code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ : str = {
'''configuration_distilbert''': [
'''DISTILBERT_P... | 38 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
Aut... | 318 | 0 |
'''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_dow... | 351 |
'''simple docstring'''
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase ... | 187 | 0 |
'''simple docstring'''
def __snake_case( _lowerCAmelCase = 1_000_000 ) -> int:
snake_case__ : Dict = set(range(3 , _lowerCAmelCase , 2 ) )
primes.add(2 )
for p in range(3 , _lowerCAmelCase , 2 ):
if p not in primes:
... | 35 |
'''simple docstring'''
# Function to print upper half of diamond (pyramid)
def __snake_case( _lowerCAmelCase ) -> Any:
for i in range(0 , _lowerCAmelCase ):
for _ in range(0 , n - i - 1 ): # printing spaces
print(""" """ , end="""""" )
... | 35 | 1 |
"""simple docstring"""
def _snake_case ( _snake_case : str ) -> bool:
'''simple docstring'''
if not all(x.isalpha() for x in string ):
raise ValueError('String must only contain alphabetic characters.' )
_A = sorted(string.low... | 271 |
"""simple docstring"""
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase_ ( __lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase : Union[str, Any] = (IPNDMScheduler,)
UpperCAmelCase :... | 271 | 1 |
'''simple docstring'''
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
lowerCamelCase__ = "\\n@inproceedings{wang2019glue,\n title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},\n ... | 234 |
'''simple docstring'''
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
import numpy as np
# Parrameters
_lowercase : Any = (7_2_0, 1_2_8_0) # Height, Width
_lowercase : List[Any] = (0.4, 0.6) # if height or width ... | 93 | 0 |
"""simple docstring"""
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL impo... | 371 | """simple docstring"""
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairscale_available
from transformers... | 30 | 0 |
'''simple docstring'''
def __lowercase ( __lowercase , __lowercase , __lowercase=False ) -> Union[str, Any]:
'''simple docstring'''
if isinstance(__lowercase , __lowercase ) and isinstance(__lowercase , __lowercase ):
_A =... | 79 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional
import numpy as np
import torch
import torch.nn as nn
from ..utils import BaseOutput, is_torch_version, randn_tensor
from .attention_processor import SpatialNorm
from .unet_ad_blocks import UNetMidBlockaD, get_down_block, get... | 42 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDCondition... | 12 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
lowercase__ = False
class lowe... | 12 | 1 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from tran... | 162 | from ...processing_utils import ProcessorMixin
class lowerCamelCase (SCREAMING_SNAKE_CASE__ ):
"""simple docstring"""
lowerCamelCase__ = ['''image_processor''', '''feature_extractor''']
lowerCamelCase__ = '''TvltImageProcessor'''
lowerCamelCase__ = '''TvltFeatureExtractor'''
... | 118 | 0 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_datas... | 356 |
"""simple docstring"""
def _lowerCamelCase(__UpperCamelCase ) -> Optional[Any]:
_lowerCAmelCase =0
_lowerCAmelCase =len(__UpperCamelCase )
for i in range(n - 1 ):
for j in range(i + 1 , __UpperCamelCase ):
if arr[i] > arr[j]:
num_inversions += 1
return num_invers... | 341 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class A ( metaclass=SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
A = ["torch", "scipy"]
def __init__(self , *_UpperCAmelCase , **_UpperCAmelCase ) -> Lis... | 298 |
'''simple docstring'''
import argparse
import os
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_task_guides.py
_lowerCAmelCase = '''src/tr... | 298 | 1 |
import inspect
import unittest
import warnings
from transformers import DeiTConfig
from transformers.models.auto import get_values
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import ... | 368 | from ....utils import logging
A : List[str] = logging.get_logger(__name__)
class lowerCamelCase (SCREAMING_SNAKE_CASE__ ):
"""simple docstring"""
def __init__( self : List[str] , __magic_name__ : Optional[Any] , __magic_name__ : Any=None ... | 305 | 0 |
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from .modules import *
| 204 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, DDPMScheduler, StableDiffusionUpscalePipeline, UNetaDConditionModel
