code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import Conf... | 20 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.t... | 20 | 1 |
"""simple docstring"""
import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse("""9.1.0"""):
A__ : str= {
"""linear""": PIL.Image.Resampling.BILINEAR,
"""... | 20 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> list[int]:
"""simple docstring"""
UpperCamelCase__ = len(SCREAMING_SNAKE_CASE )
for i in range(SCREAMING_SNAKE_CASE ):
for j in range(i + 1 , SCREAMING_SNAKE_CASE ):
... | 20 | 1 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import float... | 20 |
"""simple docstring"""
import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse("""9.1.0"""):
A__ : str= {
"""linear""": PIL.Image.Resampling.BILINEAR,
"""... | 20 | 1 |
"""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... | 20 |
"""simple docstring"""
import os
import re
import warnings
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
if TYPE_CHECKING:
from ...tokenization_ut... | 20 | 1 |
"""simple docstring"""
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ... | 20 |
"""simple docstring"""
from __future__ import annotations
from typing import Generic, TypeVar
A__ : Any= TypeVar("""T""")
class __lowerCamelCase ( Generic[T] ):
def __init__( self , snake_case_ ) -> None:
UpperCamelCase__ = data
... | 20 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ : List[str]= logging.get_logger(__name__)
class __lowerCamelCase ( _a ):
a : Optional[int] ="""timm_backbone"""
def __init__( self , snak... | 20 |
"""simple docstring"""
A__ : Tuple= """Alexander Joslin"""
import operator as op
from .stack import Stack
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
UpperCamelCase__ = {'*': op.mul, '/': op.truediv, '+': o... | 20 | 1 |
"""simple docstring"""
from string import ascii_lowercase, ascii_uppercase
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> str:
"""simple docstring"""
if not sentence:
return ""
UpperCamelCase__ = dict(zip(SCREAMING_SNAKE_CASE , SCREA... | 20 |
"""simple docstring"""
import argparse
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
A__ : Any= """src/diffusers"""
# Matches is_xxx_available()
A__ : Tuple= re.c... | 20 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
... | 20 |
"""simple docstring"""
# Copyright 2022 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... | 20 | 1 |
"""simple docstring"""
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
A__ : Optional[int]= object()
# For specifying empty leaf dict `{}`
A__ : Opti... | 20 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ : List[str]= logging.get_logger(__name__)
class __lowerCamelCase ( _a ):
a : Optional[int] ="""timm_backbone"""
def __init__( self , snak... | 20 | 1 |
"""simple docstring"""
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipelin... | 20 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimensio... | 20 | 1 |
"""simple docstring"""
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_mode... | 20 |
"""simple docstring"""
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_mo... | 20 | 1 |
"""simple docstring"""
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_tor... | 20 |
"""simple docstring"""
from collections import defaultdict
from math import ceil, sqrt
def lowerCAmelCase_( SCREAMING_SNAKE_CASE = 1_00_00_00 , SCREAMING_SNAKE_CASE = 10 ) -> int:
"""simple docstring"""
UpperCamelCase__ = defaultdict(SCREAMING_SN... | 20 | 1 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> list[int]:
"""simple docstring"""
UpperCamelCase__ = len(SCREAMING_SNAKE_CASE )
for i in range(SCREAMING_SNAKE_CASE ):
for j in range(i + 1 , SCREAMING_SNAKE_CASE ):
... | 20 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from transformers import BeitConfig
from transformers.testing_utils import require_flax, require_vision, slow
from transformers.utils import cached_property, is_flax_available, is_vision_available
from ...test_... | 20 | 1 |
"""simple docstring"""
from copy import deepcopy
class __lowerCamelCase :
