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 |
|---|---|---|---|---|
from typing import Any
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ,):
'''simple docstring'''
_validation(
lowerCAmelCase_ ,lowerCAmelCase_ ,lowerCAme... | 707 |
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__=None ):
'''simple docstring'''
lo... | 693 | 0 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
lowerCAmelCase : List[str] ={'vocab_file': 'voc... | 708 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Optional[int] ={
'configuration_autoformer': [
'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'... | 693 | 0 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _a ( lowerCAmelCase__ ):
_UpperCamelCase: List[Any] = "ClapFeatureExtractor"
_UpperCamelCase: List[Any] = ("RobertaToken... | 709 |
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
lowerCAmelCase : Optional[int]... | 693 | 0 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
HubertConfig,
HubertForCTC,
HubertModel,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
logging,
)
logging.set_v... | 710 |
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_torch_mu... | 693 | 0 |
# Algorithm for the pigeonhole sorting
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
lowerCAmelCase : Dict = min(SCREAMING_SNAKE_CASE__ ) # min() finds the minimum value
lowerCAmelCas... | 711 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : Optional[int] =logging.get_logger(__name__)
lowerCAmelCase : Optional[int] ={
'transfo-xl-wt103': 'https://huggingface.co/transfo-xl-wt103/resolve/main/config.json',
}... | 693 | 0 |
import qiskit
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
lowerCAmelCase : Any = qiskit.Aer.get_backend("""aer_simulator""" )
# Create a Quantum Circuit acting on the q regis... | 712 |
import torch
from diffusers import DiffusionPipeline
class _a ( snake_case_ ):
def __init__( self , lowercase_ , lowercase_ ) -> int:
super().__init__()
self.register_modules(unet=lowercase_ , scheduler=lowercase... | 693 | 0 |
lowerCAmelCase : List[str] =[
'Audio',
'Array2D',
'Array3D',
'Array4D',
'Array5D',
'ClassLabel',
'Features',
'Sequence',
'Value',
'Image',
'Translation',
'TranslationVariableLanguages',
]
from .audio import Audio
from .features impor... | 713 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def _UpperCAmelCase ( ):
'''simple docstring'''
with offline(O... | 693 | 0 |
from __future__ import annotations
import math
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
... | 714 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_in... | 693 | 0 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
if digit_amount > 0:
return round(number - int(lowerCamelCase__ ) ,lowerCamelCase__ )
return number - int(lowerCamelCase__ )
if __name__ ... | 715 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
lowerCAmelCase : Tuple = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return r... | 693 | 0 |
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : Any =logging.get_logger(__name__)
# TODO Update this
lowerCAmelCase : Optional[int] ={
'faceb... | 716 |
from math import factorial
class _a :
def __init__( self , lowercase_ , lowercase_ ) -> Optional[Any]:
lowerCAmelCase : Union[str, Any] = real
if isinstance(lowercase_ , lowercase_ ):
lower... | 693 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
StableDiffusionXLImgaImgPipel... | 717 |
from ..utils import DummyObject, requires_backends
class _a ( metaclass=snake_case_ ):
_UpperCamelCase: List[Any] = ["keras_nlp"]
def __init__( self , *lowercase_ , **lowercase_ ) -> Tuple:
requires_backends(self , ... | 693 | 0 |
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
AutoT... | 718 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('>=', '4.25.0')):
raise OptionalDependencyNotAvailable(... | 693 | 0 |
from typing import Dict, Iterable, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
IMAGENET_STA... | 719 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
if p < 2:
raise ValueError("""p should not be less than 2!""" )
elif p == 2:
return True
lowerCAmelCase : List[Any] = 4
lowerCAme... | 693 | 0 |
import math
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
lowerCAmelCase : List[Any] = 0
lowerCAmelCase : int = 0
while num > 0:
lowerCAmelCase : Dict = n... | 720 |
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import T... | 693 | 0 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
lowerCAmelCase : List[Any] ={"""tokenization_bertweet""": ["""BertweetTokenizer"""]}
if TYPE_CHECKING:
from .tokenization_bertweet import BertweetTokenizer
else:
import sys
