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 datetime import datetime
import requests
def __magic_name__ ( A : str ):
'''simple docstring'''
a = "https://downloadgram.net/wp-json/wppress/video-downloader/video?url="
a = requests.get(base_url + url ).json()[0]["urls"][0]["src"]
return requests.get(A ... | 107 |
'''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 .to... | 168 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase : Dict = {
'configuration_git': ['GIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GitConfig', 'GitVisionConfig'],
'processing_git': ['... | 354 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase_ ( snake_case__ ):
'''simple docstring'''
A : List[str] = 2
A : Dict = []
while i * i <= n:
if n % i:
i += 1
else:... | 311 | 0 |
'''simple docstring'''
from sklearn.metrics import mean_squared_error
import datasets
lowerCamelCase : int = "\\n@article{scikit-learn,\n title={Scikit-learn: Machine Learning in {P}ython},\n author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.\n and Thirion, B. and Grisel,... | 47 |
'''simple docstring'''
def _A ( ):
return [list(range(1000 - i , -1000 - i , -1 ) ) for i in range(1000 )]
__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, ... | 164 | 0 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
'''google/pix2struct-textcaps-base''': (
'''https:/... | 363 |
'''simple docstring'''
_lowerCAmelCase = '''Input must be a string of 8 numbers plus letter'''
_lowerCAmelCase = '''TRWAGMYFPDXBNJZSQVHLCKE'''
def _SCREAMING_SNAKE_CASE ( UpperCamelCase ):
"""simple docstring"""
if not isinstance(UpperCamelCase , U... | 184 | 0 |
from math import sqrt
def __magic_name__ ( A : int ):
'''simple docstring'''
a = 0
for i in range(1, int(sqrt(A ) + 1 ) ):
if n % i == 0 and i != sqrt(A ):
total += i + n // i
elif i == sqrt(A ):
total += i
return total - n
... | 107 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__lowerCAmelCase : List[str] = {
'configuration_resnet': ['RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ResNetConfig', '... | 107 | 1 |
import unittest
from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
class __snake_case ( lowerCamelCase__ , ... | 78 | 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_numpy, slow, torch_device
from diff... | 78 | 1 |
'''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
... | 161 |
'''simple docstring'''
import math
import unittest
def snake_case ( UpperCAmelCase )-> bool:
"""simple docstring"""
assert isinstance(UpperCAmelCase , UpperCAmelCase ) and (
number >= 0
), "'number' must been an int and posi... | 161 | 1 |
"""simple docstring"""
from queue import Queue
from typing import TYPE_CHECKING, Optional
if TYPE_CHECKING:
from ..models.auto import AutoTokenizer
class snake_case :
def UpperCAmelCase__ ( self , __UpperCAmelCase) ->str:
raise NotImplementedError()
def ... | 303 |
"""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 DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from transformers.utils i... | 303 | 1 |
'''simple docstring'''
from __future__ import annotations
def lowercase ( __magic_name__ ):
'''simple docstring'''
if len(__magic_name__ ) == 0:
return []
UpperCAmelCase , UpperCAmelCase : List[str] = min(__magic_name__ ), ma... | 311 |
'''simple docstring'''
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - %(message)s", datefmt="%m/%d/%Y %H:%M:%S", level=loggi... | 311 | 1 |
"""simple docstring"""
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin... | 69 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE_ : Tuple = {
'configuration_nllb_moe': [
'NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP',
'NllbMoeConfig',
... | 69 | 1 |
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 ModelTesterMixin, ids_tensor, ... | 5 |
from __future__ import annotations
A : Union[str, Any] = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
class _lowercase :
"""simple docstring"""
... | 184 | 0 |
"""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,
res... | 326 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def lowercase ( _SCREAMING_SNAKE_CASE : int ):
'''simple docstring'''
_UpperCAmelCase = int(number**0.5 )