from diffusers... | 204 | 1 |
def A ( _UpperCAmelCase : str , _UpperCAmelCase : str , _UpperCAmelCase : Any , _UpperCAmelCase : Tuple ) -> Tuple:
'''simple docstring'''
global f # a global dp table for knapsack
if f[i][j] < 0:
if... | 362 |
UpperCAmelCase__ = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
def A ( _UpperCAmelCase : dict , _UpperCAmelCase : Optional[int] , _Upper... | 290 | 0 |
def a ( _UpperCAmelCase : int ):
'''simple docstring'''
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 226 |
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 rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
ImageInput,
P... | 226 | 1 |
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class a__ ( __snake_case , __snake_case ):
A__ : ... | 197 | import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArguments
@requi... | 197 | 1 |
"""simple docstring"""
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class _UpperCAmelCase :
'''simple docstring'''
pass
| 102 |
"""simple docstring"""
import numpy as np
def lowercase ( _snake_case : int , _snake_case : Optional[Any] , _snake_case : Optional[int] , _snake_case : int , _snake_case : Union[str, Any] ) ->Dict:
"""simple docstrin... | 102 | 1 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel... | 122 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__snake_case : Dict = {"""configuration_focalnet""": ["""FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FocalNetConfig"""]}
tr... | 122 | 1 |
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
UpperCAmelCase__ = logging.get_logger(__name__)
UpperCAmelCase__ ... | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : int = logging.get_logger(__name__)
lowerCamelCase : List[Any] = {
'google/realm-cc-news-pretrained-embedder': (
'https://huggingface.co/google/realm-c... | 2 | 0 |
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vision_avai... | 307 |
import torch
from diffusers import DPMSolverSDEScheduler
from diffusers.utils import torch_device
from diffusers.utils.testing_utils import require_torchsde
from .test_schedulers import SchedulerCommonTest
@require_torchsde
class A__ ( __magic_name__ ):
lowercase ... | 307 | 1 |
a_ = [
'''DownloadConfig''',
'''DownloadManager''',
'''DownloadMode''',
'''StreamingDownloadManager''',
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import StreamingDownloadManager
| 340 |
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__ ( _UpperCAmelCase ):
a_ ... | 340 | 1 |
"""simple docstring"""
import socket
def __SCREAMING_SNAKE_CASE ( ):
_lowercase : Optional[int] = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
_lowercase : Optional[int] = socket.gethostname()
_lowercase : Dict = 12312
sock.co... | 356 |
"""simple docstring"""
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationSt... | 336 | 0 |
from math import asin, atan, cos, radians, sin, sqrt, tan
_snake_case = 6_3_7_8_1_3_7.0
_snake_case = 6_3_5_6_7_5_2.3_1_4_2_4_5
_snake_case = 6378137
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_,snake_case_ ):
_A : Any ... | 26 |
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 ConfigTester
from ... | 199 | 0 |
from __future__ import annotations
import math
def _lowerCamelCase( lowercase__ , lowercase__ , lowercase__ , lowercase__ , lowercase__ ) -> int:
'''simple docstring'''
if depth < 0:
raise ValueError('Depth cannot be less than 0' )
if n... | 356 |
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
lowerCAmelCase = {'''UserAgent''': UserAgent().random}
def _lowerCamelCase( lowercase__ ) -> dict:
'''simple docstring'''
__lowercase= scr... | 304 | 0 |
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_co... | 327 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"""transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json""",
}
class A__ ( lowerCAmelCase... | 325 | 0 |
from functools import reduce
lowercase = (
"""73167176531330624919225119674426574742355349194934"""
"""96983520312774506326239578318016984801869478851843"""
"""85861560789112949495459501737958331952853208805511"""
"""12540698747158523863050715693290963295227443043557"""
"""668... | 35 | from __future__ import annotations
from collections import Counter
from random import random
class __lowercase :
'''simple docstring'''
def __init__( self : List[Any] ):
UpperCamelCase__ = {}
def A_ ( self : ... | 35 | 1 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer import RoForm... | 134 |
