code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def __UpperCamelCase ( a : Any , a : List[str]=() , a : Tupl... | 44 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVi... | 44 | 1 |
'''simple docstring'''
import argparse
import copy
def __UpperCamelCase ( a : Union[str, Any] ) ->Tuple:
snake_case = {}
with open(a ) as f:
for line in f:
if line.split()[0] not in dict_of_neighbours:
snake_case = []
_list.append([line.split... | 44 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassificatio... | 44 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
'configuration_pegasus_x': ['PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PegasusXConfig'],
}
try:
if no... | 44 |
'''simple docstring'''
import argparse
import json
import logging
import os
import sys
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, get_gpu_count, slow
_lowercase = [
os.path.join(os.path.dirname(__file__), dirname)
... | 44 | 1 |
'''simple docstring'''
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, LevitForImageClassificationWithT... | 44 |
'''simple docstring'''
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairs... | 44 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
_lowercase = logging.get_logger(__name__)
class _lowercase ( __a ):
def __init__( self , *A__ , *... | 44 |
'''simple docstring'''
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .... | 44 | 1 |
'''simple docstring'''
from abc import ABC, abstractmethod
from typing import List, Optional
class _lowercase ( __a ):
def __init__( self ) -> List[str]:
# test for the above condition
self.test()
def UpperCamelC... | 44 |
'''simple docstring'''
_lowercase = {
'Pillow': 'Pillow',
'accelerate': 'accelerate>=0.11.0',
'compel': 'compel==0.1.8',
'black': 'black~=23.1',
'datasets': 'datasets',
'filelock': 'filelock',
'flax': 'flax>=0.4.1',
'hf-doc-builder': 'hf-d... | 44 | 1 |
'''simple docstring'''
def __UpperCamelCase ( a : int ) ->int:
snake_case = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def __UpperCamelCase ( a : int ) ->int:
snake_case = 0
while number > 0:
snake_case = number % 10
... | 44 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, to... | 44 | 1 |
'''simple docstring'''
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _lowercase ( __a ):
@staticmethod
@abstractmethod
def UpperCamelCase ( A__ ) -> Dict:
raise NotImplementedError()
... | 44 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
_lowercase ... | 44 | 1 |
'''simple docstring'''
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def __UpperCamelCase ( a : List[Any] ) ->List[str]:
snake_case = [
'''encoder.version''',
'''decoder.version'''... | 44 |
'''simple docstring'''
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class _lowercase ( yaml.SafeLoader ):
def UpperCamelCase ( self , A__ ) -> List[str]:
snake_case =... | 44 | 1 |
'''simple docstring'''
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
_lowercase = logging.getLogger(__name__)
class _lowercase :
... | 44 |
'''simple docstring'''
import json
import os
import re
import unittest
from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from... | 44 | 1 |
'''simple docstring'''
import pickle
import numpy as np
from matplotlib import pyplot as plt
class _lowercase :
def __init__( self , A__ , A__ , A__ , A__ , A__ , A__=0.2 , A__=0.2 ) -> int:
snake_case = bp_num... | 44 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
... | 44 | 1 |
'''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 xo... | 44 |
'''simple docstring'''
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
fro... | 44 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
_lowercase = {
'configuration_llama': ['L... | 44 |
'''simple docstring'''
def __UpperCamelCase ( a : int , a : int ) ->int:
while b:
snake_case , snake_case = b, a % b
return a
def __UpperCamelCase ( a : int , a : int ) ->int:
return a if b == 0 else euclidean_gcd_recursive(a , ... | 44 | 1 |
'''simple docstring'''
import math
import unittest
def __UpperCamelCase ( a : int ) ->bool:
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
elif number < 2... | 44 |
'''simple docstring'''
import argparse
import copy
def __UpperCamelCase ( a : Union[str, Any] ) ->Tuple:
snake_case = {}
with open(a ) as f:
for line in f:
if line.split()[0] not in dict_of_neighbours:
snake_case = []
_list.append([line.split... | 44 | 1 |
'''simple docstring'''
def __UpperCamelCase ( a : int = 50 ) ->int:
snake_case = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_length - tile_length + 1 ... | 44 |
'''simple docstring'''
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
exc... | 44 | 1 |
'''simple docstring'''
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_availa... | 44 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
class _lowercase ( __a ):
_UpperCAmelCase = '''WhisperFeatureExtractor'''
