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 ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F401
from ..controlnet.pipeline_controlnet import StableDiffusionControlNetPipeline # noqa: F401
deprecate(
"stable diffusion controlnet",
"0.22.0",
"Importing `StableDif... | 715 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import AutoencoderKL, DDIMSche... | 625 | 0 |
"""simple docstring"""
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class __SCREAMING_SNAKE_CASE ( lowerCAmelCase_ ):
'''simple docstring'''
def __init__( self : Dict, lowerCamelCase ... | 716 |
"""simple docstring"""
def snake_case__ ( __lowerCamelCase : int = 4000000 ):
"""simple docstring"""
lowerCamelCase__ : Dict =[]
lowerCamelCase__ , lowerCamelCase__ : Union[str, Any] =0, 1
while b <= n:
if b % 2 == 0:
even_fibs.append(__lowerCamelCase ... | 625 | 0 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
# Register SEW's fairseq modules
from sew_asapp import tasks # noqa: F401
from transformers import (
SEWConfig,
SEWForCTC,
SEWModel,
WavaVecaCTCTokenizer,
WavaVe... | 717 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configu... | 625 | 0 |
"""simple docstring"""
import json
import re
from typing import TYPE_CHECKING, List, Optional, Tuple, Union
import numpy as np
from ...utils import is_tf_available, is_torch_available, logging
if TYPE_CHECKING:
if is_torch_available():
import torch
if is_tf_available():
import tensorflow as tf... | 718 |
"""simple docstring"""
def snake_case__ ( __lowerCamelCase : list[list[int]] , __lowerCamelCase : int , __lowerCamelCase : int , __lowerCamelCase : list[int] ):
"""simple docstring"""
# 1. Validate that path exists between current and ne... | 625 | 0 |
"""simple docstring"""
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import... | 719 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokeniz... | 625 | 0 |
"""simple docstring"""
from math import factorial
_lowercase : Any = {str(d): factorial(d) for d in range(1_0)}
def snake_case__ ( __lowerCamelCase : int ):
"""simple docstring"""
return sum(DIGIT_FACTORIAL[d] for d in str(__lowerCamelCase ) )
def snake_ca... | 720 |
"""simple docstring"""
def snake_case__ ( __lowerCamelCase : str ):
"""simple docstring"""
return " ".join(
''''''.join(word[::-1] ) if len(__lowerCamelCase ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
... | 625 | 0 |
"""simple docstring"""
import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def snake_case__ ( __lowerCamelCase : int , __lowerCamelCase : Any , __lo... | 721 |
"""simple docstring"""
def snake_case__ ( __lowerCamelCase : int = 10 , __lowerCamelCase : int = 22 ):
"""simple docstring"""
lowerCamelCase__ : Optional[Any] =range(1 , __lowerCamelCase )
lowerCamelCase__ : str =range(1 , __lowerCamelCase )
... | 625 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
"configuration_lilt": ["LILT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LiltConfig"],
}
try:
if not is_torch_available():
raise OptionalDependenc... | 700 |
"""simple docstring"""
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_a... | 625 | 0 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTPException
from fa... | 701 |
"""simple docstring"""
def snake_case__ ( __lowerCamelCase : list , __lowerCamelCase : list , __lowerCamelCase : int , __lowerCamelCase : int , __lowerCamelCase : int ):
"""simple docstring"""
if index == number_of_items:
... | 625 | 0 |
"""simple docstring"""
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from tra... | 702 |
"""simple docstring"""
_lowercase : Optional[Any] = {
"Pillow": "Pillow<10.0.0",
"accelerate": "accelerate>=0.20.3",
"av": "av==9.2.0",
"beautifulsoup4": "beautifulsoup4",
"black": "black~=23.1",
"codecarbon": "codecarbon==1.2.0",
"cookiecutter": "cookiecutter==1.7.3",
... | 625 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowercase : Any = {
"configuration_mobilenet_v2": [
"MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP",
"MobileNetV2... | 703 |
"""simple docstring"""
def snake_case__ ( __lowerCamelCase : list[int] ):
"""simple docstring"""
if not numbers:
return 0
if not isinstance(__lowerCamelCase , (list, tuple) ) or not all(
isinstance(__lowerCamelCase , __lowerCamelCase ) for number in num... | 625 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase : Tuple = {
"configuration_megatron_bert": ["MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MegatronBertConfig"],
}
try:
if not is_torch_a... | 704 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax imp... | 625 | 0 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_uti... | 705 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowercase : Optional[Any] = {