'''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,
)
__snake_case : Any = pytest.mark.integration
@pytest.mark.parametrize("""p... | 134 | 1 |
'''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_inputs
if ... | 357 |
'''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_warmup, set_seed... | 287 | 0 |
"""simple docstring"""
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
pass
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
pass
class _UpperCamelCase :
'''simple docstring'''
def __init__( self ... | 57 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
__UpperCAmelCase : Union[str, Any] =["""image_processor""", """t... | 57 | 1 |
import math
import os
import unittest
from transformers import MegatronBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_com... | 350 |
def _a ( a :int = 600_851_475_143 ) -> int:
try:
a = int(a )
except (TypeError, ValueError):
raise TypeError('''Parameter n must be int or castable to int.''' )
if n <= 0:
raise ValueError('''Parameter n must be greater than or equal to one.''' )
a ... | 26 | 0 |
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def lowerCamelCase_ ( UpperCamelCase__ : Tuple , UpperCamelCase__ : bool = True , UpperCamelCase__ : float = math.inf , UpperCamelCase__ : float =... | 90 |
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
lowerCamelCase_ = get_tests_dir('''fixtures/spiece.model''... | 244 | 0 |
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
snake_case : Optional[Any] = re.compile(R'''\b(a|an|the)\b''', re.UNICODE)
snake_case : int = None
def __lowerCamelCase ( ):
"""simple docstring"""
... | 281 |
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def __lowerCamelCase ( UpperCAmelCase_ : dict ):
"""... | 281 | 1 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import KarrasVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class UpperCAmelCase_ ... | 4 |
from typing import Dict, Iterable, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
IMAGENET_S... | 204 | 0 |
import argparse
import torch
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_from_original_stable_diffusion_ckpt
if __name__ == "__main__":
UpperCAmelCase__ = argparse.ArgumentParser()
parser.add_argument(
"--checkpoint_path", defau... | 356 |
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 (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils impo... | 26 | 0 |
def a__ ( ):
return [list(range(10_00 - i ,-10_00 - i ,-1 ) ) for i in range(10_00 )]
a_ = generate_large_matrix()
a_ = (
[[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, -1, -2, -3]],
[[3, 2], [1, 0]],
[[7, 7, 6]],
[[7, 7, 6], [-1... | 330 |
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import DEFAULTS, task_specific_para... | 330 | 1 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
_UpperCAmelCase : Tuple = logging.get_logger(__name__)
_Upper... | 200 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_UpperCAmelCase : int = logging.get_logger(__name__)
_UpperCAmelCase : Optional[Any] = {
"""junnyu/rofo... | 200 | 1 |
'''simple docstring'''
import functools
def _lowerCamelCase ( lowercase : list[int] , lowercase : list[int] ) -> int:
# Validation
if not isinstance(lowercase , lowercase ) or not all(isinstance(lowercase , lowercase ) for day... | 63 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
lowerCAmelCase_ : int = {'configuration_gpt_neox': ['GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPT... | 63 | 1 |
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, require_torch
from tr... | 371 |
from __future__ import annotations
import os
from typing import Any
import requests
_UpperCAmelCase : int = """https://api.github.com"""
# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
_UpperCAmelCase : Dict = BASE_URL + """/user"""... | 200 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import YolosConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_com... | 191 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase_ = logging.get_logger(__name__)
lowerCamelCase_ = {
"facebo... | 191 | 1 |
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, TypedSequence
from datasets.features import ... | 363 |
from sklearn.metrics import mean_squared_error
import datasets
UpperCamelCase__ = """\
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
and Thirion, B. and Grisel, O. and Blondel, M. and Pre... | 102 | 0 |
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