return n... | 326 | 1 |
"""simple docstring"""
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
snake_case_ = HUGGINGFACE_HUB_CACHE
snake_case_ = """config.json"""
snake_case_ = """diffusion_pytorch_model.bin"""
snake_case_ = ... | 78 |
"""simple docstring"""
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.p... | 78 | 1 |
'''simple docstring'''
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self : List[Any] , ... | 358 |
'''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 ):
"""simple docstring"""
def snake_cas... | 287 | 0 |
from timeit import timeit
def a__ ( snake_case ):
"""simple docstring"""
if number < 0:
raise ValueError('''the value of input must not be negative''' )
__SCREAMING_SNAKE_CASE : Optional[Any] = 0
while number:
number &= number - 1
result += 1
return result
def a... | 303 |
import sys
from collections import defaultdict
class __UpperCamelCase :
"""simple docstring"""
def __init__( self : Union[str, Any] ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE : Optional[int] = []
def UpperCAmelCas... | 303 | 1 |
'''simple docstring'''
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ = logging.get_logger(__name__)
snake_case__ = {
"""RUCAIBox/mvp""": """https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json""",... | 4 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision.transforms import functional as F
from transformers import DetrImageProcessor, TableTransforme... | 4 | 1 |
"""simple docstring"""
def UpperCAmelCase ( UpperCAmelCase , UpperCAmelCase ) -> Union[str, Any]:
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def UpperCAmelCase ( UpperCAmelCase , UpperCAmelCase=0 ) -> List[str]:
retur... | 69 | """simple docstring"""
from __future__ import annotations
def UpperCAmelCase ( UpperCAmelCase ) -> None:
create_state_space_tree(UpperCAmelCase , [] , 0 , [0 for i in range(len(UpperCAmelCase ) )] )
def UpperCAmelCase ( UpperCAmel... | 69 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional, Tuple, 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,
... | 133 |
"""simple docstring"""
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class SCREAMING_SNAKE_CASE__ ( lowercase ):... | 133 | 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,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension_format,
)
... | 326 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class _lowerCamelCase ( unittest.TestCase ):
"""simple docstring"""
UpperCAmelCase_ : str =JukeboxTokenizer
UpperCAmelCase_ : Tuple ={... | 326 | 1 |
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCAmelCase : Union[str, Any] = logging.get_logger(__name__)
_lowerCAmelCase : Tuple = {'''vocab_file''': '''vocab.json'''}
_lowerCAmelCase ... | 355 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : int = logging.get_logger(__name__)
_lowerCAmelCase : Dict = {
'''microsoft/git-base''': '''https://huggingface.co/microsoft/git-base/resol... | 70 | 0 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=__SCREAMING_SNAKE_CASE )
class A__(__SCREAMING_SNAKE_CASE ):
"""simple docstring"""
_A : str ... | 248 |
_lowerCamelCase ={
"joule": 1.0,
"kilojoule": 1_0_0_0,
"megajoule": 1_0_0_0_0_0_0,
"gigajoule": 1_0_0_0_0_0_0_0_0_0,
"wattsecond": 1.0,
"watthour": 3_6_0_0,
"kilowatthour": 3_6_0_0_0_0_0,
"newtonmeter": 1.0,
"calorie_nutr": 4_1_8_6.8,
"kilocalorie_nutr": 4_1_8_6_8_0_0.0_0... | 287 | 0 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'asapp/sew-d-tiny-100k': 'https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main... | 360 |
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_ = {
'configuration... | 247 | 0 |
'''simple docstring'''
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case =logging.get_logger(__name__)
__snake_case ={
"""RUCAIBox/mvp""": """https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json""",
}
... | 4 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case =logging.get_logger(__name__)
__snake_case ={
"""facebook/s2t-wav2vec2-large-en-de""": (
"""https://huggingface.co/facebook/s2t-wav2vec2-large-en-d... | 4 | 1 |
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print("""Googling.....""")
