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 |
|---|---|---|---|---|
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase_ ( snake_case__ ):
'''simple docstring'''
for i in range(1 , len(matrix[0] ) ):
matrix[0][i] += matrix[0][i - 1]
# preprocessing the first column
... | 3 |
'''simple docstring'''
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 UpperCAmelCase ( a_ ) -> Dict[str, torch.Tensor]:
"""simple docstring"""
... | 344 | 0 |
"""simple docstring"""
def lowerCamelCase_ (UpperCamelCase__ : list ):
if len(UpperCamelCase__ ) <= 1:
return [tuple(UpperCamelCase__ )]
_UpperCAmelCase : Dict = []
def generate(UpperCamelCase__ : int , UpperCamelCase__ : list ):
... | 369 |
"""simple docstring"""
import datasets
from .evaluate import evaluate
_lowerCAmelCase :int = '\\n@article{hendrycks2021cuad,\n title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},\n author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},\n journal={arXiv p... | 68 | 0 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import PatchingSpec
from ...tokeniz... | 50 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepie... | 50 | 1 |
'''simple docstring'''
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def SCREAMING_SNAKE_CASE__ ( snake_case : int ) -> List[str]:
"""simple docstring"""
# A local function to see if a do... | 366 | '''simple docstring'''
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def SCREAMING_SNAKE_CASE__ ( snake_case : str... | 345 | 0 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, FalconConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...te... | 85 |
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
'''xlnet-base-cased''': '''https://huggingface.co/xlnet-base-cased/resolve/main/config.json''',
'''xlnet-large-cased''': '''https://h... | 195 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
A_ : str = {
"""configuration_roberta_prelayernorm""": [
"""ROBERTA_PRELA... | 349 |
'''simple docstring'''
from argparse import ArgumentParser
from .env import EnvironmentCommand
def snake_case_ ( )-> Union[str, Any]:
'''simple docstring'''
_UpperCAmelCase : Optional[int] = ArgumentParser("""Diffusers CLI tool""" , usage="""diffusers-... | 349 | 1 |
'''simple docstring'''
from sklearn.metrics import recall_score
import datasets
__snake_case = '\nRecall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation:\nRecall = TP / (TP + FN)\nWhere TP is the true positives and... | 97 |
def __lowerCAmelCase ( a__ ) -> str:
__a = []
__a = set({'''(''', '''[''', '''{'''} )
__a = set({''')''', ''']''', '''}'''} )
__a = {'''{''': '''}''', '''[''': ''']''', '''(''': ''')'''}
for i in range(len(a__ ) ):
if s[i]... | 6 | 0 |
'''simple docstring'''
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_to... | 353 |
'''simple docstring'''
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
a_ = 'src/diffusers'
# Matches is_xxx_available()
a_ = re.compile(R'is\_([a-z_]*)_avail... | 222 | 0 |
'''simple docstring'''
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class _snake_case ( l... | 85 |
'''simple docstring'''
from __future__ import annotations
import requests
def UpperCamelCase_( snake_case : str ):
'''simple docstring'''
snake_case_ = f'https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty'
return requests.get(s... | 85 | 1 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
__UpperCAmelCase :Optional[Any] = [
"good first issue",
"good second issue",
"good difficult issue",
"enhancement",
"new pipeline/model",
"new scheduler",
... | 240 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
S... | 240 | 1 |
def lowerCamelCase__ ( snake_case_ : int=2_8123 ) -> int:
__snake_case = [1] * (limit + 1)
for i in range(2 , int(limit**0.5 ) + 1 ):
sum_divs[i * i] += i
for k in range(i + 1 , limit // i + 1 ):
... | 24 |
import inspect
import unittest
from transformers import ConvNextConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTesterM... | 24 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import Rea... | 195 |
"""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 | 1 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common ... | 26 | from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def snake_case ( snake_case__ :Un... | 180 | 0 |
"""simple docstring"""
from __future__ import annotations
import copy
import tempfile
import unittest
from transformers import CONFIG_MAPPING, AutoConfig, BertConfig, GPTaConfig, TaConfig, TapasConfig, is_tf_available
from transformers.testing_utils import (
DUMMY_UNKNOWN_IDENTIFIER,
SMALL_MODEL_IDENTIFI... | 155 |
"""simple docstring"""
def __lowercase ( _a , _a ):
return base * power(_a , (exponent - 1) ) if exponent else 1
if __name__ == "__main__":
print('''Raise base to the power of exponent using recursion...''')
