code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformer... | 218 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import DistilBertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import ... | 95 | 0 |
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : List[str] = logging.get_logger(__name__)
# TODO Update this
__SCREAMING_SNAKE_CASE : Any = {
'facebook/e... | 670 |
"""simple docstring"""
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class UpperCamelCase... | 95 | 0 |
'''simple docstring'''
import itertools
import random
import unittest
import numpy as np
from transformers import WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, WavaVecaConfig, WavaVecaFeatureExtractor
from transformers.testing_utils import require_torch, slow
from ...test_sequence_feature_extraction_common import Seq... | 378 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def snake_case ( A__ ):
return ConvertCommand(
args.model_type ,args.tf_checkpoint ,args.pytorch_dump_output ,args.config ,args.finet... | 95 | 0 |
'''simple docstring'''
from __future__ import annotations
import pandas as pd
def lowerCamelCase (_SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : Union[str, Any] , _SCREAMING_SNAKE_CASE : Any ):
__a : Optional[Any] = [0] * no_of_processes
__a : Optional[... | 476 |
"""simple docstring"""
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
lowerCamelCase_ = {
'''<''': operator.lt,
'''<=''': operator.le,
'''==''': operator.eq,
'''!=''': operator.ne,
'''>=''': operator.ge,
... | 95 | 0 |
def lowerCAmelCase__(__snake_case ,__snake_case ) -> List[str]:
'''simple docstring'''
if not len(A__ ) == len(A__ ) == 3:
raise ValueError('''Please enter a valid equation.''' )
if equationa[0] == equationa[1] == equationa[0] == equationa[1] == 0:
raise ValueError('''Both... | 481 |
"""simple docstring"""
import os
import unittest
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
BertTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers... | 95 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_util... | 555 |
"""simple docstring"""
import os
from typing import Dict, List, Tuple, TypeVar, Union
lowerCamelCase_ = TypeVar('''T''')
lowerCamelCase_ = Union[List[T], Tuple[T, ...]]
lowerCamelCase_ = Union[T, List[T], Dict[str, T]]
lowerCamelCase_ = Union[str, bytes, os.Path... | 95 | 0 |
"""simple docstring"""
class _UpperCAmelCase :
'''simple docstring'''
def __init__( self , A ) -> None:
_UpperCAmelCase : str = len(lowerCAmelCase_ )
_UpperCAmelCase : Dict = [0] * len_array
if l... | 506 |
"""simple docstring"""
import argparse
import logging
import sys
from unittest.mock import patch
import run_glue_deebert
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
logging.basicConfig(level=logging.DEBUG)
lowerCamelCase_ = logging.getLog... | 95 | 0 |
"""simple docstring"""
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_single_gpu,
)
from accelerate.u... | 646 |
"""simple docstring"""
import json
import os
from typing import Dict, List, Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCamelCase_ = logging.get_logger(__name__)
lowerCamelCase_ = {
'''vocab_file''': ... | 95 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class UpperCamelCase ( metaclass=__A ):
lowercase = ['speech']
def __init__( self ,*__UpperCamelCase ,**__UpperCamelCase ) -> int:
'''simple docstring'''
requires_backends(... | 425 |
"""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,
)
from transformers.utils im... | 95 | 0 |
'''simple docstring'''
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, ... | 127 |
"""simple docstring"""
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (
... | 95 | 0 |
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDEN... | 148 |
"""simple docstring"""
from .integrations import (
is_optuna_available,
is_ray_available,
is_sigopt_available,
is_wandb_available,
run_hp_search_optuna,
run_hp_search_ray,
run_hp_search_sigopt,
run_hp_search_wandb,
)
from .trainer_utils import (
HPSearchBackend,
default_hp... | 95 | 0 |
"""simple docstring"""
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sen... | 218 |
"""simple docstring"""
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
clas... | 95 | 0 |
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class lowercase_ ( nn.Module ):
def __init__( self , lowercase_ = 16 , lowercase_ = 88 , lowercase_ = None , lowercase_ = 1 , lowercase_ = ... | 670 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def snake_case ( A__ ):
UpperCAmelCase_ : int = int(number**0.5 )
return number == sq * sq
def snake_case ( A__ ,A__ ,A__ ,A__ ,A__ ,A... | 95 | 0 |