UpperCAmelCase_ : str = logging.get_logger(__name__)
UpperCAmelCase_ :... | 32 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase_ : Optional[int] = {
'facebook/mask2former-swin-small-coco-instance': (
'https://huggingfa... | 32 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mvp im... | 370 |
"""simple docstring"""
from collections import defaultdict
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : Union[str, Any], lowerCamelCase : List[Any], lowerCamelCase : List[str] )-> Optional[int]:
lowerCamelCase__ : List[A... | 272 | 0 |
print((lambda quine: quine % quine)("print((lambda quine: quine %% quine)(%r))"))
| 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase__ = {
"configuration_nllb_moe": [
"NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP",
"NllbMoeConfig",
]
}
try:
if not is_torch_av... | 0 | 1 |
"""simple docstring"""
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class SCREAMING_SNAKE_CASE__ ( UpperCAmelCase__ ):
def __init__... | 366 |
"""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_convbert import ConvBertTokenizer
A: int = logging.get_logger(__name__)
... | 76 | 0 |
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def UpperCamelCase ( snake_case__ : Union[str, Any] , snake_case__ ... | 119 |
'''simple docstring'''
import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoCo... | 344 | 0 |
'''simple docstring'''
import os
import zipfile
import pytest
from datasets.utils.extract import (
BzipaExtractor,
Extractor,
GzipExtractor,
LzaExtractor,
SevenZipExtractor,
TarExtractor,
XzExtractor,
ZipExtractor,
ZstdExtractor,
)
from .utils import require_lza, require_pyazr... | 363 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
StableDiffusionXLImgaI... | 275 | 0 |
'''simple docstring'''
from functools import reduce
__a: List[Any] = (
"73167176531330624919225119674426574742355349194934"
"96983520312774506326239578318016984801869478851843"
"85861560789112949495459501737958331952853208805511"
"12540698747158523863050715693290963295227443043557"
"668... | 198 | import argparse
import logging
from collections import namedtuple
import torch
from model_bertabs import BertAbsSummarizer
from models.model_builder import AbsSummarizer # The authors' implementation
from transformers import BertTokenizer
logging.basicConfig(level=logging.INFO)
A : Optional[int] = l... | 118 | 0 |
'''simple docstring'''
def UpperCamelCase ( _lowerCamelCase : int ):
if a < 0:
raise ValueError("Input value must be a positive integer" )
elif isinstance(_lowerCamelCase , _lowerCamelCase ):
raise TypeError("Input value must be a 'int' type" )
return bin(_lowerCam... | 123 |
'''simple docstring'''
def UpperCamelCase ( _lowerCamelCase : int ):
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
A__ = F"Input value of [number={number}] must be an integer"
raise TypeError(_lowerCamelCase )
if number < 1:
A__ = F"I... | 123 | 1 |
from math import factorial
def _lowerCAmelCase ( lowerCAmelCase_ :int = 20 )->int:
'''simple docstring'''
snake_case_ = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
snake_case_ = n // 2
retu... | 159 |
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vision_available
... | 159 | 1 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCamelCase = {
'configuration_informer': [
'INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'InformerConfig',
... | 361 |
def SCREAMING_SNAKE_CASE ( __UpperCamelCase : Optional[Any] ) -> Union[str, Any]:
UpperCAmelCase_ = len(__UpperCamelCase )
while cur > 1:
# Find the maximum number in arr
UpperCAmelCase_ = arr.index(max(arr[0:cur] ) )
... | 177 | 0 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ ):
'''simple docstring'''
while b:
__SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE = b, a % b
return a
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCA... | 54 |
"""simple docstring"""
from __future__ import annotations
import pandas as pd
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = [0] * no_of_processes
__SCREAMING_SNAKE_CASE ... | 54 | 1 |
'''simple docstring'''
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
renew_vae... | 352 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class UpperCamelCase__:
__magic_name__ : List[str]
__magic_name_... | 91 | 0 |
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def UpperCAmelCase__ (UpperCamelCase_ = 3 ):
"""simple docstring"""
