code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
def __SCREAMING_SNAKE_CASE ( __UpperCamelCase : str ) -> list:
"""simple docstring"""
SCREAMING_SNAKE_CASE__ = [0] * len(__UpperCamelCase )
for i in range(1 , len(__UpperCamelCase ) ):
# use last results for better performance - dynamic ... | 219 | # 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... | 219 | 1 |
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_tokenization_common import Tokeni... | 218 |
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization_transfo_xl import CORPUS_NAM... | 218 | 1 |
"""simple docstring"""
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class __A ( unitt... | 16 |
"""simple docstring"""
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'):
f... | 16 | 1 |
"""simple docstring"""
from typing import Callable, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase_ = logging.get_logger(__name__)
lowerCamelCase_ = {
"microsoft/xprophetnet-large-wiki100-cased": (
"https://huggingface.... | 363 |
"""simple docstring"""
import argparse
import torch
from transformers import (
UniSpeechSatConfig,
UniSpeechSatForAudioFrameClassification,
UniSpeechSatForSequenceClassification,
UniSpeechSatForXVector,
WavaVecaFeatureExtractor,
logging,
)
logging.set_verbosity_inf... | 239 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class snake_case__ ( unitte... | 304 |
def _a ( lowerCamelCase ):
return " ".join(
"""""".join(word[::-1] ) if len(lowerCamelCase ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(reverse_long_words("""Hey wollef sroirraw"""))
| 287 | 0 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class __snake_case :
lowerCAmelCase_ = field(
default="codeparrot/codeparrot" , metadata={"help": "Model name or path of model to be trained."} )
... | 358 | import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse('''9.1.0'''):
__lowerCamelCase : Optional[Any] = {
'''linear''': PIL.Image.Resampling.BILINEAR,
'''bili... | 204 | 0 |
'''simple docstring'''
import argparse
import re
import requests
import torch
# git clone https://github.com/salesforce/BLIP.git
from models.blip import blip_decoder
from models.blip_itm import blip_itm
from models.blip_vqa import blip_vqa
from PIL import Image
from torchvision import transforms
from torchvision... | 89 | import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(UpperCAmelCase_ ) , '... | 65 | 0 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_sentencepiece
@require_tokenizers
@require_torch
... | 363 |
import os
# Precomputes a list of the 100 first triangular numbers
lowerCAmelCase : Optional[int] = [int(0.5 * n * (n + 1)) for n in range(1, 101)]
def A_ ( ):
SCREAMING_SNAKE_CASE_: List[str] = os.path.dirname(os.path.realpath(_UpperCAmelCase ) )
SCREAMI... | 127 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_SCREAMING_SNAKE_CASE : Optional[int] = ... | 183 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_... | 183 | 1 |
'''simple docstring'''
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def lowerCamelCase (_SCREAMING_SNAKE_CASE : str , _SCREAMING_SNAKE_CASE : Optional[int] , _SCREAMING_SNAKE_CASE : Tu... | 294 |
'''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWithNoAttention
from ...m... | 294 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_c... | 289 |
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
snake_case_ = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE__ (__snake_case ):
def __init__( self , *a , **a):
warnings.warn(
'The cla... | 214 | 0 |
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... | 262 |
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
UpperCAmelCase__ : Dict =logging.get_logger(__name__) # pylint: disable=invalid-name
class __A ( a ):
def _... | 262 | 1 |
"""simple docstring"""
import math
import unittest
def lowercase ( lowerCAmelCase__ : int ) -> bool:
assert isinstance(lowerCAmelCase__ , lowerCAmelCase__ ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 an... | 45 |
def UpperCamelCase ( __magic_name__ : str ) -> list:
"""simple docstring"""
if n_term == "":
return []
lowercase__ = []
for temp in range(int(__magic_name__ ) ):
series.append(f'''1/{temp + 1}''' if series else """1""" )
return series
... | 305 | 0 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _A ( lowerCAmelCase ):
@staticmethod
@abstractmethod
def A__ ( __lowerCAmelCase ):
"""simple docstring"""
... | 32 | """simple docstring"""
class _A :