"conf... | 625 | 0 |
"""simple docstring"""
import argparse
import json
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_warmup, set_se... | 706 |
"""simple docstring"""
import os
def snake_case__ ( ):
"""simple docstring"""
with open(os.path.dirname(__lowerCamelCase ) + '''/p022_names.txt''' ) as file:
lowerCamelCase__ : Tuple =str(file.readlines()[0] )
lowerCamelCase__ : int =names.replace('''"''' , ''''... | 625 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers impor... | 707 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Iterator
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : str, lowerCamelCase : int )-> None:
lowerCamelCase__ : str =value
... | 625 | 0 |
"""simple docstring"""
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
_lowercase : Dict = 2_0_0
# Number of elements selected in every generation of evolution. The selection takes
# place from best to wor... | 708 |
"""simple docstring"""
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
_lowercase : List[st... | 625 | 0 |
"""simple docstring"""
from copy import deepcopy
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : List[str], lowerCamelCase : list[int] | None = None, lowerCamelCase : int | None = None )-> None:
if arr is... | 709 |
"""simple docstring"""
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def snake_case__ ( __lowerCamelCase : str , __lowerCamelCase : str , __lowerCamelCase : Tuple ):
"""simple docstring"""... | 625 | 0 |
"""simple docstring"""
from __future__ import annotations
def snake_case__ ( __lowerCamelCase : list[int] , __lowerCamelCase : int ):
"""simple docstring"""
if len(__lowerCamelCase ) < k or k < 0:
raise ValueError('''Invalid Input''' ... | 710 |
"""simple docstring"""
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ConvNextConfig, UperNetConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import is_torch_a... | 625 | 0 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import Padd... | 711 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __SCREAMING_SNAKE_CASE ( metaclass=lowerCAmelCase_ ):
'''simple docstring'''
_a = ['onnx']
def __init__( self : List[str], *lowerCamelCase : Union[str, An... | 625 | 0 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_... | 712 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def snake_case__ ( __lowerCamelCase : float , __lowerCamelCase : float , __lowerCamelCase : int ):
"""simple docstring"""
lowerCamelCase__ : Optional[Any] =x
lowerC... | 625 | 0 |
"""simple docstring"""
def snake_case__ ( __lowerCamelCase : int ):
"""simple docstring"""
assert (
isinstance(__lowerCamelCase , __lowerCamelCase ) and number_of_steps > 0
), f'''number_of_steps needs to be positive integer, your input {number_of_steps}'''
if numb... | 713 |
"""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,
)
def snake_case__ ... | 625 | 0 |
"""simple docstring"""
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MO... | 714 |
"""simple docstring"""
_lowercase : str = 0 # The first color of the flag.
_lowercase : Dict = 1 # The second color of the flag.
_lowercase : Tuple = 2 # The third color of the flag.
_lowercase : Optional[int] = (red, white, blue)
def snake_case__ ( _... | 625 | 0 |
"""simple docstring"""
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class __SCREAMING_SNAKE_CASE ( lowerCAmelCase_ ):
'''simple docstring'''
def __init__( self ... | 715 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import AutoencoderKL, DDIMSche... | 625 | 0 |
"""simple docstring"""
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import Model... | 716 |
"""simple docstring"""
def snake_case__ ( __lowerCamelCase : int = 4000000 ):
"""simple docstring"""
lowerCamelCase__ : Dict =[]
lowerCamelCase__ , lowerCamelCase__ : Union[str, Any] =0, 1
while b <= n:
if b % 2 == 0:
even_fibs.append(__lowerCamelCase ... | 625 | 0 |
"""simple docstring"""
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def snake_case__ ( __lowerCamelCase : Any ):
"""simple docstring"""
lo... | 717 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configu... | 625 | 0 |
"""simple docstring"""
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : Any, lowerCamelCase : int )-> List[str]:
lowerCamelCase__ : Any =n
lowerCamelCase__ : Tuple =[None] * self.n
lowerCamelCase__ : T... | 718 |
"""simple docstring"""
def snake_case__ ( __lowerCamelCase : list[list[int]] , __lowerCamelCase : int , __lowerCamelCase : int , __lowerCamelCase : list[int] ):
"""simple docstring"""
# 1. Validate that path exists between current and ne... | 625 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowercase : int = logging.get_logger(__name__)
_lowercase : Any = {