_UpperCAmelCase = '''WhisperTokenizer'''
def __init__( self , A__ ... | 44 | 1 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
class _lowercase ( __a ):
_UpperCAmelCase = '''WhisperFeatureExtractor'''
_UpperCAmelCase = '''WhisperTokenizer'''
def __init__( self , A__ ... | 44 |
'''simple docstring'''
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class _... | 44 | 1 |
'''simple docstring'''
def __UpperCamelCase ( a : int ) ->str:
if number > 0:
raise ValueError('''input must be a negative integer''' )
snake_case = len(bin(a )[3:] )
snake_case = bin(abs(a ) - (1 << binary_number_length) )[3:]
snake_case ... | 44 |
'''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 xo... | 44 | 1 |
'''simple docstring'''
import tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class _lowercase ( __a ):
_UpperCAmelCase = (PNDMScheduler,)
_UpperCAmelCase = (('''num_in... | 44 |
'''simple docstring'''
import hashlib
import unittest
from transformers import MODEL_FOR_DEPTH_ESTIMATION_MAPPING, is_torch_available, is_vision_available
from transformers.pipelines import DepthEstimationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,... | 44 | 1 |
'''simple docstring'''
from math import sqrt
def __UpperCamelCase ( a : int ) ->bool:
assert isinstance(a , a ) and (
number >= 0
), "'number' must been an int and positive"
snake_case = True
# 0 and 1 are none primes.
if number <= 1:
snake_c... | 44 |
'''simple docstring'''
import argparse
import torch
from torch import nn
from transformers import SpeechaTextConfig, SpeechaTextForConditionalGeneration
def __UpperCamelCase ( a : Optional[int] ) ->Dict:
snake_case = [
'''encoder.version''',
'''decoder.v... | 44 | 1 |
'''simple docstring'''
import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
_lowercase = np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)
# Create two fuzzy sets by de... | 44 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _lowercase ( metaclass=__a ):
_UpperCAmelCase = ['''transformers''', '''torch''', '''note_seq''']
def __init__( self , *A__ , **A__ ) -> Union... | 44 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class _lowercase :
_UpperCAmelCase = 42
_UpperCAmelCase = 42
... | 44 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
class _lowercase :
def __init__( self , A__ ) -> None:
snake_case = value
snake_case = None
snake_case = None
cla... | 44 | 1 |
'''simple docstring'''
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 ... | 44 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVi... | 44 | 1 |
'''simple docstring'''
import math
import sys
def __UpperCamelCase ( a : str ) ->str:
snake_case = ''''''
try:
with open(a , '''rb''' ) as binary_file:
snake_case = binary_file.read()
for dat in data:
snake_case = f"""{dat:08b}"""
r... | 44 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassificatio... | 44 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowercase ... | 44 |
'''simple docstring'''
import argparse
import json
import logging
import os
import sys
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, get_gpu_count, slow
_lowercase = [
os.path.join(os.path.dirname(__file__), dirname)
... | 44 | 1 |
'''simple docstring'''
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class _... | 44 |
'''simple docstring'''
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairs... | 44 | 1 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
... | 44 |
'''simple docstring'''
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .... | 44 | 1 |
'''simple docstring'''
import unittest
from transformers import XLMConfig, 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... | 44 |
'''simple docstring'''
_lowercase = {
'Pillow': 'Pillow',
'accelerate': 'accelerate>=0.11.0',
'compel': 'compel==0.1.8',
'black': 'black~=23.1',
'datasets': 'datasets',
'filelock': 'filelock',
'flax': 'flax>=0.4.1',
'hf-doc-builder': 'hf-d... | 44 | 1 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apa... | 44 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, to... | 44 | 1 |
'''simple docstring'''
_lowercase = range(2, 20 + 1)
_lowercase = [10**k for k in range(ks[-1] + 1)]
_lowercase = {}
def __UpperCamelCase ( a : Dict , a : List[str] , a : Dict , a : Any ) ->List[Any]:
snake_... | 44 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
_lowercase ... | 44 | 1 |
'''simple docstring'''
def __UpperCamelCase ( a : list ) ->list:
if len(a ) < 2:
return collection
def circle_sort_util(a : list , a : int , a : int ) -> bool:
snake_case = False
if low == high:
return swapped
snake_case ... | 44 |
'''simple docstring'''
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class _lowercase ( yaml.SafeLoader ):
def UpperCamelCase ( self , A__ ) -> List[str]:
snake_case =... | 44 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
from collections.abc import Callable
