code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class _snake_case ( pl.LightningModule ):
def __init__( self , _SCREAMING_SNAKE_CASE ):
'''simple d... | 284 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ : str ={
'configuration_clipseg': [
'CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP',
'CLIPSegConfig',
'CLIPSegTextConfig',
'... | 101 | 0 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.ut... | 539 |
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_FILENAM... | 101 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from... | 71 |
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from tr... | 101 | 0 |
import re
def UpperCamelCase_( _A :List[str] )-> Optional[int]:
return [char.split() for char in re.split(r"[^ a-z A-Z 0-9 \s]" , str_ )]
def UpperCamelCase_( _A :Any )-> str:
UpperCamelCase__ = split_input(str_ )
return "".join(
["".join([char.capitalize() fo... | 551 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ : Union[str, Any] ={
'configuration_blip_2': [
'BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Blip2Config',
'Blip2QFormerConfig',
... | 101 | 0 |
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def __magic_name__ ( SCREAMING_SNAKE_CASE ) -> int:
_lowercase : Any = [
'encoder.version',
'decoder.version',
'... | 66 |
from ...processing_utils import ProcessorMixin
class __lowercase (__SCREAMING_SNAKE_CASE ):
"""simple docstring"""
_UpperCAmelCase = """WhisperFeatureExtractor"""
_UpperCAmelCase = """WhisperTokenizer"""
de... | 101 | 0 |
"""simple docstring"""
import argparse
import requests
import torch
from PIL import Image
from transformers import ViTMAEConfig, ViTMAEForPreTraining, ViTMAEImageProcessor
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
if "cls_token" in name:
... | 673 |
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pegasus,
biogpt,
bit,
b... | 101 | 0 |
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
from .prior_transformer import Pr... | 537 |
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowercase (__SCREAMING_SNAKE_CASE ):
... | 101 | 0 |
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImageClassification
if is_vision_available():
from transform... | 339 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | 101 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import _LazyModule
__lowerCamelCase :Dict = {'processing_wav2vec2_with_lm': ['Wav2Vec2ProcessorWithLM']}
if TYPE_CHECKING:
from .processing_wavaveca_with_lm import WavaVecaProcessorWithLM
else:
import sys
__lowerCa... | 222 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
lowerCAmelCase__ : Optional[int] ='%20'.join(argv[1:]) if len(argv) > 1 else quote(str(input('S... | 101 | 0 |
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class __A ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowerCAmelCase_ = """Speech2TextFeatureExtractor"""
lowerCAmelCase_ = """Speech2TextTokenizer"""
... | 481 |
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 ... | 101 | 0 |
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_tokenization_common import Toke... | 193 |
def a__ ( A__, A__ ):
SCREAMING_SNAKE_CASE_ : Optional[Any] = ''
for i in table:
res += inp[i - 1]
return res
def a__ ( A__ ):
return data[1:] + data[0]
def a__ ( A__, A__ ):
SCREAMING_SNAKE_CASE_... | 101 | 0 |
'''simple docstring'''
def snake_case ( snake_case : Any , snake_case : List[Any] ) -> Union[str, Any]:
"""simple docstring"""
lowerCAmelCase = len(A__ )
print('The following activities are selected:' )
# The first activity is always selected
lower... | 284 |
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_available, is_... | 101 | 0 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'microsoft/git-base': 'https://huggingface.co/microsoft/... | 539 |
from __future__ import annotations
def a__ ( A__, A__ = None, A__ = None ):
if start is None:
SCREAMING_SNAKE_CASE_ : List[str] = 0
if end is None:
SCREAMING_SNAKE_CASE_ : Optional[Any] = len(A__ ) - 1
if start >= end:... | 101 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class _snake_case (__SCREAMING_SNAKE_CAS... | 71 |
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vision_available
... | 101 | 0 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDConditionModel,
)
from diffusers.utils import nightly, slow, t... | 551 |
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from pathlib import ... | 101 | 0 |
from typing import List, Optional, Tuple, Union
import torch
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowerCAmelCase_ ( __SCREAMING_SNAKE_CASE ):