"junnyu/roformer... | 719 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokeniz... | 625 | 0 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import... | 720 |
"""simple docstring"""
def snake_case__ ( __lowerCamelCase : str ):
"""simple docstring"""
return " ".join(
''''''.join(word[::-1] ) if len(__lowerCamelCase ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
... | 625 | 0 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transfor... | 721 |
"""simple docstring"""
def snake_case__ ( __lowerCamelCase : int = 10 , __lowerCamelCase : int = 22 ):
"""simple docstring"""
lowerCamelCase__ : Optional[Any] =range(1 , __lowerCamelCase )
lowerCamelCase__ : str =range(1 , __lowerCamelCase )
... | 625 | 0 |
from ..utils import DummyObject, requires_backends
class a__ ( metaclass=snake_case ):
"""simple docstring"""
__lowerCamelCase = ['note_seq']
def __init__( self , *lowercase , **lowercase ) -> Optional[int]:
'''simple docstring'... | 626 |
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
from .prior_transformer import PriorTransformer
fr... | 626 | 1 |
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 ...image_transforms import (
center_crop,
get_res... | 626 |
from math import factorial
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int = 1_0_0 ) -> int:
'''simple docstring'''
return sum(map(SCREAMING_SNAKE_CASE_ , str(factorial(SCREAMING_SNAKE_CASE_ ) ) ) )
if __name__ == "__main__":
print(soluti... | 626 | 1 |
# 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/licenses/LICENSE-2.0
#
# Unless required by applica... | 626 |
lowerCAmelCase__ = """ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"""
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: bytes ) -> bytes:
'''simple docstring'''
if not isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
A__... | 626 | 1 |
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {"""vocab_file""": """vocab.json"""}
lowerCAmelCase__ = {
"""vocab_file""": {
"""mgp-... | 626 |
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,... | 626 | 1 |
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the config
# - generate model_cards - usef... | 626 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int ) -> int:
'''simple docstring'''
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
A__ = 1
A__ = 1
while repunit:
A__ = (1_0 * repunit + 1) % divisor
repunit_i... | 626 | 1 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: list ) -> list:
'''simple docstring'''
if len(SCREAMING_SNAKE_CASE_ ) < 2:
return collection
def circle_sort_util(SCREAMING_SNAKE_CASE_: list , SCREAMING_SNAKE_CASE_: int , SCREAMING_S... | 626 |
from __future__ import annotations
from collections.abc import Iterator
from typing import Any
class a__ :
"""simple docstring"""
def __init__( self , lowercase ) -> int:
'''simple docstring'''
A__ = data
A__ = None
class ... | 626 | 1 |
from __future__ import annotations
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int , SCREAMING_SNAKE_CASE_: int ) -> list[str]:
'''simple docstring'''
if partitions <= 0:
raise ValueError("partitions must be a positive number!" )
if parti... | 626 |
import math
lowerCAmelCase__ = 1_0
lowerCAmelCase__ = 7
lowerCAmelCase__ = BALLS_PER_COLOUR * NUM_COLOURS
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int = 2_0 ) -> str:
'''simple docstring'''
A__ = math.comb(SCREAMING_SNAKE_CASE_ , SCREAMING... | 626 | 1 |
class a__ ( snake_case ):
"""simple docstring"""
pass
class a__ ( snake_case ):
"""simple docstring"""
pass
class a__ :
"""simple docstring"""
def __init__( self ) -> Optional[Any]:
'''simple docstring'''
... | 626 |
from typing import Union
import fire
import torch
from tqdm import tqdm
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: str , SCREAMING_SNAKE_CASE_: str = "cpu" , SCREAMING_SNAKE_CASE_: Union[str, None] = None ) -> None:
'''simple docstring'''
A_... | 626 | 1 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: str ) -> str:
'''simple docstring'''
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 626 |
from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class a__ :
"""simple docstring"""
__lowerCamelCase = field(
metadata={'h... | 626 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowerCAmelCase__ = {"""configuration_vit""": ["""VIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViTConfig""", """V... | 626 |
import collections
import importlib.util
import os
import re
from pathlib import Path
lowerCAmelCase__ = """src/transformers"""
# Matches is_xxx_available()
lowerCAmelCase__ = re.compile(R"""is\_([a-z_]*)_available()""")
# Catches a one-line _import_struct = {xxx}
lowerCAmelCase__ = re.compile(R"""^_impo... | 626 | 1 |
