool:
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 multiples of 3 are not primes
... | 717 |
'''simple docstring'''
import warnings
from functools import wraps
from typing import Callable
def _snake_case ( lowercase ) -> Callable:
@wraps(lowercase )
def _inner_fn(*lowercase , **lowercase ):
warnings.warn(
(F"""'{fn.__name__}' is exp... | 697 | 0 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
UpperCamelCase__ : Union[str, Any] = '''%20'''.join(argv[1:]) if len(argv) > 1 else quote(str(input('''S... | 105 |
'''simple docstring'''
import darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
SCREAMING_SNAKE_CASE_ = {
"n_samples": 6_4,
"horizon": 3_2,
"num_inference_steps": 2_0,
"n_guide_steps": 2, # can set to 0 for faster sampl... | 597 | 0 |
def snake_case ( snake_case__ :str , snake_case__ :str) -> str:
_A = len(snake_case__)
_A = len(snake_case__)
_A = (
first_str_length if first_str_length > second_str_length else second_str_length
)
_A =... | 83 | # Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required... | 83 | 1 |
"""simple docstring"""
import logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
fr... | 19 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCAmelCase__ ( metaclass=UpperCAmelCase_):
__SCREAMING_SNAKE_CASE = ['''torch''', '''torchsde''']
def __init__( self , *lowercase , **lowercase ) -> str:
requires_... | 601 | 0 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokeniz... | 705 |
'''simple docstring'''
from typing import List, Optional
from tokenizers import ByteLevelBPETokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer
UpperCAmelCase_ : Union[str, Any] = ... | 11 | 0 |
"""simple docstring"""
import unittest
from transformers import AlbertConfig, is_torch_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_common import Mode... | 7 |
'''simple docstring'''
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf ... | 366 | 0 |
from __future__ import annotations
class a__:
def __init__( self : Dict , __snake_case : int ):
a : Dict = data
a : Node | None = None
a : Node | None = None
def lowerCamelCase__ ( _A ): # In Order travers... | 721 |
'''simple docstring'''
from collections import UserDict
from typing import Union
import numpy as np
import requests
from ..utils import (
add_end_docstrings,
logging,
)
from .audio_classification import ffmpeg_read
from .base import PIPELINE_INIT_ARGS, Pipeline
lowerCAmelCase: Optional[Any] ... | 195 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSe... | 580 |
"""simple docstring"""
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copie... | 580 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenizatio... | 710 |
"""simple docstring"""
def snake_case ( lowerCAmelCase_ = 1000 ) -> int:
return sum(e for e in range(3 , lowerCAmelCase_ ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(F"{solution() = }")
| 404 | 0 |
from __future__ import annotations
def __SCREAMING_SNAKE_CASE ( UpperCamelCase__ , UpperCamelCase__ ) -> float:
'''simple docstring'''
UpperCAmelCase = sorted(numsa + numsa )
UpperCAmelCase , UpperCAmelCase = divmod(len(U... | 130 |
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def __SCREAMING_SNAKE_CASE ( UpperCamelCase__ , UpperCamelCase__ ) -> str | Literal[False]:
'''simple docstring'''
UpperCAmelCase = list(UpperCamelCas... | 130 | 1 |
def lowerCamelCase__ ( _a):
return "".join([hex(_a)[2:].zfill(2).upper() for byte in list(_a)])
def lowerCamelCase__ ( _a):
# Check data validity, following RFC3548
# https://www.ietf.org/rfc/rfc3548.txt
if (len(_a) % 2) != 0:
raise ValueError(
"Base16 encoded data is invalid:\nData does not ha... | 193 |
import numpy as np
class _UpperCamelCase :
'''simple docstring'''
def __init__( self : Dict ) -> str:
"""simple docstring"""
SCREAMING_SNAKE_CASE : List[str] = (0, 0)
SCREAMING_SNAKE_CASE : Any = None
SCREAMING_SN... | 193 | 1 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import re... | 251 | '''simple docstring'''
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPip... | 251 | 1 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.... | 173 | """simple docstring"""
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class a ( ctypes.Structure ):