def __init__( self , _lowerCAmelCas... | 66 |
def a__ ( A__ = 5_0_0_0_0_0_0_0 ):
SCREAMING_SNAKE_CASE_ : Union[str, Any] = set()
SCREAMING_SNAKE_CASE_ : Optional[int] = int((limit - 2_4) ** (1 / 2) )
SCREAMING_SNAKE_CASE_ : Dict = set(range(3, prime_square_limit + 1, 2 ) )
... | 101 | 0 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import TransformeraDModel, VQDiffusionPipeline, VQDiffusionScheduler, VQModel
from diffusers.pipelines.vq_diffusion.pipeline_vq_diffusion ... | 673 |
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def a__ ( A__ ):
SCREAMING_SNAKE_CASE_ : Any = [
'encoder.version',
'decoder.version',
'model.encoder.version',
... | 101 | 0 |
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import Toke... | 537 |
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
lowerCAmelCase__ : Optional[int] =0B1011_0011_1110_1100_1001_0000_0111_... | 101 | 0 |
import requests
a_ = 'https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey='
def _a ( UpperCamelCase_ : Optional[int] ) -> List[str]:
"""simple docstring"""
lowerCAmelCase__ = requests.get(_NEWS_API + bbc_news_api_key ).json()
# each art... | 339 |
def a__ ( A__, A__ ):
def get_matched_characters(A__, A__ ) -> str:
SCREAMING_SNAKE_CASE_ : Dict = []
SCREAMING_SNAKE_CASE_ : Any = min(len(_stra ), len(_stra ) ) // 2
for i, l in enumerate(_stra ):
SCREAMIN... | 101 | 0 |
"""simple docstring"""
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn ... | 222 |
from __future__ import annotations
lowerCAmelCase__ : Union[str, Any] =[
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def a__ ( A__, A__, A__, A__, A__, ):
SCREAMING_SNAKE_CASE_ : List[Any] = ... | 101 | 0 |
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from pathlib import Path
from urll... | 481 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ : Tuple =logging.get_logger(__name__)
lowerCAmelCase__ : Optional[int] ={
'microsoft/git-base': 'https://huggingface.co/mi... | 101 | 0 |
from math import sqrt
def UpperCAmelCase_ ( snake_case__ ) -> int:
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples ... | 193 |
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common impo... | 101 | 0 |
'''simple docstring'''
def snake_case ( snake_case : Dict = 50000000 ) -> Any:
"""simple docstring"""
lowerCAmelCase = set()
lowerCAmelCase = int((limit - 24) ** (1 / 2) )
lowerCAmelCase = set(range(3 , prime_square_limit + 1 , 2 ... | 284 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ : str ={
'configuration_clipseg': [
'CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP',
'CLIPSegConfig',
'CLIPSegTextConfig',
'... | 101 | 0 |
'''simple docstring'''
import gc
import inspect
import unittest
import torch
from parameterized import parameterized
from diffusers import PriorTransformer
from diffusers.utils import floats_tensor, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_deter... | 539 |
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_FILENAM... | 101 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCamelCase = {
'configuration_time_series_transformer': [
'TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'TimeSeri... | 71 |
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from tr... | 101 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_image, load_numpy, slow, tor... | 551 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ : Union[str, Any] ={
'configuration_blip_2': [
'BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Blip2Config',
'Blip2QFormerConfig',
... | 101 | 0 |
def __magic_name__ ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> Any:
return price * (1 + tax_rate)
if __name__ == "__main__":
print(f'''{price_plus_tax(100, 0.25) = }''')
print(f'''{price_plus_tax(125.50, 0.05) = }''')
| 66 |
from ...processing_utils import ProcessorMixin
class __lowercase (__SCREAMING_SNAKE_CASE ):
"""simple docstring"""
_UpperCAmelCase = """WhisperFeatureExtractor"""
_UpperCAmelCase = """WhisperTokenizer"""
de... | 101 | 0 |
"""simple docstring"""
import importlib
import inspect
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
lowerCAmelCase_ : str = 'src/transformers'
# This is to make... | 673 |
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pegasus,
biogpt,
bit,
b... | 101 | 0 |
import numpy as np
def lowercase( UpperCamelCase_ , UpperCamelCase_ ) -> List[Any]:
'''simple docstring'''
return np.where(vector > 0 , A__ , (alpha * (np.exp(A__ ) - 1)) )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 537 |