import argparse
import collections
import os
import re
import tempfile
import pandas as pd
from datasets import Dataset
from huggingface_hub import hf_hub_download, upload_folder
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root ... | 626 |
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
lowerCAmelCase__ = logging.get_logger(__name__)
class a__ ( snake_case ):
"""simple docstring"""
def __init__( self , *lowercase , **lowercase ) -> ... | 626 | 1 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: List[str] ) -> Dict:
'''simple docstring'''
return [
{
0: [1, 2],
1: [0, 2],
2: [0, 1, 3, 5],
3: [2, 4],
4: [3],
5: [2, 6, 8],
6: [5, ... | 626 |
from __future__ import annotations
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: str , SCREAMING_SNAKE_CASE_: list[str] | None = None ) -> list[list[str]]:
'''simple docstring'''
A__ = word_bank or []
# create a table
A__ = len(SCR... | 626 | 1 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Dict , SCREAMING_SNAKE_CASE_: List[str] ) -> str:
'''simple docstring'''
A__ = ""
for i in table:
res += inp[i - 1]
return res
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: ... | 626 |
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: List[str] , SCREAMING_SNAKE_CASE_: List[str] , SCREAMING_SNAKE_CASE_: List[str] , SCREAMING_SNAKE_CASE_:... | 626 | 1 |
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
lowerCAmelCase__ = version.parse(importlib_metadata.version("""nltk"""))
if NLTK_VERSION >= version.Version("""3.6.4"""):
from nltk import word_tokenize
lowerCAmelCase__ = """... | 626 |
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Namespace ) -> Tuple:
'''simple docstring'''
return ConvertCommand(
args.model_type , args.t... | 626 | 1 |
import argparse
import json
import os
import torch
from torch import nn
from transformers import NllbMoeConfig, NllbMoeModel
from transformers.modeling_utils import dtype_byte_size
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Dict ... | 626 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_to... | 626 | 1 |
from __future__ import annotations
from collections.abc import Callable
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Callable[[int | float], int | float] , SCREAMING_SNAKE_CASE_: int | float , SCREAMING_SNAKE_CASE_: int | float , SCREAMING_SNAKE_CASE_: int = 1... | 626 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFCamembertModel
@require_tf... | 626 | 1 |
from typing import List, Optional
from tokenizers import ByteLevelBPETokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {... | 626 |
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipeline_params import UNCONDITION... | 626 | 1 |
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class a__ ( snake_case ):
"""simple docstring"""
__lowerCamelCase = (UnCLIPScheduler,)
def UpperCamelCase ( self , **lowercase ) -> str:
... | 626 |
from __future__ import annotations
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: list[int] , SCREAMING_SNAKE_CASE_: list[int] , SCREAMING_SNAKE_CASE_: list[int] , SCREAMING_SNAKE_CASE_: list[list[str]] , SCREAMING_SNAKE_CASE_: int , ) -> ... | 626 | 1 |
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def lowerCAmelCase__ ( SCREAMING_SNAKE_CAS... | 626 |
from __future__ import annotations
import copy
import tempfile
import unittest
from transformers import CONFIG_MAPPING, AutoConfig, BertConfig, GPTaConfig, TaConfig, TapasConfig, is_tf_available
from transformers.testing_utils import (
DUMMY_UNKNOWN_IDENTIFIER,
SMALL_MODEL_IDENTIFIER,
RequestCounter,
... | 626 | 1 |
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
... | 626 |
import inspect
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
lowerCAmelCase__ = """src/transformers"""
# This is to make sure the transforme... | 626 | 1 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import... | 626 |
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_available():
import torch
i... | 626 | 1 |
import inspect
import unittest
class a__ ( unittest.TestCase ):
"""simple docstring"""
def UpperCamelCase ( self ) -> List[str]:
'''simple docstring'''
try:
import diffusers # noqa: F401
except ImportError:
assert Fal... | 626 |
import datasets
from .evaluate import evaluate
lowerCAmelCase__ = """\
@inproceedings{Rajpurkar2016SQuAD10,
title={SQuAD: 100, 000+ Questions for Machine Comprehension of Text},
author={Pranav Rajpurkar and Jian Zhang and Konstantin Lopyrev and Percy Liang},
booktitle={EMNLP},
year={2016}
}
"""
lowerCA... | 626 | 1 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | 626 |
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
