code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
from collections import deque
from math import floor
from random import random
from time import time
class lowerCamelCase__:
def __init__( self: Any ):
__lowerCamelCase = {}
def lowerCAmelCase__ ( self: Any , UpperCamelCase_: Tuple , Upp... | 361 |
from math import ceil, sqrt
def lowerCamelCase__ ( A__ : int = 1000000 ):
'''simple docstring'''
__lowerCamelCase = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
__lowerCamelCase ... | 29 | 0 |
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState, Pa... | 362 |
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 (
TEXT_GUIDED_IMAGE_IN... | 29 | 0 |
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 transfor... | 363 |
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_tor... | 29 | 0 |
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://huggi... | 364 |
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_availa... | 29 | 0 |
from itertools import count
def lowerCamelCase__ ( A__ : int = 50 ):
'''simple docstring'''
__lowerCamelCase = [1] * min_block_length
for n in count(A__ ):
fill_count_functions.append(1 )
for block_length in range(A__ , ... | 365 |
import copy
import tempfile
import unittest
from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError
from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_staging_test
class l... | 29 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {'ctrl': 'https://huggingface.co/ctrl/resolve/main/config.json'}
class lowerCamelCase__( __lowerCamelCase):
UpperCAmelCase__ : Di... | 366 |
def lowerCamelCase__ ( A__ : list ):
'''simple docstring'''
for i in range(len(A__ ) - 1 , 0 , -1 ):
__lowerCamelCase = False
for j in range(A__ , 0 , -1 ):
if unsorted[j] < unsorted[j -... | 29 | 0 |
import math
import sys
def lowerCamelCase__ ( A__ : str ):
'''simple docstring'''
__lowerCamelCase = ''
try:
with open(A__ , 'rb' ) as binary_file:
__lowerCamelCase = binary_file.read()
for d... | 367 |
import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock
import torch
from ..state import AcceleratorState, PartialState
... | 29 | 0 |
# flake8: noqa
# Lint as: python3
from typing import Dict, List, Optional, Type
from .. import config
from ..utils import logging
from .formatting import (
ArrowFormatter,
CustomFormatter,
Formatter,
PandasFormatter,
PythonFormatter,
TensorFormatter,
format_table,
query_table,
)
fr... | 368 |
from typing import List
import datasets
from datasets.tasks import AudioClassification
from ..folder_based_builder import folder_based_builder
UpperCAmelCase_ = datasets.utils.logging.get_logger(__name__)
class lowerCamelCase__( folder_based_builder.FolderBasedBuilderConfig):
UpperCAmelCa... | 29 | 0 |
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
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCA... | 369 |
import warnings
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'n... | 29 | 0 |
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': 'dataclasses',
'data... | 370 |
import string
import numpy
def lowerCamelCase__ ( A__ : int , A__ : int ):
'''simple docstring'''
return b if a == 0 else greatest_common_divisor(b % a , A__ )
class lowerCamelCase__:
UpperCAmelCase__ : Optional[int] = string.ascii... | 29 | 0 |
import pytest
from datasets.parallel import ParallelBackendConfig, parallel_backend
from datasets.utils.py_utils import map_nested
from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows
def lowerCamelCase__ ( A__ : Optional[Any] ): # picklable for multiprocessing
... | 371 |
import qiskit
def lowerCamelCase__ ( A__ : int , A__ : int ):
'''simple docstring'''
__lowerCamelCase = qiskit.Aer.get_backend("""aer_simulator""" )
__lowerCamelCase = qiskit.QuantumCircuit(4 , 2 )
# encode inputs in qubit... | 29 | 0 |
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_availa... | 350 |
def lowerCamelCase__ ( A__ : int ):
'''simple docstring'''
__lowerCamelCase = [[0 for _ in range(A__ )] for _ in range(m + 1 )]
for i in range(m + 1 ):
__lowerCamelCase = 1
for n in range(m + 1 ):
for k... | 29 | 0 |
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, PathL... | 351 |