lowerCAmelCase : Unio... | 721 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : Optional[int] =logging.get_logger(__name__)
lowerCAmelCase : List[Any] ={}
class _a ( snake_case_ ):
_UpperCamelCase: Tuple = "llama"
... | 693 | 0 |
'''simple docstring'''
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
lowerCAmelCase : Optional[int] =logging.get_logger(... | 700 |
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_indic... | 693 | 0 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
if n == 1 or not isinstance(_lowerCAmelCase ,_lowerCAmelCase ):
return 0
elif n == 2:
return 1
else:
lowerCAmelCase : Optional[int] ... | 701 |
lowerCAmelCase : str ={
'Pillow': 'Pillow<10.0.0',
'accelerate': 'accelerate>=0.20.3',
'av': 'av==9.2.0',
'beautifulsoup4': 'beautifulsoup4',
'black': 'black~=23.1',
'codecarbon': 'codecarbon==1.2.0',
'cookiecutter': 'cookiecutter==1.7.3',
'dataclasses': '... | 693 | 0 |
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokeni... | 702 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase : Union[str, Any] ={
'configuration_roformer': ['ROFO... | 693 | 0 |
import math
from numpy import inf
from scipy.integrate import quad
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
if num <= 0:
raise ValueError("""math domain error""" )
return quad(UpperCamelCase__ ,... | 703 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
return int(input_a == input_a == 0 )
def _UpperCAmelCase ( ):
'''simple docstring'''
print("""Truth Table of NOR Gat... | 693 | 0 |
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
lowerCAmelCase : List[str] =list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
lowerCAmelCase : List[Any] =[file... | 704 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCAmelCase : int ={
'configuration_poolformer': [
'POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'PoolFormerConfig',
... | 693 | 0 |
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
lowerCAmelCase : Optional[Any] ="http://www.m... | 705 |
import os
import string
import sys
lowerCAmelCase : Optional[int] =1 << 8
lowerCAmelCase : List[Any] ={
'tab': ord('\t'),
'newline': ord('\r'),
'esc': 27,
'up': 65 + ARROW_KEY_FLAG,
'down': 66 + ARROW_KEY_FLAG,
'right': 67 + ARROW_KEY_FLAG,... | 693 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCAmelCase : Tuple ={
'configuration_pix2struct': [
'PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Pix2StructConfig',
... | 706 |
# Imports
import numpy as np
class _a :
def __init__( self , lowercase_=None , lowercase_=None , lowercase_=None , lowercase_=None , lowercase_=None ) -> List[Any]:
self.set_matricies(red=lowercase_ , gree... | 693 | 0 |
import numpy as np
lowerCAmelCase : Optional[int] =[
["a", "b", "c", "d", "e"],
["f", "g", "h", "i", "k"],
["l", "m", "n", "o", "p"],
["q", "r", "s", "t", "u"],
["v", "w", "x", "y", "z"],
]
class _a :
def __init__( self ) -> ... | 707 |
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__=None ):
'''simple docstring'''
lo... | 693 | 0 |
'''simple docstring'''
import argparse
import json
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
VideoMAEConfig,
VideoMAEForPreTraining,
VideoMAEForVideoClassification,
VideoMAEImageProcessor,
)
... | 708 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Optional[int] ={
'configuration_autoformer': [
'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'... | 693 | 0 |
'''simple docstring'''
lowerCAmelCase : List[str] =[
(1_000, 'M'),
(900, 'CM'),
(500, 'D'),
(400, 'CD'),
(100, 'C'),
(90, 'XC'),
(50, 'L'),
(40, 'XL'),
(10, 'X'),
(9, 'IX'),
(5, 'V'),
(4, 'IV'),
(1, 'I'),
]
... | 709 |
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
lowerCAmelCase : Optional[int]... | 693 | 0 |
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMI... | 710 |
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_torch_mu... | 693 | 0 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
if not head:
return True
# split the list to two parts
lowerCAmelCase , lowerCAmelCase : Tuple = head.next, head
while fast and fast.next:
... | 711 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : Optional[int] =logging.get_logger(__name__)
lowerCAmelCase : Optional[int] ={
'transfo-xl-wt103': 'https://huggingface.co/transfo-xl-wt103/resolve/main/config.json',
}... | 693 | 0 |
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
lowerCAmelCase : Any =logging.get_logg... | 712 |
import torch
from diffusers import DiffusionPipeline
class _a ( snake_case_ ):
def __init__( self , lowercase_ , lowercase_ ) -> int:
super().__init__()
self.register_modules(unet=lowercase_ , scheduler=lowercase... | 693 | 0 |
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,