from .prior_transformer import PriorTransformer
fr... | 626 | 1 |
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 ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
... | 626 |
from math import factorial
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int = 1_0_0 ) -> int:
'''simple docstring'''
return sum(map(SCREAMING_SNAKE_CASE_ , str(factorial(SCREAMING_SNAKE_CASE_ ) ) ) )
if __name__ == "__main__":
print(soluti... | 626 | 1 |
import argparse
import os
import torch
from transformers import FlavaConfig, FlavaForPreTraining
from transformers.models.flava.convert_dalle_to_flava_codebook import convert_dalle_checkpoint
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Optional[Any] ) -> Dict:
'''simple doc... | 626 |
lowerCAmelCase__ = """ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"""
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: bytes ) -> bytes:
'''simple docstring'''
if not isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
A__... | 626 | 1 |
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,
EfficientFormerForImageClassificationWithTeacher,
EfficientFormerIma... | 626 |
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,... | 626 | 1 |
import argparse
import json
import subprocess
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int , SCREAMING_SNAKE_CASE_: List[Any] ) -> Dict:
'''simple docstring'''
A__ = []
A__ = (
F'curl -H "Accept: application/vnd.github+js... | 626 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int ) -> int:
'''simple docstring'''
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
A__ = 1
A__ = 1
while repunit:
A__ = (1_0 * repunit + 1) % divisor
repunit_i... | 626 | 1 |
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_INDEX_NAME, shard_checkpoint
lowerCAmelCase__ = {
... | 626 |
from __future__ import annotations
from collections.abc import Iterator
from typing import Any
class a__ :
"""simple docstring"""
def __init__( self , lowercase ) -> int:
'''simple docstring'''
A__ = data
A__ = None
class ... | 626 | 1 |
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
lowerCAmelCase__ = logging.getLogger(__name__)
@dataclass
class a__ ( snake_case ):
"""simple docstring"""
__... | 626 |
import math
lowerCAmelCase__ = 1_0
lowerCAmelCase__ = 7
lowerCAmelCase__ = BALLS_PER_COLOUR * NUM_COLOURS
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int = 2_0 ) -> str:
'''simple docstring'''
A__ = math.comb(SCREAMING_SNAKE_CASE_ , SCREAMING... | 626 | 1 |
def lowerCAmelCase__ ( ) -> Optional[Any]:
'''simple docstring'''
A__ = []
A__ = 1
while len(SCREAMING_SNAKE_CASE_ ) < 1e6:
constant.append(str(SCREAMING_SNAKE_CASE_ ) )
i += 1
A__ = "".join(SCREAMING_SNAKE_CASE... | 626 |
from typing import Union
import fire
import torch
from tqdm import tqdm
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: str , SCREAMING_SNAKE_CASE_: str = "cpu" , SCREAMING_SNAKE_CASE_: Union[str, None] = None ) -> None:
'''simple docstring'''
A_... | 626 | 1 |
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,... | 626 |
from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class a__ :
"""simple docstring"""
__lowerCamelCase = field(
metadata={'h... | 626 | 1 |
import importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
lowerCAmelCase__ = importlib.util.find_spec("""s3fs""") is not None
if _has_safs:
from .safilesystem import SaFileSystem #... | 626 |
import collections
import importlib.util
import os
import re
from pathlib import Path
lowerCAmelCase__ = """src/transformers"""
# Matches is_xxx_available()
lowerCAmelCase__ = re.compile(R"""is\_([a-z_]*)_available()""")
# Catches a one-line _import_struct = {xxx}
lowerCAmelCase__ = re.compile(R"""^_impo... | 626 | 1 |
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers... | 626 |
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
lowerCAmelCase__ = logging.get_logger(__name__)
class a__ ( snake_case ):
"""simple docstring"""
def __init__( self , *lowercase , **lowercase ) -> ... | 626 | 1 |
import datasets
from .evaluate import evaluate
lowerCAmelCase__ = """\
@inproceedings{Rajpurkar2016SQuAD10,
title={SQuAD: 100, 000+ Questions for Machine Comprehension of Text},
author={Pranav Rajpurkar and Jian Zhang and Konstantin Lopyrev and Percy Liang},
booktitle={EMNLP},
year={2016}
}
"""
lowerCA... | 626 |
from __future__ import annotations
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: str , SCREAMING_SNAKE_CASE_: list[str] | None = None ) -> list[list[str]]:
'''simple docstring'''
A__ = word_bank or []
# create a table
A__ = len(SCR... | 626 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ = {
"""configuration_x_clip""": [
"""XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""XCLIPConfig""",