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowercase (__SCREAMING_SNAKE_CASE ):
... | 101 | 0 |
def _a ( UpperCamelCase_ : Optional[int] , UpperCamelCase_ : Optional[Any] ) -> Tuple:
"""simple docstring"""
def get_matched_characters(UpperCamelCase_ : Optional[Any] , UpperCamelCase_ : Optional[int] ) -> str:
lowerCAmelC... | 339 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | 101 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
... | 222 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
lowerCAmelCase__ : Optional[int] ='%20'.join(argv[1:]) if len(argv) > 1 else quote(str(input('S... | 101 | 0 |
from __future__ import annotations
import sys
from collections import deque
from typing import Generic, TypeVar
_a = TypeVar("T")
class __A ( Generic[T] ):
'''simple docstring'''
lowerCAmelCase_ = 42 # Cache store of keys
lowerCAmelCase_ = 42 # Referen... | 481 |
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 ... | 101 | 0 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGE... | 193 |
def a__ ( A__, A__ ):
SCREAMING_SNAKE_CASE_ : Optional[Any] = ''
for i in table:
res += inp[i - 1]
return res
def a__ ( A__ ):
return data[1:] + data[0]
def a__ ( A__, A__ ):
SCREAMING_SNAKE_CASE_... | 101 | 0 |
'''simple docstring'''
import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision... | 284 |
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_available, is_... | 101 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCAmelCase_ = {
'configuration_swiftformer': [
'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SwiftForm... | 539 |
from __future__ import annotations
def a__ ( A__, A__ = None, A__ = None ):
if start is None:
SCREAMING_SNAKE_CASE_ : List[str] = 0
if end is None:
SCREAMING_SNAKE_CASE_ : Optional[Any] = len(A__ ) - 1
if start >= end:... | 101 | 0 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
... | 71 |
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vision_available
... | 101 | 0 |
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase = logging.get_logger(__name__)
__UpperCamelCase = {
'kakaobrain/align-base': 'https://hu... | 551 |
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from pathlib import ... | 101 | 0 |
def __magic_name__ ( SCREAMING_SNAKE_CASE = 600_851_475_143 ) -> Any:
try:
_lowercase : Optional[int] = int(A__ )
except (TypeError, ValueError):
raise TypeError('Parameter n must be int or castable to int.' )
if n <= 0:
... | 66 |
def a__ ( A__ = 5_0_0_0_0_0_0_0 ):
SCREAMING_SNAKE_CASE_ : Union[str, Any] = set()
SCREAMING_SNAKE_CASE_ : Optional[int] = int((limit - 2_4) ** (1 / 2) )
SCREAMING_SNAKE_CASE_ : Dict = set(range(3, prime_square_limit + 1, 2 ) )
... | 101 | 0 |
"""simple docstring"""
from __future__ import annotations
def _lowerCAmelCase ( lowerCAmelCase , lowerCAmelCase = None ):
'''simple docstring'''
UpperCAmelCase = word_bank or []
# create a table
UpperCAmelCase = len(... | 673 |
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def a__ ( A__ ):
SCREAMING_SNAKE_CASE_ : Any = [
'encoder.version',
'decoder.version',
'model.encoder.version',
... | 101 | 0 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
_SCREAMING_SNAKE_CASE = pytest.mark.integration
@pytest.mark.parametrize("""path""" , ["""paw... | 537 |
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
lowerCAmelCase__ : Optional[int] =0B1011_0011_1110_1100_1001_0000_0111_... | 101 | 0 |
import copy
from collections import OrderedDict
from typing import Dict, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
a_ = logging.get_logger(__name__)
a_ = ... | 339 |
def a__ ( A__, A__ ):
def get_matched_characters(A__, A__ ) -> str:
SCREAMING_SNAKE_CASE_ : Dict = []
SCREAMING_SNAKE_CASE_ : Any = min(len(_stra ), len(_stra ) ) // 2
for i, l in enumerate(_stra ):
SCREAMIN... | 101 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
__lowerCamelCase :str = list[list[float | int]]
def snake_case ( UpperCamelCase__ : List[Any] , UpperCamelCase__ : Optional[Any] ) -> Dict:
lowerCamelCase ... | 222 |
from __future__ import annotations
lowerCAmelCase__ : Union[str, Any] =[
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def a__ ( A__, A__, A__, A__, A__, ):
SCREAMING_SNAKE_CASE_ : List[Any] = ... | 101 | 0 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_a = logging.get_logger(__name__)
_a = {
'Visual-Attention-Network/van-base': (
'https://huggingface.co/Visual-Attention-Network/van-base/blob/main/config.json'
),
}
class __A ( _... | 481 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ : Tuple =logging.get_logger(__name__)