def __init__( self , snake_case_ = None , snake_case_ = None ) -> None:
if arr is None and size is not None:
UpperCamelCase__ = size
UpperCam... | 20 |
"""simple docstring"""
import sys
from collections import defaultdict
class __lowerCamelCase :
def __init__( self ) -> Tuple:
UpperCamelCase__ = []
def SCREAMING_SNAKE_CASE__ ( self , snake_case_ ) -> List[str]:
... | 20 | 1 |
"""simple docstring"""
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
FEATURE_EXTRACTOR_MAPPING,
AutoConfig,
AutoFeatureExtractor,
WavaVecaConfig,
WavaVecaFeatur... | 20 |
"""simple docstring"""
from copy import deepcopy
class __lowerCamelCase :
def __init__( self , snake_case_ = None , snake_case_ = None ) -> None:
if arr is None and size is not None:
UpperCamelCase__ = size
UpperCam... | 20 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
A__ : List[str]= {
"""configuration_squeezebert""": [
"""SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
... | 20 |
"""simple docstring"""
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
A__ : Union[str, Any]= logging.getLogger()
@unitte... | 20 | 1 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> Union[str, Any]:
"""simple docstring"""
if not head:
return True
# split the list to two parts
UpperCamelCase__ , UpperCamelCase__ = head.next, head
while fa... | 20 |
"""simple docstring"""
import warnings
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A__ : str= logging.get_logger(__... | 20 | 1 |
"""simple docstring"""
from PIL import Image
def lowerCAmelCase_( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> Image:
"""simple docstring"""
UpperCamelCase__ = (2_59 * (level + 2_55)) / (2_55 * (2_59 - level))
def contrast(SCREAMING_SNA... | 20 |
"""simple docstring"""
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> Dict:
"""simple docstring"""
return DownloadCommand(args.model , args.cache_dir , args.force , args.trust_re... | 20 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
A__ : Optional[Any]= logging.get_logger(__name__)
class __lowerCamelCase ... | 20 |
"""simple docstring"""
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_mode... | 20 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> list[int]:
"""simple docstring"""
if num <= 0:
UpperCamelCase__ = F'{num}: Invalid input, please enter a positive inte... | 20 |
"""simple docstring"""
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def lowerCAmelCase_( SCRE... | 20 | 1 |
"""simple docstring"""
import json
import os
import re
import sys
import urllib.request
import requests
from bsa import BeautifulSoup
A__ : str= {
"""User-Agent""": """Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36"""
""" (KHTML, like Gecko) Chrome/70.0.35... | 20 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> bool:
"""simple docstring"""
UpperCamelCase__ = (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def lowerCAmelCase_( SCREAMING_SNAKE_CASE = 50_00 ) -> int:
... | 20 | 1 |
"""simple docstring"""
import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTester... | 20 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE = 50_00_00_00 ) -> int:
"""simple docstring"""
UpperCamelCase__ = set()
UpperCamelCase__ = int((limit - 24) ** (1 / 2) )
UpperCamelCase__ = set(range(3 , prime... | 20 | 1 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_war... | 20 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.t... | 20 | 1 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
... | 20 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> list[int]:
"""simple docstring"""
UpperCamelCase__ = len(SCREAMING_SNAKE_CASE )
for i in range(SCREAMING_SNAKE_CASE ):
for j in range(i + 1 , SCREAMING_SNAKE_CASE ):
... | 20 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import Tokeni... | 20 |
"""simple docstring"""
import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse("""9.1.0"""):
A__ : str= {
"""linear""": PIL.Image.Resampling.BILINEAR,
"""... | 20 | 1 |
"""simple docstring"""
import requests
A__ : Optional[int]= """""" # <-- Put your OpenWeatherMap appid here!