if isinstance(UpperCamelCase_ ,UpperCamelCase_ ):
... | 127 |
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def UpperCAmelCase__ (UpperCamelCase_ ):
"""simple docstring"""
snake_case = {}
snake_case = job['''started_at''']
snake_case = job['''com... | 127 | 1 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultip... | 67 |
'''simple docstring'''
def a__ ( _SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : int ) -> int:
"""simple docstring"""
return int((input_a, input_a).count(0 ) != 0 )
def a__ ( ) -> None:
"""simple docstring"""
... | 67 | 1 |
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundfile_availble, is_... | 21 |
def SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ , lowerCamelCase__ ) -> float:
if discount_rate < 0:
raise ValueError('Discount rate cannot be negative' )
if not cash_flows:
raise ValueError('Cash flows list cannot be empty' )
__lowerCamelCase : int = sum(
cash_... | 73 | 0 |
"""simple docstring"""
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class UpperCAmelCase (unittest.TestCase ):
"""simple docstring"""
... | 360 | """simple docstring"""
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS_CACHE,
WEIGHTS_NAME,
... | 2 | 0 |
'''simple docstring'''
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class SCREAMING_SNAKE_CASE (a__ ):
lowerCAmelCase = (DDIMParallelScheduler,)
lowerCAmelCase = (('''eta''', 0.0), ('''... | 190 |
'''simple docstring'''
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
lowercase__ : List[Any] = pd.read_csv('''s... | 190 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_nump... | 160 |
'''simple docstring'''
import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, L... | 160 | 1 |
"""simple docstring"""
import argparse
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM
from transformers.utils import logging
logging.set_verbosity_info()
_lowercase = logging.get_logger(__name_... | 74 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImageProcessor
from diffusers.pipe... | 21 | 0 |
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configur... | 363 |
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 : List[str] = logging.get_logger(__name__)
_lowerCAmelCase : ... | 308 | 0 |
"""simple docstring"""
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
lowerC... | 16 |
def snake_case__ ( SCREAMING_SNAKE_CASE_ : str = "The quick brown fox jumps over the lazy dog" , ):
'''simple docstring'''
lowercase__ : str = set()
# Replace all the whitespace in our sentence
lowercase__ : Tuple = input_str.replace(' ' , ... | 214 | 0 |
'''simple docstring'''
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require... | 31 |
'''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_... | 31 | 1 |
class _SCREAMING_SNAKE_CASE :
def __init__( self , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE )-> Tuple:
lowerCamelCase_ =None
lowerCamelCase_ =None
lowerCamelCase_ =graph
s... | 154 |
import argparse
import torch
from transformers import (
UniSpeechSatConfig,
UniSpeechSatForAudioFrameClassification,
UniSpeechSatForSequenceClassification,
UniSpeechSatForXVector,
WavaVecaFeatureExtractor,
logging,
)
logging.set_verbosity_info()
__A : Tuple = logging.get_logger... | 154 | 1 |
"""simple docstring"""
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
SCREAMING_SNAKE_CASE__:Any = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__:Dict = {
"""google/umt5-small""": """https://hu... | 268 | """simple docstring"""
from ..utils import DummyObject, requires_backends
class snake_case__ ( metaclass=snake_case_ ):
_snake_case : Union[str, Any] = ["""onnx"""]
def __init__( self , *lowerCamelCase , **lowerCamelCase ):
requires_backends(self , [... | 268 | 1 |
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_forma... | 15 | import math
def A ( _lowercase ):
return math.sqrt(_lowercase ) * math.sqrt(_lowercase ) == num
def A ( _lowercase ):
SCREAMING_SNAKE_CASE : Dict = 0
SCREAMING_SNAKE_CASE : Tuple = n
while left <= right:
... | 182 | 0 |
import argparse
import json
import logging
import os
import sys
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, get_gpu_count, slow
__UpperCAmelCase = [
os.path.join(os.path.dirname(__file__), dirname)
for dirname in [
"text-classification",
"langu... | 353 |
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
__UpperCAmelCase = input("Enter image url: ").strip()
print(F"""Downloading image from {url} ...""")