to_channel_dimensi... | 713 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def _UpperCAmelCase ( ):
'''simple docstring'''
with offline(O... | 693 | 0 |
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForMu... | 714 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_in... | 693 | 0 |
import requests
lowerCAmelCase : Optional[Any] ='https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey='
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
lowerCAmelCase : List[str] = re... | 715 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
lowerCAmelCase : Tuple = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return r... | 693 | 0 |
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
lowerCAmelCase : str =logging.get_logger(__name__)
class _a ( snake_case_ ):
def __init__( self , *lowercase_ , **lowercase_ )... | 716 |
from math import factorial
class _a :
def __init__( self , lowercase_ , lowercase_ ) -> Optional[Any]:
lowerCAmelCase : Union[str, Any] = real
if isinstance(lowercase_ , lowercase_ ):
lower... | 693 | 0 |
import os
import numpy
import onnx
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
lowerCAmelCase : int = a.name
lowerCAmelCase : Optional[Any] = b.name
lo... | 717 |
from ..utils import DummyObject, requires_backends
class _a ( metaclass=snake_case_ ):
_UpperCamelCase: List[Any] = ["keras_nlp"]
def __init__( self , *lowercase_ , **lowercase_ ) -> Tuple:
requires_backends(self , ... | 693 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
lowerCAmelCase : Dict ={"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.j... | 718 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('>=', '4.25.0')):
raise OptionalDependencyNotAvailable(... | 693 | 0 |
import collections
import importlib.util
import os
import re
from pathlib import Path
lowerCAmelCase : List[str] ='src/transformers'
# Matches is_xxx_available()
lowerCAmelCase : Optional[int] =re.compile(r'is\_([a-z_]*)_available()')
# Catches a one-line _impor... | 719 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
if p < 2:
raise ValueError("""p should not be less than 2!""" )
elif p == 2:
return True
lowerCAmelCase : List[Any] = 4
lowerCAme... | 693 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase : Any ={
"""configuration_mvp""": ["""MVP_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MvpConfig""", """MvpOnnxConfig"""],
"""to... | 720 |
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import T... | 693 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
lowerCAmelCase : Any ={
'albert-base-v1': 'https://huggingface.co/albert-base-v1/resolve/main/config.json',
'albert-large-v1': 'ht... | 721 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : Optional[int] =logging.get_logger(__name__)
lowerCAmelCase : List[Any] ={}
class _a ( snake_case_ ):
_UpperCamelCase: Tuple = "llama"
... | 693 | 0 |
'''simple docstring'''
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .fi... | 700 |
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_indic... | 693 | 0 |
import argparse
import torch
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_from_original_stable_diffusion_ckpt
if __name__ == "__main__":
lowerCAmelCase : str = argparse.ArgumentParser()
parser.add_argument(
'--checkpoint_path', default=N... | 701 |
lowerCAmelCase : str ={
'Pillow': 'Pillow<10.0.0',
'accelerate': 'accelerate>=0.20.3',
'av': 'av==9.2.0',
'beautifulsoup4': 'beautifulsoup4',
'black': 'black~=23.1',
'codecarbon': 'codecarbon==1.2.0',
'cookiecutter': 'cookiecutter==1.7.3',
'dataclasses': '... | 693 | 0 |
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
fr... | 702 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase : Union[str, Any] ={
'configuration_roformer': ['ROFO... | 693 | 0 |
from collections import defaultdict
from math import gcd
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ = 1_5_0_0_0_0_0 ):
'''simple docstring'''
lowerCAmelCase : defaultdict = defaultdict(SCREAMING_SNAKE_CASE__ )
lowerCAmelCase... | 703 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
return int(input_a == input_a == 0 )
def _UpperCAmelCase ( ):
'''simple docstring'''
print("""Truth Table of NOR Gat... | 693 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
lowerCAmelCase : int ={
'configuration_ernie': ['ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ErnieConfig', 'ErnieOnnxConfig'],
}
try:
if not is_tor... | 704 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCAmelCase : int ={
'configuration_poolformer': [
'POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'PoolFormerConfig',
... | 693 | 0 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ = 1_0_0_0_0_0_0 ):