A__ : str= """https://api.openweathermap.org/data/2.5/"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE = "Chicago" , SCREAMING_SNAKE_CASE = APPID ) -> ... | 20 |
"""simple docstring"""
import os
import re
import warnings
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
if TYPE_CHECKING:
from ...tokenization_ut... | 20 | 1 |
"""simple docstring"""
import warnings
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 ... | 20 |
"""simple docstring"""
from __future__ import annotations
from typing import Generic, TypeVar
A__ : Any= TypeVar("""T""")
class __lowerCamelCase ( Generic[T] ):
def __init__( self , snake_case_ ) -> None:
UpperCamelCase__ = data
... | 20 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
A__ : Optional[Any]= TypeVar("""T""")
A__ : Optional[Any]= TypeVar("""U""")
class __lowerCamelCase ( Generic[T, U] ):
def __init__( ... | 20 |
"""simple docstring"""
A__ : Tuple= """Alexander Joslin"""
import operator as op
from .stack import Stack
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
UpperCamelCase__ = {'*': op.mul, '/': op.truediv, '+': o... | 20 | 1 |
"""simple docstring"""
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestM... | 20 |
"""simple docstring"""
import argparse
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
A__ : Any= """src/diffusers"""
# Matches is_xxx_available()
A__ : Tuple= re.c... | 20 | 1 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from transformers import BeitConfig
from transformers.testing_utils import require_flax, require_vision, slow
from transformers.utils import cached_property, is_flax_available, is_vision_available
from ...test_... | 20 |
"""simple docstring"""
# Copyright 2022 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... | 20 | 1 |
"""simple docstring"""
import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelM... | 20 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ : List[str]= logging.get_logger(__name__)
class __lowerCamelCase ( _a ):
a : Optional[int] ="""timm_backbone"""
def __init__( self , snak... | 20 | 1 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apach... | 20 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimensio... | 20 | 1 |
"""simple docstring"""
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class __lowerCamelCase ( _a ):
a : str =(UnCLIPScheduler,)
def SCREAMING_SNAKE_CASE__ ( self , **snake_case_ ) -> ... | 20 |
"""simple docstring"""
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_mo... | 20 | 1 |
"""simple docstring"""
from manim import *
class __lowerCamelCase ( _a ):
def SCREAMING_SNAKE_CASE__ ( self ) -> Dict:
UpperCamelCase__ = Rectangle(height=0.5 , width=0.5 )
UpperCamelCase__ = Rectangle(height=0.4... | 20 |
"""simple docstring"""
from collections import defaultdict
from math import ceil, sqrt
def lowerCAmelCase_( SCREAMING_SNAKE_CASE = 1_00_00_00 , SCREAMING_SNAKE_CASE = 10 ) -> int:
"""simple docstring"""
UpperCamelCase__ = defaultdict(SCREAMING_SN... | 20 | 1 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class __lowerCame... | 20 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from transformers import BeitConfig
from transformers.testing_utils import require_flax, require_vision, slow
from transformers.utils import cached_property, is_flax_available, is_vision_available
from ...test_... | 20 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowerCAmelCase_( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
if len(SCREAMING_SNAKE_CASE ) < k or k < 0:
raise ValueError('Invalid Input' )
U... | 20 |
"""simple docstring"""
import sys
from collections import defaultdict
class __lowerCamelCase :
def __init__( self ) -> Tuple:
UpperCamelCase__ = []
def SCREAMING_SNAKE_CASE__ ( self , snake_case_ ) -> List[str]:
... | 20 | 1 |
"""simple docstring"""
from collections import defaultdict
from math import ceil, sqrt
def lowerCAmelCase_( SCREAMING_SNAKE_CASE = 1_00_00_00 , SCREAMING_SNAKE_CASE = 10 ) -> int:
"""simple docstring"""
UpperCamelCase__ = defaultdict(SCREAMING_SN... | 20 |
"""simple docstring"""
from copy import deepcopy
class __lowerCamelCase :
def __init__( self , snake_case_ = None , snake_case_ = None ) -> None:
if arr is None and size is not None:
UpperCamelCase__ = size
UpperCam... | 20 | 1 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor... | 20 |
"""simple docstring"""
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
A__ : Union[str, Any]= logging.getLogger()
@unitte... | 20 | 1 |
"""simple docstring"""
import importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