SCREAMING_SNAKE_CASE__ = """https://www.google.com/search?q=""" + """ """.join(sys.argv[1:])
SCREAMING_SNAKE_CASE__ ... | 297 |
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
from .tokenization_gpta import GPTaTokenizer
if TYPE_CHECKING:... | 297 | 1 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
class __lowerCAmelCase ( unittest.TestCase ):
... | 133 |
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data import Dataset
from tr... | 133 | 1 |
from __future__ import annotations
from math import pi
def __A (__A : float , __A : float , __A : float ) -> dict[str, float]:
"""simple docstring"""
if (inductance, frequency, reactance).count(0 ) != 1:
... | 354 |
from timeit import timeit
def A (__A : int ) -> int:
"""simple docstring"""
if number < 0:
raise ValueError('''the value of input must not be negative''' )
UpperCAmelCase_ = 0
while number:
number ... | 7 | 0 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
def lowercase_ ( _snake_case ):
create_state_space_tree(_snake_case ,[] ,0 )
def lowercase_ ( _snake_case ,_snake_case ,_snake_case ):
if index == len(_snake_case ):
... | 25 |
'''simple docstring'''
import heapq as hq
import math
from collections.abc import Iterator
class UpperCAmelCase :
def __init__( self : str , __snake_case : Any ) -> str:
_lowerCAmelCase = str(id_ )
_lo... | 70 | 0 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCAmelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
_lowercase : str = (DDPMScheduler,)
def _lowercase ... | 229 |
'''simple docstring'''
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
_lowercase = """2.13.1"""
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse("""3.7""... | 229 | 1 |
import random
def lowerCamelCase_ ( _a , _a ):
"""simple docstring"""
lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ : Tuple = [], [], []
for element in data:
if element < pivot:
less.append(lowercase_ ... | 131 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( lowercase_ ) -> list[int]:
if length <= 0 or not isinstance(lowercase_ , lowercase_ ):
raise ValueError("Length must be a positive integer." )
return [n * (2 * n - 1) for n in range(lowercase_ )]
if __name__ == "__ma... | 247 | 0 |
from collections.abc import Generator
def A ( ):
'''simple docstring'''
_lowerCAmelCase , _lowerCAmelCase : int = 0, 1
while True:
_lowerCAmelCase , _lowerCAmelCase : List[str] = b, a + b
... | 300 |
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
_snake_case = logging.get_logger(__name__)
class UpperCAmelCase_ ( a):
def __init__( self, *__a, **__a):
'''simple docstring'''
warnings.... | 300 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class a__:
lowercase__ = 42
lowercase__ = None
lowercase__ = None
lowerCAmelCase: Optional[Any] = namedtuple('CoinsDistri... | 297 |
'''simple docstring'''
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class a__( nn.Module ):
def __init__( self : Any , __snake_case : int = 16 , __snake_case : int = 88 , __snake_... | 297 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase : int = logging.get_logger(__name__)
UpperCamelCase : int = {
"""google/switch-base-8""": """https://huggingface.co/google/switch-base-8/blob/main/config... | 365 | '''simple docstring'''
import copy
import random
from transformers import CLIPTokenizer
class UpperCamelCase ( a_ ):
"""simple docstring"""
def __init__( self : Union[str, Any] , *UpperCAmelCase_ : Dict , **UpperCAmelCase_ : Any):
"""s... | 345 | 0 |
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 notes:
# - tqdm must be checked befor... | 71 |
import os
# Precomputes a list of the 100 first triangular numbers
lowercase_ = [int(0.5 * n * (n + 1)) for n in range(1, 101)]
def _snake_case( ) -> int:
'''simple docstring'''
A__ = os.path.dirname(os.path.realpath(SCREAMING_SNAKE_CASE__... | 7 | 0 |
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
def __UpperCamelCase... | 367 |
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataTrainingArguments
| 90 | 0 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class _lowercase ( UpperCAmelCase__ ):
'''simple docstring'''
pass
class _lowercase :
'''simple docstring'''
def __init__( self : str ... | 229 | '''simple docstring'''
import numpy as np
import qiskit
def UpperCamelCase_ ( snake_case_ : int = 8 , snake_case_ : int | None = None ) -> str:
'''simple docstring'''
__lowerCAmelCase = np.random.default_rng(see... | 229 | 1 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless... | 354 |
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, ids_tens... | 125 | 0 |
_lowerCAmelCase : Optional[Any] = 65_521