def __init__( self , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ):
"""simple docstring"""
lowercase = None
lowercase = None
l... | 32 | 1 |
'''simple docstring'''
lowerCamelCase : Dict = 65_521
def _SCREAMING_SNAKE_CASE (A ) -> int:
"""simple docstring"""
lowercase__ = 1
lowercase__ = 0
for plain_chr in plain_text:
lowercase__ = (a + or... | 2 |
'''simple docstring'''
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
lowerCamelCase : List[Any] = logging.getLogger(__name__)
class __lowerCAmelCase (lowercase_ ):
... | 2 | 1 |
"""simple docstring"""
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_lowerCAmelCase : Any = {
"""facebook/mask2former-swin-small-coco-instance""": (
"""https:/... | 363 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( snake_case : Optional[Any] , snake_case : Any )-> Any:
'''simple docstring'''
UpperCAmelCase__ : List[str] = [1]
for i in range(2 , snake_case ):
factorials.append(factoria... | 298 | 0 |
import darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
SCREAMING_SNAKE_CASE__ : int = {
'n_samples': 64,
'horizon': 32,
'num_inference_steps': 20,
'n_guide_steps': 2, # can set to 0 for faster sampling, does not use value ... | 48 |
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import glue_compute... | 48 | 1 |
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
lowercase__ :Tuple = parse(importlib.metadata.version("torch"))
def UpperCamelCase ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ... | 97 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ :Optional[int] = logging.get_logger(__name__)
lowercase__ :List[Any] = {
"camembert-base": "https://huggingfac... | 97 | 1 |
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, requ... | 0 |
from math import factorial
UpperCAmelCase__ = {str(digit): factorial(digit) for digit in range(10)}
def _a ( a :int ) -> int:
if not isinstance(a , a ):
raise TypeError('''Parameter number must be int''' )
if number < 0:
raise ValueError('''Parameter numb... | 0 | 1 |
"""simple docstring"""
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def _snake_case ( _snake_case : str , _snake_case : str , **_snake_case : List[Any] ):
lowerCAmelCase : Optional[int] = AutoConfig.from_pretrained(_... | 314 |
"""simple docstring"""
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPip... | 314 | 1 |
from __future__ import annotations
import pandas as pd
def SCREAMING_SNAKE_CASE_ ( __magic_name__ : list[int] , __magic_name__ : list[int] , __magic_name__ : int ) -> list[int]:
"""simple docstring"""
UpperCamelCase :List[str] = [0] * no_of_proce... | 38 |
"""simple docstring"""
lowercase__ = {
"""meter""": """m""",
"""kilometer""": """km""",
"""megametre""": """Mm""",
"""gigametre""": """Gm""",
"""terametre""": """Tm""",
"""petametre""": """Pm""",
"""exametre""": """Em""",
"""zettametre""": ""... | 96 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase = logging.get_logger(__name__)
__UpperCamelCase = {
"caidas/swin2sr-classicalsr-x2-64": (
"https://huggingface.co/caidas/swin2sr-classi... | 356 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from trans... | 13 | 0 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowerCamelCase : Optional[int] = {"""configuration_mmbt""": ["""MMBTConfig"""]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except O... | 52 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
class UpperCAmelCase ( _... | 15 | 0 |
'''simple docstring'''
import math
import random
def __magic_name__ ( A , A = False ) -> float:
if deriv:
return value * (1 - value)
return 1 / (1 + math.exp(-value ))
# Initial Value
lowerCAmelCase_ = 0.02
def __magic_name__ ( A , A ) -> ... | 354 |
'''simple docstring'''
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
fr... | 332 | 0 |
"""simple docstring"""
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSav... | 84 |
"""simple docstring"""
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
d... | 84 | 1 |
lowerCAmelCase__ : str ={
"A": ".-", "B": "-...", "C": "-.-.", "D": "-..", "E": ".", "F": "..-.", "G": "--.",
"H": "....", "I": "..", "J": ".---", "K": "-.-", "L": ".-..", "M": "--", "N": "-.",
"O": "---", "P": ".--.", "Q": "--.-", "R": ".-.", "S": "...", "T": "-", "U": "..-",
"V": "...-"... | 369 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ : List[str] ={
'''configuration_timesformer''': ['''TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TimesformerConfig'''],
}
try:
if not is_torch_available():... | 118 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