__UpperCAmelCase = BeautifulSoup(requests.get(url).content, "html.parser")
# The image ... | 257 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_UpperCAmelCase : List[Any] = logging.get_logger(__name__)
_UpperCAmelCase : Tuple = {
"""goog... | 285 |
def __lowerCamelCase ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
global f # a global dp table for knapsack
if f[i][j] < 0:
if j < wt[i - 1]:
snake_case_ ... | 285 | 1 |
"""simple docstring"""
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_flax_utils impor... | 362 |
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
from ...tokenization_ut... | 159 | 0 |
import collections
import os
from typing import List, Optional, Tuple
from transformers.utils import is_jieba_available, requires_backends
if is_jieba_available():
import jieba
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCamelCase : Optional[Any] =... | 14 |
import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.serialization import from_bytes, to_bytes
fro... | 20 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCAmelCase : Union[str, Any] = {
"configuration_roform... | 202 |
"""simple docstring"""
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
_lowerCAmelCase ... | 202 | 1 |
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
__A = False
class __lowerCAmelCase ( unitte... | 90 |
'''simple docstring'''
def a ( ) -> Union[str, Any]:
'''simple docstring'''
UpperCamelCase__ :Optional[int] = []
UpperCamelCase__ :int = 1
while len(__a ) < 1e6:
constant.append(str(__a ) )
i += 1
UpperCamelCase__ :U... | 97 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : int = logging.get_logger(__name__)
_lowercase : Optional[Any] = {
"tiiuae/falcon-40b": "https://huggingface.co/tiiuae/falcon-40b/resolve/mai... | 365 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowercase : Union[str, Any] = {
"""configuration_poolformer""": [
"""POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""... | 91 | 0 |
'''simple docstring'''
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
_snake_case = logging.getLogg... | 250 |
'''simple docstring'''
import argparse
import os
import re
_snake_case = 'src/transformers'
# Pattern that looks at the indentation in a line.
_snake_case = re.compile(r'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
_snake_case = re.compile(r'^\s*"([^"]+)":')
# Pattern that m... | 250 | 1 |
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
__UpperCamelCase : Optional[int] = pd.read_csv("sample_data.csv", header=None)
__... | 355 |
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,
)
__UpperCamelCase : List[Any] = pytest.mark.integration
@pytest.mark.parametrize('''path''' , ... | 51 | 0 |
import argparse
import re
from typing import Dict
import torch
from datasets import Audio, Dataset, load_dataset, load_metric
from transformers import AutoFeatureExtractor, pipeline
def a_ ( _A , _A ) -> str:
"""simple docstring"""
snake_case__ ... | 307 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
__UpperCamelCase : Any = {"""tokenization_byt5""": ["""ByT5Tokenizer"""]}
if TYPE_CHECKING:
from .tokenization_byta import ByTaTokenizer
else:
import sys
__UpperCamelCase : List... | 307 | 1 |
def lowerCAmelCase_ ( _lowercase : int = 1000) -> int:
"""simple docstring"""
return sum(e for e in range(3 , _lowercase) if e % 3 == 0 or e % 5 == 0)
if __name__ == "__main__":
print(f'{solution() = }')
| 361 |
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 accel... | 266 | 0 |
import unittest
import numpy as np
from transformers import is_flax_available
from transformers.testing_utils import require_flax
from ..test_modeling_flax_common import ids_tensor
if is_flax_available():
import jax
import jax.numpy as jnp
from transformers.generation i... | 327 |
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class A ( tf.keras.layers.Layer ):
'''simple docstring'''
... | 305 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mvp import MvpTokenizer
... | 353 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowerCamelCase__ = {
"""configuration_blip""": [
"""BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
""... | 307 | 0 |
'''simple docstring'''
import pytest
import datasets
# Import fixture modules as plugins
lowerCamelCase__ = ['tests.fixtures.files', 'tests.fixtures.hub', 'tests.fixtures.fsspec']
def __lowerCAmelCase (__lowerCAmelCase , __lowerCAmelCase ):
# Mark te... | 234 |
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase
def _lowercas... | 275 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCAmelCase : Union[str, Any] = {
"""configuration_vision_e... | 25 |
'''simple docstring'''
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_sentencepie... | 25 | 1 |