from io import BytesIO
from typing import List, Union
import requests
from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_decord_available():
import numpy as np
from decord import VideoRea... | 29 | 0 |
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@requi... | 352 |
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available():
from ..models.auto... | 29 | 0 |
"""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_commo... | 353 |
UpperCAmelCase_ = {'a': ['c', 'b'], 'b': ['d', 'e'], 'c': [], 'd': [], 'e': []}
UpperCAmelCase_ = ['a', 'b', 'c', 'd', 'e']
def lowerCamelCase__ ( A__ : Union[str, Any] , A__ : Optional[int] , A__ : str ):
'''simple docstring'''
__lowerCamelCase ... | 29 | 0 |
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
UpperCAmelCase_ = logging.get_logger(... | 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 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'facebook/s2t-wav2vec2-large-en-de': (
'https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/config.json'
),
# ... | 355 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'hustvl/yolos-smal... | 29 | 0 |
import heapq
def lowerCamelCase__ ( A__ : dict ):
'''simple docstring'''
__lowerCamelCase = []
# for each node and his adjacency list add them and the rank of the node to queue
# using heapq module the queue will be filled like a Priority Queue
#... | 356 |
import os
from math import logaa
def lowerCamelCase__ ( A__ : str = "base_exp.txt" ):
'''simple docstring'''
__lowerCamelCase = 0
__lowerCamelCase = 0
for i, line in enumerate(open(os.path.join(os.path.dirname(A__ ) , A__ ) )... | 29 | 0 |
import numpy as np
def lowerCamelCase__ ( A__ : np.array ):
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
if __name__ == "__main__":
import doctest
doctest.testmod()
| 357 |
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__ ( ... | 29 | 0 |
def lowerCamelCase__ ( A__ : int , A__ : int ):
'''simple docstring'''
if a < 0 or b < 0:
raise ValueError("""the value of both inputs must be positive""" )
__lowerCamelCase = str(bin(A__ ) )[2:] # remove the leading "0b"
__... | 358 |
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
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 TEXT_GUIDED_IM... | 29 | 0 |
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCamelCas... | 359 |
# 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... | 29 | 0 |
import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path
import pytest
import transformers
from transformers import (
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
AutoTokenizer,
BertConfig,
BertTokenizer,
BertTokenizerFast,
... | 360 |
from __future__ import annotations
UpperCAmelCase_ = {
'A': ['B', 'C', 'E'],
'B': ['A', 'D', 'E'],
'C': ['A', 'F', 'G'],
'D': ['B'],
'E': ['A', 'B', 'D'],
'F': ['C'],
'G': ['C'],
}
class lowerCamelCase__:
def __init__( self: Tuple , UpperCamelCase_: dict[... | 29 | 0 |
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
JumanppToken... | 361 |
from math import ceil, sqrt
def lowerCamelCase__ ( A__ : int = 1000000 ):
'''simple docstring'''
__lowerCamelCase = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
__lowerCamelCase ... | 29 | 0 |
# Imports
import numpy as np
class lowerCamelCase__:
def __init__( self: List[str] , UpperCamelCase_: str=None , UpperCamelCase_: Union[str, Any]=None , UpperCamelCase_: List[Any]=None , UpperCamelCase_: int=None , UpperCamelCase_: Optional[int]=None ):
sel... | 362 |
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 (
TEXT_GUIDED_IMAGE_IN... | 29 | 0 |
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def lowerCamelCase__ ( A__ : dict ):
... | 363 |
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_tor... | 29 | 0 |
def lowerCamelCase__ ( A__ : int = 1000000 ):
'''simple docstring'''
__lowerCamelCase : Optional[int] = set(range(3 , A__ , 2 ) )
primes.add(2 )
for p in range(3 , A__ , 2 ):
if p not in primes:
... | 364 |
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_availa... | 29 | 0 |
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import Flax... | 365 |
import copy
import tempfile
import unittest