lowerCAmelCase__ : Optional[int] ={
'microsoft/git-base': 'https://huggingface.co/mi... | 101 | 0 |
def UpperCAmelCase_ ( snake_case__ , snake_case__ ) -> List[str]:
"""simple docstring"""
if density <= 0:
raise ValueError('Impossible fluid density' )
if bulk_modulus <= 0:
raise ValueError('Impossible bulk modulus' )
return (bulk_modulus / den... | 193 |
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common impo... | 101 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase : Any = {
'configuration_jukebox': [
'JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP',
'JukeboxConfig',
'JukeboxPr... | 284 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ : str ={
'configuration_clipseg': [
'CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP',
'CLIPSegConfig',
'CLIPSegTextConfig',
'... | 101 | 0 |
'''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def SCREAMING_SNAKE_CASE ( a_ : Any ):
__a = FileLock(str(tmpdir / 'foo.lock' ) )
__a = FileLock(str(tmpdir / 'fo... | 539 |
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_FILENAM... | 101 | 0 |
'''simple docstring'''
import os
def a__ ( ) -> Union[str, Any]:
"""simple docstring"""
UpperCAmelCase_ : List[str] = os.path.dirname(os.path.realpath(A__ ) )
UpperCAmelCase_ : int = os.path.join(A__ , "triangle.txt" )
with op... | 71 |
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from tr... | 101 | 0 |
from __future__ import annotations
class lowerCamelCase__ :
"""simple docstring"""
def __init__( self , snake_case , snake_case ):
'''simple docstring'''
UpperCamelCase__ = text, pattern
UpperCamelCase__ = len(lowerCAmelC... | 551 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ : Union[str, Any] ={
'configuration_blip_2': [
'BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Blip2Config',
'Blip2QFormerConfig',
... | 101 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
# See all ViT MSN models at https://hugg... | 66 |
from ...processing_utils import ProcessorMixin
class __lowercase (__SCREAMING_SNAKE_CASE ):
"""simple docstring"""
_UpperCAmelCase = """WhisperFeatureExtractor"""
_UpperCAmelCase = """WhisperTokenizer"""
de... | 101 | 0 |
"""simple docstring"""
import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@require_torch
class UpperCamelC... | 673 |
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pegasus,
biogpt,
bit,
b... | 101 | 0 |
def lowercase( UpperCamelCase_ , UpperCamelCase_ ) -> List[str]:
'''simple docstring'''
if a < 0 or b < 0:
raise ValueError("""the value of both inputs must be positive""" )
UpperCamelCase = str(bin(A__ ) )[2:] # remove the leading "0b"
UpperCamelCase = ... | 537 |
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowercase (__SCREAMING_SNAKE_CASE ):
... | 101 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a_ = {
'configuration_rag': ['RagConfig'],
'retrieval_rag': ['RagRetriever'],
'tokenization_rag': ['RagTokenizer'],
}
try:
if not is_torch_available():
... | 339 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | 101 | 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_tenso... | 222 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
lowerCAmelCase__ : Optional[int] ='%20'.join(argv[1:]) if len(argv) > 1 else quote(str(input('S... | 101 | 0 |
from __future__ import annotations
def lowerCAmelCase__(__snake_case ,__snake_case ,__snake_case ,__snake_case ) -> Optional[Any]:
'''simple docstring'''
lowerCamelCase__ = []
lowerCamelCase__ = input_list[low:mid], input_list[mid : high + 1... | 481 |
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 ... | 101 | 0 |
from collections.abc import Callable
import numpy as np
def UpperCAmelCase_ ( snake_case__ , snake_case__ , snake_case__ , snake_case__ , snake_case__ ) -> int:
"""simple docstring"""
lowerCAmelCase__ = int(np.ceil((x_end - xa) / step_size ) )... | 193 |
def a__ ( A__, A__ ):
SCREAMING_SNAKE_CASE_ : Optional[Any] = ''
for i in table:
res += inp[i - 1]
return res
def a__ ( A__ ):
return data[1:] + data[0]
def a__ ( A__, A__ ):
SCREAMING_SNAKE_CASE_... | 101 | 0 |
'''simple docstring'''
import json
import os
from typing import Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_UpperCamelCase : Union[str, Any] = logging.get_logger(__name__)
_UpperCamelCase : List[str] ... | 284 |
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_available, is_... | 101 | 0 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
... | 539 |
from __future__ import annotations
def a__ ( A__, A__ = None, A__ = None ):
if start is None:
SCREAMING_SNAKE_CASE_ : List[str] = 0
if end is None:
SCREAMING_SNAKE_CASE_ : Optional[Any] = len(A__ ) - 1
if start >= end:... | 101 | 0 |
'''simple docstring'''
from typing import Dict
import numpy as np
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline, PipelineException
if is_tf_available():
import tensorflow as tf
from ..tf_u... | 71 |
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vision_available
... | 101 | 0 |
from __future__ import annotations
def UpperCamelCase_( _A :str , _A :List[str] , _A :List[str] , )-> Dict:
if (stress, tangential_force, area).count(0 ) != 1:
raise ValueError("You cannot supply more or less than 2 values" )
elif stress < 0:
raise ValueError("Stress cann... | 551 |
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from pathlib import ... | 101 | 0 |
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class lowerCAmelCase_ :
_UpperCamelCase : Dict = 42
_UpperCamelCa... | 66 |
def a__ ( A__ = 5_0_0_0_0_0_0_0 ):
SCREAMING_SNAKE_CASE_ : Union[str, Any] = set()
SCREAMING_SNAKE_CASE_ : Optional[int] = int((limit - 2_4) ** (1 / 2) )
SCREAMING_SNAKE_CASE_ : Dict = set(range(3, prime_square_limit + 1, 2 ) )
... | 101 | 0 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ : Union[str, Any] = logging.get_logger(__name__)
lowerCAmelCase_ : List[Any] = {
'BAAI/AltCLI... | 673 |
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def a__ ( A__ ):
SCREAMING_SNAKE_CASE_ : Any = [
'encoder.version',
'decoder.version',
'model.encoder.version',
... | 101 | 0 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class SCREAMING_SNAKE_CASE_ ( __SCREAMING_SNAKE_CASE ):
__lowerCAmelCase = ["""image_processor""", """tokenizer"""]
__lowerCAmelCase = """ViTImageProcessor"""
__... | 537 |
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
lowerCAmelCase__ : Optional[int] =0B1011_0011_1110_1100_1001_0000_0111_... | 101 | 0 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'microsoft/wavlm-base': 'https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json',
# See all WavLM models at https://hu... | 339 |
def a__ ( A__, A__ ):
def get_matched_characters(A__, A__ ) -> str:
SCREAMING_SNAKE_CASE_ : Dict = []
SCREAMING_SNAKE_CASE_ : Any = min(len(_stra ), len(_stra ) ) // 2
for i, l in enumerate(_stra ):
SCREAMIN... | 101 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
__lowerCamelCase :Union[str, Any] = {'tokenization_herbert': ['HerbertTokenizer']}
try:
if not is_tokenizers_available():
raise OptionalDepe... | 222 |
from __future__ import annotations
lowerCAmelCase__ : Union[str, Any] =[
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def a__ ( A__, A__, A__, A__, A__, ):
SCREAMING_SNAKE_CASE_ : List[Any] = ... | 101 | 0 |
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCAmelCase__(__snake_case ,__snake_case ,__snake_case ) -> List[Any]:
'''simple docstring'''
... | 481 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ : Tuple =logging.get_logger(__name__)
lowerCAmelCase__ : Optional[int] ={
'microsoft/git-base': 'https://huggingface.co/mi... | 101 | 0 |
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWatermarker
from diffusers.utils.tes... | 193 |
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common impo... | 101 | 0 |
'''simple docstring'''
def snake_case ( snake_case : Tuple ) -> Any:
"""simple docstring"""
return sum(i for i in range(1 , number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print("Program to check whether a number is a Perfect number or not..."... | 284 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ : str ={
'configuration_clipseg': [
'CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP',
'CLIPSegConfig',
'CLIPSegTextConfig',
'... | 101 | 0 |
'''simple docstring'''
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {'vocab_file': 'vocab.json'}
UpperCAmelCase_ ... | 539 |
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_FILENAM... | 101 | 0 |
'''simple docstring'''
from math import isqrt, loga
def a__ ( _SCREAMING_SNAKE_CASE : str ) -> List[str]:
"""simple docstring"""
UpperCAmelCase_ : List[str] = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_... | 71 |
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from tr... | 101 | 0 |
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
requ... | 551 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ : Union[str, Any] ={
'configuration_blip_2': [
'BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Blip2Config',
'Blip2QFormerConfig',
... | 101 | 0 |
import os
import unittest