lowercase__ : Optional[Any] = int(input('''Enter... | 155 | 1 |
"""simple docstring"""
from math import factorial
A_ = {str(d): factorial(d) for d in range(10)}
def UpperCAmelCase__ (snake_case__ : int ):
"""simple docstring"""
return sum(DIGIT_FACTORIAL[d] for d in str(snake_case__ ) )
def UpperCAmelCas... | 64 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_S... | 64 | 1 |
import torch
from torch import nn
class A_ ( nn.Module ):
'''simple docstring'''
def __init__( self: Any , a: Any , a: Optional[int] , a: str , a: Dict , a: Optional[int]=1 , a: Union[str, Any]=False ):
super().__init__()
__l... | 194 |
from __future__ import annotations
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ ):
__lowerCamelCase : List[Any] = str(SCREAMING_SNAKE_CASE__ )
return len(SCREAMING_SNAKE_CASE__ ) == 9 and set(SCREAMING_SNAKE_CASE__ ) == set('123456789' )
def UpperCamelCase__ ... | 194 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffusionPi... | 250 |
'''simple docstring'''
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
_snake_case = logging.getLogg... | 250 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiec... | 1 |
"""simple docstring"""
import copy
from collections import OrderedDict
from typing import Dict, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__UpperCA... | 1 | 1 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, PreTrainedTokenizerBase, Ten... | 312 |
def __snake_case ( __UpperCamelCase : int = 1000 ):
"""simple docstring"""
return sum(e for e in range(3 ,__UpperCamelCase ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(F"{solution() = }") | 312 | 1 |
"""simple docstring"""
import argparse
import os
import re
UpperCamelCase__ = 'src/diffusers'
# Pattern that looks at the indentation in a line.
UpperCamelCase__ = re.compile(R'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
UpperCamelCase__ = re... | 350 | # 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... | 143 | 0 |
"""simple docstring"""
from __future__ import annotations
def __A (_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) ->tuple[float, list[float]]:
"""simple docstring"""
lowerCAmelCase__ :List[Any] = list(range(len(_SCREAMING_SNAKE_CASE ... | 293 |
"""simple docstring"""
def __A (_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) ->float:
"""simple docstring"""
if discount_rate < 0:
raise ValueError('Discount rate cannot be negative' )
if not cash_flows:
raise ValueError('Cash flows list cannot be empty' )
lowerCA... | 293 | 1 |
'''simple docstring'''
def __UpperCamelCase ( UpperCAmelCase , UpperCAmelCase ):
lowercase__ : Dict = len(UpperCAmelCase )
print('''The following activities are selected:''' )
# The first activity is always selected
lowercase__ : str = 0
print(UpperCAmelCase ,... | 361 | '''simple docstring'''
class UpperCAmelCase :
'''simple docstring'''
def __init__( self ) -> List[str]:
lowercase__ : Dict = {}
def _lowerCAmelCase( self ) -> None:
print(self.vertex )
for i in self.vertex:
print(__lowe... | 214 | 0 |
'''simple docstring'''
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def ... | 254 |
'''simple docstring'''
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .token... | 254 | 1 |
import argparse
import json
import os
import torch
from transformers import LukeConfig, LukeModel, LukeTokenizer, RobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def __A ( __lowerCamelCase , __lowerCamelCase , __lo... | 347 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BertTokenizer, ... | 347 | 1 |
from __future__ import annotations
import math
def SCREAMING_SNAKE_CASE__ ( __a , __a ):
snake_case_ : List[str] = u
for i in range(1 , __a ):
snake_case_ : Union[str, Any] = temp * (u - i)
return temp
def SCREAMING... | 327 |
from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class snake_case__ :
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : str ... | 107 | 0 |
import argparse
import gc
import json
import os
import shutil
import warnings
import torch
from transformers import LlamaConfig, LlamaForCausalLM, LlamaTokenizer