from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError
from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_staging_test
class l... | 29 | 0 |
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_availabl... | 366 |
def lowerCamelCase__ ( A__ : list ):
'''simple docstring'''
for i in range(len(A__ ) - 1 , 0 , -1 ):
__lowerCamelCase = False
for j in range(A__ , 0 , -1 ):
if unsorted[j] < unsorted[j -... | 29 | 0 |
import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock
import torch
from ..state import AcceleratorState, PartialState
... | 367 |
import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock
import torch
from ..state import AcceleratorState, PartialState
... | 29 | 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 ... | 368 |
from typing import List
import datasets
from datasets.tasks import AudioClassification
from ..folder_based_builder import folder_based_builder
UpperCAmelCase_ = datasets.utils.logging.get_logger(__name__)
class lowerCamelCase__( folder_based_builder.FolderBasedBuilderConfig):
UpperCAmelCa... | 29 | 0 |
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from transformers import CLIPImageProcessor, CLIPVisionModel
from ...models import PriorTransformer
from ...pipelines import DiffusionPipeline
from ...schedulers import HeunDiscret... | 369 |
import warnings
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'n... | 29 | 0 |
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 lowerCamelCase__( __lowerCamelCase):
def __init__( self: Opti... | 370 |
import string
import numpy
def lowerCamelCase__ ( A__ : int , A__ : int ):
'''simple docstring'''
return b if a == 0 else greatest_common_divisor(b % a , A__ )
class lowerCamelCase__:
UpperCAmelCase__ : Optional[int] = string.ascii... | 29 | 0 |
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'huggingface/autoformer-tourism-monthly': 'https://huggingface.co/huggingface/autoformer-tourism-monthly/reso... | 371 |
import qiskit
def lowerCamelCase__ ( A__ : int , A__ : int ):
'''simple docstring'''
__lowerCamelCase = qiskit.Aer.get_backend("""aer_simulator""" )
__lowerCamelCase = qiskit.QuantumCircuit(4 , 2 )
# encode inputs in qubit... | 29 | 0 |
import json
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
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, prepa... | 350 |
def lowerCamelCase__ ( A__ : int ):
'''simple docstring'''
__lowerCamelCase = [[0 for _ in range(A__ )] for _ in range(m + 1 )]
for i in range(m + 1 ):
__lowerCamelCase = 1
for n in range(m + 1 ):
for k... | 29 | 0 |
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
RobertaTokenizer,
RobertaTokenizerFast,
XLMRob... | 351 |
from io import BytesIO
from typing import List, Union
import requests
from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_decord_available():
import numpy as np
from decord import VideoRea... | 29 | 0 |
from __future__ import annotations
def lowerCamelCase__ ( A__ : float , A__ : float , A__ : float , ):
'''simple docstring'''
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError("""You cannot supply more or less than 2 v... | 352 |
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available():
from ..models.auto... | 29 | 0 |
"""simple docstring"""
from __future__ import annotations
UpperCAmelCase_ = {
'A': ['B', 'C', 'E'],
'B': ['A', 'D', 'E'],
'C': ['A', 'F', 'G'],
'D': ['B'],
'E': ['A', 'B', 'D'],
'F': ['C'],
'G': ['C'],
}
class lowerCamelCase__:
def __init__( self: Tuple ... | 353 |
UpperCAmelCase_ = {'a': ['c', 'b'], 'b': ['d', 'e'], 'c': [], 'd': [], 'e': []}
UpperCAmelCase_ = ['a', 'b', 'c', 'd', 'e']
def lowerCamelCase__ ( A__ : Union[str, Any] , A__ : Optional[int] , A__ : str ):
'''simple docstring'''
__lowerCamelCase ... | 29 | 0 |
import json
import os
import re
import sys
import urllib.request
import requests
from bsa import BeautifulSoup
UpperCAmelCase_ = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'
' (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 Edge/18.19582'
... | 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 |
import argparse
import glob
import logging
import os
import sys
import time
from collections import defaultdict
from pathlib import Path
