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 |
|---|---|---|---|---|
import inspect
import unittest
class __lowerCAmelCase ( unittest.TestCase ):
def lowerCamelCase__ ( self :Tuple ):
'''simple docstring'''
try:
import diffusers # noqa: F401
except ImportError:
as... | 228 |
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_... | 228 | 1 |
from __future__ import annotations
from math import pow, sqrt
def lowerCAmelCase_ ( _snake_case : float , _snake_case : float , _snake_case : float ) -> dict[str, float]:
'''simple docstring'''
if (resistance, reactance, impedance).c... | 356 |
import argparse
import json
import re
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileNetVaConfig,
MobileNetVaForImageClassification,
MobileNetVaImageProcessor,
load_tf_weights_in_mobilenet_va,
)
... | 41 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"""weiweishi/roc-bert-base-zh""": """https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json""",
}
class a_ ... | 58 |
'''simple docstring'''
import os
lowerCAmelCase__ = {'''I''': 1, '''V''': 5, '''X''': 10, '''L''': 50, '''C''': 100, '''D''': 500, '''M''': 1000}
def _A ( A__ ):
"""simple docstring"""
__lowercase = 0
__lowercase = 0
while index < len(A__ ) - 1:
__... | 104 | 0 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
def SCREAMING_SNAKE_CASE_ ( snake_case : int , snake_case : int )-> bool:
return (
num != den and num % 10 == den // 10 and (num // 10) / (den % 10) == num / den
)
... | 80 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
A_ : Union[str, Any] =logging.get_logger(__name__)
class __a ( lowerCAmelCase__ ):
def __init__( self , *a__ , **a__ ):
... | 80 | 1 |
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
UpperCAmelCase_ : int = '''\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},
author={Wa... | 38 |
def lowerCAmelCase_ ( __UpperCAmelCase: float , __UpperCAmelCase: int ) -> float:
if digit_amount > 0:
return round(number - int(__UpperCAmelCase ) , __UpperCAmelCase )
return number - int(__UpperCAmelCase )
if __name__ == "__main__":
print... | 201 | 0 |
import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
a__ : List[Any] = '''▁'... | 352 |
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ConvNextConfig, UperNetConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import is_torch_available, is_vision_available
f... | 19 | 0 |
from statistics import mean, stdev
def lowercase ( SCREAMING_SNAKE_CASE__ : list , SCREAMING_SNAKE_CASE__ : int = 3 ) -> list:
_snake_case : Any = min(SCREAMING_SNAKE_CASE__ )
_snake_case : List[Any] = max(SCREAMING_SNAKE_CASE__ )
# normalize data... | 317 |
import torch
from torch import nn
class snake_case ( nn.Module ):
'''simple docstring'''
def __init__( self : int , lowerCAmelCase : Tuple , lowerCAmelCase : int , lowerCAmelCase : Any , lowerCAmelCase : T... | 317 | 1 |
'''simple docstring'''
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def a__ ( a__ ... | 331 |
'''simple docstring'''
from ....configuration_utils import PretrainedConfig
from ....utils import logging
UpperCAmelCase : List[Any] = logging.get_logger(__name__)
# TODO: upload to AWS
UpperCAmelCase : Optional[int] = {
'yjernite/retribert-base-uncased': (
'https... | 331 | 1 |
'''simple docstring'''
import warnings
from .state import AcceleratorState, GradientState
warnings.filterwarnings('ignore', category=UserWarning, module='torch.optim.lr_scheduler')
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : Any , _UpperCAmelCase ... | 346 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
import torch.nn.functional as F
from transformers import (
ClapTextConfig,
ClapTextModelWithProjection,
RobertaTokenizer,
SpeechTaHifiGan,
SpeechTaHifiGanConfig,
)
from diffusers import (
AudioLDMPipeline,
... | 164 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case = {"""configuration_xlnet""": ["""XLNET_PRET... | 112 |
"""simple docstring"""
from __future__ import annotations
import numpy as np
def __lowerCAmelCase ( lowercase : list[float] ) -> Any:
"""simple docstring"""
return np.maximum(0 , lowercase )
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5])... | 112 | 1 |
"""simple docstring"""
import re
from filelock import FileLock
try:
import nltk
UpperCAmelCase__ : Optional[Any] = True
except (ImportError, ModuleNotFoundError):
UpperCAmelCase__ : Union[str, Any] = False
if NLTK_AVAILABLE:
with FileL... | 25 |
"""simple docstring"""
import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch
from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search