try:
from transformers import LlamaTokenizerFast
except ImportError as e:
warnings.warn(e)
warnings.warn(
'''The ... | 361 |
'''simple docstring'''
from __future__ import annotations
from math import gcd
def _lowerCAmelCase ( __snake_case : int , __snake_case : int = 2 , __snake_case : int = 1 , __snake_case : int = 3 , ) -> int | None:
# A ... | 190 | 0 |
'''simple docstring'''
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 IMAGE... | 2 | '''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Optional[Any] = logging.get_logger(__name__)
_lowercase : Tuple = {
"BAAI/AltCLIP": "https://huggingface.co/BAAI/A... | 239 | 0 |
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 transformers.testing_utils import TOKEN, USER, get_tests_dir,... | 50 | import numpy
# List of input, output pairs
a_ = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
a_ = (((515, 22, 13), 555), ((61, 35, 49), 150))
a_ = [2, 4, 1, 5]
a_ = len(train_data)
a_ = 0.009
def __lowercase ( lowe... | 50 | 1 |
"""simple docstring"""
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def A_ ( _lowercase, _lowercase ):
'''simple d... | 66 |
'''simple docstring'''
import random
def lowerCAmelCase (__A):
"""simple docstring"""
_a = num - 1
_a = 0
while s % 2 == 0:
_a = s // 2
t += 1
for _ in range(5):
_a = random.randrange(2 , num - 1)
_a = ... | 211 | 0 |
"""simple docstring"""
UpperCAmelCase__ = {
'Pillow': 'Pillow<10.0.0',
'accelerate': 'accelerate>=0.20.3',
'av': 'av==9.2.0',
'beautifulsoup4': 'beautifulsoup4',
'black': 'black~=23.1',
'codecarbon': 'codecarbon==1.2.0',
'cookiecutter': 'cookiecutter==1.7.3',
'dataclasses': '... | 363 |
"""simple docstring"""
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 TFMo... | 40 | 0 |
# A Bipartite Graph is a graph whose vertices can be divided into two independent sets,
# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex
# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
# or u belongs to V and v to U. We can also say that the... | 101 |
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 | 1 |
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import Callable, Dict, List, Tuple
import timm
import torch
import torch.nn as nn
from classy_vision.models.regnet import RegNet, RegNetParams, RegNetYaagf, RegNetYaagf, RegNetYaaagf
... | 351 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ = {
'configuration_x_clip': [
'XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
'XCLIPConfig',
'XCLIPTextConfig',
'XCLIPVisionConfig',
],
... | 119 | 0 |
"""simple docstring"""
from __future__ import annotations
_snake_case : int = {
'A': ['B', 'C', 'E'],
'B': ['A', 'D', 'E'],
'C': ['A', 'F', 'G'],
'D': ['B'],
'E': ['A', 'B', 'D'],
'F': ['C'],
'G': ['C'],
}
class _UpperCAmelCase :
def __init__( ... | 292 |
"""simple docstring"""
import math
import sys
def A__ ( UpperCamelCase ):
A = ""
try:
with open(UpperCamelCase , "rb" ) as binary_file:
A = binary_file.read()
for dat in data:
A = F"{dat:08b}... | 292 | 1 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
lowerCamelCase : Union[str, Any] = ... | 356 |
'''simple docstring'''
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def _lowerCAmelCase ( ) -> int:
"""simple docstring"""
import os as original_os
from os import path as original_path
from os import rename as original_ren... | 114 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, loggi... | 1 | '''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_: Dict =logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_: Tuple ={}
class __A ( UpperCamelCase__ ):
a__ : int = """llama"""
a__ ... | 1 | 1 |
'''simple docstring'''
from __future__ import annotations
def UpperCAmelCase ( a_ , a_ , a_ , a_ , a_ , ) -> None:
"""simple docstring"""
A_ : Tuple = len(a_ )
# If row is equal to the siz... | 164 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
from typing import Any
class _lowerCAmelCase :
"""simple docstring"""
def __init__( self , _lowerCamelCase ) -> Optional[Any]:
A_ : Any = data