def __snake_case ( _lowerCAmelCase : str ) -> int:
A_ : str = 1
A_ : List[str] = 0
for plain_chr in plain_text:
A_ : Optional[Any] = (a + ord(_lowerCAmelCase )) % MOD_ADLER
A_ ... | 300 |
from typing import List, Optional, Union
import numpy as np
from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils import BatchFeature
from ....file_utils import Pa... | 300 | 1 |
'''simple docstring'''
from math import factorial
def __magic_name__ ( __UpperCAmelCase = 100 ) -> int:
'''simple docstring'''
return sum(map(__UpperCAmelCase, str(factorial(__UpperCAmelCase ) ) ) )
if __name__ == "__main__":
print(solution(int(input('Enter t... | 72 |
'''simple docstring'''
import pytest
import datasets
# Import fixture modules as plugins
a : int = ['tests.fixtures.files', 'tests.fixtures.hub', 'tests.fixtures.fsspec']
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase ) -> Tuple:
'''simple docstring'''
for it... | 72 | 1 |
'''simple docstring'''
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 ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_o... | 31 |
'''simple docstring'''
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
UpperCAmelCase_ = logging.getLogger()
@unittest.skip("""Temporarily disab... | 346 | 0 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class __magic_name__ ( __UpperCAmelCase ):
def __init__( self : Optional[int] , snake_case__ ... | 351 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbo... | 172 | 0 |
"""simple docstring"""
from math import factorial
def _SCREAMING_SNAKE_CASE (__lowerCAmelCase = 1_00 ) -> int:
'''simple docstring'''
return sum(int(UpperCamelCase__ ) for x in str(factorial(UpperCamelCase__ ) ) )
if __name__ == "__main__... | 136 |
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self ) -> Any:
'''simple docstring'''
__lowerCamelCase = 0
__lowerCamelCase = 0
__lowerCamelCase = {}
def lowercase_... | 90 | 0 |
import argparse
import os
import re
import tensorflow as tf
import torch
from transformers import BertConfig, BertModel
from transformers.utils import logging
logging.set_verbosity_info()
lowercase_ = logging.get_logger(__name__)
def __lowerCAmelCase ( __SCREAMING_SNAKE_CASE : Opt... | 20 | # Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | 20 | 1 |
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.configuration_utils import FrozenDi... | 38 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
snake_case_ : Union[str, Any] = {
"configuration_mask2former": [
"MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"M... | 125 | 0 |
import os
import sys
import unittest
lowercase : Tuple = 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_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, fin... | 151 |
import qiskit
def _SCREAMING_SNAKE_CASE ( _lowerCamelCase : int = 2) -> qiskit.result.counts.Counts:
'''simple docstring'''
__UpperCamelCase : List[str] = qubits
# Using Aer's simulator
__UpperCamelCase : i... | 151 | 1 |
"""simple docstring"""
from abc import ABC, abstractmethod
from typing import List, Optional
class __snake_case ( _lowercase):
def __init__( self : str ):
"""simple docstring"""
self.test()
def SCREAMING_SNAKE_CASE ( self : ... | 72 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
# TODO: upload to AWS
lowerCAmelCase__ = {
'''yjernite/retribert-base-uncased''': (
'''https://huggingface.co/yjernite/re... | 72 | 1 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET... | 301 |
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
def lowerCamelCase__ ... | 301 | 1 |
from typing import Optional, Union
import torch
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWithNoAttention
from ...modeling_utils i... | 283 | """simple docstring"""
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransformersCL... | 172 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase_ : Dict = logging.get_logger(__name__)
UpperCamelCase_ : Union... | 142 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase_ : List[Any] = {
'''configuration_convbert''': ['''CONVBERT... | 142 | 1 |
import os
import sys
import unittest
lowercase : Any = 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_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find... | 20 |
import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
def _snake_case( SCREAMING_SN... | 20 | 1 |
"""simple docstring"""
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def a__ ( ):
SCREAMING_SNAKE_CASE_ : Dict = ArgumentParser(
descripti... | 362 |
from __future__ import annotations
from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class __lowercase :
"""simple docstring"""
_UpperCAmelCase = 42
... | 162 | 0 |