A__: List[str] = {'''configuration_plbart''': [''... | 276 |
'''simple docstring'''
class A__ :
def __init__( self :List[Any] ) -> None:
'''simple docstring'''
_a : dict[str, TrieNode] ={} # Mapping from char to TrieNode
_a : List[str] =False
... | 276 | 1 |
import json
import os
from typing import Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase__ : Optional[Any] =logging.get_logger(__name__)
lowerCAmelCase__ : Dict ={
"vocab_file": "vocab.json",
"mer... | 365 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCAmelCase__ : str ={'''configuration_vit_mae''': ['''VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMAEConfig''']}
t... | 118 | 0 |
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 ConfigTester
from ...test_modeling_common imp... | 187 |
"""simple docstring"""
# 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
#
... | 106 | 0 |
'''simple docstring'''
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizer... | 351 | '''simple docstring'''
import tempfile
import unittest
import numpy as np
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import TOKEN, USER, is_staging_test, require_flax
if is_fla... | 18 | 0 |
from typing import Any
import numpy as np
def __UpperCamelCase ( lowerCAmelCase__ : np.ndarray ):
return np.array_equal(lowerCAmelCase__ , matrix.conjugate().T )
def __UpperCamelCase ( lowerCAmelCase__ : np.ndarray , lowerCAmelCase__ : np.ndarray ):
__... | 216 |
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is_torch_available():
import ... | 216 | 1 |
'''simple docstring'''
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
B... | 353 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.i... | 220 | 0 |
import copy
import os
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Dict, Mapping, Optional, Union
if TYPE_CHECKING:
from ...processing_utils import ProcessorMixin
from ...utils import TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfi... | 15 |
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
FEATURE_EXTRACTOR_MAPPING,
AutoConfig,
AutoFeatureExtractor,
WavaVecaConfig,
WavaVecaFeatureExtractor,
)
from transformers.testing_utils import DUM... | 12 | 0 |
"""simple docstring"""
UpperCAmelCase : List[Any] = range(2, 20 + 1)
UpperCAmelCase : Optional[int] = [10**k for k in range(ks[-1] + 1)]
UpperCAmelCase : dict[int, dict[int, list[list[int]]]] = {}
def lowerCamelCase ( _UpperCamelCase : str ,... | 356 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase : Tuple = {
'configuration_electra': ['... | 320 | 0 |
"""simple docstring"""
import math
UpperCamelCase : Union[str, Any] = 1_0
UpperCamelCase : List[str] = 7
UpperCamelCase : Any = BALLS_PER_COLOUR * NUM_COLOURS
def A ( snake_case :int = 2_0 ) -> str:
__UpperCamelCase = math.comb(snake_case , snake_case... | 316 |
"""simple docstring"""
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class __lowerCAmelCase ( __SCREAMING_SNAKE_CASE )... | 316 | 1 |
"""simple docstring"""
lowerCAmelCase_ : List[Any] = 9.80665
def _lowerCAmelCase ( lowerCAmelCase , lowerCAmelCase , lowerCAmelCase = g ):
'''simple docstring'''
if fluid_density <= 0:
raise ValueError("""Impossible fluid density""" ... | 248 |
"""simple docstring"""
import math
import time
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_model as xm
import torch_xla.debug.metrics as met
... | 248 | 1 |
'''simple docstring'''
def __snake_case ( UpperCAmelCase_ : Optional[Any] , UpperCAmelCase_ : Dict ):
_validate_point(_UpperCamelCase )
_validate_point(_UpperCamelCase )
if len(_UpperCamelCase ) != len(_UpperCamelCase ):
raise ValueError("Both points must be in... | 55 |
"""simple docstring"""
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class _UpperCamelCase ( pl.LightningModule ):
'''simple docstring'''
def __init__( self , __a ):
... | 57 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dime... | 189 |
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... | 189 | 1 |
"""simple docstring"""
import argparse
import dataclasses
import json
import logging
import os
import shutil
from typing import List, Optional
import datasets
from accelerate import Accelerator
from datasets import load_dataset
from finetuning import finetune
from tqdm.auto import tqdm
import transformers
from ... | 98 |
'''simple docstring'''
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import Tokenize... | 318 | 0 |
'''simple docstring'''
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