def __UpperCamelCase ( a : Callable[[int | float], int | float] , a : int | float , a : int | float , a : int = 100 , ) ->float:
snake_cas... | 44 |
'''simple docstring'''
import json
import os
import re
import unittest
from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from... | 44 | 1 |
'''simple docstring'''
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
fro... | 44 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
... | 44 | 1 |
'''simple docstring'''
from __future__ import annotations
def __UpperCamelCase ( a : list ) ->float:
if not nums:
raise ValueError('''List is empty''' )
return sum(a ) / len(a )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 44 |
'''simple docstring'''
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
fro... | 44 | 1 |
'''simple docstring'''
_lowercase = {
'A': ['B', 'C', 'E'],
'B': ['A', 'D', 'E'],
'C': ['A', 'F', 'G'],
'D': ['B'],
'E': ['A', 'B', 'D'],
'F': ['C'],
'G': ['C'],
}
def __UpperCamelCase ( a : dict , a : List[Any] , a ... | 44 |
'''simple docstring'''
def __UpperCamelCase ( a : int , a : int ) ->int:
while b:
snake_case , snake_case = b, a % b
return a
def __UpperCamelCase ( a : int , a : int ) ->int:
return a if b == 0 else euclidean_gcd_recursive(a , ... | 44 | 1 |
'''simple docstring'''
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class _lowercase ( unittest.TestCa... | 44 |
'''simple docstring'''
import argparse
import copy
def __UpperCamelCase ( a : Union[str, Any] ) ->Tuple:
snake_case = {}
with open(a ) as f:
for line in f:
if line.split()[0] not in dict_of_neighbours:
snake_case = []
_list.append([line.split... | 44 | 1 |
'''simple docstring'''
import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from ... | 44 |
'''simple docstring'''
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
exc... | 44 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from .... | 44 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
class _lowercase ( __a ):
_UpperCAmelCase = '''WhisperFeatureExtractor'''
_UpperCAmelCase = '''WhisperTokenizer'''
def __init__( self , A__ ... | 44 | 1 |
'''simple docstring'''
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImagePro... | 44 |
'''simple docstring'''
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class _... | 44 | 1 |
'''simple docstring'''
_lowercase = [
999,
800,
799,
600,
599,
500,
400,
399,
377,
355,
333,
311,
288,
266,
244,
222,
200,
199,
177,
155,
133,
111,
88,
66,
... | 44 |
'''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 xo... | 44 | 1 |
'''simple docstring'''
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMi... | 44 |
'''simple docstring'''
import hashlib
import unittest
from transformers import MODEL_FOR_DEPTH_ESTIMATION_MAPPING, is_torch_available, is_vision_available
from transformers.pipelines import DepthEstimationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,... | 44 | 1 |
'''simple docstring'''
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class _lowercase ( __a ):
_UpperCAmelCase = '''M-CLIP'''
def __init__( self , A__=10_24 , A__=7_68 , **A__ ... | 44 |
'''simple docstring'''
import argparse
import torch
from torch import nn
from transformers import SpeechaTextConfig, SpeechaTextForConditionalGeneration
def __UpperCamelCase ( a : Optional[int] ) ->Dict:
snake_case = [
'''encoder.version''',
'''decoder.v... | 44 | 1 |
'''simple docstring'''
# using dfs for finding eulerian path traversal
def __UpperCamelCase ( a : Tuple , a : str , a : Any , a : int=None ) ->Any:
snake_case = (path or []) + [u]
for v in graph[u]:
if visited_edge[u][v] is False:
snake_... | 44 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _lowercase ( metaclass=__a ):
_UpperCAmelCase = ['''transformers''', '''torch''', '''note_seq''']
def __init__( self , *A__ , **A__ ) -> Union... | 44 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
class _lowercase :
def __init__( self , A__ ) -> None:
snake_case = value
snake_case = None
snake_case = None
cla... | 44 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
class _lowercase :
def __init__( self , A__ ) -> None:
snake_case = value
snake_case = None
snake_case = None
cla... | 44 | 1 |
'''simple docstring'''
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
_lowercase = logging.get_logger(__name__)
def __UpperCamelCase ( a : Lis... | 44 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVi... | 44 | 1 |
'''simple docstring'''
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class _lowercase ( __a ):
_UpperCAmelCase = ['''image_processor''', '''tokenizer''']
_UpperCAmelCase ... | 44 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassificatio... | 44 | 1 |
'''simple docstring'''
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
_lowercase = input('Enter image url: ').strip()
print(f'Downloading image from {url} ...')