'''simple docstring'''
import pytest
from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict
@pytest.mark.parametrize(
'split_dict' , [
SplitDict(),
SplitDict({'train': SplitInfo(name='train' , num_bytes=13_37 , num_exam... | 151 |
'''simple docstring'''
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_mul... | 151 | 1 |
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DPMSolverMultistepScheduler,
TextToVideoSDPipeline,
UNetaDConditionModel,
)
from diffusers.utils import is_xformers_availab... | 353 |
"""simple docstring"""
from pathlib import Path
import fire
from tqdm import tqdm
def A_ ( _lowerCAmelCase : str="ro", _lowerCAmelCase : Optional[Any]="en", _lowerCAmelCase : Union[str, Any]="wmt16", _lowerCAmelCase : int=None ):
"""simple... | 153 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE_ = {
'''configuration_speecht5''': [
'''SPEECHT5_PRETRAINED_CONFIG_ARCHI... | 301 |
"""simple docstring"""
def lowercase (_lowerCAmelCase ):
__lowerCAmelCase = [[0 for _ in range(_lowerCAmelCase )] for _ in range(m + 1 )]
for i in range(m + 1 ):
__lowerCAmelCase = 1
for n in range(m + 1 ):
for k in range(1 , _lowe... | 301 | 1 |
from __future__ import annotations
import bisect
def SCREAMING_SNAKE_CASE__ ( _UpperCAmelCase, _UpperCAmelCase, _UpperCAmelCase = 0, _UpperCAmelCase = -1 ) -> int:
'''simple docstring'''
if hi < 0:
lowerCAmelCase : str = len(_UpperCAmelCase )
while lo... | 323 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__A : List[Any] = {
'''configuration_xlm_roberta'''... | 323 | 1 |
_A : Optional[Any] = {'a': ['c', 'b'], 'b': ['d', 'e'], 'c': [], 'd': [], 'e': []}
_A : List[Any] = ['a', 'b', 'c', 'd', 'e']
def _a ( UpperCAmelCase , UpperCAmelCase , UpperCAmelCase ) -> Tuple:
"""simple docstring"""
lowerCamelCase__ : Li... | 142 |
from __future__ import annotations
from typing import Any
class __SCREAMING_SNAKE_CASE :
def __init__( self : Tuple , A : int = 6 ) ->None:
lowerCamelCase__ : Node | None = None
lowerCamelCase__ : Node | None = ... | 142 | 1 |
'''simple docstring'''
import unittest
import numpy as np
import requests
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
... | 365 | '''simple docstring'''
import copy
import random
from transformers import CLIPTokenizer
class UpperCamelCase ( a_ ):
"""simple docstring"""
def __init__( self : Union[str, Any] , *UpperCAmelCase_ : Dict , **UpperCAmelCase_ : Any):
"""s... | 345 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCamelCase_ (unittest.TestC... | 31 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class A__ :
lowercase = 42
lowercase = None
lowercase = None
def... | 162 | 0 |
'''simple docstring'''
from __future__ import annotations
import os
import tempfile
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import is_tensorflow_text_available, is_tf_available
from transformers.testing_utils import require_tensorflow_text, require_tf, sl... | 331 |
'''simple docstring'''
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = len(a__ )
while cur > 1:
# Find the maximum number in arr
__SCREAMING_SNAKE_CASE = arr.index(max(arr[0:cur] ) )
# Reverse from... | 331 | 1 |
import re
from filelock import FileLock
try:
import nltk
__lowerCAmelCase : str = True
except (ImportError, ModuleNotFoundError):
__lowerCAmelCase : Tuple = False
if NLTK_AVAILABLE:
with FileLock('.lock') as lock:
nltk.download('punkt', qu... | 88 |
"""simple docstring"""
def a__ ( _SCREAMING_SNAKE_CASE = 1_000 ):
"""simple docstring"""
return sum(2 * a * ((a - 1) // 2) for a in range(3 , n + 1 ) )
if __name__ == "__main__":
print(solution())
| 153 | 0 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LIC... | 365 |
"""simple docstring"""
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 = logging.get_l... | 341 | 0 |
'''simple docstring'''
from __future__ import annotations
import bisect
def __A ( lowerCamelCase_ , lowerCamelCase_ , lowerCamelCase_ = 0 , lowerCamelCase_ = -1 ):
"""simple docstring"""
if hi < 0:
SCREAMING_SNAKE_CASE : Any ... | 323 |
'''simple docstring'''
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class UpperCamelCase__ ( lowercase_ ):
"""simple docst... | 323 | 1 |
'''simple docstring'''
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
... | 55 |
'''simple docstring'''
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def a_ ( ):
lowerCAmelCase = ArgumentParser(
description=(
'PyTorch T... | 55 | 1 |
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE :Optional[Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE :str = {
'huggingface/time-series-transformer-tourism-monthly': (
... | 15 |
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