A__ : List[Any]= importlib.util.find_spec("""s3fs""") is not None... | 20 |
"""simple docstring"""
import warnings
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A__ : str= logging.get_logger(__... | 20 | 1 |
"""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 __lowerCamelCase ( _a ):
def __init__( ... | 20 |
"""simple docstring"""
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> Dict:
"""simple docstring"""
return DownloadCommand(args.model , args.cache_dir , args.force , args.trust_re... | 20 | 1 |
"""simple docstring"""
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
A__ : Union[str, Any]= logging.getLogger()
@unitte... | 20 |
"""simple docstring"""
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_mode... | 20 | 1 |
"""simple docstring"""
from abc import ABC, abstractmethod
from typing import List, Optional
class __lowerCamelCase ( _a ):
def __init__( self ) -> Tuple:
# test for the above condition
self.test()
def SCREAMING_SNAKE_CASE__ ( self... | 20 |
"""simple docstring"""
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def lowerCAmelCase_( SCRE... | 20 | 1 |
"""simple docstring"""
import tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class __lowerCamelCase ( _a ):
a : Optional[Any] =(PNDMScheduler,)
a : Optional[int] =(("""num_inference... | 20 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> bool:
"""simple docstring"""
UpperCamelCase__ = (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def lowerCAmelCase_( SCREAMING_SNAKE_CASE = 50_00 ) -> int:
... | 20 | 1 |
"""simple docstring"""
from math import factorial
def lowerCAmelCase_( SCREAMING_SNAKE_CASE = 20 ) -> int:
"""simple docstring"""
UpperCamelCase__ = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
... | 20 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE = 50_00_00_00 ) -> int:
"""simple docstring"""
UpperCamelCase__ = set()
UpperCamelCase__ = int((limit - 24) ** (1 / 2) )
UpperCamelCase__ = set(range(3 , prime... | 20 | 1 |
"""simple docstring"""
import argparse
import requests
import torch
from PIL import Image
from transformers import ViTMAEConfig, ViTMAEForPreTraining, ViTMAEImageProcessor
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> Any:
"""simple docstring"""
if ... | 20 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.t... | 20 | 1 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.t... | 20 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> list[int]:
"""simple docstring"""
UpperCamelCase__ = len(SCREAMING_SNAKE_CASE )
for i in range(SCREAMING_SNAKE_CASE ):
for j in range(i + 1 , SCREAMING_SNAKE_CASE ):
... | 20 | 1 |
"""simple docstring"""
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_... | 20 |
"""simple docstring"""
import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse("""9.1.0"""):
A__ : str= {
"""linear""": PIL.Image.Resampling.BILINEAR,
"""... | 20 | 1 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
from filelock import FileLock
from transformers import PreTrainedTokenizer, is_tf_available, is_torch_available
A__ : List[str]= lo... | 20 |
"""simple docstring"""
import os
import re
import warnings
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
if TYPE_CHECKING:
from ...tokenization_ut... | 20 | 1 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
class __lowerCamelCase :
def __init__( self , snake_case_ ) -> None:
UpperCamelCase__ = num_of_nodes
UpperCamelCase__ = []
UpperCamel... | 20 |
"""simple docstring"""
from __future__ import annotations
from typing import Generic, TypeVar
A__ : Any= TypeVar("""T""")
class __lowerCamelCase ( Generic[T] ):
def __init__( self , snake_case_ ) -> None:
UpperCamelCase__ = data
... | 20 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __lowerCamelCase ( metaclass=_a ):
a : Tuple =["""flax"""]
def __init__( self , *snake_case_ , **snake_case_ ) -> Dict:
requires_backends(self , ['fl... | 20 |
"""simple docstring"""
A__ : Tuple= """Alexander Joslin"""
import operator as op
from .stack import Stack
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
UpperCamelCase__ = {'*': op.mul, '/': op.truediv, '+': o... | 20 | 1 |
"""simple docstring"""
from importlib import import_module
from .logging import get_logger
A__ : List[Any]= get_logger(__name__)
class __lowerCamelCase :
def __init__( self , snake_case_ , snake_case_=None ) -> List[str]:
UpperCamelCase__ ... | 20 |
"""simple docstring"""
import argparse
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
A__ : Any= """src/diffusers"""