'''simple docstring'''
lowerCAmelCase : Optional[Any] = limit + 1
lowerCAmelCase : Dict = [0] * limit
for first_term in range(1 ,SCREAMING_SNAKE_CASE__ ):
... | 705 |
import os
import string
import sys
lowerCAmelCase : Optional[int] =1 << 8
lowerCAmelCase : List[Any] ={
'tab': ord('\t'),
'newline': ord('\r'),
'esc': 27,
'up': 65 + ARROW_KEY_FLAG,
'down': 66 + ARROW_KEY_FLAG,
'right': 67 + ARROW_KEY_FLAG,... | 693 | 0 |
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_config... | 706 |
# Imports
import numpy as np
class _a :
def __init__( self , lowercase_=None , lowercase_=None , lowercase_=None , lowercase_=None , lowercase_=None ) -> List[Any]:
self.set_matricies(red=lowercase_ , gree... | 693 | 0 |
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class _a ( snake_case_ ):
def _snake_case ( self ) -> int:
return [
{"col_1": 3, "col_2": "a"},
{"co... | 707 |
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__=None ):
'''simple docstring'''
lo... | 693 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCAmelCase : int ={
'configuration_poolformer': [
'POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 708 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Optional[int] ={
'configuration_autoformer': [
'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'... | 693 | 0 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : Union[str, Any] =logging.get_logger(__name__)
lowerCAmelCase : Dict ={
'microsoft/wavlm-base': 'h... | 709 |
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
lowerCAmelCase : Optional[int]... | 693 | 0 |
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available, is_torch_available, is_vision_availa... | 710 |
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_torch_mu... | 693 | 0 |
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if version.p... | 711 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : Optional[int] =logging.get_logger(__name__)
lowerCAmelCase : Optional[int] ={
'transfo-xl-wt103': 'https://huggingface.co/transfo-xl-wt103/resolve/main/config.json',
}... | 693 | 0 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
lowerCAmelCase : Dict = current_set.copy()
for row_index, row in enumerate(SCREAMING_SNAKE_CASE__ ):
lowerCAmelCase : Union[str, Any] = row[0]... | 712 |
import torch
from diffusers import DiffusionPipeline
class _a ( snake_case_ ):
def __init__( self , lowercase_ , lowercase_ ) -> int:
super().__init__()
self.register_modules(unet=lowercase_ , scheduler=lowercase... | 693 | 0 |
import argparse
import json
import os
import torch
from torch import nn
from transformers import NllbMoeConfig, NllbMoeModel
from transformers.modeling_utils import dtype_byte_size
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
def _UpperCAmelCase ( SCREAM... | 713 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def _UpperCAmelCase ( ):
'''simple docstring'''
with offline(O... | 693 | 0 |
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
... | 714 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_in... | 693 | 0 |
from __future__ import annotations
import collections
import pprint
from pathlib import Path
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
return "".join(sorted(SCREAMING_SNAKE_CASE__ ) )
def _Upper... | 715 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
lowerCAmelCase : Tuple = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return r... | 693 | 0 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
if not all(x.isalpha() for x in string ):
raise ValueError("""String must only contain alphabetic characters.""" )
lowerCAmelCase : Dict = sorted(string... | 716 |
from math import factorial
class _a :
def __init__( self , lowercase_ , lowercase_ ) -> Optional[Any]:
lowerCAmelCase : Union[str, Any] = real
if isinstance(lowercase_ , lowercase_ ):
lower... | 693 | 0 |
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 im... | 717 |
from ..utils import DummyObject, requires_backends
class _a ( metaclass=snake_case_ ):
_UpperCamelCase: List[Any] = ["keras_nlp"]
def __init__( self , *lowercase_ , **lowercase_ ) -> Tuple:
requires_backends(self , ... | 693 | 0 |
from __future__ import annotations
from collections.abc import MutableSequence
class _a :
def __init__( self , lowercase_ , lowercase_ ) -> None:
if len(lowercase_ ) != degree + 1:
raise ValueError(
""... | 718 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('>=', '4.25.0')):
raise OptionalDependencyNotAvailable(... | 693 | 0 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
if n == 1 or not isinstance(SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ):
return 0
elif n == 2:
return 1
else:
lowerCAmelCase : Dic... | 719 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
if p < 2:
raise ValueError("""p should not be less than 2!""" )
elif p == 2:
return True
lowerCAmelCase : List[Any] = 4
lowerCAme... | 693 | 0 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class _a ( ... | 720 |
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import T... | 693 | 0 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _a ( snake_case_ ):
_UpperCamelCase: Union[str, Any] = ["image_processor", "tokenizer"]
_UpperCamelCase: str = "ChineseCLIPImageProcess... | 721 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : Optional[int] =logging.get_logger(__name__)
lowerCAmelCase : List[Any] ={}
class _a ( snake_case_ ):
_UpperCamelCase: Tuple = "llama"
... | 693 | 0 |
'''simple docstring'''
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
if index == r:
for j in range(S... | 700 |
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_indic... | 693 | 0 |
import argparse
import json
import subprocess
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
lowerCAmelCase : Optional[Any] = []
lowerCAmelCase : Optional[int] = (... | 701 |
lowerCAmelCase : str ={
'Pillow': 'Pillow<10.0.0',
'accelerate': 'accelerate>=0.20.3',
'av': 'av==9.2.0',
'beautifulsoup4': 'beautifulsoup4',
'black': 'black~=23.1',
'codecarbon': 'codecarbon==1.2.0',
'cookiecutter': 'cookiecutter==1.7.3',
'dataclasses': '... | 693 | 0 |
import os
from pathlib import Path
def _UpperCAmelCase ( ):
'''simple docstring'''
from torch.utils.cpp_extension import load
lowerCAmelCase : Optional[int] = Path(SCREAMING_SNAKE_CASE__ ).resolve().parent.parent.parent / """kernels... | 702 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase : Union[str, Any] ={
'configuration_roformer': ['ROFO... | 693 | 0 |
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
lowerCAmelCase : List[str] ={'UserAgent': UserAgent().random}
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
''... | 703 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
return int(input_a == input_a == 0 )
def _UpperCAmelCase ( ):
'''simple docstring'''
print("""Truth Table of NOR Gat... | 693 | 0 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | 704 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCAmelCase : int ={
'configuration_poolformer': [
'POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'PoolFormerConfig',
... | 693 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase : Union[str, Any] ={
'configuration_roformer': ['ROFORMER_PRE... | 705 |
import os
import string
import sys
lowerCAmelCase : Optional[int] =1 << 8
lowerCAmelCase : List[Any] ={
'tab': ord('\t'),
'newline': ord('\r'),
'esc': 27,
'up': 65 + ARROW_KEY_FLAG,
'down': 66 + ARROW_KEY_FLAG,
'right': 67 + ARROW_KEY_FLAG,... | 693 | 0 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
fro... | 706 |
# Imports
import numpy as np
class _a :
def __init__( self , lowercase_=None , lowercase_=None , lowercase_=None , lowercase_=None , lowercase_=None ) -> List[Any]:
self.set_matricies(red=lowercase_ , gree... | 693 | 0 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
lowerCAmelCase : Optional[int] =logging.get_logger(__name__)
# TODO: upload to AWS
lowerCAmelCase : Union[str, Any] ={
'yjernite/retribert-base-uncased': (
'https://huggingf... | 707 |
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__=None ):
'''simple docstring'''
lo... | 693 | 0 |
'''simple docstring'''
# flake8: noqa
# Lint as: python3
lowerCAmelCase : List[Any] =[
'VerificationMode',
'Version',
'disable_progress_bar',
'enable_progress_bar',
'is_progress_bar_enabled',
'experimental',
]
from .info_utils import VerificationMod... | 708 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Optional[int] ={
'configuration_autoformer': [
'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'... | 693 | 0 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
create_state_space_tree(SCREAMING_SNAKE_CASE__ ,[] ,0 )
def _Upper... | 709 |
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
lowerCAmelCase : Optional[int]... | 693 | 0 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : Union[str, Any] =logging.get_logger(__name__)
lowerCAmelCase : Union[str, Any] ={
'microsoft/unispeech-sat-base-100h-libri-ft': (
... | 710 |
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_torch_mu... | 693 | 0 |
from math import sqrt
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
lowerCAmelCase : Optional[Any] = 0
for i in range(1 ,int(sqrt(SCREAMING_SNAKE_CASE__ ) + 1 ) ):
if n % i == 0 and... | 711 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : Optional[int] =logging.get_logger(__name__)