a : Tuple = get_tests_dir("""fixtures/test_sentenc... | 338 |
'''simple docstring'''
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
... | 338 | 1 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
a_ :A... | 277 |
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin
from ...test_modeling_comm... | 209 | 0 |
'''simple docstring'''
lowerCAmelCase : List[Any] = {str(digit): digit**5 for digit in range(10)}
def A_( A : int):
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(A))
def A_( ):
return sum(
number
for n... | 360 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : Optional[int] = logging.get_logger(__name__)
lowerCAmelCase : Union[str, Any] = {'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/config.json'}
class... | 251 | 0 |
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def lowerCamelCase__ ( a__ : str ) -> str:
UpperCamelCase_ = [
"""encoder.version""",
"""decoder.version""",
"""model.enco... | 122 |
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 UNCONDITIONA... | 122 | 1 |
from PIL import Image
def _A ( lowerCAmelCase_ : Image , lowerCAmelCase_ : int ):
"""simple docstring"""
lowerCAmelCase__ = (259 * (level + 255)) / (255 * (259 - level))
def contrast(lowerCAmelCase_ : int ) -> int:
... | 221 |
def _A ( lowerCAmelCase_ : int = 1000 ):
"""simple docstring"""
return sum(2 * a * ((a - 1) // 2) for a in range(3 , n + 1 ) )
if __name__ == "__main__":
print(solution())
| 221 | 1 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
... | 78 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
'ut/deta': 'https://huggingface.co/ut/deta/resolve/main/conf... | 234 | 0 |
from collections import namedtuple
import requests
from lxml import html # type: ignore
_UpperCAmelCase = namedtuple('covid_data', 'cases deaths recovered')
def lowerCAmelCase_ ( UpperCamelCase_ = "https://www.worldometers.info/coronavirus/" ) -> covid_data:
UpperCamelCas... | 328 |
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
_UpperCAmelCase = '\\n@article{wang2019superglue,\n title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},\n author={Wang, Alex and Pr... | 328 | 1 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
lowerCamelCase_ : Tuple = """examples/"""
lowerCamelCase_ : str = {
"""examples""": (re.compile(R"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check_min_vers... | 81 |
"""simple docstring"""
from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class __A ( _SCREAMING_SNA... | 81 | 1 |
"""simple docstring"""
import qiskit
def __A ( a_ :int , a_ :int) -> qiskit.result.counts.Counts:
__a : Optional[Any] = qiskit.Aer.get_backend('''aer_simulator''')
# Create a Quantum Circuit acting on the q register
__a : Optional[An... | 188 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A = {
'''configuration_instructblip''': [
'''INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''InstructBlipConfig'... | 188 | 1 |
from __future__ import annotations
snake_case_ : Tuple = 10
def A (__A : list[int] ) -> list[int]:
"""simple docstring"""
UpperCAmelCase_ = 1
UpperCAmelCase_ = max(__A )
while placement <... | 51 |
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 TensorType
... | 51 | 1 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BertTokenizer, BlipImageProcessor,... | 41 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case : Dict = logging.get_logger(__name__)
snake_case : Optional[int] = {
"naver-clova-ix/donut-base": "https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json",
# See all Don... | 41 | 1 |
'''simple docstring'''
import requests
def _A ( _lowerCAmelCase , _lowerCAmelCase ):
"""simple docstring"""
__lowercase ={'Content-Type': 'application/json'}
__lowercase =requests.post(_lowerCAmelCase , json={'text': message_body} , ... | 166 |
'''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-small""": """https://huggi... | 166 | 1 |
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def snake_case_ (__A : dict ) -> tupl... | 139 |
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def snake_case_ (__A : Optional[Any] ) -> Tup... | 139 | 1 |
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
__lowerCAmelCase = logging.get_logger(__name__)
__lowerCAmelCase = ... | 196 | """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
SCREAMING_SNAKE_CASE__:List[Any] = log... | 261 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_tf_available,
is_torch_available,
)
_lowerCAmelCase = {
"configuration_speech_to_text": ["SPEE... | 98 |