# Matches is_xxx_available()
A__ : Tuple= re.c... | 20 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...... | 20 |
"""simple docstring"""
# Copyright 2022 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... | 20 | 1 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# ... | 20 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ : List[str]= logging.get_logger(__name__)
class __lowerCamelCase ( _a ):
a : Optional[int] ="""timm_backbone"""
def __init__( self , snak... | 20 | 1 |
"""simple docstring"""
from __future__ import annotations
A__ : Tuple= {
"""A""": ["""B""", """C""", """E"""],
"""B""": ["""A""", """D""", """E"""],
"""C""": ["""A""", """F""", """G"""],
"""D""": ["""B"""],
"""E""": ["""A""", """B""", """D"""],
"""F""": ["""... | 20 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimensio... | 20 | 1 |
"""simple docstring"""
import math
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> list:
"""simple docstring"""
UpperCamelCase__ = [True] * n
UpperCamelCase__ = False
UpperCamelCase__ = False
UpperCamelCase__ ... | 20 |
"""simple docstring"""
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_mo... | 20 | 1 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
A__ : int= logging.get_logger(__name__)
A__ : List[Any]= {
"""ut/deta""": """https://huggingface.co/ut/deta/resolve/mai... | 20 |
"""simple docstring"""
from collections import defaultdict
from math import ceil, sqrt
def lowerCAmelCase_( SCREAMING_SNAKE_CASE = 1_00_00_00 , SCREAMING_SNAKE_CASE = 10 ) -> int:
"""simple docstring"""
UpperCamelCase__ = defaultdict(SCREAMING_SN... | 20 | 1 |
"""simple docstring"""
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
d... | 20 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from transformers import BeitConfig
from transformers.testing_utils import require_flax, require_vision, slow
from transformers.utils import cached_property, is_flax_available, is_vision_available
from ...test_... | 20 | 1 |
"""simple docstring"""
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
f... | 20 |
"""simple docstring"""
import sys
from collections import defaultdict
class __lowerCamelCase :
def __init__( self ) -> Tuple:
UpperCamelCase__ = []
def SCREAMING_SNAKE_CASE__ ( self , snake_case_ ) -> List[str]:
... | 20 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
A__ : Union[str, Any]= {
"""configuratio... | 20 |
"""simple docstring"""
from copy import deepcopy
class __lowerCamelCase :
def __init__( self , snake_case_ = None , snake_case_ = None ) -> None:
if arr is None and size is not None:
UpperCamelCase__ = size
UpperCam... | 20 | 1 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
UpperCamelCase__ = len(SCREAMING_SNAKE_CASE )
UpperCamelCase__ = sum(SCREAMING_SNAKE_CASE )
UpperCamelCase__ = [[False for... | 20 |
"""simple docstring"""
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
A__ : Union[str, Any]= logging.getLogger()
@unitte... | 20 | 1 |
"""simple docstring"""
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
A__ : Dict= logging.get_logger(__name__)
A__ ... | 20 |
"""simple docstring"""
import warnings
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A__ : str= logging.get_logger(__... | 20 | 1 |
"""simple docstring"""
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 ImagePro... | 20 |
"""simple docstring"""
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> Dict:
"""simple docstring"""
return DownloadCommand(args.model , args.cache_dir , args.force , args.trust_re... | 20 | 1 |
"""simple docstring"""
class __lowerCamelCase :
def __init__( self , snake_case_ , snake_case_=None , snake_case_=None ) -> Optional[Any]:
UpperCamelCase__ = data
UpperCamelCase__ = previous
UpperCamelCase__ ... | 20 |
"""simple docstring"""
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_mode... | 20 | 1 |
"""simple docstring"""
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowerCAmelCase_( ... | 20 |
"""simple docstring"""
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def lowerCAmelCase_( SCRE... | 20 | 1 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> bool:
"""simple docstring"""
if not isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
UpperCamelCase__ = F'Input value of [number={number}] must be an integer'
ra... | 20 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> bool:
"""simple docstring"""
UpperCamelCase__ = (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def lowerCAmelCase_( SCREAMING_SNAKE_CASE = 50_00 ) -> int:
... | 20 | 1 |