"""XCLIPTextConfig""",
"""XCLIPVisionConfig""... | 626 |
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: List[str] , SCREAMING_SNAKE_CASE_: List[str] , SCREAMING_SNAKE_CASE_: List[str] , SCREAMING_SNAKE_CASE_:... | 626 | 1 |
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_bert import BertConfig
from tra... | 626 |
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Namespace ) -> Tuple:
'''simple docstring'''
return ConvertCommand(
args.model_type , args.t... | 626 | 1 |
class a__ :
"""simple docstring"""
def __init__( self ) -> Optional[int]:
'''simple docstring'''
A__ = 0
A__ = 0
A__ = {}
def UpperCamelCase ( self , lowercase ) -> Any:
'''sim... | 626 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_to... | 626 | 1 |
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipeline_params import UNCONDITION... | 626 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFCamembertModel
@require_tf... | 626 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ = {
"""configuration_clipseg""": [
"""CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""CLIPSegConfig""",
"""CLIPSegTextConfig""",
"""CLIPSegVisio... | 626 |
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipeline_params import UNCONDITION... | 626 | 1 |
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: ndarray ) -> float:
'''simple docstring'''
return np.dot(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ )
... | 626 |
from __future__ import annotations
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: list[int] , SCREAMING_SNAKE_CASE_: list[int] , SCREAMING_SNAKE_CASE_: list[int] , SCREAMING_SNAKE_CASE_: list[list[str]] , SCREAMING_SNAKE_CASE_: int , ) -> ... | 626 | 1 |
import os
import time
import numpy as np
import onnxruntime as ort
lowerCAmelCase__ = """1"""
lowerCAmelCase__ = """0"""
lowerCAmelCase__ = """1"""
lowerCAmelCase__ = ort.SessionOptions()
lowerCAmelCase__ = ort.GraphOptimizationLevel.ORT_DISABLE_ALL
print("""Create inference session...""")
lowerCAm... | 626 |
from __future__ import annotations
import copy
import tempfile
import unittest
from transformers import CONFIG_MAPPING, AutoConfig, BertConfig, GPTaConfig, TaConfig, TapasConfig, is_tf_available
from transformers.testing_utils import (
DUMMY_UNKNOWN_IDENTIFIER,
SMALL_MODEL_IDENTIFIER,
RequestCounter,
... | 626 | 1 |
import inspect
import os
import unittest
from dataclasses import dataclass
import torch
from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subprocess_async, require_cuda, require_multi_gpu
from a... | 626 |
import inspect
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
lowerCAmelCase__ = """src/transformers"""
# This is to make sure the transforme... | 626 | 1 |
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class a__ ( snake_case , unittest.TestCase ):
"""simple ... | 626 |
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_available():
import torch
i... | 626 | 1 |
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
from .prior_transformer import PriorTransformer
fr... | 626 |
import datasets
from .evaluate import evaluate
lowerCAmelCase__ = """\
@inproceedings{Rajpurkar2016SQuAD10,
title={SQuAD: 100, 000+ Questions for Machine Comprehension of Text},
author={Pranav Rajpurkar and Jian Zhang and Konstantin Lopyrev and Percy Liang},
booktitle={EMNLP},
year={2016}
}
"""
lowerCA... | 626 | 1 |
import collections
import importlib.util
import os
import re
from pathlib import Path
lowerCAmelCase__ = """src/transformers"""
# Matches is_xxx_available()
lowerCAmelCase__ = re.compile(R"""is\_([a-z_]*)_available()""")
# Catches a one-line _import_struct = {xxx}
lowerCAmelCase__ = re.compile(R"""^_impo... | 626 |
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
from .prior_transformer import PriorTransformer
fr... | 626 | 1 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import (
BitConfig,
ViTHybridC... | 626 |
from math import factorial
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int = 1_0_0 ) -> int:
'''simple docstring'''
return sum(map(SCREAMING_SNAKE_CASE_ , str(factorial(SCREAMING_SNAKE_CASE_ ) ) ) )
if __name__ == "__main__":
print(soluti... | 626 | 1 |
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Namespace ) -> Tuple:
'''simple docstring'''
return ConvertCommand(
args.model_type , args.t... | 626 |
lowerCAmelCase__ = """ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"""
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: bytes ) -> bytes:
'''simple docstring'''
if not isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
A__... | 626 | 1 |
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: str ) -> None:
'''simple docstring'''