_lowercase = BeautifulSoup(re... | 44 |
'''simple docstring'''
import argparse
import json
import logging
import os
import sys
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, get_gpu_count, slow
_lowercase = [
os.path.join(os.path.dirname(__file__), dirname)
... | 44 | 1 |
'''simple docstring'''
_lowercase = {
'Pillow': 'Pillow',
'accelerate': 'accelerate>=0.11.0',
'compel': 'compel==0.1.8',
'black': 'black~=23.1',
'datasets': 'datasets',
'filelock': 'filelock',
'flax': 'flax>=0.4.1',
'hf-doc-builder': 'hf-d... | 44 |
'''simple docstring'''
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairs... | 44 | 1 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVi... | 44 |
'''simple docstring'''
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .... | 44 | 1 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, NystromformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mod... | 44 |
'''simple docstring'''
_lowercase = {
'Pillow': 'Pillow',
'accelerate': 'accelerate>=0.11.0',
'compel': 'compel==0.1.8',
'black': 'black~=23.1',
'datasets': 'datasets',
'filelock': 'filelock',
'flax': 'flax>=0.4.1',
'hf-doc-builder': 'hf-d... | 44 | 1 |
'''simple docstring'''
import os
# Precomputes a list of the 100 first triangular numbers
_lowercase = [int(0.5 * n * (n + 1)) for n in range(1, 101)]
def __UpperCamelCase ( ) ->Any:
snake_case = os.path.dirname(os.path.realpath(a ) )
snake_case = ... | 44 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, to... | 44 | 1 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
impo... | 44 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
_lowercase ... | 44 | 1 |
'''simple docstring'''
from __future__ import annotations
def __UpperCamelCase ( a : list[int] , a : list[int] , a : list[int] , a : list[list[str]] , a : int , ) ->None:
snake_case = len(a )
# If row is equal to the size of th... | 44 |
'''simple docstring'''
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class _lowercase ( yaml.SafeLoader ):
def UpperCamelCase ( self , A__ ) -> List[str]:
snake_case =... | 44 | 1 |
'''simple docstring'''
def __UpperCamelCase ( a : Union[str, Any] , a : Any ) ->Optional[Any]:
snake_case = ''''''
for i in table:
res += inp[i - 1]
return res
def __UpperCamelCase ( a : str ) ->Tuple:
return data[1:] + data[0]
def __Upper... | 44 |
'''simple docstring'''
import json
import os
import re
import unittest
from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from... | 44 | 1 |
'''simple docstring'''
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def __UpperCamelCase ( *a : List[str] , a : Optional[Union[Dict, Any]] = None , a : Union[str, Any]=True , a : Dict=2 ... | 44 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
... | 44 | 1 |
'''simple docstring'''
_lowercase = '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transform... | 44 |
'''simple docstring'''
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
fro... | 44 | 1 |
'''simple docstring'''
_lowercase = {
"joule": 1.0,
"kilojoule": 1_000,
"megajoule": 1_000_000,
"gigajoule": 1_000_000_000,
"wattsecond": 1.0,
"watthour": 3_600,
"kilowatthour": 3_600_000,
"newtonmeter": 1.0,
"calorie_nutr": 4_186.8,
... | 44 |
'''simple docstring'''
def __UpperCamelCase ( a : int , a : int ) ->int:
while b:
snake_case , snake_case = b, a % b
return a
def __UpperCamelCase ( a : int , a : int ) ->int:
return a if b == 0 else euclidean_gcd_recursive(a , ... | 44 | 1 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
... | 44 |
'''simple docstring'''
import argparse
import copy
def __UpperCamelCase ( a : Union[str, Any] ) ->Tuple:
snake_case = {}
with open(a ) as f:
for line in f:
if line.split()[0] not in dict_of_neighbours:
snake_case = []
_list.append([line.split... | 44 | 1 |
'''simple docstring'''
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 ... | 44 |
'''simple docstring'''
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
exc... | 44 | 1 |
'''simple docstring'''
import math
def __UpperCamelCase ( a : int ) ->int:
if not isinstance(a , a ):
snake_case = f"""Input value of [number={number}] must be an integer"""
raise TypeError(a )
if number < 1:
snake_case = f"""Input value o... | 44 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