'''simple docstring'''
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
"files" , [
["full:README.md", "dataset_infos.json"],
["empty:README.md", "dataset_infos.js... | 378 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tens... | 95 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__lowercase : str = logging.get_logger(__name__)
__lowercase : Union[str, Any] = ... | 476 |
"""simple docstring"""
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def snake_case ( A__ ):
def wrapper(*A__ ,**A__ ):
UpperCAmelCase_ : Union[str, Any] = timeit.default_timer()... | 95 | 0 |
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def lowerCAmelCase__(__snake_case ) -> str:
'''simple docstring'''
lowerCamelCase__ = SwinConfig(image_size=192 ... | 481 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .t... | 95 | 0 |
"""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 : Optional[Any] = logging.get_logger(__name__)
a : ... | 555 |
"""simple docstring"""
def snake_case ( A__ ):
UpperCAmelCase_ : int = [0 for i in range(len(A__ ) )]
# initialize interval's left pointer and right pointer
UpperCAmelCase_ , UpperCAmelCase_ : Optional[int] = 0, 0
for i in range(1 ,len(A__ ) ):
# c... | 95 | 0 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import numpy as np
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
import ... | 506 |
"""simple docstring"""
import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig
if TYPE_CHECK... | 95 | 0 |
"""simple docstring"""
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.configuration_... | 646 |
"""simple docstring"""
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig
lowerCamelCase_ = logging.get_logger(__name__)
lowerCamelCase_ = '''T5Config'''
class Upper... | 95 | 0 |
"""simple docstring"""
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
__SCREAMING_SNAKE_CASE ... | 425 |
"""simple docstring"""
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase_ = logging.get_logger(__name__)
lowerCamelCase_ = {
'''huggingface/informer-tourism-monthly''': (
'''https://hugg... | 95 | 0 |
'''simple docstring'''
from __future__ import annotations
UpperCamelCase__: str = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
class SCREAMING_SNAKE_CASE... | 127 |
"""simple docstring"""
import warnings
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 Tensor... | 95 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCAmelCase__ : List[str] ={
'''configuration_chinese_clip''': [
'''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''ChineseCLIPConfig''',
... | 148 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_a... | 95 | 0 |
"""simple docstring"""
from .imports import is_rich_available
if is_rich_available():
from rich.traceback import install
install(show_locals=False)
else:
raise ModuleNotFoundError("""To use the rich extension, install rich with `pip install rich`""")
| 218 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import DistilBertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import ... | 95 | 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 import ANY
if is_vis... | 670 |
"""simple docstring"""
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class UpperCamelCase... | 95 | 0 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvai... | 378 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def snake_case ( A__ ):
return ConvertCommand(
args.model_type ,args.tf_checkpoint ,args.pytorch_dump_output ,args.config ,args.finet... | 95 | 0 |
'''simple docstring'''
def lowerCamelCase (_SCREAMING_SNAKE_CASE : Union[str, Any] ):
return "".join(chr(ord(A__ ) - 32 ) if 'a' <= char <= 'z' else char for char in word )
if __name__ == "__main__":
from doctest import testmod
testmod()
| 476 |
"""simple docstring"""
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
lowerCamelCase_ = {
'''<''': operator.lt,
'''<=''': operator.le,
'''==''': operator.eq,
'''!=''': operator.ne,
'''>=''': operator.ge,
... | 95 | 0 |
import os
import unittest
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
BertTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils import re... | 481 |
"""simple docstring"""
import os
import unittest
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
BertTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers... | 95 | 0 |
"""simple docstring"""
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
a : int = [
# tf -> hf
('''/''', '''.'''),
('''layer_''', '''layers.''')... | 555 |
"""simple docstring"""
import os
from typing import Dict, List, Tuple, TypeVar, Union
lowerCamelCase_ = TypeVar('''T''')
lowerCamelCase_ = Union[List[T], Tuple[T, ...]]