... | 164 | 1 |
'''simple docstring'''
import argparse
import json
import os
import re
import shutil
import torch
from transformers import BioGptConfig, BioGptForCausalLM
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES
from transformers.tokenization_utils_base import TOKENIZER_CONFIG_FILE
from transf... | 331 |
"""simple docstring"""
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
_lowerCAmelCase :Optional[Any] = False
class _UpperCA... | 263 | 0 |
"""simple docstring"""
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
_lowerCamelCase : List[Any] = '''2.13.1'''
import platform
import pyarrow
from packaging import version
if version.parse(plat... | 361 | from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class lowercase :
lowercase__ : torch.Tensor # [batch_size x 3]
lowercase__ : torch.Tensor # [batch_size x 3]
lowercase__ : torch.Tensor # [batch_size x 3]
... | 206 | 0 |
'''simple docstring'''
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
lowerCamelCase : int = logging.getLogger(__name__)
def _SCREAMING_SNAKE_CASE () -> List[Any]:
"""simple docstring"""
... | 2 | '''simple docstring'''
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class _lowercase :
'''simple docstring'''
def __init__( self : Optional[int] , SCREAMING_SNAKE_CASE... | 229 | 0 |
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
from ...generation.test_utils import Generatio... | 122 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case : Union[str, Any] = {
"""configuration_convbert""": ["""CONVBERT_PRETRAINED_CONF... | 122 | 1 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers import LukeConfig, LukeModel, LukeTokenizer, RobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def _a ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _S... | 347 |
"""simple docstring"""
import datasets
__SCREAMING_SNAKE_CASE : Tuple = '\\n@InProceedings{conneau2018xnli,\n author = "Conneau, Alexis\n and Rinott, Ruty\n and Lample, Guillaume\n and Williams, Adina\n and Bowman, Samuel R.\n ... | 347 | 1 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import... | 368 |
import warnings
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_... | 44 | 0 |
'''simple docstring'''
import warnings
from functools import wraps
from typing import Callable
def UpperCamelCase_( snake_case : Callable ):
'''simple docstring'''
@wraps(snake_case )
def _inner_fn(*snake_case : Optional[int] , **snak... | 85 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
_lowerCamelCase : str ... | 336 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( __A ) -> list:
if len(__A ) < 2:
return collection
def circle_sort_util(__A , __A , __A ) -> bool:
_snake_case = False
if low == high:
return swapped
_snake_case = low
_... | 160 |
'''simple docstring'''
import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, L... | 160 | 1 |
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import deduplicate_dataset
from transformers import AutoTo... | 154 |
def __UpperCamelCase ( _A : Dict ) ->List[str]:
"""simple docstring"""
lowerCamelCase_ =[0] * len(_A )
lowerCamelCase_ =[]
lowerCamelCase_ =[]
lowerCamelCase_ =0
for values in graph.values():
for i in ... | 154 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from torch.backends.cuda import sdp_kernel
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
from diffusers.utils import randn_tensor, slow, torch_devi... | 363 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e impo... | 38 | 0 |
from PIL import Image
def lowerCamelCase__ ( A__ : Image , A__ : float ):
'''simple docstring'''
def brightness(A__ : int ) -> float:
return 128 + level + (c - 128)
if not -255.0 <= level <= 255.0:
raise ... | 12 |
'''simple docstring'''
def a__ ( lowerCAmelCase__ ) -> int:
UpperCAmelCase__ : Tuple = 0
while num > 0:
digit_sum += num % 10
num //= 10
return digit_sum
def a__ ( lowerCAmelCase__ = 1_00 ) -> int:
Up... | 181 | 0 |
'''simple docstring'''
import os
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
_SCREAMING_SNAKE_CASE = "."