A__ , A__ = analyze_text(SCREAMING_SNAKE_CASE_ )
... | 626 |
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,... | 626 | 1 |
import argparse
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_warmup, set_seed
from accelerate import Accelerator, DistributedTy... | 626 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int ) -> int:
'''simple docstring'''
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
A__ = 1
A__ = 1
while repunit:
A__ = (1_0 * repunit + 1) % divisor
repunit_i... | 626 | 1 |
from __future__ import annotations
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Union[str, Any] , SCREAMING_SNAKE_CASE_: int , SCREAMING_SNAKE_CASE_: int , SCREAMING_SNAKE_CASE_: Dict ) -> Union[str, Any]: # noqa: E741
'''simple docstring''... | 626 |
from __future__ import annotations
from collections.abc import Iterator
from typing import Any
class a__ :
"""simple docstring"""
def __init__( self , lowercase ) -> int:
'''simple docstring'''
A__ = data
A__ = None
class ... | 626 | 1 |
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
lowerCAmelCase__ = input("""Enter image url: """).strip()
print(f"""Downloading image from {url} ...""")
lowerCAmelCase__ = BeautifulSoup(requests.get(url).content, """html.parser""")
# The image URL is ... | 626 |
import math
lowerCAmelCase__ = 1_0
lowerCAmelCase__ = 7
lowerCAmelCase__ = BALLS_PER_COLOUR * NUM_COLOURS
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int = 2_0 ) -> str:
'''simple docstring'''
A__ = math.comb(SCREAMING_SNAKE_CASE_ , SCREAMING... | 626 | 1 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Tuple ) -> List[Any]:
'''simple docstring'''
A__ = 1
A__ = 2
while i * i <= n:
A__ = 0
while n % i == 0:
n //= i
multiplicity += 1
n_divisors *... | 626 |
from typing import Union
import fire
import torch
from tqdm import tqdm
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: str , SCREAMING_SNAKE_CASE_: str = "cpu" , SCREAMING_SNAKE_CASE_: Union[str, None] = None ) -> None:
'''simple docstring'''
A_... | 626 | 1 |
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version(""">=""", FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch.distributed.checkpoint.default_pla... | 626 |
from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class a__ :
"""simple docstring"""
__lowerCamelCase = field(
metadata={'h... | 626 | 1 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: list ) -> list:
'''simple docstring'''
if len(SCREAMING_SNAKE_CASE_ ) <= 1:
return lst
A__ = 1
while i < len(SCREAMING_SNAKE_CASE_ ):
if lst[i - 1] <= lst[i]:
i += 1
... | 626 |
import collections
import importlib.util
import os
import re
from pathlib import Path
lowerCAmelCase__ = """src/transformers"""
# Matches is_xxx_available()
lowerCAmelCase__ = re.compile(R"""is\_([a-z_]*)_available()""")
# Catches a one-line _import_struct = {xxx}
lowerCAmelCase__ = re.compile(R"""^_impo... | 626 | 1 |
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if version.parse(fairseq.__ver... | 626 |
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
lowerCAmelCase__ = logging.get_logger(__name__)
class a__ ( snake_case ):
"""simple docstring"""
def __init__( self , *lowercase , **lowercase ) -> ... | 626 | 1 |
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
lowerCAmelCase__ = 2_0_0
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that generation and must be smaller t... | 626 |
from __future__ import annotations
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: str , SCREAMING_SNAKE_CASE_: list[str] | None = None ) -> list[list[str]]:
'''simple docstring'''
A__ = word_bank or []
# create a table
A__ = len(SCR... | 626 | 1 |
from __future__ import annotations
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: list[int] , SCREAMING_SNAKE_CASE_: list[int] , SCREAMING_SNAKE_CASE_: list[int] , SCREAMING_SNAKE_CASE_: list[list[str]] , SCREAMING_SNAKE_CASE_: int , ) -> ... | 626 |
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: List[str] , SCREAMING_SNAKE_CASE_: List[str] , SCREAMING_SNAKE_CASE_: List[str] , SCREAMING_SNAKE_CASE_:... | 626 | 1 |
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import numpy as np
import pandas as pd
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
BartForSequenceClassification,
DataCo... | 626 |
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Namespace ) -> Tuple:
'''simple docstring'''
return ConvertCommand(
args.model_type , args.t... | 626 | 1 |
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
lowerCAmelCase__ = datasets.utils.logging.get_logger(__name__)
@dataclass
class a__ ( datasets.BuilderConfi... | 626 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_to... | 626 | 1 |