from transformers.testing_utils import CaptureStdout, TestCasePlus, ... | 25 | 1 |
def __lowercase ( _UpperCamelCase, _UpperCamelCase ) ->list[int]:
"""simple docstring"""
lowercase : Dict = int(_UpperCamelCase )
# Initialize Result
lowercase : Union[str, Any] = []
# Traverse through all denomi... | 173 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
'''google/pegasus-large''': '''https://huggingface.co/google/pegasus-large/resolve/main/config.json''',
# See all PEGASUS models at https://huggingface.co/models?filter=p... | 173 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
SCREAMING_SNAKE_CASE_: Optional[Any] =logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_: List[Any]... | 1 | '''simple docstring'''
import os
from math import logaa
def lowerCAmelCase_ ( snake_case_ : str = "base_exp.txt" ) -> int:
'''simple docstring'''
UpperCAmelCase_ = 0
UpperCAmelCase_ = 0
for i, line in enumerate(open(os.path.join(os.path... | 1 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
def __A ( lowerCAmelCase_ ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all ... | 170 |
'''simple docstring'''
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_... | 170 | 1 |
def SCREAMING_SNAKE_CASE_ ( __magic_name__ : int = 50 ) -> int:
"""simple docstring"""
UpperCamelCase :Any = [1] * (length + 1)
for row_length in range(3 , length + 1 ):
for block_length in range(3 , row_length + 1 ):
for block_start in range(... | 38 | '''simple docstring'''
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class a__( enum.En... | 272 | 0 |
'''simple docstring'''
import math
def snake_case_ ( lowerCAmelCase_ )-> bool:
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1,... | 349 |
'''simple docstring'''
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
A_ : List[Any] = 637_8137.0
A_ : Dict = 635_6752.31_4245
A_ : int = 6_3_7_8_1_3_7
def snake_case_ ( lowerCAmelCase_ ,... | 349 | 1 |
"""simple docstring"""
def _A ( ):
"""simple docstring"""
for n in range(1 , 1_00_00_00 ):
yield n * (n + 1) // 2
def _A ( lowercase ):
"""simple docstring"""
a =1
a =2
while i * i <= n:
... | 81 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"""alibaba-damo/mgp-str-base""": """https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json""",
}... | 166 | 0 |
'''simple docstring'''
import os
def _lowerCamelCase ( lowerCamelCase_ : int ):
"""simple docstring"""
UpperCAmelCase_ : List[str] = len(grid[0] )
UpperCAmelCase_ : List[str] = len(__lowerCamelCase )
UpperCAme... | 360 | '''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common impor... | 274 | 0 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline... | 271 |
'''simple docstring'''
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def UpperCAmelCase_ (__a : List[Any] ):
"""simple docstring"""
if (
(cp >= 0x4E_00 and cp <= 0x9F_FF)
or (cp >= 0x34_00 and cp <= ... | 271 | 1 |
'''simple docstring'''
from typing import Union
import fire
import torch
from tqdm import tqdm
def _SCREAMING_SNAKE_CASE ( UpperCamelCase , UpperCamelCase = "cpu" , UpperCamelCase = None ):
"""simple docstring"""
lowerCAmelCase__ : str = torch.load(Uppe... | 357 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class lowerCAmelCase_( metaclass=SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
__lowercase : int = ['''sentencepiece''']
def __init__( self ,*__UpperCAmelCase ,**__UpperCAmelCase ... | 184 | 0 |
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.set_v... | 248 |
import requests
from bsa import BeautifulSoup
def UpperCAmelCase_ ( __snake_case = "https://www.worldometers.info/coronavirus" ) -> dict:
"""simple docstring"""
_lowercase =BeautifulSoup(requests.get(__snake_case ).text , '''html.parser''' )
_lowerc... | 5 | 0 |
"""simple docstring"""
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase_ = logging.get_logger(__name__)
lowerCamelCase_ = ... | 370 |
"""simple docstring"""
def snake_case ( A__ = 10_00 ):
UpperCAmelCase_ : Optional[Any] = 2**power
UpperCAmelCase_ : Optional[int] = str(A__ )
UpperCAmelCase_ : Tuple = list(A__ )
UpperCAmelCase_ : Any = 0
... | 253 | 0 |
'''simple docstring'''
import cmath
import math
def UpperCamelCase_ ( A__ : float , A__ : float , A__ : float , A__ : float ):
'''simple docstring'''
lowerCAmelCase_ : List[Any] = math.radians(A... | 120 |
'''simple docstring'''
from math import ceil
def UpperCamelCase_ ( A__ : int = 10_01 ):
'''simple docstring'''
lowerCAmelCase_ : List[Any] = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
lowerCAmelCase_ : ... | 120 | 1 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_comm... | 37 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps
... | 37 | 1 |
from __future__ import annotations
from collections.abc import MutableSequence
class __lowerCAmelCase :
def __init__( self , _snake_case , _snake_case ):
"""simple docstring"""
if len(_snake_case ) != degree + 1:
raise ValueError(
... | 82 |
'''simple docstring'''
def a__ ( 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''' ... | 181 | 0 |
"""simple docstring"""
from .imports import is_tqdm_available
if is_tqdm_available():
from tqdm.auto import tqdm as _tqdm
from ..state import PartialState
def lowercase ( _SCREAMING_SNAKE_CASE : bool = True , *_SCREAMING_SNAKE_CASE : List[Any] , ... | 355 |
"""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 | 0 |
'''simple docstring'''
def UpperCamelCase_ ( A__ : int = 10_00 ):
'''simple docstring'''
return sum(2 * a * ((a - 1) // 2) for a in range(3 , n + 1 ) )
if __name__ == "__main__":
print(solution())
| 120 |
"""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 _UpperCAmelCase( lowerCamelCase ):
... | 194 | 0 |
'''simple docstring'''
import os
def UpperCamelCase_ ( ):
'''simple docstring'''
with open(os.path.dirname(_UpperCAmelCase ) + """/p022_names.txt""" ) as file:
lowerCAmelCase_ : Optional[Any] = str(file.readlines()[0] )
lowerCAmel... | 350 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class __snake_case ( unittest.TestCase):
"""simple docstring"""
def __lowercase ( self : Tuple ) -> Dict:
... | 89 | 0 |
from typing import TYPE_CHECKING
from ..utils import _LazyModule
lowerCAmelCase__ : Dict ={
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq2SeqConfigWithPast''',
'''PatchingSpec''',
],
... | 257 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
"""microsoft/git-base""": """https://huggingface.co/microsoft/gi... | 323 | 0 |
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
from ...tes... | 357 |
def __lowerCamelCase ( UpperCAmelCase_ : int = 100 ):
"""simple docstring"""
a :List[Any] = 0
a :List[Any] = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_int... | 281 | 0 |
def UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
if edge <= 0 or not isinstance(lowerCAmelCase__ , lowerCAmelCase__ ):
raise ValueError('''Length must be a positive.''' )
return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)
def UpperCame... | 101 |
'''simple docstring'''
import colorsys
from PIL import Image # type: ignore
def _A ( A__ , A__ , A__ ):
"""simple docstring"""
__lowercase = x
__lowercase = y
for step in range(A__ ): # noqa: B007
__lowercase = a * a - b * b + x
__lo... | 104 | 0 |
from typing import Dict
import numpy as np
import torch
from . import residue_constants as rc
from .tensor_utils import tensor_tree_map, tree_map
def a_ ( lowerCAmelCase_ : Dict[str, torch.Tensor] ):
__lowerCAmelCase = []
__lowerCAmelCase = []
__lowerCAm... | 207 |
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
_snake_case : Union[str, Any] = False
try:
_snake_case ... | 207 | 1 |
'''simple docstring'''
import os
import sys
import unittest
A =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_... | 34 |
'''simple docstring'''
from collections.abc import Sequence
def lowercase_ ( lowerCAmelCase__ : Sequence[float] , lowerCAmelCase__ : float ):
"""simple docstring"""
return sum(c * (x**i) for i, c in enumerate(lowerCAmelCase__ ) )
def ... | 254 | 0 |
"""simple docstring"""
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
UpperCamelCase : Union[str, Any] = False
class __lowerCAmelCase ( unittest.TestCase ... | 263 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase : str = logging.get_logger(__name__)
UpperCamelCase : Dict = {
"microsoft/wavlm-base": "https://huggingface.co/microsoft/wavlm-b... | 263 | 1 |
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_configuration_comm... | 12 |
def _SCREAMING_SNAKE_CASE ( _lowerCamelCase : int , _lowerCamelCase : int) -> float:
'''simple docstring'''
return base * power(_lowerCamelCase , (exponent - 1)) if exponent else 1
if __name__ == "__main__":
print('Raise base to the power of e... | 232 | 0 |
from __future__ import annotations
from collections.abc import MutableSequence
class __lowerCamelCase :
"""simple docstring"""
def __init__( self : Dict , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : MutableSequence[fl... | 367 |
import argparse
from collections import defaultdict
def _A ( lowerCAmelCase_ : Dict , lowerCAmelCase_ : str , lowerCAmelCase_ : Dict , lowerCAmelCase_ : Dict , lowerCAmelCase_ : int ):
"""simple docstring"""
l... | 221 | 0 |
import argparse
import os
import re
lowerCAmelCase__ = """src/diffusers"""