lowerCAmelCase : Optional[int] ={
'transfo-xl-wt103': 'https://huggingface.co/transfo-xl-wt103/resolve/main/config.json',
}... | 693 | 0 |
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class _a ( nn.Module ):
def __init__( self , lowercase_ = 16 , lowercase_ = 88 , lowercase_ = None , lower... | 712 |
import torch
from diffusers import DiffusionPipeline
class _a ( snake_case_ ):
def __init__( self , lowercase_ , lowercase_ ) -> int:
super().__init__()
self.register_modules(unet=lowercase_ , scheduler=lowercase... | 693 | 0 |
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequenceClas... | 713 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def _UpperCAmelCase ( ):
'''simple docstring'''
with offline(O... | 693 | 0 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
if not isinstance(SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ):
raise ValueError("""multiplicative_persistence() only accepts integral values""" )
if num < 0:
ra... | 714 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_in... | 693 | 0 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
assert isinstance(SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ), F"""The input value of [n={number}] is not an integer"""
if number == 1:
return 2
elif number < 1... | 715 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
lowerCAmelCase : Tuple = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return r... | 693 | 0 |
def _UpperCAmelCase ( ):
'''simple docstring'''
for n in range(1 ,1_0_0_0_0_0_0 ):
yield n * (n + 1) // 2
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
lowerCAmelCase : ... | 716 |
from math import factorial
class _a :
def __init__( self , lowercase_ , lowercase_ ) -> Optional[Any]:
lowerCAmelCase : Union[str, Any] = real
if isinstance(lowercase_ , lowercase_ ):
lower... | 693 | 0 |
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate_available,
... | 717 |
from ..utils import DummyObject, requires_backends
class _a ( metaclass=snake_case_ ):
_UpperCamelCase: List[Any] = ["keras_nlp"]
def __init__( self , *lowercase_ , **lowercase_ ) -> Tuple:
requires_backends(self , ... | 693 | 0 |
from math import factorial
class _a :
def __init__( self , lowercase_ , lowercase_ ) -> Optional[Any]:
lowerCAmelCase : Union[str, Any] = real
if isinstance(lowercase_ , lowercase_ ):
lower... | 718 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('>=', '4.25.0')):
raise OptionalDependencyNotAvailable(... | 693 | 0 |
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
lowerCAmelCase : Union[str, Any] ={1: (1, 1), 2: (2, 1), 3: (3, 1), 4:... | 719 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
if p < 2:
raise ValueError("""p should not be less than 2!""" )
elif p == 2:
return True
lowerCAmelCase : List[Any] = 4
lowerCAme... | 693 | 0 |
from __future__ import annotations
from cmath import sqrt
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
if a == 0:
raise ValueError("""Coefficient 'a' must not be ze... | 720 |
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import T... | 693 | 0 |
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,
to_channel_dimensi... | 721 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : Optional[int] =logging.get_logger(__name__)
lowerCAmelCase : List[Any] ={}
class _a ( snake_case_ ):
_UpperCamelCase: Tuple = "llama"
... | 693 | 0 |
'''simple docstring'''
def _UpperCAmelCase ( ):
'''simple docstring'''
lowerCAmelCase : List[str] = []
lowerCAmelCase : Tuple = 1
while len(SCREAMING_SNAKE_CASE__ ) < 1e6:
constant.append(str(SCREA... | 700 |
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_indic... | 693 | 0 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
return int(input_a == input_a == 0 )
def _UpperCAmelCase ( ):
'''simple docstring'''
print("""Truth Table of NOR Gat... | 701 |
lowerCAmelCase : str ={
'Pillow': 'Pillow<10.0.0',
'accelerate': 'accelerate>=0.20.3',
'av': 'av==9.2.0',
'beautifulsoup4': 'beautifulsoup4',
'black': 'black~=23.1',
'codecarbon': 'codecarbon==1.2.0',
'cookiecutter': 'cookiecutter==1.7.3',
'dataclasses': '... | 693 | 0 |
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
requir... | 702 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase : Union[str, Any] ={
'configuration_roformer': ['ROFO... | 693 | 0 |
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import ScoreSdeVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class _a ( snake_case_ ):
_UpperCam... | 703 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
return int(input_a == input_a == 0 )
def _UpperCAmelCase ( ):
'''simple docstring'''