from typing import Dict, List, Tuple
import numpy as np
import pytorch_lightning as pl
import torch
from callbacks import SeqaSeqLoggingCallback, get_checkpoint_callback, get_ea... | 355 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'hustvl/yolos-smal... | 29 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ = {
'configuration_timesformer': ['TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TimesformerConfig'],
}
try:
if not is_torch_available():
raise O... | 356 |
import os
from math import logaa
def lowerCamelCase__ ( A__ : str = "base_exp.txt" ):
'''simple docstring'''
__lowerCamelCase = 0
__lowerCamelCase = 0
for i, line in enumerate(open(os.path.join(os.path.dirname(A__ ) , A__ ) )... | 29 | 0 |
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if version.parse(fairseq.__... | 357 |
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__ ( ... | 29 | 0 |
from dataclasses import dataclass
from typing import Dict, Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .attention_processor import AttentionProcessor, AttnProcessor
from .modeli... | 358 |
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
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 TEXT_GUIDED_IM... | 29 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ = {'configuration_opt': ['OPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'OPTConfig']}
try... | 359 |
# 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... | 29 | 0 |
import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
UpperCAme... | 360 |
from __future__ import annotations
UpperCAmelCase_ = {
'A': ['B', 'C', 'E'],
'B': ['A', 'D', 'E'],
'C': ['A', 'F', 'G'],
'D': ['B'],
'E': ['A', 'B', 'D'],
'F': ['C'],
'G': ['C'],
}
class lowerCamelCase__:
def __init__( self: Tuple , UpperCamelCase_: dict[... | 29 | 0 |
def lowerCamelCase__ ( A__ : int , A__ : int ):
'''simple docstring'''
__lowerCamelCase = 1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
__lowerCamelCase = n - k
# Calculate C(n,k)
... | 361 |
from math import ceil, sqrt
def lowerCamelCase__ ( A__ : int = 1000000 ):
'''simple docstring'''
__lowerCamelCase = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
__lowerCamelCase ... | 29 | 0 |
import string
import numpy
def lowerCamelCase__ ( A__ : int , A__ : int ):
'''simple docstring'''
return b if a == 0 else greatest_common_divisor(b % a , A__ )
class lowerCamelCase__:
UpperCAmelCase__ : Optional[int] = string.ascii... | 362 |
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 (
TEXT_GUIDED_IMAGE_IN... | 29 | 0 |
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def lowerCamelCase__ ( A__ : Optional[int] ):
'''simple docstring'''
__lowerCa... | 363 |
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_tor... | 29 | 0 |
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...util... | 364 |
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_availa... | 29 | 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 AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils import TOKEN, USER, ... | 365 |
import copy
import tempfile
import unittest
from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError
from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_staging_test
class l... | 29 | 0 |
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'facebook/data2vec-base-960h': 'https://huggingface.co/facebook/data2vec-audio-base-960h/resolve/main/config.json',
# See all D... | 366 |
def lowerCamelCase__ ( A__ : list ):
'''simple docstring'''
for i in range(len(A__ ) - 1 , 0 , -1 ):
__lowerCamelCase = False
for j in range(A__ , 0 , -1 ):
if unsorted[j] < unsorted[j -... | 29 | 0 |
def lowerCamelCase__ ( A__ : List[Any] , A__ : Any ):
'''simple docstring'''
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def lowerCamelCase__ ( A__ : Dict , A__ : Optional[Any]=0 ):
'''simple docstring'''
return ... | 367 |
import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock
import torch
from ..state import AcceleratorState, PartialState
... | 29 | 0 |
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data import Dataset
from tra... | 368 |
from typing import List
import datasets