lowerCamelCase_ = Union[T, List[T], Dict[str, T]]
lowerCamelCase_ = Union[str, bytes, os.Path... | 95 | 0 |
"""simple docstring"""
from __future__ import annotations
from pprint import pformat
from typing import Generic, TypeVar
_lowerCAmelCase :Dict = TypeVar('T')
class _UpperCAmelCase ( Generic[T] ):
'''simple docstring'''
def __init__( self , A = True ) -> None... | 506 |
"""simple docstring"""
import argparse
import logging
import sys
from unittest.mock import patch
import run_glue_deebert
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
logging.basicConfig(level=logging.DEBUG)
lowerCamelCase_ = logging.getLog... | 95 | 0 |
"""simple docstring"""
from collections import UserDict
from typing import Union
import numpy as np
import requests
from ..utils import (
add_end_docstrings,
logging,
)
from .audio_classification import ffmpeg_read
from .base import PIPELINE_INIT_ARGS, Pipeline
__A = logging.get_logger(__name__)
@a... | 646 |
"""simple docstring"""
import json
import os
from typing import Dict, List, Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCamelCase_ = logging.get_logger(__name__)
lowerCamelCase_ = {
'''vocab_file''': ... | 95 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
__SCREAMING_SNAKE_CASE =TypeVar("T")
__SCREAMING_SNAKE_CASE =TypeVar("U")
class UpperCamelCase ( Generic[T, U] ):
def __init__( ... | 425 |
"""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,
)
from transformers.utils im... | 95 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__: Any = logging.get_logger(__name__)
UpperCamelCase__: Any = {
"uclanlp/visualbert-vqa": "https://huggingface.co/uclanlp/visualbert-vqa/r... | 127 |
"""simple docstring"""
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (
... | 95 | 0 |
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def __lowercase ( a__ ) -> str:
return ConvertCommand(
args.model_type , args.tf_checkpoint , args.pytorch_dump_output , args.config , ar... | 148 |
"""simple docstring"""
from .integrations import (
is_optuna_available,
is_ray_available,
is_sigopt_available,
is_wandb_available,
run_hp_search_optuna,
run_hp_search_ray,
run_hp_search_sigopt,
run_hp_search_wandb,
)
from .trainer_utils import (
HPSearchBackend,
default_hp... | 95 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
a : ... | 218 |
"""simple docstring"""
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
clas... | 95 | 0 |
import json
import os
from typing import Dict, List, Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__SCREAMING_SNAKE_CASE : int = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Union[str, Any] = {
'v... | 670 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def snake_case ( A__ ):
UpperCAmelCase_ : int = int(number**0.5 )
return number == sq * sq
def snake_case ( A__ ,A__ ,A__ ,A__ ,A__ ,A... | 95 | 0 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case = logging.get_logger(__name__)
class lowerCAmelCase ( __A ):
A_ : Tuple = """encoder-decoder"""
A_ : int = True
def __init__( self : O... | 378 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tens... | 95 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
__lowercase : List[str] = {'configuration_speech_encoder_decoder': ['SpeechEncoderDecoderConfig']}
try:
if not is_torch_available():
r... | 476 |
"""simple docstring"""
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def snake_case ( A__ ):
def wrapper(*A__ ,**A__ ):
UpperCAmelCase_ : Union[str, Any] = timeit.default_timer()... | 95 | 0 |
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
_a = logging.get_logger(__name__)
_a = {name: getattr(transformers, name + "Fast") for name in SLOW_TO_FAST_CONVERTERS}
def lowe... | 481 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .t... | 95 | 0 |
"""simple docstring"""
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def _UpperCamelCase ( _A , _A=False ) -> Optional[Any]:
"""simple docstring"""
_UpperCAmelCase = OmegaConf.load(A__ )