class _lowercase ( __a ):
_UpperCAmelCase = '''WhisperFeatureExtractor'''
_UpperCAmelCase = '''WhisperTokenizer'''
def __init__( self , A__ ... | 44 | 1 |
'''simple docstring'''
import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, ... | 44 |
'''simple docstring'''
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class _... | 44 | 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_... | 44 |
'''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 xo... | 44 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinvaConfig, SwinvaForImageClassification
def ... | 44 |
'''simple docstring'''
import hashlib
import unittest
from transformers import MODEL_FOR_DEPTH_ESTIMATION_MAPPING, is_torch_available, is_vision_available
from transformers.pipelines import DepthEstimationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,... | 44 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
'configuration_timesformer': ['TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TimesformerConfig'],
}
try:
... | 44 |
'''simple docstring'''
import argparse
import torch
from torch import nn
from transformers import SpeechaTextConfig, SpeechaTextForConditionalGeneration
def __UpperCamelCase ( a : Optional[int] ) ->Dict:
snake_case = [
'''encoder.version''',
'''decoder.v... | 44 | 1 |
'''simple docstring'''
from __future__ import annotations
from scipy.special import comb # type: ignore
class _lowercase :
def __init__( self , A__ ) -> List[Any]:
snake_case = list_of_points
# Degree determines the flexibility of th... | 44 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _lowercase ( metaclass=__a ):
_UpperCAmelCase = ['''transformers''', '''torch''', '''note_seq''']
def __init__( self , *A__ , **A__ ) -> Union... | 44 | 1 |
'''simple docstring'''
def __UpperCamelCase ( a : str , a : str ) ->bool:
snake_case = len(a ) + 1
snake_case = len(a ) + 1
# dp is a 2d matrix where dp[i][j] denotes whether prefix string of
# length i of input_string matches with prefix string ... | 44 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
class _lowercase :
def __init__( self , A__ ) -> None:
snake_case = value
snake_case = None
snake_case = None
cla... | 44 | 1 |
'''simple docstring'''
import argparse
import datetime
import json
import time
import warnings
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
f... | 44 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVi... | 44 | 1 |
'''simple docstring'''
import warnings
from contextlib import contextmanager
from ....processing_utils import ProcessorMixin
class _lowercase ( __a ):
_UpperCAmelCase = '''MCTCTFeatureExtractor'''
_UpperCAmelCase = '''AutoTokenizer'... | 44 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassificatio... | 44 | 1 |
'''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_tens... | 44 |
'''simple docstring'''
import argparse
import json
import logging
import os
import sys
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, get_gpu_count, slow
_lowercase = [
os.path.join(os.path.dirname(__file__), dirname)
... | 44 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_lowercase = {
'configuration_transfo_xl': ['TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TransfoXLConfig'],
... | 44 |
'''simple docstring'''
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairs... | 44 | 1 |
'''simple docstring'''
def __UpperCamelCase ( a : int ) ->bool:
snake_case = (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def __UpperCamelCase ( a : int = 5000 ) ->int:
snake_case = [(i * (3 * i - 1)) // 2 for i in range(1 , a )]
for ... | 44 |
'''simple docstring'''
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .... | 44 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
_lowercase = {'configuration_fnet': ['FNET_PRE... | 44 |
'''simple docstring'''
_lowercase = {
'Pillow': 'Pillow',
'accelerate': 'accelerate>=0.11.0',
'compel': 'compel==0.1.8',
'black': 'black~=23.1',
'datasets': 'datasets',
'filelock': 'filelock',
'flax': 'flax>=0.4.1',
'hf-doc-builder': 'hf-d... | 44 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
'EleutherAI/gpt-neox-20b': 'https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/co... | 44 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, to... | 44 | 1 |