"""simple docstring"""
A__ : int= """ABCDEFGHIJKLMNOPQRSTUVWXYZ"""
def lowerCAmelCase_( ) -> None:
"""simple docstring"""
UpperCamelCase__ = input('Enter message: ' )
UpperCamelCase__ = input('Enter key [alphanumeric]: ' )
... | 20 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE = 50_00_00_00 ) -> int:
"""simple docstring"""
UpperCamelCase__ = set()
UpperCamelCase__ = int((limit - 24) ** (1 / 2) )
UpperCamelCase__ = set(range(3 , prime... | 20 | 1 |
"""simple docstring"""
A__ : Dict= [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
A__ : Union[str, Any]= [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
A__ : Optional[int]= {
0: """Sunday""",
1: """Monday""",
2: """Tuesday""",
3: """Wednesday""",
4: """Thursday""",
5: ""... | 20 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.t... | 20 | 1 |
"""simple docstring"""
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def lowerCAmelCase_( SCRE... | 20 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> list[int]:
"""simple docstring"""
UpperCamelCase__ = len(SCREAMING_SNAKE_CASE )
for i in range(SCREAMING_SNAKE_CASE ):
for j in range(i + 1 , SCREAMING_SNAKE_CASE ):
... | 20 | 1 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers... | 20 |
"""simple docstring"""
import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse("""9.1.0"""):
A__ : str= {
"""linear""": PIL.Image.Resampling.BILINEAR,
"""... | 20 | 1 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ : List[Any]= logging.get_logger(__name__)
A__ : List[str]= {
"""google/pix2struct-textcaps-base""": (
""... | 20 |
"""simple docstring"""
import os
import re
import warnings
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
if TYPE_CHECKING:
from ...tokenization_ut... | 20 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepar... | 20 |
"""simple docstring"""
from __future__ import annotations
from typing import Generic, TypeVar
A__ : Any= TypeVar("""T""")
class __lowerCamelCase ( Generic[T] ):
def __init__( self , snake_case_ ) -> None:
UpperCamelCase__ = data
... | 20 | 1 |
"""simple docstring"""
from itertools import product
def lowerCAmelCase_( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> list[int]:
"""simple docstring"""
UpperCamelCase__ = sides_number
UpperCamelCase__ = max_face_number * dice_... | 20 |
"""simple docstring"""
A__ : Tuple= """Alexander Joslin"""
import operator as op
from .stack import Stack
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
UpperCamelCase__ = {'*': op.mul, '/': op.truediv, '+': o... | 20 | 1 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> float:
"""simple docstring"""
if density <= 0:
raise ValueError('Impossible fluid density' )
if bulk_modulus <= 0:
raise ValueError('Impossible bulk modu... | 20 |
"""simple docstring"""
import argparse
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
A__ : Any= """src/diffusers"""
# Matches is_xxx_available()
A__ : Tuple= re.c... | 20 | 1 |
"""simple docstring"""
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
A__ : List[str]= None
try:
import msvcrt
except ImportError:
A__ : Dict= None
try:
import fcntl
except ImportError:
A__ : Dict= No... | 20 |
"""simple docstring"""
# Copyright 2022 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... | 20 | 1 |
"""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... | 20 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ : List[str]= logging.get_logger(__name__)
class __lowerCamelCase ( _a ):
a : Optional[int] ="""timm_backbone"""
def __init__( self , snak... | 20 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
for i in range(1 , len(matrix[0] ) ):
matrix[0][i] += matrix[0][i - 1]
# preprocessing the first colu... | 20 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimensio... | 20 | 1 |
"""simple docstring"""
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub... | 20 |
"""simple docstring"""
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_mo... | 20 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A__ : Dict= logging.get_logger(__name__)
A__ : List[str]= {
"""kssteve... | 20 |
"""simple docstring"""
from collections import defaultdict
from math import ceil, sqrt
def lowerCAmelCase_( SCREAMING_SNAKE_CASE = 1_00_00_00 , SCREAMING_SNAKE_CASE = 10 ) -> int:
"""simple docstring"""
UpperCamelCase__ = defaultdict(SCREAMING_SN... | 20 | 1 |
"""simple docstring"""
import datasets
A__ : Tuple= """\
@InProceedings{conneau2018xnli,
author = \"Conneau, Alexis
and Rinott, Ruty
and Lample, Guillaume
and Williams, Adina
and Bowman, Samuel R.