# Pattern that looks at the indentation in a line.
lowerCAmelCase__ = re.compile(R"""^(\s*)\S""")
# Pattern that matches `"key":" and puts `key` in group 0.
lowerCAmelCase__ = re.compile(R"""^\s*\"([^\... | 68 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from... | 55 | 0 |
"""simple docstring"""
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
fr... | 365 |
from maths.prime_factors import prime_factors
def A (__A : int ) -> int:
"""simple docstring"""
if not isinstance(__A , __A ):
UpperCAmelCase_ = F"""Input value of [number={number}] must be an integer"""
... | 7 | 0 |
from __future__ import annotations
def UpperCamelCase ( __lowercase : list[int] ,__lowercase : int ):
'''simple docstring'''
A_ : list[list[int]] = []
A_ : list[int] = []
A_ : int = 0
A_ : Any = sum(__lower... | 140 | 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
_U... | 140 | 1 |
from maths.prime_factors import prime_factors
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> int:
if not isinstance(a_ , a_ ):
SCREAMING_SNAKE_CASE_ = f"Input value of [number={number}] must be an integer"
raise TypeError(a... | 364 |
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
lowerCamelCase__ : Dict = TypeVar('T')
def UpperCAmelCase_ ( __UpperCAmelCase : int ) -> int:
return (position - 1) // 2
def UpperCAmelCase_ ( __UpperC... | 210 | 0 |
"""simple docstring"""
def _lowerCAmelCase ( UpperCamelCase_ ):
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 100 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE, XLNetTokenizer, XLNetTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__magic_name__ = get_t... | 100 | 1 |
'''simple docstring'''
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class __magic_name__ ( _UpperCamelCase ):
@staticmethod
@abstractmethod
def __lowercase ( _UpperCAmelCase : ArgumentParser ):
raise NotImplemente... | 107 |
'''simple docstring'''
import doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch
import numpy as np
import pytest
from absl.testing import parameterized
import datasets
from datasets import load... | 107 | 1 |
'''simple docstring'''
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def U... | 151 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
if partitions <= 0:
raise ValueError('partitions must be a positive number!' )
if partitions > number_of_bytes:
raise ValueError('partitions can not > number_of_b... | 151 | 1 |
# Copyright (c) 2021-, NVIDIA CORPORATION. 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... | 371 |
def SCREAMING_SNAKE_CASE ( lowercase_ ) -> str:
"""simple docstring"""
return " ".join(
''''''.join(word[::-1] ) if len(lowercase_ ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(reve... | 231 | 0 |
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
class A__ ( TensorFormatter[Mapping, '... | 99 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def __UpperCAmelCas... | 249 | 0 |
"""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
__UpperCamelCase ... | 309 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when... | 309 | 1 |
def lowerCamelCase__ ( A__ : str , A__ : str ):
'''simple docstring'''
assert x is not None
assert y is not None
__lowerCamelCase = len(A__ )
__lowerCamelCase = len(A__ )
# declaring the array for storing the d... | 12 |
from __future__ import annotations
def lowerCamelCase__ ( A__ : list[int] , A__ : list[int] , A__ : list[int] , A__ : list[list[str]] , A__ : int , ):
'''simple docstring'''
__lowerCamelCase = len(A__ ... | 12 | 1 |
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__... | 94 |
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
__snake_case : Dict =HfArgumentParser(InitializationArguments)
__snake_case : Tuple =parser.parse_args()
# Load codeparrot tokenizer trained for Pyth... | 94 | 1 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from torchvision.transforms.functional import Interpo... | 6 |
from itertools import permutations
def snake_case_ ( lowerCAmelCase_ : tuple ):
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
__lowercase : ... | 233 | 0 |
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 _snake_case ( _snake_case ):
SCREAMING_SNAKE_C... | 366 |
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 import Image
from ..image_utils impo... | 281 | 0 |
'''simple docstring'''
_lowerCAmelCase = '''0.18.2'''
from .configuration_utils import ConfigMixin
from .utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_inflect_available,
is_invisible_watermark_available,
is_k_diffusion_available,
is_k_diffusion_version... | 37 |
"""simple docstring"""
def _snake_case ( UpperCamelCase : list ):