'''simple docstring'''
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
_lowercase ... | 44 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
_lowercase ... | 44 | 1 |
'''simple docstring'''
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
_lowercase = '\\n@misc{wu2016googles,\n title={Google\'s Neural Machine Translation System: Bridging the Gap between Human ... | 44 |
'''simple docstring'''
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class _lowercase ( yaml.SafeLoader ):
def UpperCamelCase ( self , A__ ) -> List[str]:
snake_case =... | 44 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowercase = {
'configuration_mobilebert': [
... | 44 |
'''simple docstring'''
import json
import os
import re
import unittest
from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from... | 44 | 1 |
'''simple docstring'''
import argparse
import os
import re
_lowercase = 'src/transformers'
# Pattern that looks at the indentation in a line.
_lowercase = re.compile(R'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
_lowercase ... | 44 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
... | 44 | 1 |
'''simple docstring'''
import math
from datetime import datetime, timedelta
def __UpperCamelCase ( a : int ) ->datetime:
snake_case = year % 19
snake_case = year % 4
snake_case = year % 7
snake_case = math.floor(year / 100 )
snake_case = ma... | 44 |
'''simple docstring'''
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
fro... | 44 | 1 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
_lowe... | 44 |
'''simple docstring'''
def __UpperCamelCase ( a : int , a : int ) ->int:
while b:
snake_case , snake_case = b, a % b
return a
def __UpperCamelCase ( a : int , a : int ) ->int:
return a if b == 0 else euclidean_gcd_recursive(a , ... | 44 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcess... | 44 |
'''simple docstring'''
import argparse
import copy
def __UpperCamelCase ( a : Union[str, Any] ) ->Tuple:
snake_case = {}
with open(a ) as f:
for line in f:
if line.split()[0] not in dict_of_neighbours:
snake_case = []
_list.append([line.split... | 44 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
'studio-ousia/luke-base': 'https://huggingface.co/studio-ousia/luke-base/resolve/main/conf... | 44 |
'''simple docstring'''
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
exc... | 44 | 1 |
'''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
_lowercase = False
cla... | 44 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
class _lowercase ( __a ):
_UpperCAmelCase = '''WhisperFeatureExtractor'''
_UpperCAmelCase = '''WhisperTokenizer'''
def __init__( self , A__ ... | 44 | 1 |
'''simple docstring'''
def __UpperCamelCase ( a : int ) ->"list[int]":
if upper_limit < 0:
raise ValueError('''Limit for the Catalan sequence must be ≥ 0''' )
snake_case = [0] * (upper_limit + 1)
# Base case: C(0) = C(1) = 1
snake_case = 1
if upper_lim... | 44 |
'''simple docstring'''
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class _... | 44 | 1 |
'''simple docstring'''
def __UpperCamelCase ( a : Tuple , a : str , a : List[Any]=False ) ->List[Any]:
if isinstance(a , a ) and isinstance(a , a ):
snake_case = len(set_a.intersection(a ) )
if alternative_union:
sna... | 44 |
'''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 xo... | 44 | 1 |
'''simple docstring'''
class _lowercase :
def __init__( self , A__ , A__ , A__ ) -> int:
snake_case = name
snake_case = value
snake_case = weight
def __repr__( self ) -> str:
return... | 44 |
'''simple docstring'''
import hashlib
import unittest
from transformers import MODEL_FOR_DEPTH_ESTIMATION_MAPPING, is_torch_available, is_vision_available
from transformers.pipelines import DepthEstimationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,... | 44 | 1 |
'''simple docstring'''
import os
import socket
from contextlib import contextmanager
import torch
from ..commands.config.default import write_basic_config # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_avail... | 44 |
'''simple docstring'''
import argparse
import torch
from torch import nn
from transformers import SpeechaTextConfig, SpeechaTextForConditionalGeneration