# _fields is a specific attr expected by ctypes
A_ : Dict = [(... | 173 | 1 |
"""simple docstring"""
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicat... | 247 |
"""simple docstring"""
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_token... | 247 | 1 |
'''simple docstring'''
import argparse
import os
from accelerate.utils import ComputeEnvironment
from .cluster import get_cluster_input
from .config_args import cache_dir, default_config_file, default_yaml_config_file, load_config_from_file # noqa: F401
from .config_utils import _ask_field, _ask_option... | 717 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
snake_case_ : List[Any] = {
'configuration_data2vec_audio': ['DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Data2VecAudioConfig'],
... | 350 | 0 |
import warnings
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
A__ = logging.get_logger(__name__)
class _lowerCAmelCase ( __SCREAMING_SNAKE_CASE ):
_UpperCAmelCase = ['input_ids', 'at... | 166 | # Copyright 2022 The HuggingFace Team and The OpenBMB 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
#
#... | 166 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
lowerCamelCase__ = argparse.ArgumentParser(
description=(
'Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Tran... | 705 |
'''simple docstring'''
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, s... | 40 | 0 |
"""simple docstring"""
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMix... | 388 |
"""simple docstring"""
from __future__ import annotations
import math
def __a ( a, a ):
"""simple docstring"""
_a = u
for i in range(1, a ):
_a = temp * (u - i)
return temp
def __a ( ):
"""sim... | 388 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
a : int = {"configuration_speech_encoder_decoder": ["SpeechEncoderDecoderConfig"]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except Option... | 707 |
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class lowerCamelCase_ ( lowerCAmelCa... | 527 | 0 |
from __future__ import annotations
def A__ ( lowerCamelCase , lowerCamelCase , lowerCamelCase , lowerCamelCase ) -> Tuple: # noqa: E741
while r - l > 1:
UpperCamelCase_: List[str] = (l + r) // 2
if v[m] >= key:
UpperCamelCase_: ... | 548 |
'''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 BeitConfig, BeitForImageClassification, BeitForMaskedImageModeling, BeitImageProcessor
from... | 369 | 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, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase__ : Any = logging.get_logger(__n... | 329 |
'''simple docstring'''
import requests
lowerCAmelCase__ : Union[str, Any] = "" # <-- Put your OpenWeatherMap appid here!
lowerCAmelCase__ : str = "https://api.openweathermap.org/data/2.5/"
def __UpperCamelCase ( _UpperCAmelCase = "Chicago", _UpperCAmelCase = APPID ):
return r... | 329 | 1 |
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import KandinskyVaaPrior... | 63 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ap... | 668 | 0 |
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension_for... | 708 |
import argparse
import os
import numpy as np
import tensorflow as tf
import torch
from transformers import BertModel
def lowercase ( a , a , a ):
'''simple docstring'''
SCREAMING_SNAKE_CASE_ :int = ("dense.weight", "attention.self.query", "attention.self.key", "... | 140 | 0 |
'''simple docstring'''
import os
from collections import deque
import torch
from torch.utils.data import Dataset
class a__ ( lowerCamelCase_ ):
def __init__( self , _UpperCamelCase="" , _UpperCamelCase="train" ):
"""simple docstring"""
assert os.path... | 245 |
'''simple docstring'''
import os
from collections import deque
import torch
from torch.utils.data import Dataset
class a__ ( lowerCamelCase_ ):
def __init__( self , _UpperCamelCase="" , _UpperCamelCase="train" ):
"""simple docstring"""
assert os.path... | 245 | 1 |
"""simple docstring"""
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import TimesformerConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from tra... | 702 | """simple docstring"""
import heapq as hq
import math