UpperCamelCase_ = {
'''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''',
'''susnato/ernie-m-large_pytorch''': '''htt... | 345 | 0 |
"""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 _snake_case ( UpperCAmelCase_ : Optional[Any] , UpperCAmelCase_ : Optional[An... | 363 |
"""simple docstring"""
from typing import Any
class a :
"""simple docstring"""
def __init__( self: List[Any] , UpperCamelCase: Any ):
"""simple docstring"""
A__ = data
A__ = None
... | 69 | 0 |
'''simple docstring'''
from __future__ import annotations
import os
import tempfile
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import is_tensorflow_text_available, is_tf_available
from transformers.testing_utils import require_tensorflow_text, require_tf, slo... | 331 |
'''simple docstring'''
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pytest
from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex
from .utils import requ... | 331 | 1 |
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def UpperCamelCase ( ) -> Dict:
'''simple docstring'''
lowercase_ :str = {
'''repo_name''': ['''test... | 361 |
# We ignore warnings about stepping the scheduler since we step it ourselves during gradient accumulation
import warnings
from .state import AcceleratorState, GradientState
warnings.filterwarnings("ignore", category=UserWarning, module="torch.optim.lr_scheduler")
class UpperCamelCas... | 252 | 0 |
"""simple docstring"""
def _A ( lowercase = "The quick brown fox jumps over the lazy dog" , ):
"""simple docstring"""
a =set()
# Replace all the whitespace in our sentence
a =input_str.replace(''' ''' , '''''' )
for alpha in ... | 81 |
'''simple docstring'''
import uuid
from typing import Any, Dict, List, Optional, Union
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
if is_torch_available():
import torch
__... | 341 | 0 |
'''simple docstring'''
import warnings
from functools import wraps
from typing import Callable
def SCREAMING_SNAKE_CASE_ (UpperCamelCase ):
@wraps(UpperCamelCase )
def _inner_fn(*UpperCamelCase , **UpperCamelCase ):
warnings.... | 351 |
'''simple docstring'''
from collections import deque
class _lowercase :
def __init__( self: int , UpperCamelCase__: str , UpperCamelCase__: int , UpperCamelCase__: int ):
lowerCamelCase__ : int ... | 129 | 0 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
a_ : Optional[Any] = {"""vocab_file""": """vocab.txt""", """tokeni... | 55 |
'''simple docstring'''
from __future__ import annotations
from fractions import Fraction
def __snake_case ( UpperCAmelCase_ : int , UpperCAmelCase_ : int ):
return (
num != den and num % 10 == den // 10 and (num // 10) / (den % 10) == num / den
)
... | 55 | 1 |
def _A ( SCREAMING_SNAKE_CASE : int ):
"""simple docstring"""
a__ : Any =(1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def _A ( SCREAMING_SNAKE_CASE : int = 5_000 ):
"""simple docstring"""
a__ : Optiona... | 148 |
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import A... | 148 | 1 |
"""simple docstring"""
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 notes:
# - tqdm... | 78 | """simple docstring"""
import inspect
import re
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_config_docstrings.py
__UpperCamelCase = '''src/transformers'''
# This ... | 69 | 0 |
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import (
BaseOutput,
OptionalDependencyNotAvailable,
is_flax_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_onn... | 193 |
import os
import unittest
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
BertTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.test... | 193 | 1 |
'''simple docstring'''
import qiskit
def lowerCamelCase (_SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : int ):
__a : Any = qiskit.Aer.get_backend('aer_simulator' )
__a : int = qiskit.QuantumCircuit(4 , 2 )
... | 27 |
def __lowerCamelCase ( lowerCamelCase__ : Any , lowerCamelCase__ : Optional[int] ):
'''simple docstring'''
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def __lowerCamelCase ( lowerCamelCase__ : List[str] , lowerCamelCase__ ... | 252 | 0 |
"""simple docstring"""
import math
import time
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_model as xm
import torch_xla.debug.me... | 226 |
"""simple docstring"""
import sys
import turtle
def lowercase ( A_ , A_ )-> tuple[float, float]:
'''simple docstring'''
return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2
def lowercase ( A_ , A_ , A_ , A_ , ... | 226 | 1 |
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
lowerCAmelCase__ :Union[str, Any] = version.parse(importlib_metadata.version('''nltk'''))