if dis... | 555 |
"""simple docstring"""
def snake_case ( A__ ):
UpperCAmelCase_ : int = [0 for i in range(len(A__ ) )]
# initialize interval's left pointer and right pointer
UpperCAmelCase_ , UpperCAmelCase_ : Optional[int] = 0, 0
for i in range(1 ,len(A__ ) ):
# c... | 95 | 0 |
"""simple docstring"""
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils import ... | 506 |
"""simple docstring"""
import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig
if TYPE_CHECK... | 95 | 0 |
"""simple docstring"""
import argparse
import fairseq
import torch
from torch import nn
from transformers import (
MBartaaTokenizer,
MBartConfig,
MBartForCausalLM,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureEx... | 96 |
"""simple docstring"""
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin... | 96 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
__lowerCamelCase ... | 96 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
__lowerCamelCase ... | 96 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.j... | 96 |
"""simple docstring"""
def a ( __UpperCAmelCase : list[int] ) -> float:
if not nums: # Makes sure that the list is not empty
raise ValueError("""List is empty""" )
__magic_name__: Dict = sum(__UpperCAmelCase ) / len(__UpperC... | 96 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokeni... | 96 |
"""simple docstring"""
from random import randint
from tempfile import TemporaryFile
import numpy as np
def a ( __UpperCAmelCase : Optional[Any] , __UpperCAmelCase : Optional[int] , __UpperCAmelCase : Optional[int] ) -> int:
... | 96 | 1 |
"""simple docstring"""
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def a ( __UpperCAmelCase : List[Any] ) -> str:
__magic_name__: Union[str, Any] = ... | 96 |
"""simple docstring"""
def a ( __UpperCAmelCase : int = 1_0_0 ) -> int:
__magic_name__: str = 0
__magic_name__: Any = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
... | 96 | 1 |
"""simple docstring"""
__lowerCamelCase = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
__lowerCamelCase = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
__lowerCamelCase = {
0: 'Sunday',
1: 'Monday',
2: 'Tuesday',
3: 'Wednesday',
4: 'Thursday',
5: 'Friday',
... | 96 |
"""simple docstring"""
from __future__ import annotations
def a ( __UpperCAmelCase : list ) -> list:
if len(__UpperCAmelCase ) == 0:
return []
__magic_name__, __magic_name__: List[str] = min(__UpperCAmelCase ), max(__U... | 96 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __A ( metaclass=SCREAMING_SNAKE_CASE_ ):
UpperCAmelCase__ = ["transformers", "torch", "note_seq"]
def __init__( self : Optional[Any] , *__snake_case : Uni... | 96 |
"""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... | 96 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging... | 96 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteSchedu... | 96 | 1 |
"""simple docstring"""
def a ( __UpperCAmelCase : list[list[float]] ) -> list[list[float]]:
__magic_name__: list[list[float]] = []
for data in source_data:
for i, el in enumerate(__UpperCAmelCase ):
if len(__U... | 96 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
__lowerCamelCase ... | 96 | 1 |
"""simple docstring"""
import os
def a ( __UpperCAmelCase : Optional[int] ) -> str:
__magic_name__: List[str] = len(grid[0] )
__magic_name__: List[str] = len(__UpperCAmelCase )
__magic_name__: List[Any] = ... | 96 |
"""simple docstring"""
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokeni... | 96 | 1 |
"""simple docstring"""
def a ( __UpperCAmelCase : int , __UpperCAmelCase : int ) -> int:
while second != 0:
__magic_name__: Union[str, Any] = first & second
first ^= second
__magic_name__: List[s... | 96 |
"""simple docstring"""
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__... | 96 | 1 |
"""simple docstring"""
import math
from datetime import datetime, timedelta
def a ( __UpperCAmelCase : int ) -> datetime:
__magic_name__: str = year % 1_9
__magic_name__: Any = year % 4
__magic_name__: Dict = ... | 96 |
"""simple docstring"""
import argparse
import json
import os
import re
import torch
from transformers import BloomConfig, BloomModel
from transformers.file_utils import CONFIG_NAME, WEIGHTS_NAME
from transformers.utils import logging
logging.set_verbosity_info()
__lowerCamelC... | 96 | 1 |
"""simple docstring"""
from random import randint, random
def a ( __UpperCAmelCase : int , __UpperCAmelCase : int , __UpperCAmelCase : int , __UpperCAmelCase : bool = False , __UpperCAmelCase : bool = False ... | 96 |
"""simple docstring"""
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def a ( __UpperCAmelCase : bytes , __UpperCAmelCase : int ) -> np.array:
__magic_name__: Optional[i... | 96 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTe... | 96 |
"""simple docstring"""
from typing import List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
__lowerCamelCase = logging.get_lo... | 96 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
__lowerCamelCase = {
'configuration_longt5': ['LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LongT5Config', 'LongT5OnnxCo... | 96 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBas... | 96 | 1 |
"""simple docstring"""
from __future__ import annotations
import os
from collections.abc import Mapping
__lowerCamelCase = tuple[int, int]
class __A :
def __init__( self : Tuple , __snake_case : set[int] , __snake_case : Mapping[... | 96 |
"""simple docstring"""
from typing import Union
import fire
import torch
from tqdm import tqdm
def a ( __UpperCAmelCase : str , __UpperCAmelCase : str = "cpu" , __UpperCAmelCase : Union[str, None] = None ) -> None:
__ma... | 96 | 1 |
"""simple docstring"""
from typing import Union
import fire
import torch
from tqdm import tqdm
def a ( __UpperCAmelCase : str , __UpperCAmelCase : str = "cpu" , __UpperCAmelCase : Union[str, None] = None ) -> None:
__ma... | 96 |
"""simple docstring"""
def a ( __UpperCAmelCase : List[Any] ) -> str:
__magic_name__: Optional[int] = [0] * len(__UpperCAmelCase )
__magic_name__: str = []
__magic_name__: Any = []
__magic_name__: Union[... | 96 | 1 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
'microsoft/wavlm-base': 'https://huggingface.co/microsoft... | 96 |
"""simple docstring"""
from argparse import ArgumentParser
from .env import EnvironmentCommand
def a ( ) -> Tuple:
__magic_name__: Optional[int] = ArgumentParser("""Diffusers CLI tool""" , usage="""diffusers-cli <command> [<args>]""" )
... | 96 | 1 |
"""simple docstring"""
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEnc... | 96 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transforme... | 96 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__lowerCamelCase = {
'configuration_efficientformer': [
... | 96 |
"""simple docstring"""
def a ( __UpperCAmelCase : int , __UpperCAmelCase : int ) -> int:
while b:
__magic_name__, __magic_name__: Optional[int] = b, a % b
return a
def a ( __UpperCAmelCase : ... | 96 | 1 |
"""simple docstring"""
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from ..image_utils import load_i... | 96 |
"""simple docstring"""
import argparse
import gc
import json
import os
import shutil
import warnings
import torch
from transformers import LlamaConfig, LlamaForCausalLM, LlamaTokenizer
try:
from transformers import LlamaTokenizerFast
except ImportError as e:
war... | 96 | 1 |
"""simple docstring"""
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __A ( SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_ ):
@register_to_config
def __init__( s... | 96 |
"""simple docstring"""
from typing import List
from .keymap import KEYMAP, get_character
def a ( __UpperCAmelCase : str ) -> Optional[int]:
def decorator(__UpperCAmelCase : List[str] ):
__magic_name__: Union[str, Any] = ... | 96 | 1 |
"""simple docstring"""
def a ( __UpperCAmelCase : str ) -> bool:
if not all(x.isalpha() for x in string ):
raise ValueError("""String must only contain alphabetic characters.""" )