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
BertTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils import r... | 66 |
from ...processing_utils import ProcessorMixin
class __lowercase (__SCREAMING_SNAKE_CASE ):
"""simple docstring"""
_UpperCAmelCase = """WhisperFeatureExtractor"""
_UpperCAmelCase = """WhisperTokenizer"""
de... | 101 | 0 |
"""simple docstring"""
import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import ... | 673 |
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pegasus,
biogpt,
bit,
b... | 101 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_fnet import FNet... | 537 |
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowercase (__SCREAMING_SNAKE_CASE ):
... | 101 | 0 |
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vision_available
... | 339 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | 101 | 0 |
"""simple docstring"""
from __future__ import annotations
def snake_case ( UpperCamelCase__ : Any , UpperCamelCase__ : Optional[int] ) -> Union[str, Any]:
lowerCamelCase : list[list[int]] = []
lowerCamelCase : list[int] = []
... | 222 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
lowerCAmelCase__ : Optional[int] ='%20'.join(argv[1:]) if len(argv) > 1 else quote(str(input('S... | 101 | 0 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_a ... | 481 |
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 ... | 101 | 0 |
import unittest
import numpy as np
from transformers import AlbertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.numpy as jnp
from transfor... | 193 |
def a__ ( A__, A__ ):
SCREAMING_SNAKE_CASE_ : Optional[Any] = ''
for i in table:
res += inp[i - 1]
return res
def a__ ( A__ ):
return data[1:] + data[0]
def a__ ( A__, A__ ):
SCREAMING_SNAKE_CASE_... | 101 | 0 |
'''simple docstring'''
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def snake_case ( ) -> List[Any]:
"""simple docstring"""
with offline(OfflineSim... | 284 |
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_available, is_... | 101 | 0 |
'''simple docstring'''
import inspect
import unittest
import numpy as np
from transformers import ViTConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTest... | 539 |
from __future__ import annotations
def a__ ( A__, A__ = None, A__ = None ):
if start is None:
SCREAMING_SNAKE_CASE_ : List[str] = 0
if end is None:
SCREAMING_SNAKE_CASE_ : Optional[Any] = len(A__ ) - 1
if start >= end:... | 101 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCamelCase = {
'configuration_clipseg': [
'CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP',
'CLIPSegConfig',
'CLIPSegTextCon... | 71 |
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vision_available
... | 101 | 0 |
"""simple docstring"""
import csv
from collections import defaultdict
from dataclasses import dataclass, field
from typing import List, Optional
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import ScalarFormatter
from transformers import HfArgumentParser
def ... | 102 |
"""simple docstring"""
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, ... | 102 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__magic_name__ : Any = logging.get_logger(__name__)
__magic_name__ ... | 102 |
"""simple docstring"""
import math
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
return math.pow(SCREAMING_SNAKE_CASE , 2 ) - a
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
return 2 * x
def UpperCamelC... | 102 | 1 |
"""simple docstring"""
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
while second != 0:
UpperCamelCase : List[str] = first & second
first ^= second
UpperCamelCase : Optional[int] = c << 1... | 102 |
"""simple docstring"""
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class lowercase__ ( __SCREAMING_SNAKE_CASE )... | 102 | 1 |
"""simple docstring"""
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from... | 102 |
"""simple docstring"""
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
Autoenco... | 102 | 1 |
"""simple docstring"""
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class lowercase__ :
"""simple docstring"""
pass
| 102 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
UpperCamelCase : Optional[int] = x
UpperCamelCase : str = ... | 102 | 1 |
"""simple docstring"""
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm i... | 102 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ : Dict = logging.get_logger(__name__)
__magic_name__ : List[str] = {
"""microsoft/swinv2-tiny-patch4-window8-256""": (
"""https... | 102 | 1 |