from datasets.tasks import AudioClassification
from ..folder_based_builder import folder_based_builder
UpperCAmelCase_ = datasets.utils.logging.get_logger(__name__)
class lowerCamelCase__( folder_based_builder.FolderBasedBuilderConfig):
UpperCAmelCa... | 29 | 0 |
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test_tokenization_c... | 369 |
import warnings
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'n... | 29 | 0 |
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available():
from ..models.auto.modeling_auto ... | 370 |
import string
import numpy
def lowerCamelCase__ ( A__ : int , A__ : int ):
'''simple docstring'''
return b if a == 0 else greatest_common_divisor(b % a , A__ )
class lowerCamelCase__:
UpperCAmelCase__ : Optional[int] = string.ascii... | 29 | 0 |
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = 'https://openai... | 371 |
import qiskit
def lowerCamelCase__ ( A__ : int , A__ : int ):
'''simple docstring'''
__lowerCamelCase = qiskit.Aer.get_backend("""aer_simulator""" )
__lowerCamelCase = qiskit.QuantumCircuit(4 , 2 )
# encode inputs in qubit... | 29 | 0 |
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available(... | 350 |
def lowerCamelCase__ ( A__ : int ):
'''simple docstring'''
__lowerCamelCase = [[0 for _ in range(A__ )] for _ in range(m + 1 )]
for i in range(m + 1 ):
__lowerCamelCase = 1
for n in range(m + 1 ):
for k... | 29 | 0 |
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_modeling_common import ModelTest... | 351 |
from io import BytesIO
from typing import List, Union
import requests
from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_decord_available():
import numpy as np
from decord import VideoRea... | 29 | 0 |
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules import _PACKAGED_DATASE... | 352 |
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available():
from ..models.auto... | 29 | 0 |
"""simple docstring"""
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
UNetaDConditionModel,
VideoToVideoSDPipeline,
)
from diffusers.utils import floats_t... | 353 |
UpperCAmelCase_ = {'a': ['c', 'b'], 'b': ['d', 'e'], 'c': [], 'd': [], 'e': []}
UpperCAmelCase_ = ['a', 'b', 'c', 'd', 'e']
def lowerCamelCase__ ( A__ : Union[str, Any] , A__ : Optional[int] , A__ : str ):
'''simple docstring'''
__lowerCamelCase ... | 29 | 0 |
import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format='%(message)s')
def lowerCamelCase__ ( A__ : np.ndarray ):
'''simple docstring'''
return input_array.reshape((input_array.size,... | 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 |
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeacher, LevitImageProcessor
from transformers.utils imp... | 355 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'hustvl/yolos-smal... | 29 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
UpperCAmelCase_ = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
el... | 356 |
import os
from math import logaa
def lowerCamelCase__ ( A__ : str = "base_exp.txt" ):
'''simple docstring'''
__lowerCamelCase = 0
__lowerCamelCase = 0
for i, line in enumerate(open(os.path.join(os.path.dirname(A__ ) , A__ ) )... | 29 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'funnel-transformer/small': 'https://huggingface.co/funnel-transformer/small/resolve/main/config.json',
'funnel-transformer/small-base': 'ht... | 357 |
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__ ( ... | 29 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_convbert import ConvBertTokenizer
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = ... | 358 |
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
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 TEXT_GUIDED_IM... | 29 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
UpperCAmelCase_ = {'tokenization_herbert': ['HerbertTokenizer']}
try:
if not is_tokenizers_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAva... | 359 |
# 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... | 29 | 0 |
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def lowerCamelCase__ ( A__ : Namespace ):
'''simple docstring'''
return ConvertCommand(