if NLTK_VERSION >= version.Version('''3.6.4'''):
from nltk import word_tokenize... | 329 |
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class lowerCamelCase__ ( lowerCamelCase__):
'''simple docstring'''
snake_case_ ="""Speech2TextFeatureExtractor"""
snake_case_ ="""Speech2TextTokenizer"""
def __init__(self ,__lo... | 129 | 0 |
'''simple docstring'''
from math import sqrt
def UpperCAmelCase ( lowerCamelCase_ :Optional[int] ):
'''simple docstring'''
snake_case_ : Any = 0
for i in range(1 , int(sqrt(lowercase__ ) + 1 ) ):
if n % i == 0 and i != sqrt(lowercase__ ):
total ... | 362 |
'''simple docstring'''
def UpperCAmelCase ( lowerCamelCase_ :list ):
'''simple docstring'''
if len(lowerCamelCase_ ) <= 1:
return lst
snake_case_ : Union[str, Any] = 1
while i < len(lowerCamelCase_ ):
if lst[i - 1] <= lst[i]:
i += 1
else:
... | 8 | 0 |
"""simple docstring"""
def UpperCamelCase__ ( lowercase__ : str ):
snake_case : Dict = 0
for ch in input_str:
snake_case : List[str] = ord(lowercase__ )
snake_case : Tuple = pow(2 , lowercase__ )
# If we already turn... | 148 |
"""simple docstring"""
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__A = {
"facebook/mask2former-swin-small-coco-instance": (
"https://huggingface.... | 148 | 1 |
'''simple docstring'''
import itertools
import random
import unittest
import numpy as np
from transformers import WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, WavaVecaConfig, WavaVecaFeatureExtractor
from transformers.testing_utils import require_torch, slow
from ...test_sequence_feature_extraction_common ... | 360 |
'''simple docstring'''
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def _UpperCamelCase... | 83 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
a__: str = {
'configuration_owlvit': [
... | 193 |
class SCREAMING_SNAKE_CASE__ :
def __init__( self,__lowerCamelCase ):
A__ = set_counts
A__ = max(__lowerCamelCase )
A__ = len(__lowerCamelCase )
A__ = [1] * num_sets
A__ = ... | 193 | 1 |
import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'''facebook/encodec_24khz''': '''https://huggingface.co/fa... | 350 |
import os
def __lowerCamelCase ( __magic_name__ : str = "input.txt" ):
with open(os.path.join(os.path.dirname(__magic_name__ ) , __magic_name__ ) ) as input_file:
a__: str =[
[int(__magic_name__ ) for element in line.split("," )]
... | 42 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__A ={
"configuration_blip": [
"BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
"BlipConfig",
... | 226 |
import argparse
import shlex
import runhouse as rh
if __name__ == "__main__":
# Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
# setup instructions, if using on-demand hardware
# If user passes --user <user> --hos... | 226 | 1 |
'''simple docstring'''
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/resolv... | 356 |
'''simple docstring'''
from __future__ import annotations
from fractions import Fraction
def UpperCamelCase ( a , a ) -> bool:
'''simple docstring'''
return (
num != den and num % 10 == den // 10 and (num // 10) / (den % 10) == num / den
)
def Up... | 98 | 0 |
"""simple docstring"""
import argparse
import os
import torch
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
A : List[str] = {
"sample_size": 3_2,
"in_channels": 3,
"out_channels": 3,
"layers_per_block": 2,
"num_cla... | 57 |
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
import jax.numpy as ... | 8 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_albert import... | 351 |
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def UpperCAmelCase_ ( __UpperCAmelCase : str = "isbn/0140328726" ) -> dict:
SCREAMING_SNAKE_CASE_ = olid.strip().strip('/' ) # Remove leading/trailing whit... | 210 | 0 |
'''simple docstring'''
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnal... | 251 |
'''simple docstring'''
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ : int = logging.get_logger(__name__)
snake_case_ : Optional[Any] = {
'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json',
}
c... | 83 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
a__ : List[Any] = {'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json... | 19 |
import unittest
import numpy as np
import torch
from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
from ..pipeline_params import UNCONDITIONAL_IMAGE_GENERATION_BATCH_PARAMS, UNCONDITIONAL_IMAGE_GENER... | 19 | 1 |
from __future__ import annotations
class _lowerCamelCase:
def __init__( self, lowerCamelCase=None) -> Optional[int]:
"""simple docstring"""
_lowercase : Optional[Any] = data
_lowercase : List[str] = None