from collections.abc import Iterator
class _lowercase :
"""simple docstring"""
def __init__( self : Tuple , UpperCamelCase__ : int ) -> List[str]:
'''s... | 296 | 0 |
"""simple docstring"""
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def _A( ):
A__ : Any = [randint(-1000 , 1000 ) for i in range(10 )]
A__ : Union[str, Any] = randint(... | 363 | """simple docstring"""
import argparse
import hashlib
import os
import urllib
import warnings
import torch
from torch import nn
from tqdm import tqdm
from transformers import WhisperConfig, WhisperForConditionalGeneration
_UpperCamelCase = {
"tiny.en": "https://openaipublic.azureedge.net/main/whisper... | 363 | 1 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
Wav... | 344 |
'''simple docstring'''
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/faceb... | 344 | 1 |
'''simple docstring'''
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
Auto... | 585 |
'''simple docstring'''
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
__lowerCAmelCase = '\\n@article{wang2019superglue,\n title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},\n author... | 585 | 1 |
"""simple docstring"""
a = tuple[float, float, float]
a = tuple[float, float, float]
def _snake_case ( _snake_case : Pointad , _snake_case : Pointad ) -> Vectorad:
'''simple docstring'''
_A = en... | 713 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
a = logging.get_logger(__name__)
a = {
'''Visual-Attention-Network/van-base''': (
'''https://huggingface.co/Visual-Attention-Network/van-base/blob/main/config.json'''
... | 505 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
"""google/vivit-b-16x2-kinetics400""": (
"""https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json"""
),
... | 411 |
from __future__ import annotations
from collections.abc import MutableSequence
class _lowerCAmelCase :
'''simple docstring'''
def __init__( self : Optional[int] , UpperCamelCase : int , UpperCamelCase : MutableSequence[float] ):
'''simple ... | 411 | 1 |
"""simple docstring"""
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_torch_available():
impor... | 132 | """simple docstring"""
import unittest
import numpy as np
from transformers import MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING, TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING
from transformers.pipelines import AudioClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simp... | 132 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE__ : Optional[int] = {
"""configuration_x_clip""": [
"""XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""XCLIPConfig""",
"""XCLIPTextConfig... | 0 |
import os
import unittest
from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils ... | 0 | 1 |
def A__( __lowerCAmelCase ):
if not isinstance(__lowerCAmelCase , __lowerCAmelCase ):
raise TypeError('only integers accepted as input' )
else:
_snake_case : Any = str(abs(__lowerCAmelCase ) )
_snake_case : List[str] = [list(__lowerCAmelC... | 719 |
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
lowercase_ : Optional[int] = object()
# For specifying empty leaf dict `{}`
lowercase_ : List[Any] = ... | 652 | 0 |
'''simple docstring'''
import json
import os
import unittest
from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common... | 69 | '''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
SCREAMING_SNAKE_CASE_ = 'scheduler_config.json'
class a ... | 523 | 0 |
'''simple docstring'''
from __future__ import annotations
import requests
def __magic_name__( _A ):
'''simple docstring'''
UpperCamelCase__ = f"https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"
return requests.get(_A ).json()
def __... | 265 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
lowerCamelCase_ : List[str] = TypeVar('''T''')
lowerCamelCase_ : Optional[int] = TypeVar('''U''')
class _SCREAMING_SNAKE_CASE ( Generic[T, U] ... | 265 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> 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:... | 638 |
"""simple docstring"""
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
__A = {
"""<""": operator.lt,
"""<=""": operator.le,
"""==""": operator.eq,
"""!=""": operator.ne,