"""simple docstring"""
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 tra... | 172 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a : Union[str, Any]= logging.get_logger(__name__)
_a : str= {
"alibaba-damo/mgp-str-base": "https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json",
}... | 172 | 1 |
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : Dict = logging.get_logger(__name__)
lowerCamelCase : Tuple = {
"RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json",
}
... | 365 |
from ..utils import DummyObject, requires_backends
class A( metaclass=UpperCamelCase ):
'''simple docstring'''
UpperCamelCase = ['''transformers''', '''torch''', '''note_seq''']
def __init__( self : Any , *A_ : Any , **A... | 208 | 0 |
from collections.abc import Iterable
from typing import Any
class A__ :
def __init__( self : Union[str, Any] , _UpperCAmelCase : Tuple = None ) -> Optional[Any]:
"""simple docstring"""
__lowercase = value
__lowercase = None ... | 325 |
from __future__ import annotations
def UpperCAmelCase__ ( _A : float , _A : float , _A : float , ):
'''simple docstring'''
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError('''You cannot supply more or less than 2 values'... | 188 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase__ = {}
try:
if not is_sentencepiece_available():
rai... | 370 | """simple docstring"""
def __UpperCAmelCase ( lowercase = 10_00 ):
"""simple docstring"""
_UpperCAmelCase = 2**power
_UpperCAmelCase = 0
while n:
_UpperCAmelCase , _UpperCAmelCase = r + n % 10, n // 10
return r
if __name__ == "__main__":
print(solution(int(str(input... | 30 | 0 |
from __future__ import annotations
import copy
import inspect
import json
import math
import os
import tempfile
import unittest
from importlib import import_module
import numpy as np
from transformers import ViTMAEConfig
from transformers.file_utils import cached_property, is_tf_available, is_vision_available
f... | 169 |
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
lowerCAmelCase = logging.get_logger(__name__)
def _a ( SCREAMING_SNAKE_CASE... | 110 | 0 |
"""simple docstring"""
def _lowerCamelCase ( _UpperCamelCase , _UpperCamelCase ):
'''simple docstring'''
__lowerCAmelCase = 0
__lowerCAmelCase = len(_UpperCamelCase ) - 1
while left <= right:
# avoid divided by 0 during interpolation
if sorted_coll... | 259 |
"""simple docstring"""
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transformers.models... | 259 | 1 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify... | 316 |
"""simple docstring"""
def A ( snake_case :int ) -> int:
__UpperCamelCase = [1]
__UpperCamelCase , __UpperCamelCase , __UpperCamelCase = 0, 0, 0
__UpperCamelCase = ugly_nums[ia] * 2
__UpperCamelCase = ugly_nums[ia] * 3
__UpperCamelCase ... | 316 | 1 |
'''simple docstring'''
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict impor... | 362 |
'''simple docstring'''
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,
res... | 246 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase ) -> list:
'''simple docstring'''
if len(__UpperCAmelCase ) != 2 or len(a[0] ) != 2 or len(__UpperCAmelCase ) != 2 or len(b[0] ) != 2:
raise Excepti... | 56 |
def _UpperCAmelCase ( snake_case ):
"""simple docstring"""
_lowerCAmelCase = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def _UpperCAmelCase ( snake_case ):
"""simple docstring"""
_lowerCAmelCase = 0
... | 82 | 0 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
)
from diffusers.utils import load_numpy, skip_mps, ... | 45 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_UpperCAmelCase : List[Any] = logging.get_logger(__name__)
_UpperCAmelCase : U... | 45 | 1 |
"""simple docstring"""
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import Token... | 177 | """simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from torch import nn
from torch.nn import CrossEntropyLoss
from ... import AutoBackbone
from ...modeling_outputs import SemanticSegmenterOutput
from ...modeling_utils import PreTrainedModel
from ...utils import add_start_docstri... | 177 | 1 |
def A(__a: int , __a: int ):
return int((input_a, input_a).count(0 ) == 0 )
def A():
assert and_gate(0 , 0 ) == 0
assert and_gate(0 , 1 ) == 0
assert and_gate(1 , 0 ) == 0
assert and_gate(1 , 1 ) == 1
if __name__ == "__main__":
test_and_gate(... | 365 |
import math
def A(__a: int ):
return math.sqrt(__a ) * math.sqrt(__a ) == num
def A(__a: int ):
lowerCAmelCase_ = 0
lowerCAmelCase_ = n
while left <= right:
lowerCAmelCase_ = (left + right) // 2
if mid**2 == n:
return True
el... | 22 | 0 |
import math
def __UpperCamelCase ( _A : int , _A : List[str] ) ->Tuple:
"""simple docstring"""
if 0 not in (x, y):