__magic_name__: Optional[Any] = sorted(string... | 96 |
"""simple docstring"""
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin... | 96 | 1 |
"""simple docstring"""
def a ( __UpperCAmelCase : List[Any] ) -> str:
__magic_name__: Optional[int] = [0] * len(__UpperCAmelCase )
__magic_name__: str = []
__magic_name__: Any = []
__magic_name__: Union[... | 96 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
__lowerCamelCase ... | 96 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_mod... | 96 |
"""simple docstring"""
def a ( __UpperCAmelCase : list[int] ) -> float:
if not nums: # Makes sure that the list is not empty
raise ValueError("""List is empty""" )
__magic_name__: Dict = sum(__UpperCAmelCase ) / len(__UpperC... | 96 | 1 |
"""simple docstring"""
import argparse
import re
from pathlib import Path
import requests
import torch
from PIL import Image
from torchvision.transforms import CenterCrop, Compose, Normalize, Resize, ToTensor
from transformers import (
EfficientFormerConfig,
EfficientFormer... | 96 |
"""simple docstring"""
from random import randint
from tempfile import TemporaryFile
import numpy as np
def a ( __UpperCAmelCase : Optional[Any] , __UpperCAmelCase : Optional[int] , __UpperCAmelCase : Optional[int] ) -> int:
... | 96 | 1 |
"""simple docstring"""
from queue import Queue
from typing import TYPE_CHECKING, Optional
if TYPE_CHECKING:
from ..models.auto import AutoTokenizer
class __A :
def lowerCamelCase__ ( self : List[Any] , __snake_case : Tuple ) -> ... | 96 |
"""simple docstring"""
def a ( __UpperCAmelCase : int = 1_0_0 ) -> int:
__magic_name__: str = 0
__magic_name__: Any = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
... | 96 | 1 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_mode... | 96 |
"""simple docstring"""
from __future__ import annotations
def a ( __UpperCAmelCase : list ) -> list:
if len(__UpperCAmelCase ) == 0:
return []
__magic_name__, __magic_name__: List[str] = min(__UpperCAmelCase ), max(__U... | 96 | 1 |
"""simple docstring"""
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class __A ( unittest.TestCase ):
def lowerCamelCase__ ( self : Dict ) -> None... | 96 |
"""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... | 96 | 1 |
"""simple docstring"""
from string import ascii_uppercase
__lowerCamelCase = {char: i for i, char in enumerate(ascii_uppercase)}
__lowerCamelCase = dict(enumerate(ascii_uppercase))
def a ( __UpperCAmelCase : str , __UpperCAmelCase : str ... | 96 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteSchedu... | 96 | 1 |
"""simple docstring"""
import math
def a ( __UpperCAmelCase : int ) -> bool:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all... | 96 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
__lowerCamelCase ... | 96 | 1 |
"""simple docstring"""
from __future__ import annotations
from math import gcd
def a ( __UpperCAmelCase : int , __UpperCAmelCase : int = 2 , __UpperCAmelCase : int = 1 , __UpperCAmelCase : int = 3 , ) -> int... | 96 |
"""simple docstring"""
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokeni... | 96 | 1 |
"""simple docstring"""
def a ( __UpperCAmelCase : int , __UpperCAmelCase : int , __UpperCAmelCase : int ) -> int:
if exponent == 1:
return base
if exponent % 2 == 0:
__magic_name__: List[Any] ... | 96 |
"""simple docstring"""
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__... | 96 | 1 |
"""simple docstring"""
import numpy as np
import qiskit
def a ( __UpperCAmelCase : int = 8 , __UpperCAmelCase : int | None = None ) -> str:
__magic_name__: List[Any] = np.random.default_rng(seed=__UpperCAmelCase )
# ... | 96 |
"""simple docstring"""
import argparse
import json
import os
import re
import torch
from transformers import BloomConfig, BloomModel
from transformers.file_utils import CONFIG_NAME, WEIGHTS_NAME
from transformers.utils import logging
logging.set_verbosity_info()
__lowerCamelC... | 96 | 1 |
"""simple docstring"""