... | 21 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@... | 42 | 0 |
'''simple docstring'''
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
lowerCamelCase : List[Any] = "\\n@inproceedings{wang2019glue,\n title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},\n ... | 371 |
'''simple docstring'''
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
lowerCamelCase : List[Any] = "\\n@inproceedings{wang2019glue,\n title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},\n ... | 114 | 0 |
def _a ( SCREAMING_SNAKE_CASE_ : List[str] ):
__lowerCAmelCase , __lowerCAmelCase = [], []
while len(SCREAMING_SNAKE_CASE_ ) > 1:
__lowerCAmelCase , __lowerCAmelCase = min(SCREAMING_SNAKE_CASE_ ), max(SCREAMING_SNAKE_CASE_ ... | 92 | """simple docstring"""
import warnings
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase__ : Optional[int] = logging.get_logger(__name__)
class snake_case ( __UpperCAmelCase ):
... | 98 | 0 |
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
lowerCAmelCase__ : Tuple ="\\n@misc{chen2021evaluating,\n title={Evalu... | 350 |
def a__ ( A__ ):
SCREAMING_SNAKE_CASE_ : Optional[Any] = 0
SCREAMING_SNAKE_CASE_ : Union[str, Any] = len(A__ )
for i in range(n - 1 ):
for j in range(i + 1, A__ ):
if arr[i] > arr[j]:
num_inversions... | 162 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_flax, require_tf, require_torch
from transformers.utils import (
expand_dims,
flatten_dict,
is_flax_available,
is_tf_available,
is_torch_available,
reshape,
... | 40 | import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin
if... | 210 | 0 |
'''simple docstring'''
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pytest
from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex
fr... | 363 |
'''simple docstring'''
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def ... | 249 | 0 |
import os
import re
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__A =logging.get_logger(__name__)
__A ={'''vocab_file''': '''spiece.model'''}
__A ... | 19 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__A ={'''configuration_xglm''': ['''XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP'''... | 19 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class _A :
snake_case__ : int
snake_case__ : Node | ... | 32 | """simple docstring"""
def UpperCAmelCase__ ( lowerCAmelCase__ :int ) -> bool:
'''simple docstring'''
lowercase = n ** (1 / 3)
return (val * val * val) == n
if __name__ == "__main__":
print(perfect_cube(2_7))
print(perfect_cub... | 32 | 1 |
"""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_a... | 33 |
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,
resize,
to_channel_d... | 114 | 0 |
def _SCREAMING_SNAKE_CASE ( lowercase : float , lowercase : float , lowercase : int ):
'''simple docstring'''
if principal <= 0:
raise Exception('Principal borrowed must be > 0' )
if rate_per_annum < 0:
... | 370 |
import argparse
import os
import sys
from unittest.mock import patch
import pytorch_lightning as pl
import timeout_decorator
import torch
from distillation import SummarizationDistiller, distill_main
from finetune import SummarizationModule, main
from transformers import MarianMTModel
from trans... | 208 | 0 |
'''simple docstring'''
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
import torch
cla... | 63 |
'''simple docstring'''
def UpperCAmelCase__ ( UpperCAmelCase__ ) -> list[list[float]]:
A_ = []
for data in source_data:
for i, el in enumerate(UpperCAmelCase__ ):
if len(UpperCAmelCase__ ) < i + 1:
data_lists.appen... | 162 | 0 |
import pprint
import requests
A : int = 'https://zenquotes.io/api'
def UpperCamelCase ( ) -> list:
"""simple docstring"""
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def UpperCamelCase ( ) -> list:
... | 353 |
A : Union[str, Any] = [
(1_0_0_0, 'M'),
(9_0_0, 'CM'),
(5_0_0, 'D'),
(4_0_0, 'CD'),
(1_0_0, 'C'),
(9_0, 'XC'),
(5_0, 'L'),
(4_0, 'XL'),
(1_0, 'X'),
(9, 'IX'),
(5, 'V'),
(4, 'IV'),
(1, 'I'),
]
def UpperCamelCase ( __mag... | 146 | 0 |
import inspect
import unittest
from transformers import ViTMSNConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester... | 95 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except Opt... | 249 | 0 |
"""simple docstring"""
from queue import Queue
from typing import TYPE_CHECKING, Optional
if TYPE_CHECKING:
from ..models.auto import AutoTokenizer
class UpperCamelCase_ :
"""simple docstring"""
def UpperCAmelCase_ ( self : Tuple , UpperCAmelCase__ : Lis... | 357 |
"""simple docstring"""
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMSched... | 195 | 0 |
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