# We use the relation x^y = y*log10(x), where 10 is the base.
return y * math.logaa(_A )
else:
if x == ... | 154 |
import os
import unicodedata
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 SPIECE_UNDERLINE, logging
__A : Any = logging.get_logger(__name__)
__A : ... | 154 | 1 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from diffusers import (
AudioDiffusionPipeline,
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
DiffusionPipeline,
Mel,
UNetaDConditionModel,
UNetaDModel,
)
from diffusers.u... | 164 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
from typing import Any
class _lowerCAmelCase :
"""simple docstring"""
def __init__( self , _lowerCamelCase ) -> Optional[Any]:
A_ : Any = data
... | 164 | 1 |
"""simple docstring"""
import os
from typing import Dict, List, Tuple, TypeVar, Union
UpperCAmelCase : Union[str, Any] = TypeVar("T")
UpperCAmelCase : Dict = Union[List[T], Tuple[T, ...]]
UpperCAmelCase : int = Union[T, List[T], Dict[str, T]]
UpperCAmelCase : ... | 136 |
"""simple docstring"""
import os
from typing import Dict, List, Tuple, TypeVar, Union
UpperCAmelCase : Union[str, Any] = TypeVar("T")
UpperCAmelCase : Dict = Union[List[T], Tuple[T, ...]]
UpperCAmelCase : int = Union[T, List[T], Dict[str, T]]
UpperCAmelCase : ... | 136 | 1 |
def lowerCamelCase__ ( a = 1_00_00_00 ) -> int:
_A: Optional[Any] = [i - 1 for i in range(limit + 1 )]
for i in range(2 , limit + 1 ):
if phi[i] == i - 1:
for j in range(2 * i , limit + 1 , a ):
phi[j] -= phi[j] // i
return sum(phi[2 : li... | 301 |
import os
from pathlib import Path
def lowerCamelCase__ ( ) -> Optional[Any]:
from torch.utils.cpp_extension import load
_A: str = Path(a ).resolve().parent.parent.parent / '''kernels''' / '''deformable_detr'''
_A: Tuple = [
root / filename
for filename... | 301 | 1 |
'''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 A__ ( __SCREAMING_SNAKE_CASE ... | 162 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
WavaVecaProcessor,
logging,
)
logging.s... | 10 | 0 |
"""simple docstring"""
import re
def SCREAMING_SNAKE_CASE__ ( snake_case : str )-> bool:
'''simple docstring'''
UpperCAmelCase__ : Dict = re.compile(r"^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$" )
if match := re.search(snake_case , snake_case ... | 298 |
"""simple docstring"""
import numpy as np
import datasets
_lowerCAmelCase : Optional[int] = """
Compute the Mahalanobis Distance
Mahalonobis distance is the distance between a point and a distribution.
And not between two distinct points. It is effectively a multivariate equivalent of the... | 298 | 1 |
import warnings
from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor
snake_case : Union[str, Any] = logging.get_logger(__name__)
class _snake_case ( snake_case ):
def __init__( self , *_a , **_a ):
warni... | 281 |
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 (
BitConfig,
ViTHybridCo... | 281 | 1 |
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.... | 351 |
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
__snake_case : Any = """https://www.indeed.co.in/jobs?q=mobile+app+development&l="""
def _UpperCamelCase ( UpperCamelCase_ : str = "mumbai" ... | 122 | 0 |
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