""">=""": operator.ge,
"... | 93 | 0 |
"""simple docstring"""
from .integrations import (
is_optuna_available,
is_ray_available,
is_sigopt_available,
is_wandb_available,
run_hp_search_optuna,
run_hp_search_ray,
run_hp_search_sigopt,
run_hp_search_wandb,
)
from .trainer_utils import (
HPSearchBackend,
default... | 706 |
"""simple docstring"""
from __future__ import annotations
class __SCREAMING_SNAKE_CASE :
def __init__( self : Any , snake_case : str , snake_case : str ):
'''simple docstring'''
A__ , A__ : List[s... | 498 | 0 |
'''simple docstring'''
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class _lowercase( unittest.TestCase ):
"""simple docstring"""
def snake_case ( self: Tuple ):
__UpperCAmelCas... | 396 | '''simple docstring'''
import argparse
from collections import defaultdict
import yaml
_UpperCamelCase : int = 'docs/source/en/_toctree.yml'
def __snake_case ( lowerCAmelCase : Union[str, Any] ):
__UpperCAmelCase = defaultdict(lowerCAmelCase )
__Up... | 396 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case ={
"""configuration_roformer""": ["... | 513 |
'''simple docstring'''
class UpperCAmelCase_ :
def __init__( self : List[str] , UpperCAmelCase__ : int , UpperCAmelCase__ : List[Any]=None , UpperCAmelCase__ : Union[str, Any]=None ) -> str:
lowerCAmelCase = data
lowerCA... | 513 | 1 |
'''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 _lowerCAmelCase ( _UpperCamelCase : List[str] , _UpperCamelCase : Tuple , _UpperCamelCase : Union[str, Any... | 405 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCamelCase : List[str] = {
"configuration_biogpt": ["BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BioGptConfig"],
"tokenization_bio... | 405 | 1 |
from __future__ import annotations
def a (lowerCAmelCase__ ):
if len(lowerCAmelCase__ ) == 0:
return array
__a , __a = min(lowerCAmelCase__ ), max(lowerCAmelCase__ )
# Compute the variables
__a = _max - _min + 1
__a ... | 209 |
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
SCREAMING_SNAKE_CASE = {'UserAgent': UserAgent().random}
def a (lowerCAmelCase__ ):
__a = script.contents[0]
__a ... | 209 | 1 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
UpperCamelCase : int = {'vocab_file': 'vocab.txt', 'tokenizer_fi... | 50 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqCo... | 18 | 0 |
"""simple docstring"""
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
lowerCamelCase_ = get_logger(__name__)
class UpperCamelCase_ (enum.Enum ):
__magic_name__ = '''all_checks'''
__magic_nam... | 463 |
"""simple docstring"""
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
lowerCamelCase_ = pytest.mark.integration
@pytest.mark.parametrize("path"... | 463 | 1 |
'''simple docstring'''
def __A ( UpperCAmelCase ) -> str:
'''simple docstring'''
_UpperCamelCase : str = [0] * len(UpperCAmelCase )
_UpperCamelCase : int = []
_UpperCamelCase : Tuple = []
... | 435 | '''simple docstring'''
import sys
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific note... | 435 | 1 |
from __future__ import annotations
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: str , SCREAMING_SNAKE_CASE_: list[str] | None = None ) -> list[list[str]]:
'''simple docstring'''
A__ = word_bank or []
# create a table
A__ = len(SCR... | 720 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import torch
i... | 626 | 0 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
SCREAMING_SNAKE_CASE_ = logging... | 34 |
"""simple docstring"""
import operator
def __snake_case ( _lowercase ,_lowercase = False ,_lowercase = None ):
"""simple docstring"""
UpperCamelCase = operator.lt if reverse else operator.gt
UpperCamelCase = solution or []
if not arr:
... | 34 | 1 |
'''simple docstring'''
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def __snake_case ( lowercase : int ):
... | 420 |
'''simple docstring'''
import json
import re
from typing import TYPE_CHECKING, List, Optional, Tuple, Union
import numpy as np
from ...utils import is_tf_available, is_torch_available, logging
if TYPE_CHECKING:
if is_torch_available():
import torch
if is_tf_available():
import... | 420 | 1 |
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