args.model_type , args.tf_checkpoint , args.pytorch... | 360 |
from __future__ import annotations
UpperCAmelCase_ = {
'A': ['B', 'C', 'E'],
'B': ['A', 'D', 'E'],
'C': ['A', 'F', 'G'],
'D': ['B'],
'E': ['A', 'B', 'D'],
'F': ['C'],
'G': ['C'],
}
class lowerCamelCase__:
def __init__( self: Tuple , UpperCamelCase_: dict[... | 29 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ = {
'configuration_lxmert': ['LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LxmertConfig'],
'tokeniz... | 361 |
from math import ceil, sqrt
def lowerCamelCase__ ( A__ : int = 1000000 ):
'''simple docstring'''
__lowerCamelCase = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
__lowerCamelCase ... | 29 | 0 |
import warnings
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
... | 362 |
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 (
TEXT_GUIDED_IMAGE_IN... | 29 | 0 |
from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class lowerCamelCase__( __lowerCamelCase):
UpperCAmelCase__ : ... | 363 |
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_tor... | 29 | 0 |
def lowerCamelCase__ ( A__ : list[int] ):
'''simple docstring'''
if not numbers:
return 0
if not isinstance(A__ , (list, tuple) ) or not all(
isinstance(A__ , A__ ) for number in numbers ):
raise ValueError("""nu... | 364 |
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_availa... | 29 | 0 |
import string
# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
UpperCAmelCase_ = {
'E': 12.70,
'T': 9.06,
'A': 8.17,
'O': 7.51,
'I': 6.97,
'N': 6.75,
'S': 6.33,
'H': 6.09,
'R': 5.99,
'D': 4.25,
'L': 4.03,
'C': 2.78,
'U': 2.76,
'M... | 365 |
import copy
import tempfile
import unittest
from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError
from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_staging_test
class l... | 29 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCAmelCase_ = {
'configuration_vision_encoder_decoder': ['VisionEncoderDecoderConfig', 'VisionEncoderDecoderOnnxConfi... | 366 |
def lowerCamelCase__ ( A__ : list ):
'''simple docstring'''
for i in range(len(A__ ) - 1 , 0 , -1 ):
__lowerCamelCase = False
for j in range(A__ , 0 , -1 ):
if unsorted[j] < unsorted[j -... | 29 | 0 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelerator, ... | 367 |
import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock
import torch
from ..state import AcceleratorState, PartialState
... | 29 | 0 |
UpperCAmelCase_ = {'a': ['c', 'b'], 'b': ['d', 'e'], 'c': [], 'd': [], 'e': []}
UpperCAmelCase_ = ['a', 'b', 'c', 'd', 'e']
def lowerCamelCase__ ( A__ : Union[str, Any] , A__ : Optional[int] , A__ : str ):
'''simple docstring'''
__lowerCamelCase ... | 368 |
from typing import List
import datasets
from datasets.tasks import AudioClassification
from ..folder_based_builder import folder_based_builder
UpperCAmelCase_ = datasets.utils.logging.get_logger(__name__)
class lowerCamelCase__( folder_based_builder.FolderBasedBuilderConfig):
UpperCAmelCa... | 29 | 0 |
from math import sqrt
def lowerCamelCase__ ( A__ : int = 1000000 ):
'''simple docstring'''
__lowerCamelCase = 0
__lowerCamelCase = 0
__lowerCamelCase = 42
while num_cuboids <= limit:
ma... | 369 |
import warnings
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'n... | 29 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_torch_available,
is_vision_available,
)
UpperCAmelCase_ = {'configuration_beit': ['BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BeitConfig', 'BeitOnnxConfig']}
try:
... | 370 |
import string
import numpy
def lowerCamelCase__ ( A__ : int , A__ : int ):
'''simple docstring'''
return b if a == 0 else greatest_common_divisor(b % a , A__ )
class lowerCamelCase__:
UpperCAmelCase__ : Optional[int] = string.ascii... | 29 | 0 |
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers import VQDiffusionScheduler
from ...util... | 371 |
import qiskit
def lowerCamelCase__ ( A__ : int , A__ : int ):
'''simple docstring'''
__lowerCamelCase = qiskit.Aer.get_backend("""aer_simulator""" )
__lowerCamelCase = qiskit.QuantumCircuit(4 , 2 )
# encode inputs in qubit... | 29 | 0 |
UpperCAmelCase_ = {
0: '0',
1: '1',
2: '2',
3: '3',
4: '4',
5: '5',
6: '6',
7: '7',
8: '8',
9: '9',