'''simple docstring'''
import collections
import inspect
import unittest
from transformers import SwinvaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configurati... | 98 | 1 |
class _lowercase :
"""simple docstring"""
def __init__( self : Any , __lowerCamelCase : str ):
'''simple docstring'''
lowerCamelCase__ : int = arr.split("," )
def lowerCAmelC... | 184 |
from manim import *
class __magic_name__ ( lowerCAmelCase_ ):
def __magic_name__ ( self ) -> Any:
'''simple docstring'''
__a =Rectangle(height=0.5 , width=0.5 )
__a =Rectangle(height=0.25 , width=0.25 )
... | 218 | 0 |
class a :
def __init__( self :Optional[Any] ):
snake_case__ : str = ''''''
snake_case__ : Union[str, Any] = ''''''
snake_case__ : int = []
def __lowerCamelCase ( self :str ,__lowe... | 358 |
import argparse
from collections import defaultdict
def _lowerCAmelCase ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ) -> Optional[Any]:
"""simple docstring"""
snake_case__ : Dict = f"""{file}_{clas... | 44 | 0 |
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class __A ( a , a ):
... | 71 |
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization_transfo_xl ... | 51 | 0 |
'''simple docstring'''
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = Order... | 367 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import TransformeraDModel, VQDiffusionPipeline, VQDiffusionScheduler, VQModel
from diffusers.pipelines.vq_diffusion.pipeline_vq_diffusion import Lear... | 332 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaImgaImgPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, ... | 215 |
'''simple docstring'''
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ )-... | 215 | 1 |
'''simple docstring'''
# 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/licen... | 89 |
'''simple docstring'''
from pathlib import Path
import cva
import numpy as np
from matplotlib import pyplot as plt
def UpperCamelCase_ ( A__ : np.ndarray , A__ : np.ndarray , A__ : np.ndarray , A__ : int , A__ : ... | 89 | 1 |
'''simple docstring'''
import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
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_con... | 162 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
__lowerCamelCase = logging.get_logger(__name__)
class A__ ( _snake_case ):
def __init__( self , *UpperCamelCase__ , **UpperCamelCase__ ) ... | 162 | 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
if is_tf_available():
import numpy as np
import tensorflow as tf
from transfo... | 168 |
"""simple docstring"""
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def a__ ( snake_case__ ) -> Optional[Any]:
lowerCamelCase = {}
lowerCamelCase = job["""started_at"""]
lowerCamelCase = job["""comple... | 168 | 1 |
'''simple docstring'''
import inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
import torch.utils.checkpoint
from ...models import UNetaDModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteSc... | 104 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase__ = {"configuration_yolos": ["YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP", "YolosConfig", "YolosOnnxConfig"]}
try:
if not is_vi... | 151 | 0 |
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
fro... | 266 |
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class snake_case__ (A__ ):
"""simple docstring"""
def __init__( self , __lowercase , __lowercase ) -> int:
"""simple docstring"""
... | 266 | 1 |
'''simple docstring'''
A__ : Union[str, Any] =6_55_21
def UpperCamelCase__ ( lowerCAmelCase ):
"""simple docstring"""
_lowerCAmelCase = 1
_lowerCAmelCase = 0
for plain_chr in plain_text:
... | 70 |
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def __lowerCamelCase ( lowerCamelCase__ : str , lowerCamelCase__ : str , **lowerCamelCase__ : Tuple ):
'''simple docstring'''
lowerCamelCase = AutoConfig.from_pret... | 252 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A : Any = logging.get_logger(__name__)
_A : Dict = {
'tanreinama/GPTSAN-2.8B-spout_is_uniform': (
'https://huggingface.co/tanreinama/GPTSAN-2.8B-spout_is_uniform/resolve/main/config.json'
),
}
clas... | 265 |
def _a ( UpperCAmelCase ) -> int:
"""simple docstring"""
if not isinstance(UpperCAmelCase , UpperCAmelCase ):
raise TypeError('''only integers accepted as input''' )
else:
lowerCamelCase__ : Any = str(abs(UpperCAmelCase ) ... | 265 | 1 |
'''simple docstring'''
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
... | 41 |
'''simple docstring'''