an... | 20 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from transformers import BeitConfig
from transformers.testing_utils import require_flax, require_vision, slow
from transformers.utils import cached_property, is_flax_available, is_vision_available
from ...test_... | 20 | 1 |
"""simple docstring"""
import gc
import unittest
from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
impo... | 20 |
"""simple docstring"""
import sys
from collections import defaultdict
class __lowerCamelCase :
def __init__( self ) -> Tuple:
UpperCamelCase__ = []
def SCREAMING_SNAKE_CASE__ ( self , snake_case_ ) -> List[str]:
... | 20 | 1 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE = 1_00_00_00 ) -> int:
"""simple docstring"""
UpperCamelCase__ = [i - 1 for i in range(limit + 1 )]
for i in range(2 , limit + 1 ):
if phi[i] == i - 1:
for j in... | 20 |
"""simple docstring"""
from copy import deepcopy
class __lowerCamelCase :
def __init__( self , snake_case_ = None , snake_case_ = None ) -> None:
if arr is None and size is not None:
UpperCamelCase__ = size
UpperCam... | 20 | 1 |
"""simple docstring"""
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,
... | 20 |
"""simple docstring"""
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
A__ : Union[str, Any]= logging.getLogger()
@unitte... | 20 | 1 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> Any:
"""simple docstring"""
assert x is not None
assert y is not None
UpperCamelCase__ = len(SCREAMING_SNAKE_CASE )
UpperCamelCase__ = le... | 20 |
"""simple docstring"""
import warnings
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A__ : str= logging.get_logger(__... | 20 | 1 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers import LukeConfig, LukeModel, LukeTokenizer, RobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def lowerCAmelCase_( SCREAMING_SNAKE_... | 20 |
"""simple docstring"""
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> Dict:
"""simple docstring"""
return DownloadCommand(args.model , args.cache_dir , args.force , args.trust_re... | 20 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import FunnelConfig, is_tf_available
from transformers.testing_utils import require_tf
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTeste... | 20 |
"""simple docstring"""
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_mode... | 20 | 1 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> bool:
"""simple docstring"""
UpperCamelCase__ = int(number**0.5 )
retur... | 20 |
"""simple docstring"""
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def lowerCAmelCase_( SCRE... | 20 | 1 |
"""simple docstring"""
A__ : Union[str, Any]= tuple[float, float, float]
A__ : Dict= tuple[float, float, float]
def lowerCAmelCase_( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> Vectorad:
"""simple docstring"""
UpperCamelCase__ = end_... | 20 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> bool:
"""simple docstring"""
UpperCamelCase__ = (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def lowerCAmelCase_( SCREAMING_SNAKE_CASE = 50_00 ) -> int:
... | 20 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from diffusers import LMSDiscreteScheduler, OnnxStableDiffusionInpaintPipeline
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
nightly,
require_onnxruntime,
require_torch_gpu,
)... | 20 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE = 50_00_00_00 ) -> int:
"""simple docstring"""
UpperCamelCase__ = set()
UpperCamelCase__ = int((limit - 24) ** (1 / 2) )
UpperCamelCase__ = set(range(3 , prime... | 20 | 1 |
"""simple docstring"""
class __lowerCamelCase :
def __init__( self , snake_case_ , snake_case_ ) -> Union[str, Any]:
UpperCamelCase__ = name
UpperCamelCase__ = val
def __str__( self ) -> Any:
r... | 20 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.t... | 20 | 1 |
"""simple docstring"""
import math
import unittest
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> bool:
"""simple docstring"""
assert isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) and (
number >= 0
), "'number' must been an int ... | 20 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> list[int]:
"""simple docstring"""
UpperCamelCase__ = len(SCREAMING_SNAKE_CASE )
for i in range(SCREAMING_SNAKE_CASE ):
for j in range(i + 1 , SCREAMING_SNAKE_CASE ):
... | 20 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
def lowerCAmelCase_( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> float:
"""simple docstring"""
UpperCamelCase__ = u
for i in range(1 , SCREAMING_SNAKE_CASE ):
... | 20 |
"""simple docstring"""
import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse("""9.1.0"""):
A__ : str= {
"""linear""": PIL.Image.Resampling.BILINEAR,
"""... | 20 | 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
... | 20 |
"""simple docstring"""
import os
import re
import warnings
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
if TYPE_CHECKING:
from ...tokenization_ut... | 20 | 1 |
"""simple docstring"""
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,
)
f... | 20 |
"""simple docstring"""
from __future__ import annotations
from typing import Generic, TypeVar
A__ : Any= TypeVar("""T""")
class __lowerCamelCase ( Generic[T] ):
def __init__( self , snake_case_ ) -> None:
UpperCamelCase__ = data
... | 20 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDCondi... | 20 |
"""simple docstring"""
A__ : Tuple= """Alexander Joslin"""
import operator as op
from .stack import Stack
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
UpperCamelCase__ = {'*': op.mul, '/': op.truediv, '+': o... | 20 | 1 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> float:
"""simple docstring"""
if not nums: # Makes sure that the list is not empty
raise ValueError('List is empty' )
UpperCamelCase__ = sum(SCREAMING_SNAKE_CASE ) / l... | 20 |
"""simple docstring"""
import argparse
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
A__ : Any= """src/diffusers"""
# Matches is_xxx_available()
A__ : Tuple= re.c... | 20 | 1 |
"""simple docstring"""
A__ : dict[str, float]= {
"km/h": 1.0,
"m/s": 3.6,
"mph": 1.6_0_9_3_4_4,
"knot": 1.8_5_2,
}
A__ : dict[str, float]= {
"km/h": 1.0,
"m/s": 0.2_7_7_7_7_7_7_7_8,
"mph": 0.6_2_1_3_7_1_1_9_2,
"knot": 0.5_3_9_9_5_6_8_0_3,
}
... | 20 |
"""simple docstring"""
# Copyright 2022 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... | 20 | 1 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.pat... | 20 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ : List[str]= logging.get_logger(__name__)
class __lowerCamelCase ( _a ):
a : Optional[int] ="""timm_backbone"""
def __init__( self , snak... | 20 | 1 |
"""simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transform... | 20 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimensio... | 20 | 1 |
"""simple docstring"""
import math
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> str:
"""simple docstring"""
UpperCamelCase__ = 0
UpperCamelCase__ = 0
while num > 0:
UpperCamelCase__ = num % 8
Upp... | 20 |
"""simple docstring"""
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_mo... | 20 | 1 |
"""simple docstring"""
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 ImagePro... | 20 |
"""simple docstring"""
from collections import defaultdict
from math import ceil, sqrt
def lowerCAmelCase_( SCREAMING_SNAKE_CASE = 1_00_00_00 , SCREAMING_SNAKE_CASE = 10 ) -> int:
"""simple docstring"""
UpperCamelCase__ = defaultdict(SCREAMING_SN... | 20 | 1 |
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