if __name__ == "__main__":
_SCREAMING_SNAKE_CASE = os.path.join... | 370 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
HubertConfig,
HubertForCTC,
HubertModel,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,... | 3 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase_ = {"""configuration_unispeech""": ["""UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP""", """UniSpeec... | 58 |
"""simple docstring"""
# 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
#
... | 106 | 0 |
"""simple docstring"""
lowercase_ = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
lowercase_ = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
lowercase_ = {
0: "Sunday",
1: "Monday",
2: "Tuesday",
3: "Wednesday",
4: "Thursday",
5: "Friday",
6: "Saturday"... | 11 |
"""simple docstring"""
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, Sched... | 11 | 1 |
def _a ( lowerCamelCase, lowerCamelCase ):
def get_matched_characters(lowerCamelCase, lowerCamelCase ) -> str:
lowerCamelCase : Tuple = []
lowerCamelCase : Any = min(len(_stra ), len(_stra ) ) // 2
for i, l in enumerate(_stra ):
lowerC... | 287 |
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIPModel, CL... | 201 | 0 |
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
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_params import (
TE... | 358 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_SCREAMING_SNAKE_CASE = {
'''configuration_... | 217 | 0 |
'''simple docstring'''
import math
import unittest
from transformers import BioGptConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling... | 47 |
'''simple docstring'''
class A__ :
def __init__( self : Union[str, Any] , _a : int ) -> None:
'''simple docstring'''
_SCREAMING_SNAKE_CASE =size
_SCREAMING_SNAKE_CASE =[0] * size
_SCREAMING_SNAKE_CASE =[0] * ... | 47 | 1 |
from __future__ import annotations
import time
UpperCamelCase = list[tuple[int, int]]
UpperCamelCase = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],
[1, 0, 1, ... | 125 |
import logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
from transformers import... | 125 | 1 |
"""simple docstring"""
import os
def SCREAMING_SNAKE_CASE ( ) -> List[str]:
_lowerCAmelCase : Optional[int] = os.path.dirname(os.path.realpath(_lowerCamelCase ) )
_lowerCAmelCase : List[Any] = os.path.join(_lowerCamelCase ,"""triangle.txt""" )... | 44 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a : int= logging.get_logger(__name__)
_a : Optional[Any]= {
"SCUT-DLVCLab/lilt-roberta-en-base": (
"https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/reso... | 172 | 0 |
from __future__ import annotations
import inspect
import unittest
from typing import List, Tuple
from transformers import RegNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_config... | 357 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffusionPipeline,
UNetaDC... | 201 | 0 |
"""simple docstring"""
from __future__ import annotations
def __lowercase ( snake_case_ : str ,snake_case_ : list[str] | None = None ,snake_case_ : dict[str, float] | None = None ,snake_case_ : bool = False ,) ->tuple[int, float, str]:
'''simple docstring'''
... | 179 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE... | 179 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inp... | 228 |
'''simple docstring'''
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
__UpperCAmelCase = '''\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Un... | 228 | 1 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BlipaProcessor, BlipImageProcessor... | 26 |
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
_enforce_args(snake_case_,snake_case_ )
if n == 0:
return 0
_A : Tuple = float("""-inf""" )
for i in range(1,n + 1 ):
_A : str = max(
snake_case... | 26 | 1 |
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokenizer,
TFAutoModelForSequenceCla... | 90 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTester... | 90 | 1 |
'''simple docstring'''
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow ... | 56 |
'''simple docstring'''
import unittest
from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
f... | 56 | 1 |
from __future__ import annotations
import inspect
import unittest
from typing import List, Tuple
from transformers import RegNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ... | 350 |
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class A( UpperCamelCase ):
'''... | 208 | 0 |
"""simple docstring"""
from __future__ import annotations
from dataclasses import dataclass
@dataclass
class UpperCamelCase :
UpperCamelCase : float
UpperCamelCase : TreeNode | None = None
UpperCamelCase : TreeNode | None = ... | 294 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap im... | 294 | 1 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ = False ) -> str:
if not isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
lowerCAmelCase__ : Tuple = F'''Expected string as input, found {type(SCREAMING_SNAKE_CASE_ )}'''
... | 307 |
import torch
from diffusers import DPMSolverSDEScheduler
from diffusers.utils import torch_device
from diffusers.utils.testing_utils import require_torchsde
from .test_schedulers import SchedulerCommonTest
@require_torchsde
class A__ ( __magic_name__ ):
lowercase ... | 307 | 1 |
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 logging
__lowercase = logging.get_logger(__name__)
__lowercase = {'''v... | 43 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase : Union[str, Any] = logging.get_logger(__name__)
lowercase : str ... | 3 | 0 |
__A = {
"""meter""": """m""",
"""kilometer""": """km""",
"""megametre""": """Mm""",
"""gigametre""": """Gm""",
"""terametre""": """Tm""",
"""petametre""": """Pm""",
"""exametre""": """Em""",
"""zettametre""": """Zm""",
"""yottametre""": """Ym""",
}
# Exponent of th... | 351 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'microsoft/cvt-13': 'https://huggingface.co/microsoft/cvt-13/resolve/main/config.json',
# See all Cvt models at https://huggingface.co/... | 341 | 0 |
lowerCAmelCase__ = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
lowerCAmelCase__ = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
lowerCAmelCase__ = {
0: 'Sunday',
1: 'Monday',
2: 'Tuesday',
3: 'Wednesday',
4: 'Thursday',
5: 'Friday',
6: 'Saturday',
}
def _UpperCAmelCase (Upp... | 11 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
lowerCAmelCase__ = {
'configuration_speecht5': [
'SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SPEECHT5_PRETRAINED_HIFIGAN_... | 11 | 1 |
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.kandinsky... | 361 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFXLMRobertaM... | 146 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers im... | 294 |
"""simple docstring"""
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , ):
'''simple docstring'''
_a : Optional[Any] = [redshift, radiation_density, matter_... | 294 | 1 |
import json
import os
import torch
from diffusers import UNetaDModel
os.makedirs("""hub/hopper-medium-v2/unet/hor32""", exist_ok=True)
os.makedirs("""hub/hopper-medium-v2/unet/hor128""", exist_ok=True)
os.makedirs("""hub/hopper-medium-v2/value_function""", exist_ok=True)
def lowerCAmelCase( ... | 197 | from collections import defaultdict
def lowerCAmelCase( __lowerCamelCase , __lowerCamelCase ):
__a = first_str.lower().strip()
__a = second_str.lower().strip()
# Remove whitespace
__a = first_str.replace(' ' , '' )
__a = s... | 197 | 1 |
'''simple docstring'''
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
snake_case_ : Any = TypeVar("KT")
snake_case_ : Optional[int] = TypeVar("VT")
class __a (Generic[KT, VT] ):
def __init__( self : st... | 125 |
'''simple docstring'''
snake_case_ : List[str] = {
"Pillow": "Pillow<10.0.0",
"accelerate": "accelerate>=0.20.3",
"av": "av==9.2.0",
"beautifulsoup4": "beautifulsoup4",
"black": "black~=23.1",
"codecarbon": "codecarbon==1.2.0",
"cookiecutter": "cookiecutter==1.7.3",
... | 125 | 1 |
"""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 : List[str] = logging.g... | 351 |
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn # noqa: F401 # Here to hav... | 49 | 0 |
'''simple docstring'''
import torch
from diffusers import DDPMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class _lowercase ( _lowercase ):
a = (DDPMParallelScheduler,)
def lowerCamelCase_ ( self: Union[... | 41 |
from math import isclose, sqrt
def SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ) -> tuple[float, float, float]:
__lowerCamelCase : Tuple = point_y / 4 / point_x
__lowerCamelCase : Tuple = 2 * normal_gradient / (1... | 73 | 0 |
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase_ ( UpperCAmelCase__ ):
'''simple docstring'''
UpperCAmelCase__ = (DDIMParallelScheduler,)
UpperCAmelCase__ = (('''eta''', 0.0), (''... | 367 |
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ , lowercase_ ) -> Tuple:
"""simple docstring"""
A__ = AutoConfig.from_pretrained(lowercase_ )... | 231 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_pegasus import PegasusTokenizer
else:... | 289 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_a... | 324 | 0 |
"""simple docstring"""
import unittest
from transformers import BertGenerationConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_mode... | 358 |
"""simple docstring"""
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import Ten... | 128 | 0 |
'''simple docstring'''
def __UpperCamelCase ( UpperCAmelCase ):
return sum(i for i in range(1 , number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print("""Program to check whether a number is a Perfect number or not...""")