# This script creates a super tiny model that is useful inside tests, when we just want to test that
# the machinery works, without needing to the check the quality of the outcomes.
#
# This version creates a tiny vocab first, and then a tiny model - so the outcome... | 41 | 1 |
'''simple docstring'''
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock import FileLock
fro... | 287 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class __lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def snake_case__ ( self : Tuple ) -> int:
'''simple d... | 287 | 1 |
import math
from numpy import inf
from scipy.integrate import quad
def _UpperCamelCase ( lowercase__ ):
if num <= 0:
raise ValueError('''math domain error''' )
return quad(lowercase__ , 0 , lowercase__ , args=(lowercase__) )[0]
... | 9 |
'''simple docstring'''
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transformers im... | 309 | 0 |
"""simple docstring"""
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class lowerCamelCase__ ( unittest.TestCase ):
def _lowerCamelCase ( self : Tuple ):
a__: Lis... | 364 |
import pytest
from datasets import inspect_metric, list_metrics, load_metric
@pytest.fixture
def __lowerCamelCase ( __magic_name__ : List[Any] ):
monkeypatch.setattr("datasets.utils.deprecation_utils._emitted_deprecation_warnings" , set() )
@pytest.fixture
def __lowerCamelCase ... | 42 | 0 |
'''simple docstring'''
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_prop... | 55 |
'''simple docstring'''
from collections import Counter
from timeit import timeit
def __a ( UpperCAmelCase = "" , ) ->bool:
"""simple docstring"""
return sum(c % 2 for c in Counter(input_str.replace(""" """ , """""" ).lower() ).values() ) < 2
def __a ... | 258 | 0 |
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate_available,
is_accele... | 94 |
def lowerCAmelCase__ ( lowerCamelCase_ : str ,lowerCamelCase_ : str):
'''simple docstring'''
lowerCAmelCase__ : Optional[Any] = len(lowerCamelCase_)
lowerCAmelCase__ : str = len(lowerCamelCase_)
lowerCAmelCase__ : Union[str, Any] ... | 94 | 1 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def _snake_case ( _snake_case : Namespace ):
return ConvertCommand(
args.model_type , args.tf_checkpoint , args.pytorch_dump_ou... | 60 |
"""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 .to... | 60 | 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 b... | 295 |
def lowerCamelCase__ ( UpperCamelCase__ : list[list[int]] , UpperCamelCase__ : int , UpperCamelCase__ : int , UpperCamelCase__ : list[int] ) -> bool:
'''simple docstring'''
if graph[path[curr_ind - 1]][next_ver] == 0:
... | 295 | 1 |
'''simple docstring'''
import baseaa
def _A ( _lowerCAmelCase ):
"""simple docstring"""
return baseaa.baaencode(string.encode('utf-8' ) )
def _A ( _lowerCAmelCase ):
"""simple docstring"""
return baseaa.baadecode(__lowerCamelCase... | 166 |
import math
def A__ ( __lowerCamelCase ):
SCREAMING_SNAKE_CASE_ = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(__lowerCamelCase )
def A__ ( __lowerCamelCase = 1 / 1_23_45 ):
SCREAMING_SNAKE_CASE_ = 0
SCREAMING_SNAKE_CASE_ ... | 299 | 0 |
'''simple docstring'''
import os
import shutil
from pathlib import Path
from typing import Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging
if is_onnx_available():
... | 246 |
'''simple docstring'''
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common ... | 246 | 1 |
# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def lowerCamelCase__ ( _a , _a , _a ... | 76 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
_A : str = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( lowerCAmelCase_ ):
def __init__( self : Dict , *A : Any , **A : List[... | 142 | 0 |
'''simple docstring'''
import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_common import ids_tensor... | 370 |
'''simple docstring'''
class lowercase__ :
def __init__( self : List[str] ,lowerCamelCase__ : List[Any] ,lowerCamelCase__ : Optional[int] ,lowerCamelCase__ : Any ):