if not isinstance(UpperCamelCase , UpperCamelCase ):
raise ValueError("""Input series is not valid, valid series - [2, 4, 6]""" )
if len(UpperCamelCase ) == 0:
raise ValueError("""Input list must be ... | 109 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
class __UpperCAmelCase ( A__ ):
'''simple docstring'''
__lowerCAmelCase = '''bert-generation'''
def __init__(self : Any , _lowerCAmelCase : Tuple=5_0358 , _lowerCAmelCase : Tuple=1024... | 353 |
'''simple docstring'''
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
_lowerCamelCase : Dict = logging.get_logger(__name__)
_lowerCamelCase : Any = {
'google/umt5-small'... | 337 | 0 |
"""simple docstring"""
def _lowercase ( __snake_case ) -> int:
__lowerCAmelCase : List[str] = len(__snake_case )
__lowerCAmelCase : Dict = sum(__snake_case )
__lowerCAmelCase : List[Any] = [[False for x... | 269 |
"""simple docstring"""
from itertools import zip_longest
import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def _lowercase ( __snake_case = "laptop" ) -> DataFrame:
__lowerCAmelCase : str = F"""https://www.amazon.in/laptop/s... | 269 | 1 |
from __future__ import annotations
import numpy as np
def lowerCamelCase__ ( A__ : list[float] ):
'''simple docstring'''
return np.maximum(0 , A__ )
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0, 5]
| 354 |
import requests
from bsa import BeautifulSoup
def lowerCamelCase__ ( A__ : str = "https://www.worldometers.info/coronavirus" ):
'''simple docstring'''
__lowerCamelCase = BeautifulSoup(requests.get(A__ ).text , """html.parser""" )
__lowerCamelCase ... | 29 | 0 |
'''simple docstring'''
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class lowerCAmelCase__ ( lowerCamelCase_ ):
... | 93 | 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 transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import logging
logging.... | 143 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowerCAmelCase = {"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}
try:
if not is_vision_available():... | 98 |
'''simple docstring'''
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class _SCREAMING_SNAKE_CASE :
def __init__( self : Optional[Any] , ... | 98 | 1 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __A ( SCREAMING_SNAKE_CASE_ ):
_UpperCamelCase : Optional[Any] = ["image_processor", "tokenizer"]
_UpperCamelCase : List[Any... | 44 | """simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyImgaImgPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandin... | 44 | 1 |
'''simple docstring'''
import json
import os
import unittest
from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers... | 322 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
lowerCamelCase__ = TypeVar('T')
class lowerCAmelCase__ ( Generic[T] ):
def __init__( self : Union[str, Any]... | 322 | 1 |
"""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/licens... | 260 |
"""simple docstring"""
def lowercase ( _SCREAMING_SNAKE_CASE : list[list[int]] , _SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : set ):
'''simple docstring'''
_UpperCAmelCase , _UpperCAm... | 260 | 1 |
'''simple docstring'''
from typing import Union
import fire
import torch
from tqdm import tqdm
def _lowerCAmelCase ( lowercase , lowercase = "cpu" , lowercase = None ) -> None:
__lowerCAmelCase = torch.load(lowercase , map_location=lowercase )
for k... | 46 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_a : List[Any] = {"""configuration_focalnet""": ["""FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FocalNetConfig"""]}
... | 46 | 1 |
import math
def a_ ( SCREAMING_SNAKE_CASE__ : int = 100 ):
'''simple docstring'''
_lowerCamelCase : Optional[Any] =sum(i * i for i in range(1 , n + 1 ) )
_lowerCamelCase : Tuple =int(math.pow(sum(range(1 , n + 1 ) ) , 2 ... | 199 |
from sklearn.metrics import mean_squared_error
import datasets
lowerCamelCase = '\\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, O. and Blondel, M. and Pr... | 199 | 1 |
"""simple docstring"""
from math import pi, sqrt
def lowercase ( _SCREAMING_SNAKE_CASE : float ):
'''simple docstring'''
if num <= 0:
raise ValueError('''math domain error''' )
if num > 171.5:
raise OverflowError('''math range erro... | 326 |
"""simple docstring"""
class _a :
"""simple docstring"""
def __init__( self : Tuple , __UpperCamelCase : list[int] )->None:
_UpperCAmelCase = len(__UpperCamelCase )
_UpperCAmelCase = [0] * len_array
... | 326 | 1 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ = logging.get_logger(__name__)
UpperCAmelCase__ = {