def __UpperCamelCase ( a : Optional[int] ) ->Dict:
snake_case = [
'''encoder.version''',
'''decoder.v... | 44 | 1 |
'''simple docstring'''
import hashlib
import unittest
from typing import Dict
import numpy as np
from transformers import (
MODEL_FOR_MASK_GENERATION_MAPPING,
TF_MODEL_FOR_MASK_GENERATION_MAPPING,
is_vision_available,
pipeline,
)
from transformers.pipelines impor... | 44 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _lowercase ( metaclass=__a ):
_UpperCAmelCase = ['''transformers''', '''torch''', '''note_seq''']
def __init__( self , *A__ , **A__ ) -> Union... | 44 | 1 |
'''simple docstring'''
import math
def __UpperCamelCase ( a : float , a : float ) ->float:
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''' )
# handling of negative values of initial intensity
if angle < 0 or angl... | 44 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
class _lowercase :
def __init__( self , A__ ) -> None:
snake_case = value
snake_case = None
snake_case = None
cla... | 44 | 1 |
'''simple docstring'''
def __UpperCamelCase ( a : int = 1000 ) ->int:
snake_case = 2**power
snake_case = str(a )
snake_case = list(a )
snake_case = 0
for i in list_num:
sum_of_num += int(a )
return sum_of_num
if __name__ == "__... | 44 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVi... | 44 | 1 |
'''simple docstring'''
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class _lowercase ( yaml.SafeLoader ):
def UpperCamelCase ( self , A__ ) -> List[str]:
snake_case =... | 44 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassificatio... | 44 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
'microsoft/trocr-base-handwritten': (
'https://huggingface.co/microsoft/trocr-bas... | 44 |
'''simple docstring'''
import argparse
import json
import logging
import os
import sys
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, get_gpu_count, slow
_lowercase = [
os.path.join(os.path.dirname(__file__), dirname)
... | 44 | 1 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_... | 44 |
'''simple docstring'''
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairs... | 44 | 1 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
... | 44 |
'''simple docstring'''
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .... | 44 | 1 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=__a )
class _lowercase ( __a ):
_UpperCAmelCase ... | 44 |
'''simple docstring'''
_lowercase = {
'Pillow': 'Pillow',
'accelerate': 'accelerate>=0.11.0',
'compel': 'compel==0.1.8',
'black': 'black~=23.1',
'datasets': 'datasets',
'filelock': 'filelock',
'flax': 'flax>=0.4.1',
'hf-doc-builder': 'hf-d... | 44 | 1 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def __UpperCamelCase ( a : List[Any] , a : str , a : Optional[Any]=None , **a : int ) ->Any:
snake_case = [x.strip() for x in open(a ).readlines()]
snake_cas... | 44 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, to... | 44 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
'vinvino02/glpn-kitti': 'https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.j... | 44 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
_lowercase ... | 44 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
'tanreinama/GPTSAN-2.8B-spout_is_uniform': (
'https://huggingface.co/tanreinama/G... | 44 |
'''simple docstring'''
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class _lowercase ( yaml.SafeLoader ):
def UpperCamelCase ( self , A__ ) -> List[str]:
snake_case =... | 44 | 1 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils... | 44 |
'''simple docstring'''
import json
import os
import re
import unittest
from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from... | 44 | 1 |
'''simple docstring'''
import json
import os
from collections import Counter
import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset
_lowercase = {1: (1, 1), 2: (2,... | 44 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
... | 44 | 1 |
'''simple docstring'''
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_s... | 44 |
'''simple docstring'''
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
fro... | 44 | 1 |
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