__a: Any = int(input("""... | 198 | from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class a__ ( yaml.SafeLoader ):
def __UpperCamelCase ( self : str,_A : List[str] ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_... | 18 | 0 |
from typing import Dict, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
ChannelDimension,
ImageInp... | 306 |
from __future__ import annotations
def snake_case_ ( lowerCAmelCase_ : str , lowerCAmelCase_ : str ):
__lowercase : Any = get_failure_array(lowerCAmelCase_ )
# 2) Step through text searching for pattern
__lowercase , __lowercase : Op... | 306 | 1 |
"""simple docstring"""
import os
from datetime import datetime as dt
from github import Github
__lowercase = [
"""good first issue""",
"""good second issue""",
"""good difficult issue""",
"""enhancement""",
"""new pipeline/model""",
"""new schedul... | 40 |
"""simple docstring"""
def lowercase ( A_ )-> str:
'''simple docstring'''
if isinstance(A_ , A_ ):
raise TypeError("'float' object cannot be interpreted as an integer" )
if isinstance(A_ , A_ ):
raise TypeError("'str' obj... | 40 | 1 |
import os
import string
import sys
_lowerCamelCase : List[Any] = 1 << 8
_lowerCamelCase : Union[str, Any] = {
"tab": ord("\t"),
"newline": ord("\r"),
"esc": 2_7,
"up": 6_5 + ARROW_KEY_FLAG,
"down": 6_6 + ARROW_KEY_FLAG,
"right": 6_7 + ARROW_KEY_FL... | 99 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin
if is_torch_available():
import torch
if is_vision_availa... | 99 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE_ = {
'''configuration_roc_bert''': ['''ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RoCBertConfig'''],
'... | 301 |
"""simple docstring"""
import math
def lowercase (_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 multiples of 3 are not primes
... | 301 | 1 |
from __future__ import annotations
__UpperCamelCase : Union[str, Any] = 10
def _a ( SCREAMING_SNAKE_CASE : list[int] ):
"""simple docstring"""
UpperCamelCase__ : Dict = 1
UpperCamelCase__ : Tuple = max(SCREAMING_SNAKE_CASE )
whi... | 51 |
import inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
import torch.utils.checkpoint
from ...models import UNetaDModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteSc... | 51 | 1 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transformers import AutoProcessor
from tra... | 292 |
'''simple docstring'''
import argparse
import copy
def lowercase ( __magic_name__ ):
'''simple docstring'''
UpperCAmelCase : List[str] = {}
with open(__magic_name__ ) as f:
for line in f:
if line.split()[0] not in dict_... | 311 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Any = logging.get_logger(__name__)
UpperCAmelCase : Any = {
"google/realm-cc-news-pretrained-embedder": (
"https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/mai... | 66 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def __lowerCamelCase ( lowerCamelCase__ : List[Any] , lowerCamelCase__ : List[str] , lowerCamelCase__ : str ):
'''simple docstring'''
lowerCamelCase = 0... | 66 | 1 |
from __future__ import annotations
import requests
_lowerCamelCase =set(
"""approved_at_utc approved_by author_flair_background_color
author_flair_css_class author_flair_richtext author_flair_template_id author_fullname
author_premium can_mod_post category clicked content_categories created_utc downs
edit... | 287 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFCamembertMode... | 287 | 1 |
import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from ... | 361 |
'''simple docstring'''
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTe... | 101 | 0 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_t... | 32 | '''simple docstring'''
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock import FileLock
from .... | 31 | 0 |
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
D... | 363 |
import unittest
import torch
from torch import nn
from accelerate.test_utils import require_cuda
from accelerate.utils.memory import find_executable_batch_size, release_memory
def a__ ( ):
raise RuntimeError('CUDA out of memory.' )