import os
from typing import Dict, List, Tuple, TypeVar, Union
__lowerCamelCase = TypeVar('T')
__lowerCamelCase = Union[List[T], Tuple[T, ...]]
__lowerCamelCase = Union[T, List[T], Dict[str, T]]
__lowerCamelCase = Union[str, bytes, o... | 96 |
"""simple docstring"""
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def a ( __UpperCAmelCase : bytes , __UpperCAmelCase : int ) -> np.array:
__magic_name__: Optional[i... | 96 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowerCamelCase = {
'configuration_transfo_xl': ['TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TransfoXLConfig'],
... | 96 |
"""simple docstring"""
from typing import List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
__lowerCamelCase = logging.get_lo... | 96 | 1 |
"""simple docstring"""
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def a ( ) -> List[Any]:
with offline(Offline... | 96 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBas... | 96 | 1 |
"""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,
)... | 96 |
"""simple docstring"""
from typing import Union
import fire
import torch
from tqdm import tqdm
def a ( __UpperCAmelCase : str , __UpperCAmelCase : str = "cpu" , __UpperCAmelCase : Union[str, None] = None ) -> None:
__ma... | 96 | 1 |
"""simple docstring"""
from collections import namedtuple
import requests
from lxml import html # type: ignore
__lowerCamelCase = namedtuple('covid_data', 'cases deaths recovered')
def a ( __UpperCAmelCase : str = "https://www.worldometers.info/coronavirus... | 96 |
"""simple docstring"""
def a ( __UpperCAmelCase : List[Any] ) -> str:
__magic_name__: Optional[int] = [0] * len(__UpperCAmelCase )
__magic_name__: str = []
__magic_name__: Any = []
__magic_name__: Union[... | 96 | 1 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from .... | 96 |
"""simple docstring"""
from argparse import ArgumentParser
from .env import EnvironmentCommand
def a ( ) -> Tuple:
__magic_name__: Optional[int] = ArgumentParser("""Diffusers CLI tool""" , usage="""diffusers-cli <command> [<args>]""" )
... | 96 | 1 |
"""simple docstring"""
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
__lowerCamelCase = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
__lowerCamelCase = [ord(letter)... | 96 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transforme... | 96 | 1 |
"""simple docstring"""
from statistics import mean
import numpy as np
def a ( __UpperCAmelCase : list , __UpperCAmelCase : list , __UpperCAmelCase : list , __UpperCAmelCase : int ) -> list:
__magic_name__: ... | 96 |
"""simple docstring"""
def a ( __UpperCAmelCase : int , __UpperCAmelCase : int ) -> int:
while b:
__magic_name__, __magic_name__: Optional[int] = b, a % b
return a
def a ( __UpperCAmelCase : ... | 96 | 1 |
"""simple docstring"""
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
'google/umt5-smal... | 96 |
"""simple docstring"""
import argparse
import gc
import json
import os
import shutil
import warnings
import torch
from transformers import LlamaConfig, LlamaForCausalLM, LlamaTokenizer
try:
from transformers import LlamaTokenizerFast
except ImportError as e:
war... | 96 | 1 |
"""simple docstring"""
from math import sqrt
def a ( __UpperCAmelCase : int ) -> bool:
assert isinstance(__UpperCAmelCase , __UpperCAmelCase ) and (
number >= 0
), "'number' must been an int and positive"
__magic_name__... | 96 |
"""simple docstring"""
from typing import List
from .keymap import KEYMAP, get_character
def a ( __UpperCAmelCase : str ) -> Optional[int]:
def decorator(__UpperCAmelCase : List[str] ):
__magic_name__: Union[str, Any] = ... | 96 | 1 |
"""simple docstring"""
def a ( __UpperCAmelCase : str , __UpperCAmelCase : str = " " ) -> list:
__magic_name__: List[Any] = []
__magic_name__: Optional[int] = 0
for index, char in enumerate(__UpperCAmelCase... | 96 |
"""simple docstring"""
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin... | 96 | 1 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTea... | 96 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
__lowerCamelCase ... | 96 | 1 |
"""simple docstring"""
import argparse
import json
import os
import re
import torch
from transformers import BloomConfig, BloomModel
from transformers.file_utils import CONFIG_NAME, WEIGHTS_NAME
from transformers.utils import logging
logging.set_verbosity_info()
__lowerCamelC... | 96 |
"""simple docstring"""
def a ( __UpperCAmelCase : list[int] ) -> float:
if not nums: # Makes sure that the list is not empty
raise ValueError("""List is empty""" )
__magic_name__: Dict = sum(__UpperCAmelCase ) / len(__UpperC... | 96 | 1 |
"""simple docstring"""
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(good_file_paths())
assert filepaths, "good_file_paths() failed!"