'''simple docstring'''
_UpperCamelCase : Dict = None
_UpperCamelCase : ... | 236 | 0 |
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors import TemplateProcessing
... | 107 |
import numpy as np
def __magic_name__ ( A : np.array ):
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
def __magic_name__ ( A : np.array ):
'''simple docstring'''
return vector * sigmoid(1.7_02 * vector )
if __name__ == "__main... | 107 | 1 |
'''simple docstring'''
def lowerCamelCase (_SCREAMING_SNAKE_CASE : Optional[Any] ):
if not isinstance(__lowerCAmelCase , __lowerCAmelCase ):
raise ValueError('Input series is not valid, valid series - [2, 4, 6]' )
if len(__lowerCAmelCase ) == 0... | 350 |
'''simple docstring'''
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
__lowercase : List[Any] = {
'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json',
'susnato/ernie-m-l... | 294 | 0 |
def __snake_case ( _lowerCAmelCase : int = 1000 ) -> int:
A_ : str = 3
A_ : Optional[int] = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 15 == 0:
result -= a
a += 1
return result
if __name__ == "__... | 300 |
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
_lowerCamelCase : List[str] = logging.get... | 282 | 0 |
"""simple docstring"""
from math import loga
def __UpperCAmelCase ( __lowerCamelCase ) -> int:
if a < 0:
raise ValueError('''Input value must be a positive integer''' )
elif isinstance(__lowerCamelCase , __lowerCamelCase ):
raise Type... | 302 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase_ = {
'configu... | 302 | 1 |
'''simple docstring'''
from math import factorial
__a = {str(d): factorial(d) for d in range(10)}
def __snake_case( _lowerCAmelCase ) -> int:
return sum(DIGIT_FACTORIAL[d] for d in str(_lowerCAmelCase ) )
def __snake_case( ) -> int:
snake_case__ : Opt... | 35 |
'''simple docstring'''
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def __snake_case( _lowerCAmelCase ) -> List[Any]:
... | 35 | 1 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
A : Any = {'tokenization_byt5': ['ByT5Tokenizer']}
if TYPE_CHECKING:
from .tokenization_byta import ByTaTokenizer
else:
import sys
A : Any = _LazyModule(__name__, globals()['__file__'], _import_... | 33 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
A : Optional[Any] = {}
try:
if not is_sentencepiece_available():
raise OptionalDepend... | 33 | 1 |
def UpperCamelCase_( lowerCamelCase_ , lowerCamelCase_ ) -> List[Any]:
_lowercase : Optional[Any] = [1]
for i in range(2 , lowerCamelCase_ ):
factorials.append(factorials[-1] * i )
assert 0 <= k < factorials[-1] * n, "k out of bounds"
_lowerca... | 21 |
from typing import Dict
from .base import GenericTensor, Pipeline
class SCREAMING_SNAKE_CASE_ ( snake_case_ ):
def UpperCAmelCase_ ( self : str , _A : Optional[Any]=None , _A : List[str]=None , _A : Optional[Any]... | 327 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if... | 111 |
'''simple docstring'''
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
lowerCamelCase_ = '<<<<<<< This should probably be modified because it mentions: '
lowerCamelCase_... | 111 | 1 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
f... | 28 |
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class lowerCAmelCase_ ( a__ ):
def __init__( self, SCREAMING_SNAKE_CASE_, SCREAMING... | 119 | 0 |
from __future__ import annotations
import unittest
from transformers import DebertaVaConfig, 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_tensor, random_atte... | 367 |
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 transformers.utils import loggin... | 198 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import center_crop, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAGENET_STANDARD... | 147 |
import math
from typing import Callable, List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion.pipeline_st... | 147 | 1 |
def __lowerCamelCase ( ) -> int:
"""simple docstring"""
return 1