'microsoft/git-base': 'https://huggingface.co/microsof... | 288 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase__ = logging.get_logger(__name__)
UpperCAmelCase__ ... | 288 | 1 |
"""simple docstring"""
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def _A ( _a : Optional[Any] ):
"""simple docstring"""
A = args.pr... | 77 |
"""simple docstring"""
def _A ( _a : str , _a : str ):
"""simple docstring"""
A = len(_a ) + 1
A = len(_a ) + 1
# dp is a 2d matrix where dp[i][j] denotes whether prefix string of
... | 77 | 1 |
def lowerCamelCase__ ( _a):
assert (
isinstance(lowerCAmelCase_ , lowerCAmelCase_) and number_of_steps > 0
), f"number_of_steps needs to be positive integer, your input {number_of_steps}"
if number_of_steps == 1:
return 1
SCREAMING_SNAKE_CASE : str = 1, 1
for _ in rang... | 76 |
from typing import Union
import fire
import torch
from tqdm import tqdm
def lowerCAmelCase ( lowerCAmelCase_ , lowerCAmelCase_ = "cpu" , lowerCAmelCase_ = None )-> None:
lowerCAmelCase_ : str = torch.load(lowerCAmelCase_ , map_location=low... | 262 | 0 |
'''simple docstring'''
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
a_ = logging.getLogger(__name__)
def _a( ):
SCREAMING_SNAKE_CASE__ : str =argparse.ArgumentParser(
... | 371 |
'''simple docstring'''
import math
def _a( UpperCamelCase__ : int ):
'''simple docstring'''
return math.sqrt(UpperCamelCase__ ) * math.sqrt(UpperCamelCase__ ) == num
def _a( UpperCamelCase__ : int ):
... | 222 | 0 |
from __future__ import annotations
import collections
import pprint
from pathlib import Path
def __magic_name__ ( A : str ):
'''simple docstring'''
return "".join(sorted(A ) )
def __magic_name__ ( A : str ):
'''simple docstring'''
return ... | 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 PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_flax_available():
import ... | 350 |
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
_A = logging.get_logger(__name__)
_A = {'''vocab_fil... | 261 | 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,
)
A: Union[str, Any] = {
"configuration_blenderbot": [
"BLENDE... | 109 |
"""simple docstring"""
import inspect
import unittest
from datasets import load_dataset
from packaging import version
from transformers import BeitConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
... | 316 | 0 |
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class snake_case__ :
"""simple docstring"""
lowerCamelCase = 42
lowerCamelCase = 42
c... | 354 |
'''simple docstring'''
import requests
lowercase__ = "" # <-- Put your OpenWeatherMap appid here!
lowercase__ = "https://api.openweathermap.org/data/2.5/"
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = "Chicago" , SCREAMING_SNAKE_CASE__ = APPID ) -> dict:
'''sim... | 83 | 0 |
from typing import Dict
import numpy as np
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline, PipelineException
if is_tf_available():
import tensorflow as tf
from ..tf_utils import stable_softmax
if is_... | 52 |
'''simple docstring'''
import itertools
import random
import unittest
import numpy as np
from transformers import is_speech_available
from transformers.testing_utils import require_torch, require_torchaudio
from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
if is_spe... | 75 | 0 |
def lowerCAmelCase__ ( _a : Union[str, Any] , _a : List[str] , _a : Union[str, Any] ):
if n == 0:
return 1
elif n % 2 == 1:
return (binary_exponentiation(_a , n - 1 , _a ) * a) % mod
else:
snake_case_ : Any = binary_expo... | 36 |
def lowerCAmelCase__ ( _a : dict ):
snake_case_ : List[Any] = set()
# edges = list of graph's edges
snake_case_ : int = get_edges(_a )
# While there are still elements in edges list, take an arbitrary edge
# (from_node, to_node) and add his extre... | 36 | 1 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
__lowerCamelCase : Any = datasets.logging.get_logger(__name__)
__lowerCamelCase : Any = '''\
@InProceedings{moosavi2... | 219 |
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
_a = get_logger(__name__)
class __lowerCamelCase ( enum.Enum):
"""simple docstring"""
UpperCamelCase__ = ... | 39 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowerCAmelCase = {
'''configuration_x_clip''': [
'''XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''XCLIPConfig''',
'''XCLIPTextC... | 107 |
'''simple docstring'''
from __future__ import annotations
import collections
import pprint
from pathlib import Path
def __lowerCamelCase ( lowerCAmelCase_ ) -> str:
return "".join(sorted(lowerCAmelCase_ ) )
def __lowerCamelCase ( lowerCAmelCase_ ) -> list[str]:
... | 107 | 1 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embedd... | 28 |