"""simple docstring"""
from typing import List, Optional
from tokenizers import ByteLevelBPETokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer
__magic_name__ : L... | 102 |
"""simple docstring"""
from bisect import bisect
from itertools import accumulate
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
UpperCamelCase : Dict = sorted(zip(SCREA... | 102 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
UpperCamelCase : int = list(SCREAMING_SNAKE_CASE )
U... | 102 |
"""simple docstring"""
import os
def UpperCamelCase ():
UpperCamelCase : Union[str, Any] = os.path.join(os.path.dirname(SCREAMING_SNAKE_CASE ) , """num.txt""" )
with open(SCREAMING_SNAKE_CASE ) as file_hand:
return str(sum(int(S... | 102 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import MutableSequence
class lowercase__ :
"""simple docstring"""
def __init__( self , _A , _A ):
'''simple docstring'''
... | 102 |
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
__magic_name__ : Dict = logging.getLogger(__name__)
@dataclass
c... | 102 | 1 |
"""simple docstring"""
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 ..... | 102 |
"""simple docstring"""
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
UpperCamelCase : int = 0
# if input_string is "aba" than new_input_string become "a|b|a"
UpperCamelCase : str = """"""
UpperCamelCase : Dict = """"""
... | 102 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
__magic_name__ : Tuple = """2020.9.26"""
__magic_name__ : Union[str, Any] = """xcodz-dot, cclaus, dhruvmanila"""
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SN... | 102 |
"""simple docstring"""
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
Musicgen... | 102 | 1 |
"""simple docstring"""
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import Schedule... | 102 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/license... | 102 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils im... | 102 |
"""simple docstring"""
import io
import json
import fsspec
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_incr... | 102 | 1 |
"""simple docstring"""
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
__magic_name__ : int = logging.get_logger(__name__) # pylint: disable=in... | 102 |
"""simple docstring"""
from math import ceil, sqrt
def UpperCamelCase (SCREAMING_SNAKE_CASE = 100_0000 ):
UpperCamelCase : int = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
Uppe... | 102 | 1 |
"""simple docstring"""
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
UpperCamelCase : List[Any] = """"""
for i in table:
res += inp[i - 1]
return res
def UpperCamelCase (SCREAMING_SNAKE_CASE ):... | 102 |
"""simple docstring"""
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
UpperCamelCase : List[Any] = """"""
for i in table:
res += inp[i - 1]
return res
def UpperCamelCase (SCREAMING_SNAKE_CASE ):... | 102 | 1 |
"""simple docstring"""
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import d... | 102 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__magic_name__ : Dict = {
"""conf... | 102 | 1 |
"""simple docstring"""
# HF Trainer benchmarking tool
#
# This tool can be used to run and compare multiple dimensions of the HF Trainers args.
#
# It then prints a report once in github format with all the information that needs to be shared
# with others and second time in a console-friendly for... | 102 |
"""simple docstring"""
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTes... | 102 | 1 |
"""simple docstring"""
import heapq
import sys
import numpy as np
__magic_name__ : Optional[int] = tuple[int, int]
class lowercase__ :
"""simple docstring"""
def __init__( self ):
'''simple docstring'''
... | 102 |
"""simple docstring"""
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils im... | 102 | 1 |
"""simple docstring"""
import math
import tensorflow as tf
from packaging import version
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
UpperCamelCase : int = tf.convert_to_tensor(SCREAMING_SNAKE_CASE )
UpperCamelCase : Any = 0.5 * (1.0 + tf.... | 102 |
"""simple docstring"""
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 102 | 1 |
"""simple docstring"""
import gc
import inspect
import unittest
import torch
from parameterized import parameterized
from diffusers import PriorTransformer
from diffusers.utils import floats_tensor, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_det... | 102 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...t... | 102 | 1 |
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