def __lowerCamelCase ( snake_case__ ) -> int:
"""simple docstring"""
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def __lo... | 125 |
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def __lowerCamelCase ( snake_case__ ) -> int:
"""simple docstring"""
_SCREAMING_SNAKE_CASE = prime_factors(snake_case__ )
if is_square_free(... | 125 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase_ : int = {
'configuration_maskformer': ['MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MaskFormerConfig'],
'configur... | 200 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import ScoreSdeVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowercase__ ( _snake_case ... | 200 | 1 |
class __A :
"""simple docstring"""
def __init__( self , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
"""simple docstring"""
__UpperCamelCase : Union[str, Any] =name
__UpperCamelCase... | 366 |
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class __A ( unittest.TestCase ):
"""simple docstring"""
def __lowercase ( self ):
"""simple docstring"""
__Upper... | 245 | 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 : str = logging.get_logger(__name__)
_lowercase : List[str] ... | 332 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : Dict = logging.get_logger(__name__)
UpperCAmelCase_ : Union[str, Any] = {
'google/switch-base-8': 'https://huggingface.co/google/switch-base-8/blob/main/config.json',
... | 32 | 0 |
import argparse
import torch
from transformers import GPTaLMHeadModel, RobertaForMaskedLM
if __name__ == "__main__":
_A = argparse.ArgumentParser(
description=(
'Extraction some layers of the full RobertaForMaskedLM or GPT2LMHeadModel for Transfer Learned'
' Distillation'
... | 117 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_download, hf_hub_url
from PIL import Image
from transformers import DetaConfig, DetaForObjectDetection, DetaImageProcessor, SwinConfig
from transformers.utils import logging
loggi... | 117 | 1 |
import flax.linen as nn
import jax
import jax.numpy as jnp
class SCREAMING_SNAKE_CASE__ ( nn.Module ):
A_ : int
A_ : jnp.dtype = jnp.floataa
def a (self : str ):
"""simple docstring"""
_... | 24 |
"""simple docstring"""
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def snake_case_ ( A_ : Tuple, A_ : int, A_ : Dict ):
... | 72 | 0 |
'''simple docstring'''
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class SCREAMING_SNAKE_CASE (a__ , a__ ):
@register_to_config
def __init__( self , *,
... | 190 |
'''simple docstring'''
import math
def _lowerCAmelCase ( __snake_case : int ) -> int:
if not isinstance(__snake_case , __snake_case ):
__A : List[Any] = f'Input value of [number={number}] must be an integer'
... | 190 | 1 |
'''simple docstring'''
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def UpperCAmelCase__ ( ) -> Any:
__lowerCamelCase : List[Any] = 9, 14 # noqa: F841
__lowerCamelCase : int = [
[0, 1, 4],
... | 185 |
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 transformers import AutoImageProcessor, SwinvaConfig, SwinvaForImageClassification
def UpperCamelCase( __UpperCamelCase : List[str] ):
... | 103 | 0 |
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class __snake_case ( nn.Module ):
de... | 285 |
from ...processing_utils import ProcessorMixin
class __snake_case ( lowerCAmelCase ):
_a : Union[str, Any]= "WhisperFeatureExtractor"
_a : int= "WhisperTokenizer"
def __init__( self ,snake_case ,snake_case ):
'''simple docstring'''
super().__... | 285 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"s-JoL/Open-Llama-V1": "https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json",
}
class A ( _UpperCAmelCase ):
... | 7 |
"""simple docstring"""
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, re... | 144 | 0 |
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 TFCamembertM... | 223 |
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import ConfigT... | 223 | 1 |
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