__l... | 96 |
"""simple docstring"""
from random import randint
from tempfile import TemporaryFile
import numpy as np
def a ( __UpperCAmelCase : Optional[Any] , __UpperCAmelCase : Optional[int] , __UpperCAmelCase : Optional[int] ) -> int:
... | 96 | 1 |
"""simple docstring"""
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
... | 96 |
"""simple docstring"""
def a ( __UpperCAmelCase : int = 1_0_0 ) -> int:
__magic_name__: str = 0
__magic_name__: Any = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
... | 96 | 1 |
"""simple docstring"""
import gc
import unittest
from transformers import CTRLConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTe... | 96 |
"""simple docstring"""
from __future__ import annotations
def a ( __UpperCAmelCase : list ) -> list:
if len(__UpperCAmelCase ) == 0:
return []
__magic_name__, __magic_name__: List[str] = min(__UpperCAmelCase ), max(__U... | 96 | 1 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
... | 96 |
"""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... | 96 | 1 |
"""simple docstring"""
import warnings
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
fro... | 96 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteSchedu... | 96 | 1 |
"""simple docstring"""
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class __A ( SCREAMING_SNAKE_CASE_... | 96 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
__lowerCamelCase ... | 96 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils im... | 96 |
"""simple docstring"""
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokeni... | 96 | 1 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transforme... | 96 |
"""simple docstring"""
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__... | 96 | 1 |
"""simple docstring"""
from __future__ import annotations
def a ( __UpperCAmelCase : list[float] ) -> bool:
if len(__UpperCAmelCase ) < 2:
raise ValueError("""Monogons and Digons are not polygons in the Euclidean space""" )
if any(i... | 96 |
"""simple docstring"""
import argparse
import json
import os
import re
import torch
from transformers import BloomConfig, BloomModel
from transformers.file_utils import CONFIG_NAME, WEIGHTS_NAME
from transformers.utils import logging
logging.set_verbosity_info()
__lowerCamelC... | 96 | 1 |
"""simple docstring"""
def a ( __UpperCAmelCase : str ) -> str:
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 96 |
"""simple docstring"""
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def a ( __UpperCAmelCase : bytes , __UpperCAmelCase : int ) -> np.array:
__magic_name__: Optional[i... | 96 | 1 |
"""simple docstring"""
import argparse
import gc
import json
import os
import shutil
import warnings
import torch
from transformers import LlamaConfig, LlamaForCausalLM, LlamaTokenizer
try:
from transformers import LlamaTokenizerFast
except ImportError as e:
war... | 96 |
"""simple docstring"""
from typing import List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
__lowerCamelCase = logging.get_lo... | 96 | 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... | 96 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBas... | 96 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ..utils import _LazyModule
__lowerCamelCase = {
'config': [
'EXTERNAL_DATA_FORMAT_SIZE_LIMIT',
'OnnxConfig',
'OnnxConfigWithPast',
'OnnxSeq2SeqConfigWithPast',
'Patching... | 96 |
"""simple docstring"""
from typing import Union
import fire
import torch
from tqdm import tqdm
def a ( __UpperCAmelCase : str , __UpperCAmelCase : str = "cpu" , __UpperCAmelCase : Union[str, None] = None ) -> None:
__ma... | 96 | 1 |
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