10: 'a',
11: 'b',
12: 'c',
13: 'd',
14: 'e',
15: 'f',
}
def lowerCamelCase__ ( A__ : float ):
'''simple docstring'''
... | 350 |
def lowerCamelCase__ ( A__ : int ):
'''simple docstring'''
__lowerCamelCase = [[0 for _ in range(A__ )] for _ in range(m + 1 )]
for i in range(m + 1 ):
__lowerCamelCase = 1
for n in range(m + 1 ):
for k... | 29 | 0 |
import math
def lowerCamelCase__ ( A__ : int ):
'''simple docstring'''
assert isinstance(A__ , A__ ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are primes
return True
... | 351 |
from io import BytesIO
from typing import List, Union
import requests
from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_decord_available():
import numpy as np
from decord import VideoRea... | 29 | 0 |
from __future__ import annotations
def lowerCamelCase__ ( A__ : tuple[int, int] , A__ : int ):
'''simple docstring'''
__lowerCamelCase, __lowerCamelCase = position
__lowerCamelCase = [
(y + 1, x + 2),
(y - 1, x + 2),... | 352 |
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available():
from ..models.auto... | 29 | 0 |
"""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
UpperCAmelCase_ = g... | 353 |
UpperCAmelCase_ = {'a': ['c', 'b'], 'b': ['d', 'e'], 'c': [], 'd': [], 'e': []}
UpperCAmelCase_ = ['a', 'b', 'c', 'd', 'e']
def lowerCamelCase__ ( A__ : Union[str, Any] , A__ : Optional[int] , A__ : str ):
'''simple docstring'''
__lowerCamelCase ... | 29 | 0 |
from collections.abc import Sequence
def lowerCamelCase__ ( A__ : Sequence[int] | None = None ):
'''simple docstring'''
if nums is None or not nums:
raise ValueError("""Input sequence should not be empty""" )
__lowerCamelCase ... | 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 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'distilbert-base-uncased': 'https://huggingface.c... | 355 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'hustvl/yolos-smal... | 29 | 0 |
import operator
def lowerCamelCase__ ( A__ : list , A__ : bool = False , A__ : list | None = None ):
'''simple docstring'''
__lowerCamelCase = operator.lt if reverse else operator.gt
__lowerCamelCase = solution or []
if not arr:
... | 356 |
import os
from math import logaa
def lowerCamelCase__ ( A__ : str = "base_exp.txt" ):
'''simple docstring'''
__lowerCamelCase = 0
__lowerCamelCase = 0
for i, line in enumerate(open(os.path.join(os.path.dirname(A__ ) , A__ ) )... | 29 | 0 |
import inspect
import logging
import os
import random
import shutil
import tempfile
import unittest
import pytest
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_cuda
fr... | 357 |
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__ ( ... | 29 | 0 |
from functools import lru_cache
def lowerCamelCase__ ( A__ : int ):
'''simple docstring'''
__lowerCamelCase = 2
__lowerCamelCase = set()
while i * i <= n:
if n % i:
i += 1
else:
... | 358 |
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
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 TEXT_GUIDED_IM... | 29 | 0 |
from graphs.minimum_spanning_tree_kruskal import kruskal
def lowerCamelCase__ ( ):
'''simple docstring'''
__lowerCamelCase = 9
__lowerCamelCase = [
[0, 1, 4],
[0, 7, 8],
[1, 2, 8],
[7, 8, 7],
[7, 6, ... | 359 |
# 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... | 29 | 0 |
from __future__ import annotations
def lowerCamelCase__ ( A__ : list[int] , A__ : list[int] , A__ : int ):
'''simple docstring'''
__lowerCamelCase = list(range(len(A__ ) ) )
__lowerCamelCase = [v / w for v, w in zip(A__ , ... | 360 |
from __future__ import annotations
UpperCAmelCase_ = {
'A': ['B', 'C', 'E'],
'B': ['A', 'D', 'E'],
'C': ['A', 'F', 'G'],
'D': ['B'],
'E': ['A', 'B', 'D'],
'F': ['C'],
'G': ['C'],
}
class lowerCamelCase__:
def __init__( self: Tuple , UpperCamelCase_: dict[... | 29 | 0 |
import math
def lowerCamelCase__ ( A__ : list , A__ : int ):
'''simple docstring'''
__lowerCamelCase = len(A__ )
__lowerCamelCase = int(math.floor(math.sqrt(A__ ) ) )
__lowerCamelCase = 0
while arr[min(... | 361 |
from math import ceil, sqrt
def lowerCamelCase__ ( A__ : int = 1000000 ):
'''simple docstring'''
__lowerCamelCase = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
__lowerCamelCase ... | 29 | 0 |
UpperCAmelCase_ = {