'''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, TableTransformerConfi... | 28 | 1 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transform... | 4 |
'''simple docstring'''
import inspect
import unittest
from transformers import BitConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_comm... | 4 | 1 |
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def __snake_case ( _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase ):
# Initialise PyTorch model
... | 49 |
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_torch_available():
import torch
from ..mode... | 49 | 1 |
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class A (_UpperCAmelCase ):
'''simple docstring'''
__lowerCamelCase : Tuple = ['image_processor', 'tokenizer']
__lowerCamelCase : Union[str, Any] = ... | 355 |
import unittest
import numpy as np
def __lowerCamelCase ( __a :np.ndarray , __a :np.ndarray , __a :np.ndarray , __a :np.ndarray | None = None , ) -> np.ndarray:
"""simple docstring"""
A__ = np.s... | 276 | 0 |
'''simple docstring'''
from abc import ABC, abstractmethod
from typing import Optional, Union
from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike
class _A ( __SCREAMING_SNAKE_CASE ):
... | 254 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class _lowerCAmelCase ( unittest.TestCase ,lowercase ):
"""simple docstring"""
def _lowercase ( self : List[Any] ):
__lowercase = ... | 17 | 0 |
'''simple docstring'''
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class UpperCAmelCase_ ( unittest.TestCase ):
'''simple docstring'''
def _lowercase ( self ):
... | 364 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class UpperCAmelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docs... | 229 | 0 |
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
a : Optional[int] = logging.get_logger(__name__)
class a ( SCREAMING_SNAKE_CASE__ ):
"""simple docstring"""
def __init__( self : Dict ... | 114 |
"""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_dataset
from... | 179 | 0 |
'''simple docstring'''
from math import factorial
_A : Optional[Any] ={str(d): factorial(d) for d in range(10)}
def SCREAMING_SNAKE_CASE_ (UpperCamelCase ) -> Any:
return sum(DIGIT_FACTORIAL[d] for d in str(A_ ) )
def SCREAM... | 358 |
'''simple docstring'''
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_uti... | 129 | 0 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class _a :
'''simple docstring'''
def __init__( self, A = 6 ):
'''simple docstring'''
SCREAMING_S... | 251 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
... | 251 | 1 |
'''simple docstring'''
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class UpperCAmelCase ( UpperCamelCase__ ):
@staticmethod
@abstractmethod
def UpperCAmelCase_ ( lowercase_ :ArgumentParser )-> Dict:
raise NotImplementedError()
... | 365 |
'''simple docstring'''
from .imports import is_tqdm_available
if is_tqdm_available():
from tqdm.auto import tqdm as _tqdm
from ..state import PartialState
def UpperCamelCase ( _lowerCamelCase : bool = True , *_lowerCamelCase : Optional[int] , **_lowerCamelCase : Optional[Any] )... | 123 | 0 |
from math import pi, sqrt
def A__ ( __lowerCamelCase ):
if num <= 0:
raise ValueError('''math domain error''' )
if num > 1_71.5:
raise OverflowError('''math range error''' )
elif num - int(__lowerCamelCase ) not in (0, 0.5):
raise NotImplementedError('''num must be an int... | 299 |
import math
def A__ ( __lowerCamelCase ):
SCREAMING_SNAKE_CASE_ = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(__lowerCamelCase )
def A__ ( __lowerCamelCase = 1 / 1_23_45 ):
SCREAMING_SNAKE_CASE_ = 0
SCREAMING_SNAKE_CASE_ ... | 299 | 1 |
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_ ( __lowercase ):
UpperCame... | 278 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from transformers import TvltFeatureExtractor, is_datasets_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.utils.import_utils import is... | 278 | 1 |
'''simple docstring'''
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_... | 346 |
'''simple docstring'''
from math import factorial
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : int = 20 ):
'''simple docstring'''
UpperCAmelCase__ = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
UpperCAmelCase__ = n // 2... | 346 | 1 |
'''simple docstring'''
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class lowerCamelCase_ :
lowerCAmelCase__ = None
def lowercase_ ( self : Tuple ):
'''simp... | 360 |
'''simple docstring'''
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import Mode... | 299 | 0 |