import contextlib
import importlib
import io
import unittest
import transformers
# Try to import everything from transformers to ensure every object can be loaded.
from transformers import * # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, require_tf, require_torch
from tr... | 626 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFCamembertModel
@require_tf... | 626 | 1 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ap... | 626 |
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipeline_params import UNCONDITION... | 626 | 1 |
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures, SingleSentenceClassificat... | 626 |
from __future__ import annotations
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: list[int] , SCREAMING_SNAKE_CASE_: list[int] , SCREAMING_SNAKE_CASE_: list[int] , SCREAMING_SNAKE_CASE_: list[list[str]] , SCREAMING_SNAKE_CASE_: int , ) -> ... | 626 | 1 |
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def lowerCAmelCase__ ( SCREAMING_SNAKE_CAS... | 626 |
from __future__ import annotations
import copy
import tempfile
import unittest
from transformers import CONFIG_MAPPING, AutoConfig, BertConfig, GPTaConfig, TaConfig, TapasConfig, is_tf_available
from transformers.testing_utils import (
DUMMY_UNKNOWN_IDENTIFIER,
SMALL_MODEL_IDENTIFIER,
RequestCounter,
... | 626 | 1 |
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
lowerCAmelCase__ = """http://www.mocksite.com/file1.txt"""
lowerCAm... | 626 |
import inspect
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
lowerCAmelCase__ = """src/transformers"""
# This is to make sure the transforme... | 626 | 1 |
import math
from typing import Any, Callable, List, Optional, Tuple, Union
import numpy as np
import torch
from ...models import TaFilmDecoder
from ...schedulers import DDPMScheduler
from ...utils import is_onnx_available, logging, randn_tensor
if is_onnx_available():
from ..onnx_utils import OnnxRuntimeModel
f... | 626 |
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_available():
import torch
i... | 626 | 1 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def lowerCAmelCase__ ( ) -> Tuple:
'''simple docstring'''
with offline(OfflineSimulationMo... | 626 |
import datasets
from .evaluate import evaluate
lowerCAmelCase__ = """\
@inproceedings{Rajpurkar2016SQuAD10,
title={SQuAD: 100, 000+ Questions for Machine Comprehension of Text},
author={Pranav Rajpurkar and Jian Zhang and Konstantin Lopyrev and Percy Liang},
booktitle={EMNLP},
year={2016}
}
"""
lowerCA... | 626 | 1 |
import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pytorch_model
from transformers.ut... | 626 |
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
from .prior_transformer import PriorTransformer
fr... | 626 | 1 |
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import patch
import pyarrow as pa
i... | 626 |
from math import factorial
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int = 1_0_0 ) -> int:
'''simple docstring'''
return sum(map(SCREAMING_SNAKE_CASE_ , str(factorial(SCREAMING_SNAKE_CASE_ ) ) ) )
if __name__ == "__main__":
print(soluti... | 626 | 1 |
from __future__ import annotations
from collections.abc import Iterator
from typing import Any
class a__ :
"""simple docstring"""
def __init__( self , lowercase ) -> int:
'''simple docstring'''
A__ = data
A__ = None
class ... | 626 |
lowerCAmelCase__ = """ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"""
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: bytes ) -> bytes:
'''simple docstring'''
if not isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
A__... | 626 | 1 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dime... | 626 |
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,... | 626 | 1 |
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
generate_identified_filename,
infer_shap... | 626 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int ) -> int:
'''simple docstring'''
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
A__ = 1
A__ = 1
while repunit:
A__ = (1_0 * repunit + 1) % divisor
repunit_i... | 626 | 1 |
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