print("""Truth Table of NOR Gat... | 693 | 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, to... | 704 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCAmelCase : int ={
'configuration_poolformer': [
'POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'PoolFormerConfig',
... | 693 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Union[str, Any] ={
'configuration_x_clip': [
'XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
'XCLIPConfig',
'XCLIPTextConfig',
'X... | 705 |
import os
import string
import sys
lowerCAmelCase : Optional[int] =1 << 8
lowerCAmelCase : List[Any] ={
'tab': ord('\t'),
'newline': ord('\r'),
'esc': 27,
'up': 65 + ARROW_KEY_FLAG,
'down': 66 + ARROW_KEY_FLAG,
'right': 67 + ARROW_KEY_FLAG,... | 693 | 0 |
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 (
AutoConfig,
AutoModelForSeqaSeqLM,
... | 706 |
# Imports
import numpy as np
class _a :
def __init__( self , lowercase_=None , lowercase_=None , lowercase_=None , lowercase_=None , lowercase_=None ) -> List[Any]:
self.set_matricies(red=lowercase_ , gree... | 693 | 0 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
def is_in_circle(SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE_... | 707 |
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__=None ):
'''simple docstring'''
lo... | 693 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
lowerCAmelCase : int ={}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except Opt... | 708 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Optional[int] ={
'configuration_autoformer': [
'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'... | 693 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_pegasus impor... | 709 |
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
lowerCAmelCase : Optional[int]... | 693 | 0 |
lowerCAmelCase : Tuple ='\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/transformers.git\n'
lowerCAmelCase ... | 710 |
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_torch_mu... | 693 | 0 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
return "".join([hex(SCREAMING_SNAKE_CASE__ )[2:].zfill(2 ).upper() for byte in list(SCREAMING_SNAKE_CASE__ )] )
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE... | 711 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : Optional[int] =logging.get_logger(__name__)
lowerCAmelCase : Optional[int] ={
'transfo-xl-wt103': 'https://huggingface.co/transfo-xl-wt103/resolve/main/config.json',
}... | 693 | 0 |
import unittest
from transformers import is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common import ANY
... | 712 |
import torch
from diffusers import DiffusionPipeline
class _a ( snake_case_ ):
def __init__( self , lowercase_ , lowercase_ ) -> int:
super().__init__()
self.register_modules(unet=lowercase_ , scheduler=lowercase... | 693 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : Optional[int] =logging.get_logger(__name__)
lowerCAmelCase : Optional[int] ={
'transfo-xl-wt103': 'https://huggingface.co/transfo-xl-wt103/resolve/main/config.json',
}... | 713 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def _UpperCAmelCase ( ):
'''simple docstring'''
with offline(O... | 693 | 0 |
import argparse
from collections import defaultdict
import yaml
lowerCAmelCase : Any ='docs/source/en/_toctree.yml'
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
lowerCAmelCase : Any = defaultdict... | 714 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_in... | 693 | 0 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Tuple ={
'configuration_informer': [
'INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'InformerConf... | 715 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
lowerCAmelCase : Tuple = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return r... | 693 | 0 |
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def _UpperCAmelCase ( ):
'''simple docstring'''
lowerCAmelCase : int = ArgumentP... | 716 |
from math import factorial
class _a :
def __init__( self , lowercase_ , lowercase_ ) -> Optional[Any]:
lowerCAmelCase : Union[str, Any] = real
if isinstance(lowercase_ , lowercase_ ):
lower... | 693 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_ava... | 717 |
from ..utils import DummyObject, requires_backends
class _a ( metaclass=snake_case_ ):
_UpperCamelCase: List[Any] = ["keras_nlp"]
def __init__( self , *lowercase_ , **lowercase_ ) -> Tuple:
requires_backends(self , ... | 693 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase : Dict ={'configuration_x... | 718 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('>=', '4.25.0')):
raise OptionalDependencyNotAvailable(... | 693 | 0 |
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