'''simple docstring'''
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class a__ ( UpperCAmelCase__ )... | 67 |
"""simple docstring"""
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
__A = TypeVar("""KEY""")
__A = TypeVar("""VAL""")
@dataclass(frozen=a , slots=a )
class _lowerCAmelCase ( Generic[... | 293 | 0 |
'''simple docstring'''
_lowercase : Union[str, Any] = "0.21.0"
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_di... | 264 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
_lowercase : Any = logging.get_logger(__name__)
class lowerCAmelCase__ ( lowerCamelCase_ ):
def __init__( s... | 264 | 1 |
"""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__ = {
'bert-base-un... | 108 |
'''simple docstring'''
import contextlib
from multiprocessing import Pool, RLock
from tqdm.auto import tqdm
from ..utils import experimental, logging
lowercase__ : Any = logging.get_logger(__name__)
class __lowerCAmelCase :
"""simple docstring"""
_snake_case : ... | 324 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE__( _UpperCamelCase : str ) -> bool:
'''simple docstring'''
return credit_card_number.startswith(("34", "35", "37", "4", "5", "6") )
def SCREAMING_SNAKE_CASE__( _UpperCamelCase : str ) ... | 31 |
'''simple docstring'''
import inspect
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel, VQModel
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
cl... | 31 | 1 |
'''simple docstring'''
import unittest
import torch
from diffusers import VQModel
from diffusers.utils import floats_tensor, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
enable_full_determinism()... | 139 |
'''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,
resize,
... | 139 | 1 |
import os
from pickle import UnpicklingError
from typing import Dict, Tuple
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict, unflatten_dict
import transformers
from .utils import logging
lowercase : Any ... | 36 |
import argparse
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
lowercase : Optional[Any] = '''src/diffusers'''
# Matches is_xxx_available()
lowercase : Any ... | 36 | 1 |
__lowerCamelCase : dict[tuple[int, int, int], int] = {}
def _snake_case ( lowerCAmelCase : int , lowerCAmelCase : int , lowerCAmelCase : int ):
"""simple docstring"""
if late == 3 or absent == 2:
return 0
# if we have no days left, and have not failed... | 18 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__lowerCamelCase : Dict = {'''configuration_vit_mae''': ['''VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMAEConfig''']}
try... | 18 | 1 |
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class __magic_name__ :
"""simple docstring"""
__UpperCamelCase = 42
__UpperCamelCase = None
__UpperCamelCase = None
... | 70 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def __snake_case ( _lowerCAmelCase : Optional[int] , _lowerCAmelCase : str , _lowerCAmelCase : Optional[int] ) -> Dict:
A_ : Optional[Any] = 0
if start < end:
A_ : Tuple = ... | 70 | 1 |
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_flax_available():
import os... | 329 |
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class __a ( UpperCAmelCase ):
def __init__( self , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> Any:
"""... | 329 | 1 |
import dataclasses
import re
import string
from typing import Any, Dict, Iterator, List, Mapping, Optional, Sequence, Tuple
import numpy as np
from . import residue_constants
_UpperCAmelCase : Dict = Mapping[str, np.ndarray]
_UpperCAmelCase : Union[str, Any] = Mapping[str, Any] # ... | 200 |
def __lowerCamelCase ( UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
return int((input_a, input_a).count(0 ) != 0 )
def __lowerCamelCase ( ):
'''simple docstring'''
assert nand_gate(0 , 0 ) == ... | 200 | 1 |
import time
import warnings
from abc import ABC
from copy import deepcopy
from typing import Optional
import torch
from ..utils import add_start_docstrings, logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = R"""
Args:
input_ids (`torch.LongTensor` of shape... | 92 |
'''simple docstring'''
from collections import defaultdict
def __magic_name__ ( __UpperCAmelCase ) -> int:
'''simple docstring'''
snake_case_ = 1
snake_case_ = True
for v in tree[start]:
if v not in visited:
ret += dfs(__UpperCAmelCa... | 56 | 0 |
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... | 360 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
"s-JoL/Open-Llama-V1": "https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json",
}
class a_ ( _snake_case ):
... | 344 | 0 |
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