'km/h': 1.0,
'm/s': 3.6,
'mph': 1.60_9344,
'knot': 1.852,
}
UpperCAmelCase_ = {
'km/h': 1.0,
'm/s': 0.2_7777_7778,
'mph': 0.6_2137_1192,
'knot': 0.5_3995_6803,
}
def lowerCamelCase__ ( A__ : float , A__ : str , A__ : s... | 362 |
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 (
TEXT_GUIDED_IMAGE_IN... | 29 | 0 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
# TODO: upload to AWS
UpperCAmelCase_ = {
'yjernite/retribert-base-uncased': (
'https://huggingface.co/yjernite/retribert-base-uncased/resol... | 363 |
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_tor... | 29 | 0 |
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/musicgen-small/resolve/main/compression... | 364 |
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_availa... | 29 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ = {
'configuration_time_series_transformer': [
'TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'TimeSeriesTransformerConfig',
],
}
try:
... | 365 |
import copy
import tempfile
import unittest
from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError
from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_staging_test
class l... | 29 | 0 |
import qiskit
def lowerCamelCase__ ( A__ : int , A__ : int ):
'''simple docstring'''
__lowerCamelCase = qiskit.Aer.get_backend("""aer_simulator""" )
__lowerCamelCase = qiskit.QuantumCircuit(4 , 2 )
# encode inputs in qubit... | 366 |
def lowerCamelCase__ ( A__ : list ):
'''simple docstring'''
for i in range(len(A__ ) - 1 , 0 , -1 ):
__lowerCamelCase = False
for j in range(A__ , 0 , -1 ):
if unsorted[j] < unsorted[j -... | 29 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ = {'configuration_vit_msn': ['VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ViTMSNConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNot... | 367 |
import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock
import torch
from ..state import AcceleratorState, PartialState
... | 29 | 0 |
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def lowerCamelCase__ ( ):
'''simple docstring'''
__lowerCamelCase, __lowerCamelCase = 9, 14 # noqa: F841
__lowerCamelCase = [
[0,... | 368 |
from typing import List
import datasets
from datasets.tasks import AudioClassification
from ..folder_based_builder import folder_based_builder
UpperCAmelCase_ = datasets.utils.logging.get_logger(__name__)
class lowerCamelCase__( folder_based_builder.FolderBasedBuilderConfig):
UpperCAmelCa... | 29 | 0 |
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
UpperCAmelCase_ = '\\n@article{wang2019superglue,\n title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},\n author={Wang... | 369 |
import warnings
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'n... | 29 | 0 |
import math
from typing import Any, Callable, List, Optional, Tuple, Union
import numpy as np
import torch
from ...models import TaFilmDecoder
from ...schedulers import DDPMScheduler
from ...utils import is_onnx_available, logging, randn_tensor
if is_onnx_available():
from ..onnx_utils import OnnxRuntimeMode... | 370 |
import string
import numpy
def lowerCamelCase__ ( A__ : int , A__ : int ):
'''simple docstring'''
return b if a == 0 else greatest_common_divisor(b % a , A__ )
class lowerCamelCase__:
UpperCAmelCase__ : Optional[int] = string.ascii... | 29 | 0 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
UpperCAmelCase_ = ... | 371 |
import qiskit
def lowerCamelCase__ ( A__ : int , A__ : int ):
'''simple docstring'''
__lowerCamelCase = qiskit.Aer.get_backend("""aer_simulator""" )
__lowerCamelCase = qiskit.QuantumCircuit(4 , 2 )
# encode inputs in qubit... | 29 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase__ = {
"""configuration_git""": ["""GIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GitConfig""", """GitVisionConfig"""],
"""processing_git""": ["""... | 30 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase__ = {
"""configuration_git""": ["""GIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GitConfig""", """GitVisionConfig"""],
"""processing_git""": ["""... | 30 | 1 |
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