class __lowercase (nn.... | 162 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase_ = logging.get_logger(__name__)
lowerCamelCase_ = {
"funnel-transformer/small": "https://huggingface.co/funnel-transformer/small/resolve/main/config.json",
... | 191 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase_ = logging.get_logger(__name__)
lowerCamelCase_ = {}
class _SCREAMING_SNAKE_CASE( A ):
SCREAMING_SNAKE_CASE_ : List[Any] ... | 191 | 1 |
from collections import defaultdict
def lowerCamelCase_ ( UpperCamelCase__ : str, UpperCamelCase__ : str ):
'''simple docstring'''
UpperCamelCase__ = first_str.lower().strip()
UpperCamelCase__ = second_str.lower().strip... | 351 | lowercase = {
"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... | 35 | 0 |
import random
class UpperCAmelCase_ :
@staticmethod
def snake_case__ ( __a):
'''simple docstring'''
_lowerCAmelCase : List[str] = [ord(lowerCamelCase__) for i in text]
_lowerCAmelCase : Union[str, Any] = ... | 36 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import is_speech_available, is_vision_available
from transformers.testing_utils import require_torch
if is_vision_available():
from transformers import TvltImageProcessor
if is_speech_available():
from... | 146 | 0 |
"""simple docstring"""
from __future__ import annotations
def a__ ( snake_case__ , snake_case__ , snake_case__ ) -> tuple[float, list[float]]:
lowerCamelCase = list(range(len(snake_case__ ) ) )
lowerCamelCase = [v / w for v, w in zip(snake_case__ , snak... | 366 |
"""simple docstring"""
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table... | 168 | 0 |
'''simple docstring'''
import numpy as np
import pandas as pd
from sklearn.preprocessing import Normalizer
from sklearn.svm import SVR
from statsmodels.tsa.statespace.sarimax import SARIMAX
def _UpperCamelCase ( __A , __A , __A , __A , __A ) -> Any:
... | 80 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import BitConfig, Bit... | 101 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__snake_case = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMConfig''', '''XLMOnnxConfig'''],
'''token... | 359 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=a__ )
class __lowerCamelCase ( a__ ):
'''simple docstring'''
# `task` is not a ClassVar since w... | 153 | 0 |
snake_case_ : Optional[int] = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"
def A (__A : bytes ) -> bytes:
"""simple docstring"""
if not isinstance(__A , __A ):
UpperCAmelCase_ = F... | 51 | '''simple docstring'''
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cas... | 145 | 0 |
"""simple docstring"""
lowerCamelCase_ : Dict = [
(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, """... | 352 |
"""simple docstring"""
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, req... | 215 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ ... | 45 |
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
lowerCamelCase : int = input("Enter image url: ").strip()
print(F"""Downloading image from {url} ...""")
lowerCamelCase : Tuple = BeautifulSoup(requests.get(url).content, "ht... | 204 | 0 |
"""simple docstring"""
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def __lowercase ( __lowerCAmelCase : Tuple , __lowerCAmelCase : List[str]=None ):
a__ = ... | 367 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils import logging
logging.set_... | 109 | 0 |
"""simple docstring"""
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
UpperCAmelCase : Dict = 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_c... | 136 |
"""simple docstring"""
from math import isqrt, loga
def _SCREAMING_SNAKE_CASE (__lowerCAmelCase ) -> list[int]:
'''simple docstring'''
lowercase_ = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prim... | 136 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = ... | 359 |
from graphs.minimum_spanning_tree_kruskal import kruskal
def A__ ( ):
SCREAMING_SNAKE_CASE_ = 9
SCREAMING_SNAKE_CASE_ = [
[0, 1, 4],
[0, 7, 8],
[1, 2, 8],
[7, 8, 7],
[7, 6, 1],
[2, 8, 2],
[8, 6, 6],
[2, 3, 7],
[2, 5, 4],
... | 257 | 0 |
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